MCP Tools Reference: bigquery.googleapis.com

Tool: cancel_job

Cancel a running BigQuery job.

Use this tool to cancel a query job that is currently executing (i.e. returned job_complete: false with a job_id from execute_sql or execute_sql_readonly). Specify the job_id to abort.

The following code sample shows how to use curl to call the cancel_job MCP tool.

Curl Request 
curl --location 'https://bigquery.googleapis.com/mcp' \
--header 'content-type: application/json' \
--header 'accept: application/json, text/event-stream' \
--data '{
  "method": "tools/call",
  "params": {
    "name": "cancel_job",
    "arguments": {
      // Provide these details according to the MCP tool specification.
    }
  },
  "jsonrpc": "2.0",
  "id": 1
}'

Input Schema

Request for cancelling a job.

CancelJobRequest

JSON representation 
{
  "projectId": string,
  "jobId": string,
  "location": string
}
Fields
projectId

string

Required. Project ID of the job to cancel.
jobId

string

Required. Job ID of the job to cancel.
location

string

Optional. The geographic location of the job.

Output Schema

Describes format of a jobs cancellation response.

JobCancelResponse

JSON representation 
{
  "kind": string,
  "job": {
    object (Job)
  }
}
Fields
kind

string

The resource type of the response.
job

object (Job)

The final state of the job.

Job

JSON representation 
{
  "kind": string,
  "etag": string,
  "id": string,
  "selfLink": string,
  "user_email": string,
  "configuration": {
    object (JobConfiguration)
  },
  "jobReference": {
    object (JobReference)
  },
  "statistics": {
    object (JobStatistics)
  },
  "status": {
    object (JobStatus)
  },
  "principal_subject": string,
  "jobCreationReason": {
    object (JobCreationReason)
  }
}
Fields
kind

string

Output only. The type of the resource.
etag

string

Output only. A hash of this resource.
id

string

Output only. Opaque ID field of the job.
selfLink

string

Output only. A URL that can be used to access the resource again.
user_email

string

Output only. Email address of the user who ran the job.
configuration

object (JobConfiguration)

Required. Describes the job configuration.
jobReference

object (JobReference)

Optional. Reference describing the unique-per-user name of the job.
statistics

object (JobStatistics)

Output only. Information about the job, including starting time and ending time of the job.
status

object (JobStatus)

Output only. The status of this job. Examine this value when polling an asynchronous job to see if the job is complete.
principal_subject

string

Output only. [Full-projection-only] String representation of identity of requesting party. Populated for both first- and third-party identities. Only present for APIs that support third-party identities.
jobCreationReason

object (JobCreationReason)

Output only. The reason why a Job was created.

JobConfiguration

JSON representation 
{
  "jobType": string,
  "query": {
    object (JobConfigurationQuery)
  },
  "load": {
    object (JobConfigurationLoad)
  },
  "copy": {
    object (JobConfigurationTableCopy)
  },
  "extract": {
    object (JobConfigurationExtract)
  },
  "dryRun": boolean,
  "jobTimeoutMs": string,
  "labels": {
    string: string,
    ...
  },

  // Union field _max_slots can be only one of the following:
  "maxSlots": integer
  // End of list of possible types for union field _max_slots.

  // Union field _reservation can be only one of the following:
  "reservation": string
  // End of list of possible types for union field _reservation.
}
Fields
jobType

string

Output only. The type of the job. Can be QUERY, LOAD, EXTRACT, COPY or UNKNOWN.
query

object (JobConfigurationQuery)

[Pick one] Configures a query job.
load

object (JobConfigurationLoad)

[Pick one] Configures a load job.
copy

object (JobConfigurationTableCopy)

[Pick one] Copies a table.
extract

object (JobConfigurationExtract)

[Pick one] Configures an extract job.
dryRun

boolean

Optional. If set, don't actually run this job. A valid query will return a mostly empty response with some processing statistics, while an invalid query will return the same error it would if it wasn't a dry run. Behavior of non-query jobs is undefined.
jobTimeoutMs

string (Int64Value format)

Optional. Job timeout in milliseconds relative to the job creation time. If this time limit is exceeded, BigQuery attempts to stop the job, but might not always succeed in canceling it before the job completes. For example, a job that takes more than 60 seconds to complete has a better chance of being stopped than a job that takes 10 seconds to complete.
labels

map (key: string, value: string)

The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key.

An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass": "1.3kg", "count": "3" }.

Union field _max_slots.

_max_slots can be only one of the following:
maxSlots

integer

Optional. A target limit on the rate of slot consumption by this job. If set to a value > 0, BigQuery will attempt to limit the rate of slot consumption by this job to keep it below the configured limit, even if the job is eligible for more slots based on fair scheduling. The unused slots will be available for other jobs and queries to use.

Note: This feature is not yet generally available.

Union field _reservation.

_reservation can be only one of the following:
reservation

string

Optional. The reservation that job would use. User can specify a reservation to execute the job. If reservation is not set, reservation is determined based on the rules defined by the reservation assignments. The expected format is projects/{project}/locations/{location}/reservations/{reservation}. Forces the query to use on-demand billing when set to none, which requires the project or organization to have reservation_override_mode set to ALLOW_ANY_OVERRIDE.

JobConfigurationQuery

JSON representation 
{
  "query": string,
  "destinationTable": {
    object (TableReference)
  },
  "tableDefinitions": {
    string: {
      object (ExternalDataConfiguration)
    },
    ...
  },
  "userDefinedFunctionResources": [
    {
      object (UserDefinedFunctionResource)
    }
  ],
  "createDisposition": string,
  "writeDisposition": string,
  "defaultDataset": {
    object (DatasetReference)
  },
  "priority": string,
  "preserveNulls": boolean,
  "allowLargeResults": boolean,
  "useQueryCache": boolean,
  "flattenResults": boolean,
  "maximumBillingTier": integer,
  "maximumBytesBilled": string,
  "useLegacySql": boolean,
  "parameterMode": string,
  "queryParameters": [
    {
      object (QueryParameter)
    }
  ],
  "schemaUpdateOptions": [
    string
  ],
  "timePartitioning": {
    object (TimePartitioning)
  },
  "rangePartitioning": {
    object (RangePartitioning)
  },
  "clustering": {
    object (Clustering)
  },
  "destinationEncryptionConfiguration": {
    object (EncryptionConfiguration)
  },
  "scriptOptions": {
    object (ScriptOptions)
  },
  "connectionProperties": [
    {
      object (ConnectionProperty)
    }
  ],
  "createSession": boolean,
  "continuous": boolean,
  "writeIncrementalResults": boolean,
  "secureContext": {
    object (SecureContext)
  },

  // Union field _system_variables can be only one of the following:
  "systemVariables": {
    object (SystemVariables)
  }
  // End of list of possible types for union field _system_variables.
}
Fields
query

string

[Required] SQL query text to execute. The useLegacySql field can be used to indicate whether the query uses legacy SQL or GoogleSQL.
destinationTable

object (TableReference)

Optional. Describes the table where the query results should be stored. This property must be set for large results that exceed the maximum response size. For queries that produce anonymous (cached) results, this field will be populated by BigQuery.
tableDefinitions

map (key: string, value: object (ExternalDataConfiguration))

Optional. You can specify external table definitions, which operate as ephemeral tables that can be queried. These definitions are configured using a JSON map, where the string key represents the table identifier, and the value is the corresponding external data configuration object.

An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass": "1.3kg", "count": "3" }.
userDefinedFunctionResources[]

object (UserDefinedFunctionResource)

Describes user-defined function resources used in the query.
createDisposition

string

Optional. Specifies whether the job is allowed to create new tables. The following values are supported:

  • CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table.
  • CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result.

The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.
writeDisposition

string

Optional. Specifies the action that occurs if the destination table already exists. The following values are supported:

  • WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the data, removes the constraints, and uses the schema from the query result.
  • WRITE_TRUNCATE_DATA: If the table already exists, BigQuery overwrites the data, but keeps the constraints and schema of the existing table.
  • WRITE_APPEND: If the table already exists, BigQuery appends the data to the table.
  • WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result.

The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.
defaultDataset

object (DatasetReference)

Optional. Specifies the default dataset to use for unqualified table names in the query. This setting does not alter behavior of unqualified dataset names. Setting the system variable @@dataset_id achieves the same behavior. See https://cloud.google.com/bigquery/docs/reference/system-variables for more information on system variables.
priority

string

Optional. Specifies a priority for the query. Possible values include INTERACTIVE and BATCH. The default value is INTERACTIVE.
preserveNulls

boolean

[Deprecated] This property is deprecated.
allowLargeResults

boolean

Optional. If true and query uses legacy SQL dialect, allows the query to produce arbitrarily large result tables at a slight cost in performance. Requires destinationTable to be set. For GoogleSQL queries, this flag is ignored and large results are always allowed. However, you must still set destinationTable when result size exceeds the allowed maximum response size.
useQueryCache

boolean

Optional. Whether to look for the result in the query cache. The query cache is a best-effort cache that will be flushed whenever tables in the query are modified. Moreover, the query cache is only available when a query does not have a destination table specified. The default value is true.
flattenResults

boolean

Optional. If true and query uses legacy SQL dialect, flattens all nested and repeated fields in the query results. allowLargeResults must be true if this is set to false. For GoogleSQL queries, this flag is ignored and results are never flattened.
maximumBillingTier

integer

Optional. [Deprecated] Maximum billing tier allowed for this query. The billing tier controls the amount of compute resources allotted to the query, and multiplies the on-demand cost of the query accordingly. A query that runs within its allotted resources will succeed and indicate its billing tier in statistics.query.billingTier, but if the query exceeds its allotted resources, it will fail with billingTierLimitExceeded. WARNING: The billed byte amount can be multiplied by an amount up to this number! Most users should not need to alter this setting, and we recommend that you avoid introducing new uses of it.
maximumBytesBilled

string (Int64Value format)

Limits the bytes billed for this job. Queries that will have bytes billed beyond this limit will fail (without incurring a charge). If unspecified, this will be set to your project default.
useLegacySql

boolean

Optional. Specifies whether to use BigQuery's legacy SQL dialect for this query. The default value is true. If set to false, the query uses BigQuery's GoogleSQL.

When useLegacySql is set to false, the value of flattenResults is ignored; query will be run as if flattenResults is false.
parameterMode

string

GoogleSQL only. Set to POSITIONAL to use positional (?) query parameters or to NAMED to use named (@myparam) query parameters in this query.
queryParameters[]

object (QueryParameter)

Query parameters for GoogleSQL queries.
schemaUpdateOptions[]

string

Allows the schema of the destination table to be updated as a side effect of the query job. Schema update options are supported in three cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE_DATA; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified:

  • ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema.
  • ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable.
timePartitioning

object (TimePartitioning)

Time-based partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified.
rangePartitioning

object (RangePartitioning)

Range partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified.
clustering

object (Clustering)

Clustering specification for the destination table.
destinationEncryptionConfiguration

object (EncryptionConfiguration)

Custom encryption configuration (e.g., Cloud KMS keys)
scriptOptions

object (ScriptOptions)

Options controlling the execution of scripts.
connectionProperties[]

object (ConnectionProperty)

Connection properties which can modify the query behavior.
createSession

boolean

If this property is true, the job creates a new session using a randomly generated session_id. To continue using a created session with subsequent queries, pass the existing session identifier as a ConnectionProperty value. The session identifier is returned as part of the SessionInfo message within the query statistics.

The new session's location will be set to Job.JobReference.location if it is present, otherwise it's set to the default location based on existing routing logic.
continuous

boolean

Optional. Whether to run the query as continuous or a regular query. Continuous query is currently in experimental stage and not ready for general usage.
writeIncrementalResults

boolean

Optional. This is only supported for a SELECT query using a temporary table. If set, the query is allowed to write results incrementally to the temporary result table. This may incur a performance penalty. This option cannot be used with Legacy SQL. This feature is not yet available.
secureContext

object (SecureContext)

Optional. A set of key-value pairs representing the secure context. This can be used to pass sensitive or context-specific information. They can be retrieved via the SECURE_CONTEXT() function and used to modify the run-time behavior of a query.

Union field _system_variables.

_system_variables can be only one of the following:
systemVariables

object (SystemVariables)

Output only. System variables for GoogleSQL queries. A system variable is output if the variable is settable and its value differs from the system default. "@@" prefix is not included in the name of the System variables.

TableReference

JSON representation 
{
  "projectId": string,
  "datasetId": string,
  "tableId": string
}
Fields
projectId

string

Required. The ID of the project containing this table.
datasetId

string

Required. The ID of the dataset containing this table.
tableId

string

Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see General Category. The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as sample_table$20190123.

ExternalTableDefinitionsEntry

JSON representation 
{
  "key": string,
  "value": {
    object (ExternalDataConfiguration)
  }
}
Fields
key

string
value

object (ExternalDataConfiguration)

ExternalDataConfiguration

JSON representation 
{
  "sourceUris": [
    string
  ],
  "fileSetSpecType": enum (FileSetSpecType),
  "schema": {
    object (TableSchema)
  },
  "sourceFormat": string,
  "maxBadRecords": integer,
  "autodetect": boolean,
  "ignoreUnknownValues": boolean,
  "compression": string,
  "csvOptions": {
    object (CsvOptions)
  },
  "jsonOptions": {
    object (JsonOptions)
  },
  "bigtableOptions": {
    object (BigtableOptions)
  },
  "googleSheetsOptions": {
    object (GoogleSheetsOptions)
  },
  "hivePartitioningOptions": {
    object (HivePartitioningOptions)
  },
  "connectionId": string,
  "decimalTargetTypes": [
    enum (DecimalTargetType)
  ],
  "avroOptions": {
    object (AvroOptions)
  },
  "jsonExtension": enum (JsonExtension),
  "parquetOptions": {
    object (ParquetOptions)
  },
  "referenceFileSchemaUri": string,
  "metadataCacheMode": enum (MetadataCacheMode),
  "timestampTargetPrecision": [
    integer
  ],

  // Union field _object_metadata can be only one of the following:
  "objectMetadata": enum (ObjectMetadata)
  // End of list of possible types for union field _object_metadata.

  // Union field _time_zone can be only one of the following:
  "timeZone": string
  // End of list of possible types for union field _time_zone.

  // Union field _date_format can be only one of the following:
  "dateFormat": string
  // End of list of possible types for union field _date_format.

  // Union field _datetime_format can be only one of the following:
  "datetimeFormat": string
  // End of list of possible types for union field _datetime_format.

  // Union field _time_format can be only one of the following:
  "timeFormat": string
  // End of list of possible types for union field _time_format.

  // Union field _timestamp_format can be only one of the following:
  "timestampFormat": string
  // End of list of possible types for union field _timestamp_format.
}
Fields
sourceUris[]

string

[Required] The fully-qualified URIs that point to your data in Google Cloud. For Google Cloud Storage URIs: Each URI can contain one '*' wildcard character and it must come after the 'bucket' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups, exactly one URI can be specified. Also, the '*' wildcard character is not allowed.
fileSetSpecType

enum (FileSetSpecType)

Optional. Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
schema

object (TableSchema)

Optional. The schema for the data. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, ORC and Parquet formats.
sourceFormat

string

[Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". For Apache Iceberg tables, specify "ICEBERG". For ORC files, specify "ORC". For Parquet files, specify "PARQUET". [Beta] For Google Cloud Bigtable, specify "BIGTABLE".
maxBadRecords

integer

Optional. The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats.
autodetect

boolean

Try to detect schema and format options automatically. Any option specified explicitly will be honored.
ignoreUnknownValues

boolean

Optional. Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored. ORC: This setting is ignored. Parquet: This setting is ignored.
compression

string

Optional. The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats. An empty string is an invalid value.
csvOptions

object (CsvOptions)

Optional. Additional properties to set if sourceFormat is set to CSV.
jsonOptions

object (JsonOptions)

Optional. Additional properties to set if sourceFormat is set to JSON.
bigtableOptions

object (BigtableOptions)

Optional. Additional options if sourceFormat is set to BIGTABLE.
googleSheetsOptions

object (GoogleSheetsOptions)

Optional. Additional options if sourceFormat is set to GOOGLE_SHEETS.
hivePartitioningOptions

object (HivePartitioningOptions)

Optional. When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification.
connectionId

string

Optional. The connection specifying the credentials to be used to read external storage, such as Azure Blob, Cloud Storage, or S3. The connection_id can have the form {project_id}.{location_id};{connection_id} or projects/{project_id}/locations/{location_id}/connections/{connection_id}.
decimalTargetTypes[]

enum (DecimalTargetType)

Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown.

Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is:

  • (38,9) -> NUMERIC;
  • (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits);
  • (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits);
  • (76,38) -> BIGNUMERIC;
  • (77,38) -> BIGNUMERIC (error if value exceeds supported range).

This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC.

Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
avroOptions

object (AvroOptions)

Optional. Additional properties to set if sourceFormat is set to AVRO.
jsonExtension

enum (JsonExtension)

Optional. Load option to be used together with source_format newline-delimited JSON to indicate that a variant of JSON is being loaded. To load newline-delimited GeoJSON, specify GEOJSON (and source_format must be set to NEWLINE_DELIMITED_JSON).
parquetOptions

object (ParquetOptions)

Optional. Additional properties to set if sourceFormat is set to PARQUET.
referenceFileSchemaUri

string

Optional. When creating an external table, the user can provide a reference file with the table schema. This is enabled for the following formats: AVRO, PARQUET, ORC.
metadataCacheMode

enum (MetadataCacheMode)

Optional. Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.
timestampTargetPrecision[]

integer

Precisions (maximum number of total digits in base 10) for seconds of TIMESTAMP types that are allowed to the destination table for autodetection mode.

Available for the formats: CSV, PARQUET, AVRO, and Iceberg External Table.

Possible values include: Not Specified, [], or [6]: timestamp(6) for all auto detected TIMESTAMP columns [6, 12]: timestamp(6) for all auto detected TIMESTAMP columns that have less than 6 digits of subseconds. timestamp(12) for all auto detected TIMESTAMP columns that have more than 6 digits of subseconds. [12]: timestamp(12) for all auto detected TIMESTAMP columns.

The order of the elements in this array is ignored. Inputs that have higher precision than the highest target precision in this array will be truncated.

Union field _object_metadata.

_object_metadata can be only one of the following:
objectMetadata

enum (ObjectMetadata)

Optional. ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted.

Currently SIMPLE is the only supported Object Metadata type.

Union field _time_zone.

_time_zone can be only one of the following:
timeZone

string

Optional. Time zone used when parsing timestamp values that do not have specific time zone information (e.g. 2024-04-20 12:34:56). The expected format is a IANA timezone string (e.g. America/Los_Angeles).

Union field _date_format.

_date_format can be only one of the following:
dateFormat

string

Optional. Format used to parse DATE values. Supports C-style and SQL-style values.

Union field _datetime_format.

_datetime_format can be only one of the following:
datetimeFormat

string

Optional. Format used to parse DATETIME values. Supports C-style and SQL-style values.

Union field _time_format.

_time_format can be only one of the following:
timeFormat

string

Optional. Format used to parse TIME values. Supports C-style and SQL-style values.

Union field _timestamp_format.

_timestamp_format can be only one of the following:
timestampFormat

string

Optional. Format used to parse TIMESTAMP values. Supports C-style and SQL-style values.

TableSchema

JSON representation 
{
  "fields": [
    {
      object (TableFieldSchema)
    }
  ],
  "foreignTypeInfo": {
    object (ForeignTypeInfo)
  }
}
Fields
fields[]

object (TableFieldSchema)

Describes the fields in a table.
foreignTypeInfo

object (ForeignTypeInfo)

Optional. Specifies metadata of the foreign data type definition in field schema (TableFieldSchema.foreign_type_definition).

TableFieldSchema

JSON representation 
{
  "name": string,
  "type": string,
  "mode": string,
  "fields": [
    {
      object (TableFieldSchema)
    }
  ],
  "description": string,
  "policyTags": {
    object (PolicyTagList)
  },
  "dataGovernanceTagsInfo": {
    object (DataGovernanceTagsInfo)
  },
  "dataPolicies": [
    {
      object (DataPolicyOption)
    }
  ],
  "dataPolicyList": {
    object (DataPolicyList)
  },
  "maxLength": string,
  "precision": string,
  "scale": string,
  "timestampPrecision": string,
  "roundingMode": enum (RoundingMode),
  "collation": string,
  "defaultValueExpression": string,
  "rangeElementType": {
    object (FieldElementType)
  },
  "foreignTypeDefinition": string,
  "generatedColumn": {
    object (GeneratedColumn)
  }
}
Fields
name

string

Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
type

string

Required. The field data type. Possible values include:

  • STRING
  • BYTES
  • INTEGER (or INT64)
  • FLOAT (or FLOAT64)
  • BOOLEAN (or BOOL)
  • TIMESTAMP
  • DATE
  • TIME
  • DATETIME
  • GEOGRAPHY
  • NUMERIC
  • BIGNUMERIC
  • JSON
  • RECORD (or STRUCT)
  • RANGE

Use of RECORD/STRUCT indicates that the field contains a nested schema.
mode

string

Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
fields[]

object (TableFieldSchema)

Optional. Describes the nested schema fields if the type property is set to RECORD.
description

string

Optional. The field description. The maximum length is 1,024 characters.
policyTags

object (PolicyTagList)

Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
dataGovernanceTagsInfo

object (DataGovernanceTagsInfo)

Optional. Specifies the data governance tags on this field. This field works with other column-level security fields as follows:

  • Precedence: If a data governance tag is attached to a column, it takes precedence over the policy tag attached to the column. However, if a data policy is attached to a column, it takes precedence over the data governance tag.
  • Patching behavior: Describes how this field behaves during a Table.patch schema update:
    • Unset: If the data_governance_tags_info field is omitted from the update request, the existing tags on the column are preserved.
    • Empty Field: To clear data governance tags from a column, send the data_governance_tags_info field as an empty object. This removes all tags from the column.
    • Updating tags: To replace an existing tag, send the field with the new tag.
dataPolicies[]

object (DataPolicyOption)

Optional. Data policies attached to this field, used for field-level access control.
dataPolicyList

object (DataPolicyList)

Optional. Specifies data policies attached to this field, used for field-level access control. When set, this will be the source of truth for data policy information.
maxLength

string (int64 format)

Optional. Maximum length of values of this field for STRINGS or BYTES.

If max_length is not specified, no maximum length constraint is imposed on this field.

If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field.

If type = "BYTES", then max_length represents the maximum number of bytes in this field.

It is invalid to set this field if type ≠ "STRING" and ≠ "BYTES".
precision

string (int64 format)

Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC.

It is invalid to set precision or scale if type ≠ "NUMERIC" and ≠ "BIGNUMERIC".

If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type.

Values of this NUMERIC or BIGNUMERIC field must be in this range when:

  • Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S]
  • Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1].

Acceptable values for precision and scale if both are specified:

  • If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9.
  • If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38.

Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero):

  • If type = "NUMERIC": 1 ≤ precision ≤ 29.
  • If type = "BIGNUMERIC": 1 ≤ precision ≤ 38.

If scale is specified but not precision, then it is invalid.
scale

string (int64 format)

Optional. See documentation for precision.
timestampPrecision

string (Int64Value format)

Optional. Precision (maximum number of total digits in base 10) for seconds of TIMESTAMP type.

Possible values include: * 6 (Default, for TIMESTAMP type with microsecond precision) * 12 (For TIMESTAMP type with picosecond precision)
roundingMode

enum (RoundingMode)

Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
collation

string

Optional. Field collation can be set only when the type of field is STRING. The following values are supported:

  • 'und:ci': undetermined locale, case insensitive.
  • '': empty string. Default to case-sensitive behavior.
defaultValueExpression

string

Optional. A SQL expression to specify the default value for this field.
rangeElementType

object (FieldElementType)

Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Values for the field element type can be the following:

  • DATE
  • DATETIME
  • TIMESTAMP
foreignTypeDefinition

string

Optional. Definition of the foreign data type. Only valid for top-level schema fields (not nested fields). If the type is FOREIGN, this field is required.
generatedColumn

object (GeneratedColumn)

Optional. Definition of how values are generated for the field. Only valid for top-level schema fields (not nested fields).

StringValue

JSON representation 
{
  "value": string
}
Fields
value

string

The string value.

PolicyTagList

JSON representation 
{
  "names": [
    string
  ]
}
Fields
names[]

string

A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.

DataGovernanceTagsInfo

JSON representation 
{
  "dataGovernanceTags": {
    string: string,
    ...
  }
}
Fields
dataGovernanceTags

map (key: string, value: string)

Optional. The data governance tags added to this field are used for field-level access control. Only one data governance tag is currently supported on a field. Tag keys are globally unique. Tag key is expected to be in the namespaced format, for example "parent-id/pii" where parent-id is the ID of the parent organization or project resource for this tag key. Tag value is expected to be the short name, for example "sensitive". See Tag definitions for more details. For example: "parent-id/pii": "sensitive", "myProject/cost_center": "sales"

An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass": "1.3kg", "count": "3" }.

DataGovernanceTagsEntry

JSON representation 
{
  "key": string,
  "value": string
}
Fields
key

string
value

string

DataPolicyOption

JSON representation 
{

  // Union field _name can be only one of the following:
  "name": string
  // End of list of possible types for union field _name.
}
Fields

Union field _name.

_name can be only one of the following:
name

string

Data policy resource name in the form of projects/project_id/locations/location_id/dataPolicies/data_policy_id.

DataPolicyList

JSON representation 
{
  "dataPolicies": [
    {
      object (DataPolicyOption)
    }
  ]
}
Fields
dataPolicies[]

object (DataPolicyOption)

Contains a list of data policy options. At most 9 data policies are allowed per field.

Int64Value

JSON representation 
{
  "value": string
}
Fields
value

string (int64 format)

The int64 value.

FieldElementType

JSON representation 
{
  "type": string
}
Fields
type

string

Required. The type of a field element. For more information, see TableFieldSchema.type.

GeneratedColumn

JSON representation 
{

  // Union field _generated_mode can be only one of the following:
  "generatedMode": enum (GeneratedMode)
  // End of list of possible types for union field _generated_mode.

  // Union field definition can be only one of the following:
  "generatedExpressionInfo": {
    object (GeneratedExpressionInfo)
  }
  // End of list of possible types for union field definition.
}
Fields

Union field _generated_mode.

_generated_mode can be only one of the following:
generatedMode

enum (GeneratedMode)

Optional. Dictates when system generated values are used to populate the field.

Union field definition.

definition can be only one of the following:
generatedExpressionInfo

object (GeneratedExpressionInfo)

Definition of the expression used to generate the field.

GeneratedExpressionInfo

JSON representation 
{

  // Union field _generation_expression can be only one of the following:
  "generationExpression": string
  // End of list of possible types for union field _generation_expression.

  // Union field _asynchronous can be only one of the following:
  "asynchronous": boolean
  // End of list of possible types for union field _asynchronous.

  // Union field _stored can be only one of the following:
  "stored": boolean
  // End of list of possible types for union field _stored.
}
Fields

Union field _generation_expression.

_generation_expression can be only one of the following:
generationExpression

string

Optional. The generation expression (e.g. AI.EMBED(...)) used to generate the field.

Union field _asynchronous.

_asynchronous can be only one of the following:
asynchronous

boolean

Optional. Whether the column generation is done asynchronously.

Union field _stored.

_stored can be only one of the following:
stored

boolean

Optional. Whether the generated column is stored in the table.

ForeignTypeInfo

JSON representation 
{
  "typeSystem": enum (TypeSystem)
}
Fields
typeSystem

enum (TypeSystem)

Required. Specifies the system which defines the foreign data type.

Int32Value

JSON representation 
{
  "value": integer
}
Fields
value

integer

The int32 value.

BoolValue

JSON representation 
{
  "value": boolean
}
Fields
value

boolean

The bool value.

CsvOptions

JSON representation 
{
  "fieldDelimiter": string,
  "skipLeadingRows": string,
  "quote": string,
  "allowQuotedNewlines": boolean,
  "allowJaggedRows": boolean,
  "encoding": string,
  "preserveAsciiControlCharacters": boolean,
  "nullMarker": string,
  "nullMarkers": [
    string
  ],
  "sourceColumnMatch": string
}
Fields
fieldDelimiter

string

Optional. The separator character for fields in a CSV file. The separator is interpreted as a single byte. For files encoded in ISO-8859-1, any single character can be used as a separator. For files encoded in UTF-8, characters represented in decimal range 1-127 (U+0001-U+007F) can be used without any modification. UTF-8 characters encoded with multiple bytes (i.e. U+0080 and above) will have only the first byte used for separating fields. The remaining bytes will be treated as a part of the field. BigQuery also supports the escape sequence "\t" (U+0009) to specify a tab separator. The default value is comma (",", U+002C).
skipLeadingRows

string (Int64Value format)

Optional. The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following:

  • skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row.
  • skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row.
  • skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
quote

string

Optional. The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ("). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. To include the specific quote character within a quoted value, precede it with an additional matching quote character. For example, if you want to escape the default character ' " ', use ' "" '.
allowQuotedNewlines

boolean

Optional. Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
allowJaggedRows

boolean

Optional. Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.
encoding

string

Optional. The character encoding of the data. The supported values are UTF-8, ISO-8859-1, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
preserveAsciiControlCharacters

boolean

Optional. Indicates if the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') are preserved.
nullMarker

string

Optional. Specifies a string that represents a null value in a CSV file. For example, if you specify "\N", BigQuery interprets "\N" as a null value when querying a CSV file. The default value is the empty string. If you set this property to a custom value, BigQuery throws an error if an empty string is present for all data types except for STRING and BYTE. For STRING and BYTE columns, BigQuery interprets the empty string as an empty value.
nullMarkers[]

string

Optional. A list of strings represented as SQL NULL value in a CSV file.

null_marker and null_markers can't be set at the same time. If null_marker is set, null_markers has to be not set. If null_markers is set, null_marker has to be not set. If both null_marker and null_markers are set at the same time, a user error would be thrown. Any strings listed in null_markers, including empty string would be interpreted as SQL NULL. This applies to all column types.
sourceColumnMatch

string

Optional. Controls the strategy used to match loaded columns to the schema. If not set, a sensible default is chosen based on how the schema is provided. If autodetect is used, then columns are matched by name. Otherwise, columns are matched by position. This is done to keep the behavior backward-compatible. Acceptable values are: POSITION - matches by position. This assumes that the columns are ordered the same way as the schema. NAME - matches by name. This reads the header row as column names and reorders columns to match the field names in the schema.

JsonOptions

JSON representation 
{
  "encoding": string
}
Fields
encoding

string

Optional. The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.

BigtableOptions

JSON representation 
{
  "columnFamilies": [
    {
      object (BigtableColumnFamily)
    }
  ],
  "ignoreUnspecifiedColumnFamilies": boolean,
  "readRowkeyAsString": boolean,
  "outputColumnFamiliesAsJson": boolean
}
Fields
columnFamilies[]

object (BigtableColumnFamily)

Optional. List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.
ignoreUnspecifiedColumnFamilies

boolean

Optional. If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.
readRowkeyAsString

boolean

Optional. If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.
outputColumnFamiliesAsJson

boolean

Optional. If field is true, then each column family will be read as a single JSON column. Otherwise they are read as a repeated cell structure containing timestamp/value tuples. The default value is false.

BigtableColumnFamily

JSON representation 
{
  "familyId": string,
  "type": string,
  "encoding": string,
  "columns": [
    {
      object (BigtableColumn)
    }
  ],
  "onlyReadLatest": boolean,
  "protoConfig": {
    object (BigtableProtoConfig)
  }
}
Fields
familyId

string

Identifier of the column family.
type

string

Optional. The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive):

  • BYTES
  • STRING
  • INTEGER
  • FLOAT
  • BOOLEAN
  • JSON

Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.
encoding

string

Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. PROTO_BINARY - indicates values are encoded using serialized proto messages. This can only be used in combination with JSON type. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.
columns[]

object (BigtableColumn)

Optional. Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as <family field name>.<column field name>. Other columns can be accessed as a list through the <family field name>.Column field.
onlyReadLatest

boolean

Optional. If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.
protoConfig

object (BigtableProtoConfig)

Optional. Protobuf-specific configurations, only takes effect when the encoding is PROTO_BINARY.

BigtableColumn

JSON representation 
{
  "qualifierEncoded": string,
  "qualifierString": string,
  "fieldName": string,
  "type": string,
  "encoding": string,
  "onlyReadLatest": boolean,
  "protoConfig": {
    object (BigtableProtoConfig)
  }
}
Fields
qualifierEncoded

string (BytesValue format)

[Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as <family field name>.<column field name> field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as field_name.
qualifierString

string

Qualifier string.
fieldName

string

Optional. If the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as the column field name and is used as field name in queries.
type

string

Optional. The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive):

  • BYTES
  • STRING
  • INTEGER
  • FLOAT
  • BOOLEAN
  • JSON

Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.
encoding

string

Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. PROTO_BINARY - indicates values are encoded using serialized proto messages. This can only be used in combination with JSON type. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.
onlyReadLatest

boolean

Optional. If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.
protoConfig

object (BigtableProtoConfig)

Optional. Protobuf-specific configurations, only takes effect when the encoding is PROTO_BINARY.

BytesValue

JSON representation 
{
  "value": string
}
Fields
value

string (bytes format)

The bytes value.

A base64-encoded string.

BigtableProtoConfig

JSON representation 
{
  "schemaBundleId": string,
  "protoMessageName": string
}
Fields
schemaBundleId

string

Optional. The ID of the Bigtable SchemaBundle resource associated with this protobuf. The ID should be referred to within the parent table, e.g., foo rather than projects/{project}/instances/{instance}/tables/{table}/schemaBundles/foo. See more details on Bigtable SchemaBundles.
protoMessageName

string

Optional. The fully qualified proto message name of the protobuf. In the format of "foo.bar.Message".

GoogleSheetsOptions

JSON representation 
{
  "skipLeadingRows": string,
  "range": string
}
Fields
skipLeadingRows

string (Int64Value format)

Optional. The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
range

string

Optional. Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20

HivePartitioningOptions

JSON representation 
{
  "mode": string,
  "sourceUriPrefix": string,
  "requirePartitionFilter": boolean,
  "fields": [
    string
  ]
}
Fields
mode

string

Optional. When set, what mode of hive partitioning to use when reading data. The following modes are supported:

  • AUTO: automatically infer partition key name(s) and type(s).

  • STRINGS: automatically infer partition key name(s). All types are strings.

  • CUSTOM: partition key schema is encoded in the source URI prefix.

Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported formats are: JSON, CSV, ORC, Avro and Parquet.
sourceUriPrefix

string

Optional. When hive partition detection is requested, a common prefix for all source uris must be required. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout:

gs://bucket/path_to_table/dt=2019-06-01/country=USA/id=7/file.avro

gs://bucket/path_to_table/dt=2019-05-31/country=CA/id=3/file.avro

When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/.

CUSTOM detection requires encoding the partitioning schema immediately after the common prefix. For CUSTOM, any of

  • gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:INTEGER}

  • gs://bucket/path_to_table/{dt:STRING}/{country:STRING}/{id:INTEGER}

  • gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:STRING}

would all be valid source URI prefixes.
requirePartitionFilter

boolean

Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified.

Note that this field should only be true when creating a permanent external table or querying a temporary external table.

Hive-partitioned loads with require_partition_filter explicitly set to true will fail.
fields[]

string

Output only. For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.

AvroOptions

JSON representation 
{
  "useAvroLogicalTypes": boolean
}
Fields
useAvroLogicalTypes

boolean

Optional. If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).

ParquetOptions

JSON representation 
{
  "enumAsString": boolean,
  "enableListInference": boolean,
  "mapTargetType": enum (MapTargetType)
}
Fields
enumAsString

boolean

Optional. Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
enableListInference

boolean

Optional. Indicates whether to use schema inference specifically for Parquet LIST logical type.
mapTargetType

enum (MapTargetType)

Optional. Indicates how to represent a Parquet map if present.

UserDefinedFunctionResource

JSON representation 
{
  "resourceUri": string,
  "inlineCode": string
}
Fields
resourceUri

string

[Pick one] A code resource to load from a Google Cloud Storage URI (gs://bucket/path).
inlineCode

string

[Pick one] An inline resource that contains code for a user-defined function (UDF). Providing a inline code resource is equivalent to providing a URI for a file containing the same code.

DatasetReference

JSON representation 
{
  "datasetId": string,
  "projectId": string
}
Fields
datasetId

string

Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
projectId

string

Optional. The ID of the project containing this dataset.

QueryParameter

JSON representation 
{
  "name": string,
  "parameterType": {
    object (QueryParameterType)
  },
  "parameterValue": {
    object (QueryParameterValue)
  }
}
Fields
name

string

Optional. If unset, this is a positional parameter. Otherwise, should be unique within a query.
parameterType

object (QueryParameterType)

Required. The type of this parameter.
parameterValue

object (QueryParameterValue)

Required. The value of this parameter.

QueryParameterType

JSON representation 
{
  "type": string,
  "arrayType": {
    object (QueryParameterType)
  },
  "structTypes": [
    {
      object (QueryParameterStructType)
    }
  ],
  "rangeElementType": {
    object (QueryParameterType)
  },

  // Union field _timestamp_precision can be only one of the following:
  "timestampPrecision": string
  // End of list of possible types for union field _timestamp_precision.
}
Fields
type

string

Required. The top level type of this field.
arrayType

object (QueryParameterType)

Optional. The type of the array's elements, if this is an array.
structTypes[]

object (QueryParameterStructType)

Optional. The types of the fields of this struct, in order, if this is a struct.
rangeElementType

object (QueryParameterType)

Optional. The element type of the range, if this is a range.

Union field _timestamp_precision.

_timestamp_precision can be only one of the following:
timestampPrecision

string (int64 format)

Optional. Precision (maximum number of total digits in base 10) for seconds of TIMESTAMP type.

Possible values include: * 6 (Default, for TIMESTAMP type with microsecond precision) * 12 (For TIMESTAMP type with picosecond precision)

QueryParameterStructType

JSON representation 
{
  "name": string,
  "type": {
    object (QueryParameterType)
  },
  "description": string
}
Fields
name

string

Optional. The name of this field.
type

object (QueryParameterType)

Required. The type of this field.
description

string

Optional. Human-oriented description of the field.

QueryParameterValue

JSON representation 
{
  "value": string,
  "arrayValues": [
    {
      object (QueryParameterValue)
    }
  ],
  "structValues": {
    string: {
      object (QueryParameterValue)
    },
    ...
  },
  "rangeValue": {
    object (RangeValue)
  }
}
Fields
value

string

Optional. The value of this value, if a simple scalar type.
arrayValues[]

object (QueryParameterValue)

Optional. The array values, if this is an array type.
structValues

map (key: string, value: object (QueryParameterValue))

The struct field values.

An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass": "1.3kg", "count": "3" }.
rangeValue

object (RangeValue)

Optional. The range value, if this is a range type.

StructValuesEntry

JSON representation 
{
  "key": string,
  "value": {
    object (QueryParameterValue)
  }
}
Fields
key

string
value

object (QueryParameterValue)

RangeValue

JSON representation 
{
  "start": {
    object (QueryParameterValue)
  },
  "end": {
    object (QueryParameterValue)
  }
}
Fields
start

object (QueryParameterValue)

Optional. The start value of the range. A missing value represents an unbounded start.
end

object (QueryParameterValue)

Optional. The end value of the range. A missing value represents an unbounded end.

SystemVariables

JSON representation 
{
  "types": {
    string: {
      object (StandardSqlDataType)
    },
    ...
  },
  "values": {
    object
  }
}
Fields
types

map (key: string, value: object (StandardSqlDataType))

Output only. Data type for each system variable.

An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass": "1.3kg", "count": "3" }.
values

object (Struct format)

Output only. Value for each system variable.

TypesEntry

JSON representation 
{
  "key": string,
  "value": {
    object (StandardSqlDataType)
  }
}
Fields
key

string
value

object (StandardSqlDataType)

StandardSqlDataType

JSON representation 
{
  "typeKind": enum (TypeKind),

  // Union field sub_type can be only one of the following:
  "arrayElementType": {
    object (StandardSqlDataType)
  },
  "structType": {
    object (StandardSqlStructType)
  },
  "rangeElementType": {
    object (StandardSqlDataType)
  }
  // End of list of possible types for union field sub_type.
}
Fields
typeKind

enum (TypeKind)

Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
Union field sub_type. For complex types, the sub type information. sub_type can be only one of the following:
arrayElementType

object (StandardSqlDataType)

The type of the array's elements, if type_kind = "ARRAY".
structType

object (StandardSqlStructType)

The fields of this struct, in order, if type_kind = "STRUCT".
rangeElementType

object (StandardSqlDataType)

The type of the range's elements, if type_kind = "RANGE".

StandardSqlStructType

JSON representation 
{
  "fields": [
    {
      object (StandardSqlField)
    }
  ]
}
Fields
fields[]

object (StandardSqlField)

Fields within the struct.

StandardSqlField

JSON representation 
{
  "name": string,
  "type": {
    object (StandardSqlDataType)
  }
}
Fields
name

string

Optional. The name of this field. Can be absent for struct fields.
type

object (StandardSqlDataType)

Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).

Struct

JSON representation 
{
  "fields": {
    string: value,
    ...
  }
}
Fields
fields

map (key: string, value: value (Value format))

Unordered map of dynamically typed values.

An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass": "1.3kg", "count": "3" }.

FieldsEntry

JSON representation 
{
  "key": string,
  "value": value
}
Fields
key

string
value

value (Value format)

Value

JSON representation 
{

  // Union field kind can be only one of the following:
  "nullValue": null,
  "numberValue": number,
  "stringValue": string,
  "boolValue": boolean,
  "structValue": {
    object
  },
  "listValue": array
  // End of list of possible types for union field kind.
}
Fields
Union field kind. The kind of value. kind can be only one of the following:
nullValue

null

Represents a JSON null.
numberValue

number

Represents a JSON number. Must not be NaN, Infinity or -Infinity, since those are not supported in JSON. This also cannot represent large Int64 values, since JSON format generally does not support them in its number type.
stringValue

string

Represents a JSON string.
boolValue

boolean

Represents a JSON boolean (true or false literal in JSON).
structValue

object (Struct format)

Represents a JSON object.
listValue

array (ListValue format)

Represents a JSON array.

ListValue

JSON representation 
{
  "values": [
    value
  ]
}
Fields
values[]

value (Value format)

Repeated field of dynamically typed values.

TimePartitioning

JSON representation 
{
  "type": string,
  "expirationMs": string,
  "field": string,
  "requirePartitionFilter": boolean
}
Fields
type

string

Required. The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively.
expirationMs

string (Int64Value format)

Optional. Number of milliseconds for which to keep the storage for a partition. A wrapper is used here because 0 is an invalid value.
field

string

Optional. If not set, the table is partitioned by pseudo column '_PARTITIONTIME'; if set, the table is partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. A wrapper is used here because an empty string is an invalid value.
requirePartitionFilter
(deprecated)

boolean

If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. This field is deprecated; please set the field with the same name on the table itself instead. This field needs a wrapper because we want to output the default value, false, if the user explicitly set it.

RangePartitioning

JSON representation 
{
  "field": string,
  "range": {
    object (Range)
  }
}
Fields
field

string

Required. The name of the column to partition the table on. It must be a top-level, INT64 column whose mode is NULLABLE or REQUIRED.
range

object (Range)

Defines the ranges for range partitioning.

Range

JSON representation 
{
  "start": string,
  "end": string,
  "interval": string
}
Fields
start

string

Required. The start of range partitioning, inclusive. This field is an INT64 value represented as a string.
end

string

Required. The end of range partitioning, exclusive. This field is an INT64 value represented as a string.
interval

string

Required. The width of each interval. This field is an INT64 value represented as a string.

Clustering

JSON representation 
{
  "fields": [
    string
  ]
}
Fields
fields[]

string

One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. The ordering of the clustering fields should be prioritized from most to least important for filtering purposes.

For additional information, see Introduction to clustered tables.

EncryptionConfiguration

JSON representation 
{
  "kmsKeyName": string
}
Fields
kmsKeyName

string

Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.

ScriptOptions

JSON representation 
{
  "statementTimeoutMs": string,
  "statementByteBudget": string,
  "keyResultStatement": enum (KeyResultStatementKind)
}
Fields
statementTimeoutMs

string (Int64Value format)

Timeout period for each statement in a script.
statementByteBudget

string (Int64Value format)

Limit on the number of bytes billed per statement. Exceeding this budget results in an error.
keyResultStatement

enum (KeyResultStatementKind)

Determines which statement in the script represents the "key result", used to populate the schema and query results of the script job. Default is LAST.

ConnectionProperty

JSON representation 
{
  "key": string,
  "value": string
}
Fields
key

string

The key of the property to set.
value

string

The value of the property to set.

SecureContext

JSON representation 
{
  "secureParameterEntries": {
    object
  }
}
Fields
secureParameterEntries

object (Struct format)

Optional. A set of key-value pairs representing the secure parameter values. They can be retrieved via the SECURE_CONTEXT() function and used to modify the run-time behavior of a query.

JobConfigurationLoad

JSON representation 
{
  "sourceUris": [
    string
  ],
  "fileSetSpecType": enum (FileSetSpecType),
  "schema": {
    object (TableSchema)
  },
  "destinationTable": {
    object (TableReference)
  },
  "destinationTableProperties": {
    object (DestinationTableProperties)
  },
  "createDisposition": string,
  "writeDisposition": string,
  "nullMarker": string,
  "fieldDelimiter": string,
  "skipLeadingRows": integer,
  "encoding": string,
  "quote": string,
  "maxBadRecords": integer,
  "schemaInlineFormat": string,
  "schemaInline": string,
  "allowQuotedNewlines": boolean,
  "sourceFormat": string,
  "allowJaggedRows": boolean,
  "ignoreUnknownValues": boolean,
  "projectionFields": [
    string
  ],
  "autodetect": boolean,
  "schemaUpdateOptions": [
    string
  ],
  "timePartitioning": {
    object (TimePartitioning)
  },
  "rangePartitioning": {
    object (RangePartitioning)
  },
  "clustering": {
    object (Clustering)
  },
  "destinationEncryptionConfiguration": {
    object (EncryptionConfiguration)
  },
  "useAvroLogicalTypes": boolean,
  "referenceFileSchemaUri": string,
  "hivePartitioningOptions": {
    object (HivePartitioningOptions)
  },
  "decimalTargetTypes": [
    enum (DecimalTargetType)
  ],
  "thriftOptions": {
    object (ThriftOptions)
  },
  "jsonExtension": enum (JsonExtension),
  "parquetOptions": {
    object (ParquetOptions)
  },
  "preserveAsciiControlCharacters": boolean,
  "connectionProperties": [
    {
      object (ConnectionProperty)
    }
  ],
  "createSession": boolean,
  "columnNameCharacterMap": enum (ColumnNameCharacterMap),
  "copyFilesOnly": boolean,
  "timeZone": string,
  "nullMarkers": [
    string
  ],
  "sourceColumnMatch": enum (SourceColumnMatch),
  "timestampTargetPrecision": [
    integer
  ],

  // Union field _date_format can be only one of the following:
  "dateFormat": string
  // End of list of possible types for union field _date_format.

  // Union field _datetime_format can be only one of the following:
  "datetimeFormat": string
  // End of list of possible types for union field _datetime_format.

  // Union field _time_format can be only one of the following:
  "timeFormat": string
  // End of list of possible types for union field _time_format.

  // Union field _timestamp_format can be only one of the following:
  "timestampFormat": string
  // End of list of possible types for union field _timestamp_format.
}
Fields
sourceUris[]

string

[Required] The fully-qualified URIs that point to your data in Google Cloud. For Google Cloud Storage URIs: Each URI can contain one '*' wildcard character and it must come after the 'bucket' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups: Exactly one URI can be specified. Also, the '*' wildcard character is not allowed.
fileSetSpecType

enum (FileSetSpecType)

Optional. Specifies how source URIs are interpreted for constructing the file set to load. By default, source URIs are expanded against the underlying storage. You can also specify manifest files to control how the file set is constructed. This option is only applicable to object storage systems.
schema

object (TableSchema)

Optional. The schema for the destination table. The schema can be omitted if the destination table already exists, or if you're loading data from Google Cloud Datastore.
destinationTable

object (TableReference)

[Required] The destination table to load the data into.
destinationTableProperties

object (DestinationTableProperties)

Optional. [Experimental] Properties with which to create the destination table if it is new.
createDisposition

string

Optional. Specifies whether the job is allowed to create new tables. The following values are supported:

  • CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table.
  • CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.
writeDisposition

string

Optional. Specifies the action that occurs if the destination table already exists. The following values are supported:

  • WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the data, removes the constraints and uses the schema from the load job.
  • WRITE_TRUNCATE_DATA: If the table already exists, BigQuery overwrites the data, but keeps the constraints and schema of the existing table.
  • WRITE_APPEND: If the table already exists, BigQuery appends the data to the table.
  • WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result.

The default value is WRITE_APPEND. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.
nullMarker

string

Optional. Specifies a string that represents a null value in a CSV file. For example, if you specify "\N", BigQuery interprets "\N" as a null value when loading a CSV file. The default value is the empty string. If you set this property to a custom value, BigQuery throws an error if an empty string is present for all data types except for STRING and BYTE. For STRING and BYTE columns, BigQuery interprets the empty string as an empty value.
fieldDelimiter

string

Optional. The separator character for fields in a CSV file. The separator is interpreted as a single byte. For files encoded in ISO-8859-1, any single character can be used as a separator. For files encoded in UTF-8, characters represented in decimal range 1-127 (U+0001-U+007F) can be used without any modification. UTF-8 characters encoded with multiple bytes (i.e. U+0080 and above) will have only the first byte used for separating fields. The remaining bytes will be treated as a part of the field. BigQuery also supports the escape sequence "\t" (U+0009) to specify a tab separator. The default value is comma (",", U+002C).
skipLeadingRows

integer

Optional. The number of rows at the top of a CSV file that BigQuery will skip when loading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following:

  • skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row.
  • skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row.
  • skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
encoding

string

Optional. The character encoding of the data. The supported values are UTF-8, ISO-8859-1, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.

If you don't specify an encoding, or if you specify a UTF-8 encoding when the CSV file is not UTF-8 encoded, BigQuery attempts to convert the data to UTF-8. Generally, your data loads successfully, but it may not match byte-for-byte what you expect. To avoid this, specify the correct encoding by using the --encoding flag.

If BigQuery can't convert a character other than the ASCII 0 character, BigQuery converts the character to the standard Unicode replacement character: �.
quote

string

Optional. The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. To include the specific quote character within a quoted value, precede it with an additional matching quote character. For example, if you want to escape the default character ' " ', use ' "" '. @default "
maxBadRecords

integer

Optional. The maximum number of bad records that BigQuery can ignore when running the job. If the number of bad records exceeds this value, an invalid error is returned in the job result. The default value is 0, which requires that all records are valid. This is only supported for CSV and NEWLINE_DELIMITED_JSON file formats.
schemaInlineFormat

string

[Deprecated] The format of the schemaInline property.
schemaInline

string

[Deprecated] The inline schema. For CSV schemas, specify as "Field1:Type1[,Field2:Type2]*". For example, "foo:STRING, bar:INTEGER, baz:FLOAT".
allowQuotedNewlines

boolean

Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
sourceFormat

string

Optional. The format of the data files. For CSV files, specify "CSV". For datastore backups, specify "DATASTORE_BACKUP". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro, specify "AVRO". For parquet, specify "PARQUET". For orc, specify "ORC". The default value is CSV.
allowJaggedRows

boolean

Optional. Accept rows that are missing trailing optional columns. The missing values are treated as nulls. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. Only applicable to CSV, ignored for other formats.
ignoreUnknownValues

boolean

Optional. Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names in the table schema Avro, Parquet, ORC: Fields in the file schema that don't exist in the table schema.
projectionFields[]

string

If sourceFormat is set to "DATASTORE_BACKUP", indicates which entity properties to load into BigQuery from a Cloud Datastore backup. Property names are case sensitive and must be top-level properties. If no properties are specified, BigQuery loads all properties. If any named property isn't found in the Cloud Datastore backup, an invalid error is returned in the job result.
autodetect

boolean

Optional. Indicates if we should automatically infer the options and schema for CSV and JSON sources.
schemaUpdateOptions[]

string

Allows the schema of the destination table to be updated as a side effect of the load job if a schema is autodetected or supplied in the job configuration. Schema update options are supported in three cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE_DATA; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified:

  • ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema.
  • ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable.
timePartitioning

object (TimePartitioning)

Time-based partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified.
rangePartitioning

object (RangePartitioning)

Range partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified.
clustering

object (Clustering)

Clustering specification for the destination table.
destinationEncryptionConfiguration

object (EncryptionConfiguration)

Custom encryption configuration (e.g., Cloud KMS keys)
useAvroLogicalTypes

boolean

Optional. If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
referenceFileSchemaUri

string

Optional. The user can provide a reference file with the reader schema. This file is only loaded if it is part of source URIs, but is not loaded otherwise. It is enabled for the following formats: AVRO, PARQUET, ORC.
hivePartitioningOptions

object (HivePartitioningOptions)

Optional. When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification.
decimalTargetTypes[]

enum (DecimalTargetType)

Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown.

Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is:

  • (38,9) -> NUMERIC;
  • (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits);
  • (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits);
  • (76,38) -> BIGNUMERIC;
  • (77,38) -> BIGNUMERIC (error if value exceeds supported range).

This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC.

Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
thriftOptions

object (ThriftOptions)

Optional. [Experimental] The load options for Apache Thrift serialized data. It defines the source of IDL bundle that should be used to be parsed as the schema and deserialization options to parse Thrift data.
jsonExtension

enum (JsonExtension)

Optional. Load option to be used together with source_format newline-delimited JSON to indicate that a variant of JSON is being loaded. To load newline-delimited GeoJSON, specify GEOJSON (and source_format must be set to NEWLINE_DELIMITED_JSON).
parquetOptions

object (ParquetOptions)

Optional. Additional properties to set if sourceFormat is set to PARQUET.
preserveAsciiControlCharacters

boolean

Optional. When sourceFormat is set to "CSV", this indicates whether the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') are preserved.
connectionProperties[]

object (ConnectionProperty)

Optional. Connection properties which can modify the load job behavior. Currently, only the 'session_id' connection property is supported, and is used to resolve _SESSION appearing as the dataset id.
createSession

boolean

Optional. If this property is true, the job creates a new session using a randomly generated session_id. To continue using a created session with subsequent queries, pass the existing session identifier as a ConnectionProperty value. The session identifier is returned as part of the SessionInfo message within the query statistics.

The new session's location will be set to Job.JobReference.location if it is present, otherwise it's set to the default location based on existing routing logic.
columnNameCharacterMap

enum (ColumnNameCharacterMap)

Optional. Character map supported for column names in CSV/Parquet loads. Defaults to STRICT and can be overridden by Project Config Service. Using this option with unsupporting load formats will result in an error.
copyFilesOnly

boolean

Optional. [Experimental] Configures the load job to copy files directly to the destination BigLake managed table, bypassing file content reading and rewriting.

Copying files only is supported when all the following are true:

  • source_uris are located in the same Cloud Storage location as the destination table's storage_uri location.
  • source_format is PARQUET.
  • destination_table is an existing BigLake managed table. The table's schema does not have flexible column names. The table's columns do not have type parameters other than precision and scale.
  • No options other than the above are specified.
timeZone

string

Optional. Default time zone that will apply when parsing timestamp values that have no specific time zone.
nullMarkers[]

string

Optional. A list of strings represented as SQL NULL value in a CSV file.

null_marker and null_markers can't be set at the same time. If null_marker is set, null_markers has to be not set. If null_markers is set, null_marker has to be not set. If both null_marker and null_markers are set at the same time, a user error would be thrown. Any strings listed in null_markers, including empty string would be interpreted as SQL NULL. This applies to all column types.
sourceColumnMatch

enum (SourceColumnMatch)

Optional. Controls the strategy used to match loaded columns to the schema. If not set, a sensible default is chosen based on how the schema is provided. If autodetect is used, then columns are matched by name. Otherwise, columns are matched by position. This is done to keep the behavior backward-compatible.
timestampTargetPrecision[]

integer

Precisions (maximum number of total digits in base 10) for seconds of TIMESTAMP types that are allowed to the destination table for autodetection mode.

Available for the formats: CSV, PARQUET, AVRO, and Iceberg External Table.

Possible values include: Not Specified, [], or [6]: timestamp(6) for all auto detected TIMESTAMP columns [6, 12]: timestamp(6) for all auto detected TIMESTAMP columns that have less than 6 digits of subseconds. timestamp(12) for all auto detected TIMESTAMP columns that have more than 6 digits of subseconds. [12]: timestamp(12) for all auto detected TIMESTAMP columns.

The order of the elements in this array is ignored. Inputs that have higher precision than the highest target precision in this array will be truncated.

Union field _date_format.

_date_format can be only one of the following:
dateFormat

string

Optional. Date format used for parsing DATE values.

Union field _datetime_format.

_datetime_format can be only one of the following:
datetimeFormat

string

Optional. Date format used for parsing DATETIME values.

Union field _time_format.

_time_format can be only one of the following:
timeFormat

string

Optional. Date format used for parsing TIME values.

Union field _timestamp_format.

_timestamp_format can be only one of the following:
timestampFormat

string

Optional. Date format used for parsing TIMESTAMP values.

DestinationTableProperties

JSON representation 
{
  "friendlyName": string,
  "description": string,
  "labels": {
    string: string,
    ...
  }
}
Fields
friendlyName

string

Optional. Friendly name for the destination table. If the table already exists, it should be same as the existing friendly name.
description

string

Optional. The description for the destination table. This will only be used if the destination table is newly created. If the table already exists and a value different than the current description is provided, the job will fail.
labels

map (key: string, value: string)

Optional. The labels associated with this table. You can use these to organize and group your tables. This will only be used if the destination table is newly created. If the table already exists and labels are different than the current labels are provided, the job will fail.

An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass": "1.3kg", "count": "3" }.

LabelsEntry

JSON representation 
{
  "key": string,
  "value": string
}
Fields
key

string
value

string

ThriftOptions

JSON representation 
{
  "schemaIdlRootDir": string,
  "schemaIdlUri": string,
  "schemaStruct": string,
  "deserializationOption": enum (DeserializationOption),
  "framingOption": enum (FramingOption),
  "boundaryBytes": string
}
Fields
schemaIdlRootDir

string

Required. The root directory of the IDL file bundle defining the schema. All IDL files that are used to parse the schema should be in this directory. This directory should be different from the source_uris.
schemaIdlUri

string

Required. The Thrift IDL file in the schema_idl_root_dir that should be used as the root file to parse the schema. All included idl files in the schema_idl_uri should also be in the schema_idl_root_dir or its sub-directory.
schemaStruct

string

Required. The root struct specified in schema_idl_uri that should be used to parse the schema.
deserializationOption

enum (DeserializationOption)

Optional. deserialization_option sets how the serialized Thrift should be deserialized. The following options are supported:

  • THRIFT_BINARY_PROTOCOL_OPTION: using TBinaryProtocol to deserialize the data.
framingOption

enum (FramingOption)

Optional. Framing in Thrift means 4 bytes slipped in front of the serialized record or data block to inidicate the size of the followed record or data block. The following options are support:

  • NOT_FRAMED: Serialized Thrift records or data blocks are not framed, there are no 4-byte record size in front of the record.

  • FRAMED_WITH_BIG_ENDIAN: Serialized Thrift records or data blocks are framed with the 4-byte record size in big endian.

  • FRAMED_WITH_LITTLE_ENDIAN: Serialized Thrift records or data blocks are framed with the 4-byte record size in little endian.

One option to frame Thrift record at serialization time is using TFramedTransport, which writes the 4-byte record or data block size in big endian. By default framing_option is set to "NOT_FRAMED".
boundaryBytes

string (bytes format)

Optional. Sequence of bytes used to separate two serialized Thrift data blocks. When it's used with framing_option, the boundary_bytes are expected to be in front of the framed block.

A base64-encoded string.

JobConfigurationTableCopy

JSON representation 
{
  "sourceTable": {
    object (TableReference)
  },
  "sourceTables": [
    {
      object (TableReference)
    }
  ],
  "destinationTable": {
    object (TableReference)
  },
  "createDisposition": string,
  "writeDisposition": string,
  "destinationEncryptionConfiguration": {
    object (EncryptionConfiguration)
  },
  "operationType": enum (OperationType),
  "destinationExpirationTime": string
}
Fields
sourceTable

object (TableReference)

[Pick one] Source table to copy.
sourceTables[]

object (TableReference)

[Pick one] Source tables to copy.
destinationTable

object (TableReference)

[Required] The destination table.
createDisposition

string

Optional. Specifies whether the job is allowed to create new tables. The following values are supported:

  • CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table.
  • CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result.

The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.
writeDisposition

string

Optional. Specifies the action that occurs if the destination table already exists. The following values are supported:

  • WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data and uses the schema and table constraints from the source table.
  • WRITE_APPEND: If the table already exists, BigQuery appends the data to the table.
  • WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result.

The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.
destinationEncryptionConfiguration

object (EncryptionConfiguration)

Custom encryption configuration (e.g., Cloud KMS keys).
operationType

enum (OperationType)

Optional. Supported operation types in table copy job.
destinationExpirationTime

string (Timestamp format)

Optional. The time when the destination table expires. Expired tables will be deleted and their storage reclaimed.

Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z", "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30".

Timestamp

JSON representation 
{
  "seconds": string,
  "nanos": integer
}
Fields
seconds

string (int64 format)

Represents seconds of UTC time since Unix epoch 1970-01-01T00:00:00Z. Must be between -62135596800 and 253402300799 inclusive (which corresponds to 0001-01-01T00:00:00Z to 9999-12-31T23:59:59Z).
nanos

integer

Non-negative fractions of a second at nanosecond resolution. This field is the nanosecond portion of the duration, not an alternative to seconds. Negative second values with fractions must still have non-negative nanos values that count forward in time. Must be between 0 and 999,999,999 inclusive.

JobConfigurationExtract

JSON representation 
{
  "destinationUri": string,
  "destinationUris": [
    string
  ],
  "printHeader": boolean,
  "fieldDelimiter": string,
  "destinationFormat": string,
  "compression": string,
  "useAvroLogicalTypes": boolean,
  "modelExtractOptions": {
    object (ModelExtractOptions)
  },
  "nativeGeographyExportEnabled": boolean,

  // Union field source can be only one of the following:
  "sourceTable": {
    object (TableReference)
  },
  "sourceModel": {
    object (ModelReference)
  }
  // End of list of possible types for union field source.
}
Fields
destinationUri

string

[Pick one] DEPRECATED: Use destinationUris instead, passing only one URI as necessary. The fully-qualified Google Cloud Storage URI where the extracted table should be written.
destinationUris[]

string

[Pick one] A list of fully-qualified Google Cloud Storage URIs where the extracted table should be written.
printHeader

boolean

Optional. Whether to print out a header row in the results. Default is true. Not applicable when extracting models.
fieldDelimiter

string

Optional. When extracting data in CSV format, this defines the delimiter to use between fields in the exported data. Default is ','. Not applicable when extracting models.
destinationFormat

string

Optional. The exported file format. Possible values include CSV, NEWLINE_DELIMITED_JSON, PARQUET, or AVRO for tables and ML_TF_SAVED_MODEL or ML_XGBOOST_BOOSTER for models. The default value for tables is CSV. Tables with nested or repeated fields cannot be exported as CSV. The default value for models is ML_TF_SAVED_MODEL.
compression

string

Optional. The compression type to use for exported files. Possible values include DEFLATE, GZIP, NONE, SNAPPY, and ZSTD. The default value is NONE. Not all compression formats are support for all file formats. DEFLATE is only supported for Avro. ZSTD is only supported for Parquet. Not applicable when extracting models.
useAvroLogicalTypes

boolean

Whether to use logical types when extracting to AVRO format. Not applicable when extracting models.
modelExtractOptions

object (ModelExtractOptions)

Optional. Model extract options only applicable when extracting models.
nativeGeographyExportEnabled

boolean

Optional. Applicable to formats: PARQUET. If enabled, BigQuery to Parquet export will write the native Parquet Geography type instead of the default GeoParquet type.
Union field source. Required. Source reference for the export. source can be only one of the following:
sourceTable

object (TableReference)

A reference to the table being exported.
sourceModel

object (ModelReference)

A reference to the model being exported.

ModelReference

JSON representation 
{
  "projectId": string,
  "datasetId": string,
  "modelId": string
}
Fields
projectId

string

Required. The ID of the project containing this model.
datasetId

string

Required. The ID of the dataset containing this model.
modelId

string

Required. The ID of the model. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.

ModelExtractOptions

JSON representation 
{
  "trialId": string
}
Fields
trialId

string (Int64Value format)

The 1-based ID of the trial to be exported from a hyperparameter tuning model. If not specified, the trial with id = Model.defaultTrialId is exported. This field is ignored for models not trained with hyperparameter tuning.

LabelsEntry

JSON representation 
{
  "key": string,
  "value": string
}
Fields
key

string
value

string

JobReference

JSON representation 
{
  "projectId": string,
  "jobId": string,
  "location": string
}
Fields
projectId

string

Required. The ID of the project containing this job.
jobId

string

Required. The ID of the job. The ID must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), or dashes (-). The maximum length is 1,024 characters.
location

string

Optional. The geographic location of the job. The default value is US.

For more information about BigQuery locations, see: https://cloud.google.com/bigquery/docs/locations

JobStatistics

JSON representation 
{
  "creationTime": string,
  "startTime": string,
  "endTime": string,
  "totalBytesProcessed": string,
  "completionRatio": number,
  "quotaDeferments": [
    string
  ],
  "query": {
    object (JobStatistics2)
  },
  "load": {
    object (JobStatistics3)
  },
  "extract": {
    object (JobStatistics4)
  },
  "copy": {
    object (CopyJobStatistics)
  },
  "totalSlotMs": string,
  "reservationUsage": [
    {
      object (ReservationResourceUsage)
    }
  ],
  "reservation_id": string,
  "numChildJobs": string,
  "parentJobId": string,
  "scriptStatistics": {
    object (ScriptStatistics)
  },
  "rowLevelSecurityStatistics": {
    object (RowLevelSecurityStatistics)
  },
  "dataMaskingStatistics": {
    object (DataMaskingStatistics)
  },
  "transactionInfo": {
    object (TransactionInfo)
  },
  "sessionInfo": {
    object (SessionInfo)
  },
  "finalExecutionDurationMs": string,
  "edition": enum (ReservationEdition),
  "reservationGroupPath": [
    string
  ],
  "globalQueryRemoteRegions": [
    string
  ],
  "parentGlobalQueryJob": {
    object (JobReference)
  }
}
Fields
creationTime

string (int64 format)

Output only. Creation time of this job, in milliseconds since the epoch. This field will be present on all jobs.
startTime

string (int64 format)

Output only. Start time of this job, in milliseconds since the epoch. This field will be present when the job transitions from the PENDING state to either RUNNING or DONE.
endTime

string (int64 format)

Output only. End time of this job, in milliseconds since the epoch. This field will be present whenever a job is in the DONE state.
totalBytesProcessed

string (Int64Value format)

Output only. Total bytes processed for the job.
completionRatio

number

Output only. [TrustedTester] Job progress (0.0 -> 1.0) for LOAD and EXTRACT jobs.
quotaDeferments[]

string

Output only. Quotas which delayed this job's start time.
query

object (JobStatistics2)

Output only. Statistics for a query job.
load

object (JobStatistics3)

Output only. Statistics for a load job.
extract

object (JobStatistics4)

Output only. Statistics for an extract job.
copy

object (CopyJobStatistics)

Output only. Statistics for a copy job.
totalSlotMs

string (Int64Value format)

Output only. Slot-milliseconds for the job.
reservationUsage[]
(deprecated)

object (ReservationResourceUsage)

Output only. Job resource usage breakdown by reservation. This field reported misleading information and will no longer be populated.
reservation_id

string

Output only. Name of the primary reservation assigned to this job. Note that this could be different than reservations reported in the reservation usage field if parent reservations were used to execute this job.
numChildJobs

string (int64 format)

Output only. Number of child jobs executed.
parentJobId

string

Output only. If this is a child job, specifies the job ID of the parent.
scriptStatistics

object (ScriptStatistics)

Output only. If this a child job of a script, specifies information about the context of this job within the script.
rowLevelSecurityStatistics

object (RowLevelSecurityStatistics)

Output only. Statistics for row-level security. Present only for query and extract jobs.
dataMaskingStatistics

object (DataMaskingStatistics)

Output only. Statistics for data-masking. Present only for query and extract jobs.
transactionInfo

object (TransactionInfo)

Output only. [Alpha] Information of the multi-statement transaction if this job is part of one.

This property is only expected on a child job or a job that is in a session. A script parent job is not part of the transaction started in the script.
sessionInfo

object (SessionInfo)

Output only. Information of the session if this job is part of one.
finalExecutionDurationMs

string (int64 format)

Output only. The duration in milliseconds of the execution of the final attempt of this job, as BigQuery may internally re-attempt to execute the job.
edition

enum (ReservationEdition)

Output only. Name of edition corresponding to the reservation for this job at the time of this update.
reservationGroupPath[]

string

Output only. The reservation group path of the reservation assigned to this job. This field has a limit of 10 nested reservation groups. This is to maintain consistency between reservations info schema and jobs info schema. The first reservation group is the root reservation group and the last is the leaf or lowest level reservation group.
globalQueryRemoteRegions[]

string

Output only. The list of remote regions from which a global query accesses data.

This field is populated only for parent global query jobs in the primary execution region. It is empty for child global query jobs and single-region queries. For more information, see Global queries.
parentGlobalQueryJob

object (JobReference)

Output only. Reference to the parent global query job, if this is a child global query job.

This field is populated only for child global query jobs (remote subqueries or cross-region table copy jobs) executed in remote regions on behalf of a global query. It contains the project ID, job ID, and location of the parent global query job. It is unset for parent global query jobs and single-region queries. For more information, see Global queries.

DoubleValue

JSON representation 
{
  "value": number
}
Fields
value

number

The double value.

JobStatistics2

JSON representation 
{
  "queryPlan": [
    {
      object (ExplainQueryStage)
    }
  ],
  "estimatedBytesProcessed": string,
  "timeline": [
    {
      object (QueryTimelineSample)
    }
  ],
  "totalPartitionsProcessed": string,
  "totalBytesProcessed": string,
  "totalBytesProcessedAccuracy": string,
  "totalBytesBilled": string,
  "billingTier": integer,
  "totalSlotMs": string,
  "reservationUsage": [
    {
      object (ReservationResourceUsage)
    }
  ],
  "cacheHit": boolean,
  "referencedTables": [
    {
      object (TableReference)
    }
  ],
  "referencedRoutines": [
    {
      object (RoutineReference)
    }
  ],
  "referencedPropertyGraphs": [
    {
      object (PropertyGraphReference)
    }
  ],
  "schema": {
    object (TableSchema)
  },
  "numDmlAffectedRows": string,
  "dmlStats": {
    object (DmlStats)
  },
  "undeclaredQueryParameters": [
    {
      object (QueryParameter)
    }
  ],
  "statementType": string,
  "ddlOperationPerformed": string,
  "ddlTargetTable": {
    object (TableReference)
  },
  "ddlDestinationTable": {
    object (TableReference)
  },
  "ddlTargetRowAccessPolicy": {
    object (RowAccessPolicyReference)
  },
  "ddlAffectedRowAccessPolicyCount": string,
  "ddlTargetRoutine": {
    object (RoutineReference)
  },
  "ddlTargetDataset": {
    object (DatasetReference)
  },
  "mlStatistics": {
    object (MlStatistics)
  },
  "exportDataStatistics": {
    object (ExportDataStatistics)
  },
  "externalServiceCosts": [
    {
      object (ExternalServiceCost)
    }
  ],
  "biEngineStatistics": {
    object (BiEngineStatistics)
  },
  "loadQueryStatistics": {
    object (LoadQueryStatistics)
  },
  "dclTargetTable": {
    object (TableReference)
  },
  "dclTargetView": {
    object (TableReference)
  },
  "dclTargetDataset": {
    object (DatasetReference)
  },
  "searchStatistics": {
    object (SearchStatistics)
  },
  "vectorSearchStatistics": {
    object (VectorSearchStatistics)
  },
  "performanceInsights": {
    object (PerformanceInsights)
  },
  "queryInfo": {
    object (QueryInfo)
  },
  "sparkStatistics": {
    object (SparkStatistics)
  },
  "transferredBytes": string,
  "materializedViewStatistics": {
    object (MaterializedViewStatistics)
  },
  "metadataCacheStatistics": {
    object (MetadataCacheStatistics)
  },
  "incrementalResultStats": {
    object (IncrementalResultStats)
  },
  "genAiStats": {
    object (GenAiStats)
  },
  "objectStorageStats": [
    {
      object (ObjectStorageStats)
    }
  ],

  // Union field _total_services_sku_slot_ms can be only one of the following:
  "totalServicesSkuSlotMs": string
  // End of list of possible types for union field _total_services_sku_slot_ms.
}
Fields
queryPlan[]

object (ExplainQueryStage)

Output only. Describes execution plan for the query.
estimatedBytesProcessed

string (Int64Value format)

Output only. The original estimate of bytes processed for the job.
timeline[]

object (QueryTimelineSample)

Output only. Describes a timeline of job execution.
totalPartitionsProcessed

string (Int64Value format)

Output only. Total number of partitions processed from all partitioned tables referenced in the job.
totalBytesProcessed

string (Int64Value format)

Output only. Total bytes processed for the job.
totalBytesProcessedAccuracy

string

Output only. For dry-run jobs, totalBytesProcessed is an estimate and this field specifies the accuracy of the estimate. Possible values can be: UNKNOWN: accuracy of the estimate is unknown. PRECISE: estimate is precise. LOWER_BOUND: estimate is lower bound of what the query would cost. UPPER_BOUND: estimate is upper bound of what the query would cost.
totalBytesBilled

string (Int64Value format)

Output only. If the project is configured to use on-demand pricing, then this field contains the total bytes billed for the job. If the project is configured to use flat-rate pricing, then you are not billed for bytes and this field is informational only.
billingTier

integer

Output only. Billing tier for the job. This is a BigQuery-specific concept which is not related to the Google Cloud notion of "free tier". The value here is a measure of the query's resource consumption relative to the amount of data scanned. For on-demand queries, the limit is 100, and all queries within this limit are billed at the standard on-demand rates. On-demand queries that exceed this limit will fail with a billingTierLimitExceeded error.
totalSlotMs

string (Int64Value format)

Output only. Slot-milliseconds for the job.
reservationUsage[]
(deprecated)

object (ReservationResourceUsage)

Output only. Job resource usage breakdown by reservation. This field reported misleading information and will no longer be populated.
cacheHit

boolean

Output only. Whether the query result was fetched from the query cache.
referencedTables[]

object (TableReference)

Output only. Referenced tables for the job.
referencedRoutines[]

object (RoutineReference)

Output only. Referenced routines for the job.
referencedPropertyGraphs[]

object (PropertyGraphReference)

Output only. Referenced property graphs for the job. Queries that reference more than 50 property graphs will not have a complete list.
schema

object (TableSchema)

Output only. The schema of the results. Present only for successful dry run of non-legacy SQL queries.
numDmlAffectedRows

string (Int64Value format)

Output only. The number of rows affected by a DML statement. Present only for DML statements INSERT, UPDATE or DELETE.
dmlStats

object (DmlStats)

Output only. Detailed statistics for DML statements INSERT, UPDATE, DELETE, MERGE or TRUNCATE.
undeclaredQueryParameters[]

object (QueryParameter)

Output only. GoogleSQL only: list of undeclared query parameters detected during a dry run validation.
statementType

string

Output only. The type of query statement, if valid. Possible values:
ddlOperationPerformed

string

Output only. The DDL operation performed, possibly dependent on the pre-existence of the DDL target.
ddlTargetTable

object (TableReference)

Output only. The DDL target table. Present only for CREATE/DROP TABLE/VIEW and DROP ALL ROW ACCESS POLICIES queries.
ddlDestinationTable

object (TableReference)

Output only. The table after rename. Present only for ALTER TABLE RENAME TO query.
ddlTargetRowAccessPolicy

object (RowAccessPolicyReference)

Output only. The DDL target row access policy. Present only for CREATE/DROP ROW ACCESS POLICY queries.
ddlAffectedRowAccessPolicyCount

string (Int64Value format)

Output only. The number of row access policies affected by a DDL statement. Present only for DROP ALL ROW ACCESS POLICIES queries.
ddlTargetRoutine

object (RoutineReference)

Output only. [Beta] The DDL target routine. Present only for CREATE/DROP FUNCTION/PROCEDURE queries.
ddlTargetDataset

object (DatasetReference)

Output only. The DDL target dataset. Present only for CREATE/ALTER/DROP SCHEMA(dataset) queries.
mlStatistics

object (MlStatistics)

Output only. Statistics of a BigQuery ML training job.
exportDataStatistics

object (ExportDataStatistics)

Output only. Stats for EXPORT DATA statement.
externalServiceCosts[]

object (ExternalServiceCost)

Output only. Job cost breakdown as bigquery internal cost and external service costs.
biEngineStatistics

object (BiEngineStatistics)

Output only. BI Engine specific Statistics.
loadQueryStatistics

object (LoadQueryStatistics)

Output only. Statistics for a LOAD query.
dclTargetTable

object (TableReference)

Output only. Referenced table for DCL statement.
dclTargetView

object (TableReference)

Output only. Referenced view for DCL statement.
dclTargetDataset

object (DatasetReference)

Output only. Referenced dataset for DCL statement.
searchStatistics

object (SearchStatistics)

Output only. Search query specific statistics.
vectorSearchStatistics

object (VectorSearchStatistics)

Output only. Vector Search query specific statistics.
performanceInsights

object (PerformanceInsights)

Output only. Performance insights.
queryInfo

object (QueryInfo)

Output only. Query optimization information for a QUERY job.
sparkStatistics

object (SparkStatistics)

Output only. Statistics of a Spark procedure job.
transferredBytes

string (Int64Value format)

Output only. Total bytes transferred for BigQuery Omni queries from the remote cloud back to Google Cloud. This tracks data movement over Google-managed connections (like query results). It doesn't include input data read from the external data lake (for example, S3) because that data stays within the remote cloud.
materializedViewStatistics

object (MaterializedViewStatistics)

Output only. Statistics of materialized views of a query job.
metadataCacheStatistics

object (MetadataCacheStatistics)

Output only. Statistics of metadata cache usage in a query for BigLake tables.
incrementalResultStats

object (IncrementalResultStats)

Output only. Statistics related to incremental query results, if enabled for the query. This feature is not yet available.
genAiStats

object (GenAiStats)

Output only. Statistics related to GenAI usage in the query.
objectStorageStats[]

object (ObjectStorageStats)

Output only. Storage and caching statistics per cloud provider for queries over object storage.

Union field _total_services_sku_slot_ms.

_total_services_sku_slot_ms can be only one of the following:
totalServicesSkuSlotMs

string (int64 format)

Output only. Total slot milliseconds for the job that ran on external services and billed on the services SKU. This field is only populated for jobs that have external service costs, and is the total of the usage for costs whose billing method is "SERVICES_SKU".

ExplainQueryStage

JSON representation 
{
  "name": string,
  "id": string,
  "startMs": string,
  "endMs": string,
  "inputStages": [
    string
  ],
  "waitRatioAvg": number,
  "waitMsAvg": string,
  "waitRatioMax": number,
  "waitMsMax": string,
  "readRatioAvg": number,
  "readMsAvg": string,
  "readRatioMax": number,
  "readMsMax": string,
  "computeRatioAvg": number,
  "computeMsAvg": string,
  "computeRatioMax": number,
  "computeMsMax": string,
  "writeRatioAvg": number,
  "writeMsAvg": string,
  "writeRatioMax": number,
  "writeMsMax": string,
  "shuffleOutputBytes": string,
  "shuffleOutputBytesSpilled": string,
  "recordsRead": string,
  "recordsWritten": string,
  "parallelInputs": string,
  "completedParallelInputs": string,
  "status": string,
  "steps": [
    {
      object (ExplainQueryStep)
    }
  ],
  "slotMs": string,
  "computeMode": enum (ComputeMode)
}
Fields
name

string

Human-readable name for the stage.
id

string (Int64Value format)

Unique ID for the stage within the plan.
startMs

string (int64 format)

Stage start time represented as milliseconds since the epoch.
endMs

string (int64 format)

Stage end time represented as milliseconds since the epoch.
inputStages[]

string (int64 format)

IDs for stages that are inputs to this stage.
waitRatioAvg

number

Relative amount of time the average shard spent waiting to be scheduled.
waitMsAvg

string (Int64Value format)

Milliseconds the average shard spent waiting to be scheduled.
waitRatioMax

number

Relative amount of time the slowest shard spent waiting to be scheduled.
waitMsMax

string (Int64Value format)

Milliseconds the slowest shard spent waiting to be scheduled.
readRatioAvg

number

Relative amount of time the average shard spent reading input.
readMsAvg

string (Int64Value format)

Milliseconds the average shard spent reading input.
readRatioMax

number

Relative amount of time the slowest shard spent reading input.
readMsMax

string (Int64Value format)

Milliseconds the slowest shard spent reading input.
computeRatioAvg

number

Relative amount of time the average shard spent on CPU-bound tasks.
computeMsAvg

string (Int64Value format)

Milliseconds the average shard spent on CPU-bound tasks.
computeRatioMax

number

Relative amount of time the slowest shard spent on CPU-bound tasks.
computeMsMax

string (Int64Value format)

Milliseconds the slowest shard spent on CPU-bound tasks.
writeRatioAvg

number

Relative amount of time the average shard spent on writing output.
writeMsAvg

string (Int64Value format)

Milliseconds the average shard spent on writing output.
writeRatioMax

number

Relative amount of time the slowest shard spent on writing output.
writeMsMax

string (Int64Value format)

Milliseconds the slowest shard spent on writing output.
shuffleOutputBytes

string (Int64Value format)

Total number of bytes written to shuffle.
shuffleOutputBytesSpilled

string (Int64Value format)

Total number of bytes written to shuffle and spilled to disk.
recordsRead

string (Int64Value format)

Number of records read into the stage.
recordsWritten

string (Int64Value format)

Number of records written by the stage.
parallelInputs

string (Int64Value format)

Number of parallel input segments to be processed
completedParallelInputs

string (Int64Value format)

Number of parallel input segments completed.
status

string

Current status for this stage.
steps[]

object (ExplainQueryStep)

List of operations within the stage in dependency order (approximately chronological).
slotMs

string (Int64Value format)

Slot-milliseconds used by the stage.
computeMode

enum (ComputeMode)

Output only. Compute mode for this stage.

ExplainQueryStep

JSON representation 
{
  "kind": string,
  "substeps": [
    string
  ]
}
Fields
kind

string

Machine-readable operation type.
substeps[]

string

Human-readable description of the step(s).

QueryTimelineSample

JSON representation 
{
  "elapsedMs": string,
  "totalSlotMs": string,
  "pendingUnits": string,
  "completedUnits": string,
  "activeUnits": string,
  "shuffleRamUsageRatio": number,
  "estimatedRunnableUnits": string
}
Fields
elapsedMs

string (Int64Value format)

Milliseconds elapsed since the start of query execution.
totalSlotMs

string (Int64Value format)

Cumulative slot-ms consumed by the query.
pendingUnits

string (Int64Value format)

Total units of work remaining for the query. This number can be revised (increased or decreased) while the query is running.
completedUnits

string (Int64Value format)

Total parallel units of work completed by this query.
activeUnits

string (Int64Value format)

Total number of active workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample.
shuffleRamUsageRatio

number

Total shuffle usage ratio in shuffle RAM per reservation of this query. This will be provided for reservation customers only.
estimatedRunnableUnits

string (Int64Value format)

Units of work that can be scheduled immediately. Providing additional slots for these units of work will accelerate the query, if no other query in the reservation needs additional slots.

ReservationResourceUsage

JSON representation 
{
  "name": string,
  "slotMs": string
}
Fields
name

string

Reservation name or "unreserved" for on-demand resource usage and multi-statement queries.
slotMs

string (Int64Value format)

Total slot milliseconds used by the reservation for a particular job.

RoutineReference

JSON representation 
{
  "projectId": string,
  "datasetId": string,
  "routineId": string
}
Fields
projectId

string

Required. The ID of the project containing this routine.
datasetId

string

Required. The ID of the dataset containing this routine.
routineId

string

Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.

PropertyGraphReference

JSON representation 
{
  "projectId": string,
  "datasetId": string,
  "propertyGraphId": string
}
Fields
projectId

string

Required. The ID of the project containing this property graph.
datasetId

string

Required. The ID of the dataset containing this property graph.
propertyGraphId

string

Required. The ID of the property graph. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.

DmlStats

JSON representation 
{
  "insertedRowCount": string,
  "deletedRowCount": string,
  "updatedRowCount": string,
  "dmlMode": enum (DmlMode),
  "fineGrainedDmlUnusedReason": enum (FineGrainedDmlUnusedReason)
}
Fields
insertedRowCount

string (Int64Value format)

Output only. Number of inserted Rows. Populated by DML INSERT and MERGE statements
deletedRowCount

string (Int64Value format)

Output only. Number of deleted Rows. populated by DML DELETE, MERGE and TRUNCATE statements.
updatedRowCount

string (Int64Value format)

Output only. Number of updated Rows. Populated by DML UPDATE and MERGE statements.
dmlMode

enum (DmlMode)

Output only. DML mode used.
fineGrainedDmlUnusedReason

enum (FineGrainedDmlUnusedReason)

Output only. Reason for disabling fine-grained DML if applicable.

RowAccessPolicyReference

JSON representation 
{
  "projectId": string,
  "datasetId": string,
  "tableId": string,
  "policyId": string
}
Fields
projectId

string

Required. The ID of the project containing this row access policy.
datasetId

string

Required. The ID of the dataset containing this row access policy.
tableId

string

Required. The ID of the table containing this row access policy.
policyId

string

Required. The ID of the row access policy. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.

MlStatistics

JSON representation 
{
  "maxIterations": string,
  "iterationResults": [
    {
      object (IterationResult)
    }
  ],
  "modelType": enum (ModelType),
  "trainingType": enum (TrainingType),
  "hparamTrials": [
    {
      object (HparamTuningTrial)
    }
  ]
}
Fields
maxIterations

string (int64 format)

Output only. Maximum number of iterations specified as max_iterations in the 'CREATE MODEL' query. The actual number of iterations may be less than this number due to early stop.
iterationResults[]

object (IterationResult)

Results for all completed iterations. Empty for hyperparameter tuning jobs.
modelType

enum (ModelType)

Output only. The type of the model that is being trained.
trainingType

enum (TrainingType)

Output only. Training type of the job.
hparamTrials[]

object (HparamTuningTrial)

Output only. Trials of a hyperparameter tuning job sorted by trial_id.

IterationResult

JSON representation 
{
  "index": integer,
  "durationMs": string,
  "trainingLoss": number,
  "evalLoss": number,
  "learnRate": number,
  "clusterInfos": [
    {
      object (ClusterInfo)
    }
  ],
  "arimaResult": {
    object (ArimaResult)
  },
  "principalComponentInfos": [
    {
      object (PrincipalComponentInfo)
    }
  ]
}
Fields
index

integer

Index of the iteration, 0 based.
durationMs

string (Int64Value format)

Time taken to run the iteration in milliseconds.
trainingLoss

number

Loss computed on the training data at the end of iteration.
evalLoss

number

Loss computed on the eval data at the end of iteration.
learnRate

number

Learn rate used for this iteration.
clusterInfos[]

object (ClusterInfo)

Information about top clusters for clustering models.
arimaResult

object (ArimaResult)

Arima result.
principalComponentInfos[]

object (PrincipalComponentInfo)

The information of the principal components.

ClusterInfo

JSON representation 
{
  "centroidId": string,
  "clusterRadius": number,
  "clusterSize": string
}
Fields
centroidId

string (int64 format)

Centroid id.
clusterRadius

number

Cluster radius, the average distance from centroid to each point assigned to the cluster.
clusterSize

string (Int64Value format)

Cluster size, the total number of points assigned to the cluster.

ArimaResult

JSON representation 
{
  "arimaModelInfo": [
    {
      object (ArimaModelInfo)
    }
  ],
  "seasonalPeriods": [
    enum (SeasonalPeriodType)
  ]
}
Fields
arimaModelInfo[]

object (ArimaModelInfo)

This message is repeated because there are multiple arima models fitted in auto-arima. For non-auto-arima model, its size is one.
seasonalPeriods[]

enum (SeasonalPeriodType)

Seasonal periods. Repeated because multiple periods are supported for one time series.

ArimaModelInfo

JSON representation 
{
  "nonSeasonalOrder": {
    object (ArimaOrder)
  },
  "arimaCoefficients": {
    object (ArimaCoefficients)
  },
  "arimaFittingMetrics": {
    object (ArimaFittingMetrics)
  },
  "hasDrift": boolean,
  "timeSeriesId": string,
  "timeSeriesIds": [
    string
  ],
  "seasonalPeriods": [
    enum (SeasonalPeriodType)
  ],
  "hasHolidayEffect": boolean,
  "hasSpikesAndDips": boolean,
  "hasStepChanges": boolean
}
Fields
nonSeasonalOrder

object (ArimaOrder)

Non-seasonal order.
arimaCoefficients

object (ArimaCoefficients)

Arima coefficients.
arimaFittingMetrics

object (ArimaFittingMetrics)

Arima fitting metrics.
hasDrift

boolean

Whether Arima model fitted with drift or not. It is always false when d is not 1.
timeSeriesId

string

The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used.
timeSeriesIds[]

string

The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns.
seasonalPeriods[]

enum (SeasonalPeriodType)

Seasonal periods. Repeated because multiple periods are supported for one time series.
hasHolidayEffect

boolean

If true, holiday_effect is a part of time series decomposition result.
hasSpikesAndDips

boolean

If true, spikes_and_dips is a part of time series decomposition result.
hasStepChanges

boolean

If true, step_changes is a part of time series decomposition result.

ArimaOrder

JSON representation 
{
  "p": string,
  "d": string,
  "q": string
}
Fields
p

string (Int64Value format)

Order of the autoregressive part.
d

string (Int64Value format)

Order of the differencing part.
q

string (Int64Value format)

Order of the moving-average part.

ArimaCoefficients

JSON representation 
{
  "autoRegressiveCoefficients": [
    number
  ],
  "movingAverageCoefficients": [
    number
  ],
  "interceptCoefficient": number
}
Fields
autoRegressiveCoefficients[]

number

Auto-regressive coefficients, an array of double.
movingAverageCoefficients[]

number

Moving-average coefficients, an array of double.
interceptCoefficient

number

Intercept coefficient, just a double not an array.

ArimaFittingMetrics

JSON representation 
{
  "logLikelihood": number,
  "aic": number,
  "variance": number
}
Fields
logLikelihood

number

Log-likelihood.
aic

number

AIC.
variance

number

Variance.

PrincipalComponentInfo

JSON representation 
{
  "principalComponentId": string,
  "explainedVariance": number,
  "explainedVarianceRatio": number,
  "cumulativeExplainedVarianceRatio": number
}
Fields
principalComponentId

string (Int64Value format)

Id of the principal component.
explainedVariance

number

Explained variance by this principal component, which is simply the eigenvalue.
explainedVarianceRatio

number

Explained_variance over the total explained variance.
cumulativeExplainedVarianceRatio

number

The explained_variance is pre-ordered in the descending order to compute the cumulative explained variance ratio.

HparamTuningTrial

JSON representation 
{
  "trialId": string,
  "startTimeMs": string,
  "endTimeMs": string,
  "hparams": {
    object (TrainingOptions)
  },
  "evaluationMetrics": {
    object (EvaluationMetrics)
  },
  "status": enum (TrialStatus),
  "errorMessage": string,
  "trainingLoss": number,
  "evalLoss": number,
  "hparamTuningEvaluationMetrics": {
    object (EvaluationMetrics)
  }
}
Fields
trialId

string (int64 format)

1-based index of the trial.
startTimeMs

string (int64 format)

Starting time of the trial.
endTimeMs

string (int64 format)

Ending time of the trial.
hparams

object (TrainingOptions)

The hyperprameters selected for this trial.
evaluationMetrics

object (EvaluationMetrics)

Evaluation metrics of this trial calculated on the test data. Empty in Job API.
status

enum (TrialStatus)

The status of the trial.
errorMessage

string

Error message for FAILED and INFEASIBLE trial.
trainingLoss

number

Loss computed on the training data at the end of trial.
evalLoss

number

Loss computed on the eval data at the end of trial.
hparamTuningEvaluationMetrics

object (EvaluationMetrics)

Hyperparameter tuning evaluation metrics of this trial calculated on the eval data. Unlike evaluation_metrics, only the fields corresponding to the hparam_tuning_objectives are set.

TrainingOptions

JSON representation 
{
  "maxIterations": string,
  "lossType": enum (LossType),
  "learnRate": number,
  "l1Regularization": number,
  "l2Regularization": number,
  "minRelativeProgress": number,
  "warmStart": boolean,
  "earlyStop": boolean,
  "inputLabelColumns": [
    string
  ],
  "dataSplitMethod": enum (DataSplitMethod),
  "dataSplitEvalFraction": number,
  "dataSplitColumn": string,
  "learnRateStrategy": enum (LearnRateStrategy),
  "initialLearnRate": number,
  "labelClassWeights": {
    string: number,
    ...
  },
  "userColumn": string,
  "itemColumn": string,
  "distanceType": enum (DistanceType),
  "numClusters": string,
  "modelUri": string,
  "optimizationStrategy": enum (OptimizationStrategy),
  "hiddenUnits": [
    string
  ],
  "batchSize": string,
  "dropout": number,
  "maxTreeDepth": string,
  "subsample": number,
  "minSplitLoss": number,
  "boosterType": enum (BoosterType),
  "numParallelTree": string,
  "dartNormalizeType": enum (DartNormalizeType),
  "treeMethod": enum (TreeMethod),
  "minTreeChildWeight": string,
  "colsampleBytree": number,
  "colsampleBylevel": number,
  "colsampleBynode": number,
  "numFactors": string,
  "feedbackType": enum (FeedbackType),
  "walsAlpha": number,
  "kmeansInitializationMethod": enum (KmeansInitializationMethod),
  "kmeansInitializationColumn": string,
  "timeSeriesTimestampColumn": string,
  "timeSeriesDataColumn": string,
  "autoArima": boolean,
  "nonSeasonalOrder": {
    object (ArimaOrder)
  },
  "dataFrequency": enum (DataFrequency),
  "calculatePValues": boolean,
  "includeDrift": boolean,
  "holidayRegion": enum (HolidayRegion),
  "holidayRegions": [
    enum (HolidayRegion)
  ],
  "timeSeriesIdColumn": string,
  "timeSeriesIdColumns": [
    string
  ],
  "forecastLimitLowerBound": number,
  "forecastLimitUpperBound": number,
  "horizon": string,
  "autoArimaMaxOrder": string,
  "autoArimaMinOrder": string,
  "numTrials": string,
  "maxParallelTrials": string,
  "hparamTuningObjectives": [
    enum (HparamTuningObjective)
  ],
  "decomposeTimeSeries": boolean,
  "cleanSpikesAndDips": boolean,
  "adjustStepChanges": boolean,
  "enableGlobalExplain": boolean,
  "sampledShapleyNumPaths": string,
  "integratedGradientsNumSteps": string,
  "categoryEncodingMethod": enum (EncodingMethod),
  "tfVersion": string,
  "colorSpace": enum (ColorSpace),
  "instanceWeightColumn": string,
  "trendSmoothingWindowSize": string,
  "timeSeriesLengthFraction": number,
  "minTimeSeriesLength": string,
  "maxTimeSeriesLength": string,
  "xgboostVersion": string,
  "approxGlobalFeatureContrib": boolean,
  "fitIntercept": boolean,
  "numPrincipalComponents": string,
  "pcaExplainedVarianceRatio": number,
  "scaleFeatures": boolean,
  "pcaSolver": enum (PcaSolver),
  "autoClassWeights": boolean,
  "activationFn": string,
  "optimizer": string,
  "budgetHours": number,
  "standardizeFeatures": boolean,
  "l1RegActivation": number,
  "modelRegistry": enum (ModelRegistry),
  "vertexAiModelVersionAliases": [
    string
  ],
  "dimensionIdColumns": [
    string
  ],
  "reservationAffinityValues": [
    string
  ],

  // Union field _contribution_metric can be only one of the following:
  "contributionMetric": string
  // End of list of possible types for union field _contribution_metric.

  // Union field _is_test_column can be only one of the following:
  "isTestColumn": string
  // End of list of possible types for union field _is_test_column.

  // Union field _min_apriori_support can be only one of the following:
  "minAprioriSupport": number
  // End of list of possible types for union field _min_apriori_support.

  // Union field external_model_id can be only one of the following:
  "huggingFaceModelId": string,
  "modelGardenModelName": string
  // End of list of possible types for union field external_model_id.

  // Union field _endpoint_idle_ttl can be only one of the following:
  "endpointIdleTtl": string
  // End of list of possible types for union field _endpoint_idle_ttl.

  // Union field _machine_type can be only one of the following:
  "machineType": string
  // End of list of possible types for union field _machine_type.

  // Union field _min_replica_count can be only one of the following:
  "minReplicaCount": string
  // End of list of possible types for union field _min_replica_count.

  // Union field _max_replica_count can be only one of the following:
  "maxReplicaCount": string
  // End of list of possible types for union field _max_replica_count.

  // Union field _reservation_affinity_type can be only one of the following:
  "reservationAffinityType": enum (ReservationAffinityType)
  // End of list of possible types for union field _reservation_affinity_type.

  // Union field _reservation_affinity_key can be only one of the following:
  "reservationAffinityKey": string
  // End of list of possible types for union field _reservation_affinity_key.
}
Fields
maxIterations

string (int64 format)

The maximum number of iterations in training. Used only for iterative training algorithms.
lossType

enum (LossType)

Type of loss function used during training run.
learnRate

number

Learning rate in training. Used only for iterative training algorithms.
l1Regularization

number

L1 regularization coefficient.
l2Regularization

number

L2 regularization coefficient.
minRelativeProgress

number

When early_stop is true, stops training when accuracy improvement is less than 'min_relative_progress'. Used only for iterative training algorithms.
warmStart

boolean

Whether to train a model from the last checkpoint.
earlyStop

boolean

Whether to stop early when the loss doesn't improve significantly any more (compared to min_relative_progress). Used only for iterative training algorithms.
inputLabelColumns[]

string

Name of input label columns in training data.
dataSplitMethod

enum (DataSplitMethod)

The data split type for training and evaluation, e.g. RANDOM.
dataSplitEvalFraction

number

The fraction of evaluation data over the whole input data. The rest of data will be used as training data. The format should be double. Accurate to two decimal places. Default value is 0.2.
dataSplitColumn

string

The column to split data with. This column won't be used as a feature. 1. When data_split_method is CUSTOM, the corresponding column should be boolean. The rows with true value tag are eval data, and the false are training data. 2. When data_split_method is SEQ, the first DATA_SPLIT_EVAL_FRACTION rows (from smallest to largest) in the corresponding column are used as training data, and the rest are eval data. It respects the order in Orderable data types: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#data_type_properties
learnRateStrategy

enum (LearnRateStrategy)

The strategy to determine learn rate for the current iteration.
initialLearnRate

number

Specifies the initial learning rate for the line search learn rate strategy.
labelClassWeights

map (key: string, value: number)

Weights associated with each label class, for rebalancing the training data. Only applicable for classification models.

An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass": "1.3kg", "count": "3" }.
userColumn

string

User column specified for matrix factorization models.
itemColumn

string

Item column specified for matrix factorization models.
distanceType

enum (DistanceType)

Distance type for clustering models.
numClusters

string (int64 format)

Number of clusters for clustering models.
modelUri

string

Google Cloud Storage URI from which the model was imported. Only applicable for imported models.
optimizationStrategy

enum (OptimizationStrategy)

Optimization strategy for training linear regression models.
hiddenUnits[]

string (int64 format)

Hidden units for dnn models.
batchSize

string (int64 format)

Batch size for dnn models.
dropout

number

Dropout probability for dnn models.
maxTreeDepth

string (int64 format)

Maximum depth of a tree for boosted tree models.
subsample

number

Subsample fraction of the training data to grow tree to prevent overfitting for boosted tree models.
minSplitLoss

number

Minimum split loss for boosted tree models.
boosterType

enum (BoosterType)

Booster type for boosted tree models.
numParallelTree

string (Int64Value format)

Number of parallel trees constructed during each iteration for boosted tree models.
dartNormalizeType

enum (DartNormalizeType)

Type of normalization algorithm for boosted tree models using dart booster.
treeMethod

enum (TreeMethod)

Tree construction algorithm for boosted tree models.
minTreeChildWeight

string (Int64Value format)

Minimum sum of instance weight needed in a child for boosted tree models.
colsampleBytree

number

Subsample ratio of columns when constructing each tree for boosted tree models.
colsampleBylevel

number

Subsample ratio of columns for each level for boosted tree models.
colsampleBynode

number

Subsample ratio of columns for each node(split) for boosted tree models.
numFactors

string (int64 format)

Num factors specified for matrix factorization models.
feedbackType

enum (FeedbackType)

Feedback type that specifies which algorithm to run for matrix factorization.
walsAlpha

number

Hyperparameter for matrix factoration when implicit feedback type is specified.
kmeansInitializationMethod

enum (KmeansInitializationMethod)

The method used to initialize the centroids for kmeans algorithm.
kmeansInitializationColumn

string

The column used to provide the initial centroids for kmeans algorithm when kmeans_initialization_method is CUSTOM.
timeSeriesTimestampColumn

string

Column to be designated as time series timestamp for ARIMA model.
timeSeriesDataColumn

string

Column to be designated as time series data for ARIMA model.
autoArima

boolean

Whether to enable auto ARIMA or not.
nonSeasonalOrder

object (ArimaOrder)

A specification of the non-seasonal part of the ARIMA model: the three components (p, d, q) are the AR order, the degree of differencing, and the MA order.
dataFrequency

enum (DataFrequency)

The data frequency of a time series.
calculatePValues

boolean

Whether or not p-value test should be computed for this model. Only available for linear and logistic regression models.
includeDrift

boolean

Include drift when fitting an ARIMA model.
holidayRegion

enum (HolidayRegion)

The geographical region based on which the holidays are considered in time series modeling. If a valid value is specified, then holiday effects modeling is enabled.
holidayRegions[]

enum (HolidayRegion)

A list of geographical regions that are used for time series modeling.
timeSeriesIdColumn

string

The time series id column that was used during ARIMA model training.
timeSeriesIdColumns[]

string

The time series id columns that were used during ARIMA model training.
forecastLimitLowerBound

number

The forecast limit lower bound that was used during ARIMA model training with limits. To see more details of the algorithm: https://otexts.com/fpp2/limits.html
forecastLimitUpperBound

number

The forecast limit upper bound that was used during ARIMA model training with limits.
horizon

string (int64 format)

The number of periods ahead that need to be forecasted.
autoArimaMaxOrder

string (int64 format)

The max value of the sum of non-seasonal p and q.
autoArimaMinOrder

string (int64 format)

The min value of the sum of non-seasonal p and q.
numTrials

string (int64 format)

Number of trials to run this hyperparameter tuning job.
maxParallelTrials

string (int64 format)

Maximum number of trials to run in parallel.
hparamTuningObjectives[]

enum (HparamTuningObjective)

The target evaluation metrics to optimize the hyperparameters for.
decomposeTimeSeries

boolean

If true, perform decompose time series and save the results.
cleanSpikesAndDips

boolean

If true, clean spikes and dips in the input time series.
adjustStepChanges

boolean

If true, detect step changes and make data adjustment in the input time series.
enableGlobalExplain

boolean

If true, enable global explanation during training.
sampledShapleyNumPaths

string (int64 format)

Number of paths for the sampled Shapley explain method.
integratedGradientsNumSteps

string (int64 format)

Number of integral steps for the integrated gradients explain method.
categoryEncodingMethod

enum (EncodingMethod)

Categorical feature encoding method.
tfVersion

string

Based on the selected TF version, the corresponding docker image is used to train external models.
colorSpace

enum (ColorSpace)

Enums for color space, used for processing images in Object Table. See more details at https://www.tensorflow.org/io/tutorials/colorspace.
instanceWeightColumn

string

Name of the instance weight column for training data. This column isn't be used as a feature.
trendSmoothingWindowSize

string (int64 format)

Smoothing window size for the trend component. When a positive value is specified, a center moving average smoothing is applied on the history trend. When the smoothing window is out of the boundary at the beginning or the end of the trend, the first element or the last element is padded to fill the smoothing window before the average is applied.
timeSeriesLengthFraction

number

The fraction of the interpolated length of the time series that's used to model the time series trend component. All of the time points of the time series are used to model the non-trend component. This training option accelerates modeling training without sacrificing much forecasting accuracy. You can use this option with minTimeSeriesLength but not with maxTimeSeriesLength.
minTimeSeriesLength

string (int64 format)

The minimum number of time points in a time series that are used in modeling the trend component of the time series. If you use this option you must also set the timeSeriesLengthFraction option. This training option ensures that enough time points are available when you use timeSeriesLengthFraction in trend modeling. This is particularly important when forecasting multiple time series in a single query using timeSeriesIdColumn. If the total number of time points is less than the minTimeSeriesLength value, then the query uses all available time points.
maxTimeSeriesLength

string (int64 format)

The maximum number of time points in a time series that can be used in modeling the trend component of the time series. Don't use this option with the timeSeriesLengthFraction or minTimeSeriesLength options.
xgboostVersion

string

User-selected XGBoost versions for training of XGBoost models.
approxGlobalFeatureContrib

boolean

Whether to use approximate feature contribution method in XGBoost model explanation for global explain.
fitIntercept

boolean

Whether the model should include intercept during model training.
numPrincipalComponents

string (int64 format)

Number of principal components to keep in the PCA model. Must be <= the number of features.
pcaExplainedVarianceRatio

number

The minimum ratio of cumulative explained variance that needs to be given by the PCA model.
scaleFeatures

boolean

If true, scale the feature values by dividing the feature standard deviation. Currently only apply to PCA.
pcaSolver

enum (PcaSolver)

The solver for PCA.
autoClassWeights

boolean

Whether to calculate class weights automatically based on the popularity of each label.
activationFn

string

Activation function of the neural nets.
optimizer

string

Optimizer used for training the neural nets.
budgetHours

number

Budget in hours for AutoML training.
standardizeFeatures

boolean

Whether to standardize numerical features. Default to true.
l1RegActivation

number

L1 regularization coefficient to activations.
modelRegistry

enum (ModelRegistry)

The model registry.
vertexAiModelVersionAliases[]

string

The version aliases to apply in Vertex AI model registry. Always overwrite if the version aliases exists in a existing model.
dimensionIdColumns[]

string

Optional. Names of the columns to slice on. Applies to contribution analysis models.
reservationAffinityValues[]

string

Corresponds to the label values of a reservation resource used by Vertex AI. This must be the full resource name of the reservation or reservation block.

Union field _contribution_metric.

_contribution_metric can be only one of the following:
contributionMetric

string

The contribution metric. Applies to contribution analysis models. Allowed formats supported are for summable and summable ratio contribution metrics. These include expressions such as SUM(x) or SUM(x)/SUM(y), where x and y are column names from the base table.

Union field _is_test_column.

_is_test_column can be only one of the following:
isTestColumn

string

Name of the column used to determine the rows corresponding to control and test. Applies to contribution analysis models.

Union field _min_apriori_support.

_min_apriori_support can be only one of the following:
minAprioriSupport

number

The apriori support minimum. Applies to contribution analysis models.
Union field external_model_id. The id that uniquely identifies an external model. external_model_id can be only one of the following:
huggingFaceModelId

string

The id of a Hugging Face model. For example, google/gemma-2-2b-it.
modelGardenModelName

string

The name of a Vertex model garden publisher model. Format is publishers/{publisher}/models/{model}@{optional_version_id}.

Union field _endpoint_idle_ttl.

_endpoint_idle_ttl can be only one of the following:
endpointIdleTtl

string (Duration format)

The idle TTL of the endpoint before the resources get destroyed. The default value is 6.5 hours.

A duration in seconds with up to nine fractional digits, ending with 's'. Example: "3.5s".

Union field _machine_type.

_machine_type can be only one of the following:
machineType

string

The type of the machine used to deploy and serve the model.

Union field _min_replica_count.

_min_replica_count can be only one of the following:
minReplicaCount

string (int64 format)

The minimum number of machine replicas that will be always deployed on an endpoint. This value must be greater than or equal to 1. The default value is 1.

Union field _max_replica_count.

_max_replica_count can be only one of the following:
maxReplicaCount

string (int64 format)

The maximum number of machine replicas that will be deployed on an endpoint. The default value is equal to min_replica_count.

Union field _reservation_affinity_type.

_reservation_affinity_type can be only one of the following:
reservationAffinityType

enum (ReservationAffinityType)

Specifies the reservation affinity type used to configure a Vertex AI resource. The default value is NO_RESERVATION.

Union field _reservation_affinity_key.

_reservation_affinity_key can be only one of the following:
reservationAffinityKey

string

Corresponds to the label key of a reservation resource used by Vertex AI. To target a SPECIFIC_RESERVATION by name, use compute.googleapis.com/reservation-name as the key and specify the name of your reservation as its value.

LabelClassWeightsEntry

JSON representation 
{
  "key": string,
  "value": number
}
Fields
key

string
value

number

Duration

JSON representation 
{
  "seconds": string,
  "nanos": integer
}
Fields
seconds

string (int64 format)

Signed seconds of the span of time. Must be from -315,576,000,000 to +315,576,000,000 inclusive. Note: these bounds are computed from: 60 sec/min * 60 min/hr * 24 hr/day * 365.25 days/year * 10000 years
nanos

integer

Signed fractions of a second at nanosecond resolution of the span of time. Durations less than one second are represented with a 0 seconds field and a positive or negative nanos field. For durations of one second or more, a non-zero value for the nanos field must be of the same sign as the seconds field. Must be from -999,999,999 to +999,999,999 inclusive.

EvaluationMetrics

JSON representation 
{

  // Union field metrics can be only one of the following:
  "regressionMetrics": {
    object (RegressionMetrics)
  },
  "binaryClassificationMetrics": {
    object (BinaryClassificationMetrics)
  },
  "multiClassClassificationMetrics": {
    object (MultiClassClassificationMetrics)
  },
  "clusteringMetrics": {
    object (ClusteringMetrics)
  },
  "rankingMetrics": {
    object (RankingMetrics)
  },
  "arimaForecastingMetrics": {
    object (ArimaForecastingMetrics)
  },
  "dimensionalityReductionMetrics": {
    object (DimensionalityReductionMetrics)
  }
  // End of list of possible types for union field metrics.
}
Fields
Union field metrics. Metrics. metrics can be only one of the following:
regressionMetrics

object (RegressionMetrics)

Populated for regression models and explicit feedback type matrix factorization models.
binaryClassificationMetrics

object (BinaryClassificationMetrics)

Populated for binary classification/classifier models.
multiClassClassificationMetrics

object (MultiClassClassificationMetrics)

Populated for multi-class classification/classifier models.
clusteringMetrics

object (ClusteringMetrics)

Populated for clustering models.
rankingMetrics

object (RankingMetrics)

Populated for implicit feedback type matrix factorization models.
arimaForecastingMetrics

object (ArimaForecastingMetrics)

Populated for ARIMA models.
dimensionalityReductionMetrics

object (DimensionalityReductionMetrics)

Evaluation metrics when the model is a dimensionality reduction model, which currently includes PCA.

RegressionMetrics

JSON representation 
{
  "meanAbsoluteError": number,
  "meanSquaredError": number,
  "meanSquaredLogError": number,
  "medianAbsoluteError": number,
  "rSquared": number
}
Fields
meanAbsoluteError

number

Mean absolute error.
meanSquaredError

number

Mean squared error.
meanSquaredLogError

number

Mean squared log error.
medianAbsoluteError

number

Median absolute error.
rSquared

number

R^2 score. This corresponds to r2_score in ML.EVALUATE.

BinaryClassificationMetrics

JSON representation 
{
  "aggregateClassificationMetrics": {
    object (AggregateClassificationMetrics)
  },
  "binaryConfusionMatrixList": [
    {
      object (BinaryConfusionMatrix)
    }
  ],
  "positiveLabel": string,
  "negativeLabel": string
}
Fields
aggregateClassificationMetrics

object (AggregateClassificationMetrics)

Aggregate classification metrics.
binaryConfusionMatrixList[]

object (BinaryConfusionMatrix)

Binary confusion matrix at multiple thresholds.
positiveLabel

string

Label representing the positive class.
negativeLabel

string

Label representing the negative class.

AggregateClassificationMetrics

JSON representation 
{
  "precision": number,
  "recall": number,
  "accuracy": number,
  "threshold": number,
  "f1Score": number,
  "logLoss": number,
  "rocAuc": number
}
Fields
precision

number

Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier.
recall

number

Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric.
accuracy

number

Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric.
threshold

number

Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classification models this is the confidence threshold.
f1Score

number

The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric.
logLoss

number

Logarithmic Loss. For multiclass this is a macro-averaged metric.
rocAuc

number

Area Under a ROC Curve. For multiclass this is a macro-averaged metric.

BinaryConfusionMatrix

JSON representation 
{
  "positiveClassThreshold": number,
  "truePositives": string,
  "falsePositives": string,
  "trueNegatives": string,
  "falseNegatives": string,
  "precision": number,
  "recall": number,
  "f1Score": number,
  "accuracy": number
}
Fields
positiveClassThreshold

number

Threshold value used when computing each of the following metric.
truePositives

string (Int64Value format)

Number of true samples predicted as true.
falsePositives

string (Int64Value format)

Number of false samples predicted as true.
trueNegatives

string (Int64Value format)

Number of true samples predicted as false.
falseNegatives

string (Int64Value format)

Number of false samples predicted as false.
precision

number

The fraction of actual positive predictions that had positive actual labels.
recall

number

The fraction of actual positive labels that were given a positive prediction.
f1Score

number

The equally weighted average of recall and precision.
accuracy

number

The fraction of predictions given the correct label.

MultiClassClassificationMetrics

JSON representation 
{
  "aggregateClassificationMetrics": {
    object (AggregateClassificationMetrics)
  },
  "confusionMatrixList": [
    {
      object (ConfusionMatrix)
    }
  ]
}
Fields
aggregateClassificationMetrics

object (AggregateClassificationMetrics)

Aggregate classification metrics.
confusionMatrixList[]

object (ConfusionMatrix)

Confusion matrix at different thresholds.

ConfusionMatrix

JSON representation 
{
  "confidenceThreshold": number,
  "rows": [
    {
      object (Row)
    }
  ]
}
Fields
confidenceThreshold

number

Confidence threshold used when computing the entries of the confusion matrix.
rows[]

object (Row)

One row per actual label.

Row

JSON representation 
{
  "actualLabel": string,
  "entries": [
    {
      object (Entry)
    }
  ]
}
Fields
actualLabel

string

The original label of this row.
entries[]

object (Entry)

Info describing predicted label distribution.

Entry

JSON representation 
{
  "predictedLabel": string,
  "itemCount": string
}
Fields
predictedLabel

string

The predicted label. For confidence_threshold > 0, we will also add an entry indicating the number of items under the confidence threshold.
itemCount

string (Int64Value format)

Number of items being predicted as this label.

ClusteringMetrics

JSON representation 
{
  "daviesBouldinIndex": number,
  "meanSquaredDistance": number,
  "clusters": [
    {
      object (Cluster)
    }
  ]
}
Fields
daviesBouldinIndex

number

Davies-Bouldin index.
meanSquaredDistance

number

Mean of squared distances between each sample to its cluster centroid.
clusters[]

object (Cluster)

Information for all clusters.

Cluster

JSON representation 
{
  "centroidId": string,
  "featureValues": [
    {
      object (FeatureValue)
    }
  ],
  "count": string
}
Fields
centroidId

string (int64 format)

Centroid id.
featureValues[]

object (FeatureValue)

Values of highly variant features for this cluster.
count

string (Int64Value format)

Count of training data rows that were assigned to this cluster.

FeatureValue

JSON representation 
{
  "featureColumn": string,

  // Union field value can be only one of the following:
  "numericalValue": number,
  "categoricalValue": {
    object (CategoricalValue)
  }
  // End of list of possible types for union field value.
}
Fields
featureColumn

string

The feature column name.
Union field value. Value. value can be only one of the following:
numericalValue

number

The numerical feature value. This is the centroid value for this feature.
categoricalValue

object (CategoricalValue)

The categorical feature value.

CategoricalValue

JSON representation 
{
  "categoryCounts": [
    {
      object (CategoryCount)
    }
  ]
}
Fields
categoryCounts[]

object (CategoryCount)

Counts of all categories for the categorical feature. If there are more than ten categories, we return top ten (by count) and return one more CategoryCount with category "_OTHER_" and count as aggregate counts of remaining categories.

CategoryCount

JSON representation 
{
  "category": string,
  "count": string
}
Fields
category

string

The name of category.
count

string (Int64Value format)

The count of training samples matching the category within the cluster.

RankingMetrics

JSON representation 
{
  "meanAveragePrecision": number,
  "meanSquaredError": number,
  "normalizedDiscountedCumulativeGain": number,
  "averageRank": number
}
Fields
meanAveragePrecision

number

Calculates a precision per user for all the items by ranking them and then averages all the precisions across all the users.
meanSquaredError

number

Similar to the mean squared error computed in regression and explicit recommendation models except instead of computing the rating directly, the output from evaluate is computed against a preference which is 1 or 0 depending on if the rating exists or not.
normalizedDiscountedCumulativeGain

number

A metric to determine the goodness of a ranking calculated from the predicted confidence by comparing it to an ideal rank measured by the original ratings.
averageRank

number

Determines the goodness of a ranking by computing the percentile rank from the predicted confidence and dividing it by the original rank.

ArimaForecastingMetrics

JSON representation 
{
  "nonSeasonalOrder": [
    {
      object (ArimaOrder)
    }
  ],
  "arimaFittingMetrics": [
    {
      object (ArimaFittingMetrics)
    }
  ],
  "seasonalPeriods": [
    enum (SeasonalPeriodType)
  ],
  "hasDrift": [
    boolean
  ],
  "timeSeriesId": [
    string
  ],
  "arimaSingleModelForecastingMetrics": [
    {
      object (ArimaSingleModelForecastingMetrics)
    }
  ]
}
Fields
nonSeasonalOrder[]
(deprecated)

object (ArimaOrder)

Non-seasonal order.
arimaFittingMetrics[]
(deprecated)

object (ArimaFittingMetrics)

Arima model fitting metrics.
seasonalPeriods[]
(deprecated)

enum (SeasonalPeriodType)

Seasonal periods. Repeated because multiple periods are supported for one time series.
hasDrift[]
(deprecated)

boolean

Whether Arima model fitted with drift or not. It is always false when d is not 1.
timeSeriesId[]
(deprecated)

string

Id to differentiate different time series for the large-scale case.
arimaSingleModelForecastingMetrics[]

object (ArimaSingleModelForecastingMetrics)

Repeated as there can be many metric sets (one for each model) in auto-arima and the large-scale case.

ArimaSingleModelForecastingMetrics

JSON representation 
{
  "nonSeasonalOrder": {
    object (ArimaOrder)
  },
  "arimaFittingMetrics": {
    object (ArimaFittingMetrics)
  },
  "hasDrift": boolean,
  "timeSeriesId": string,
  "timeSeriesIds": [
    string
  ],
  "seasonalPeriods": [
    enum (SeasonalPeriodType)
  ],
  "hasHolidayEffect": boolean,
  "hasSpikesAndDips": boolean,
  "hasStepChanges": boolean
}
Fields
nonSeasonalOrder

object (ArimaOrder)

Non-seasonal order.
arimaFittingMetrics

object (ArimaFittingMetrics)

Arima fitting metrics.
hasDrift

boolean

Is arima model fitted with drift or not. It is always false when d is not 1.
timeSeriesId

string

The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used.
timeSeriesIds[]

string

The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns.
seasonalPeriods[]

enum (SeasonalPeriodType)

Seasonal periods. Repeated because multiple periods are supported for one time series.
hasHolidayEffect

boolean

If true, holiday_effect is a part of time series decomposition result.
hasSpikesAndDips

boolean

If true, spikes_and_dips is a part of time series decomposition result.
hasStepChanges

boolean

If true, step_changes is a part of time series decomposition result.

DimensionalityReductionMetrics

JSON representation 
{
  "totalExplainedVarianceRatio": number
}
Fields
totalExplainedVarianceRatio

number

Total percentage of variance explained by the selected principal components.

ExportDataStatistics

JSON representation 
{
  "fileCount": string,
  "rowCount": string
}
Fields
fileCount

string (Int64Value format)

Number of destination files generated in case of EXPORT DATA statement only.
rowCount

string (Int64Value format)

[Alpha] Number of destination rows generated in case of EXPORT DATA statement only.

ExternalServiceCost

JSON representation 
{
  "externalService": string,
  "bytesProcessed": string,
  "bytesBilled": string,
  "slotMs": string,
  "reservedSlotCount": string,
  "billingMethod": string
}
Fields
externalService

string

External service name.
bytesProcessed

string (Int64Value format)

External service cost in terms of bigquery bytes processed.
bytesBilled

string (Int64Value format)

External service cost in terms of bigquery bytes billed.
slotMs

string (Int64Value format)

External service cost in terms of bigquery slot milliseconds.
reservedSlotCount

string (int64 format)

Non-preemptable reserved slots used for external job. For example, reserved slots for Cloua AI Platform job are the VM usages converted to BigQuery slot with equivalent mount of price.
billingMethod

string

The billing method used for the external job. This field, set to SERVICES_SKU, is only used when billing under the services SKU. Otherwise, it is unspecified for backward compatibility.

BiEngineStatistics

JSON representation 
{
  "biEngineMode": enum (BiEngineMode),
  "accelerationMode": enum (BiEngineAccelerationMode),
  "biEngineReasons": [
    {
      object (BiEngineReason)
    }
  ]
}
Fields
biEngineMode

enum (BiEngineMode)

Output only. Specifies which mode of BI Engine acceleration was performed (if any).
accelerationMode

enum (BiEngineAccelerationMode)

Output only. Specifies which mode of BI Engine acceleration was performed (if any).
biEngineReasons[]

object (BiEngineReason)

In case of DISABLED or PARTIAL bi_engine_mode, these contain the explanatory reasons as to why BI Engine could not accelerate. In case the full query was accelerated, this field is not populated.

BiEngineReason

JSON representation 
{
  "code": enum (Code),
  "message": string
}
Fields
code

enum (Code)

Output only. High-level BI Engine reason for partial or disabled acceleration
message

string

Output only. Free form human-readable reason for partial or disabled acceleration.

LoadQueryStatistics

JSON representation 
{
  "inputFiles": string,
  "inputFileBytes": string,
  "outputRows": string,
  "outputBytes": string,
  "badRecords": string,
  "bytesTransferred": string
}
Fields
inputFiles

string (Int64Value format)

Output only. Number of source files in a LOAD query.
inputFileBytes

string (Int64Value format)

Output only. Number of bytes of source data in a LOAD query.
outputRows

string (Int64Value format)

Output only. Number of rows imported in a LOAD query. Note that while a LOAD query is in the running state, this value may change.
outputBytes

string (Int64Value format)

Output only. Size of the loaded data in bytes. Note that while a LOAD query is in the running state, this value may change.
badRecords

string (Int64Value format)

Output only. The number of bad records encountered while processing a LOAD query. Note that if the job has failed because of more bad records encountered than the maximum allowed in the load job configuration, then this number can be less than the total number of bad records present in the input data.
bytesTransferred
(deprecated)

string (Int64Value format)

Output only. This field is deprecated. The number of bytes of source data copied over the network for a LOAD query. transferred_bytes has the canonical value for physical transferred bytes, which is used for BigQuery Omni billing.

SearchStatistics

JSON representation 
{
  "indexUsageMode": enum (IndexUsageMode),
  "indexUnusedReasons": [
    {
      object (IndexUnusedReason)
    }
  ],
  "indexPruningStats": [
    {
      object (IndexPruningStats)
    }
  ]
}
Fields
indexUsageMode

enum (IndexUsageMode)

Specifies the index usage mode for the query.
indexUnusedReasons[]

object (IndexUnusedReason)

When indexUsageMode is UNUSED or PARTIALLY_USED, this field explains why indexes were not used in all or part of the search query. If indexUsageMode is FULLY_USED, this field is not populated.
indexPruningStats[]

object (IndexPruningStats)

Search index pruning statistics, one for each base table that has a search index. If a base table does not have a search index or the index does not help with pruning on the base table, then there is no pruning statistics for that table.

IndexUnusedReason

JSON representation 
{

  // Union field _code can be only one of the following:
  "code": enum (Code)
  // End of list of possible types for union field _code.

  // Union field _message can be only one of the following:
  "message": string
  // End of list of possible types for union field _message.

  // Union field _base_table can be only one of the following:
  "baseTable": {
    object (TableReference)
  }
  // End of list of possible types for union field _base_table.

  // Union field _index_name can be only one of the following:
  "indexName": string
  // End of list of possible types for union field _index_name.
}
Fields

Union field _code.

_code can be only one of the following:
code

enum (Code)

Specifies the high-level reason for the scenario when no search index was used.

Union field _message.

_message can be only one of the following:
message

string

Free form human-readable reason for the scenario when no search index was used.

Union field _base_table.

_base_table can be only one of the following:
baseTable

object (TableReference)

Specifies the base table involved in the reason that no search index was used.

Union field _index_name.

_index_name can be only one of the following:
indexName

string

Specifies the name of the unused search index, if available.

IndexPruningStats

JSON representation 
{

  // Union field _base_table can be only one of the following:
  "baseTable": {
    object (TableReference)
  }
  // End of list of possible types for union field _base_table.

  // Union field _index_id can be only one of the following:
  "indexId": string
  // End of list of possible types for union field _index_id.

  // Union field _pre_index_pruning_parallel_input_count can be only one of the
  // following:
  "preIndexPruningParallelInputCount": string
  // End of list of possible types for union field
  // _pre_index_pruning_parallel_input_count.

  // Union field _post_index_pruning_parallel_input_count can be only one of the
  // following:
  "postIndexPruningParallelInputCount": string
  // End of list of possible types for union field
  // _post_index_pruning_parallel_input_count.
}
Fields

Union field _base_table.

_base_table can be only one of the following:
baseTable

object (TableReference)

The base table reference.

Union field _index_id.

_index_id can be only one of the following:
indexId

string

The index id.

Union field _pre_index_pruning_parallel_input_count.

_pre_index_pruning_parallel_input_count can be only one of the following:
preIndexPruningParallelInputCount

string (int64 format)

The number of parallel inputs before index pruning.

Union field _post_index_pruning_parallel_input_count.

_post_index_pruning_parallel_input_count can be only one of the following:
postIndexPruningParallelInputCount

string (int64 format)

The number of parallel inputs after index pruning.

VectorSearchStatistics

JSON representation 
{
  "indexUsageMode": enum (IndexUsageMode),
  "indexUnusedReasons": [
    {
      object (IndexUnusedReason)
    }
  ],
  "storedColumnsUsages": [
    {
      object (StoredColumnsUsage)
    }
  ]
}
Fields
indexUsageMode

enum (IndexUsageMode)

Specifies the index usage mode for the query.
indexUnusedReasons[]

object (IndexUnusedReason)

When indexUsageMode is UNUSED or PARTIALLY_USED, this field explains why indexes were not used in all or part of the vector search query. If indexUsageMode is FULLY_USED, this field is not populated.
storedColumnsUsages[]

object (StoredColumnsUsage)

Specifies the usage of stored columns in the query when stored columns are used in the query.

StoredColumnsUsage

JSON representation 
{
  "storedColumnsUnusedReasons": [
    {
      object (StoredColumnsUnusedReason)
    }
  ],

  // Union field _is_query_accelerated can be only one of the following:
  "isQueryAccelerated": boolean
  // End of list of possible types for union field _is_query_accelerated.

  // Union field _base_table can be only one of the following:
  "baseTable": {
    object (TableReference)
  }
  // End of list of possible types for union field _base_table.
}
Fields
storedColumnsUnusedReasons[]

object (StoredColumnsUnusedReason)

If stored columns were not used, explain why.

Union field _is_query_accelerated.

_is_query_accelerated can be only one of the following:
isQueryAccelerated

boolean

Specifies whether the query was accelerated with stored columns.

Union field _base_table.

_base_table can be only one of the following:
baseTable

object (TableReference)

Specifies the base table.

StoredColumnsUnusedReason

JSON representation 
{
  "uncoveredColumns": [
    string
  ],

  // Union field _code can be only one of the following:
  "code": enum (Code)
  // End of list of possible types for union field _code.

  // Union field _message can be only one of the following:
  "message": string
  // End of list of possible types for union field _message.
}
Fields
uncoveredColumns[]

string

Specifies which columns were not covered by the stored columns for the specified code up to 20 columns. This is populated when the code is STORED_COLUMNS_COVER_INSUFFICIENT and BASE_TABLE_HAS_CLS.

Union field _code.

_code can be only one of the following:
code

enum (Code)

Specifies the high-level reason for the unused scenario, each reason must have a code associated.

Union field _message.

_message can be only one of the following:
message

string

Specifies the detailed description for the scenario.

PerformanceInsights

JSON representation 
{
  "avgPreviousExecutionMs": string,
  "stagePerformanceStandaloneInsights": [
    {
      object (StagePerformanceStandaloneInsight)
    }
  ],
  "stagePerformanceChangeInsights": [
    {
      object (StagePerformanceChangeInsight)
    }
  ],
  "tableChangeInsights": [
    {
      object (TableChangeInsight)
    }
  ]
}
Fields
avgPreviousExecutionMs

string (int64 format)

Output only. Average execution ms of previous runs. Indicates the job ran slow compared to previous executions. To find previous executions, use INFORMATION_SCHEMA tables and filter jobs with same query hash.
stagePerformanceStandaloneInsights[]

object (StagePerformanceStandaloneInsight)

Output only. Standalone query stage performance insights, for exploring potential improvements.
stagePerformanceChangeInsights[]

object (StagePerformanceChangeInsight)

Output only. Query stage performance insights compared to previous runs, for diagnosing performance regression.
tableChangeInsights[]

object (TableChangeInsight)

Output only. Performance insights for table-level attributes that changed compared to previous runs.

StagePerformanceStandaloneInsight

JSON representation 
{
  "stageId": string,
  "biEngineReasons": [
    {
      object (BiEngineReason)
    }
  ],
  "highCardinalityJoins": [
    {
      object (HighCardinalityJoin)
    }
  ],

  // Union field _slot_contention can be only one of the following:
  "slotContention": boolean
  // End of list of possible types for union field _slot_contention.

  // Union field _insufficient_shuffle_quota can be only one of the following:
  "insufficientShuffleQuota": boolean
  // End of list of possible types for union field _insufficient_shuffle_quota.

  // Union field _partition_skew can be only one of the following:
  "partitionSkew": {
    object (PartitionSkew)
  }
  // End of list of possible types for union field _partition_skew.
}
Fields
stageId

string (int64 format)

Output only. The stage id that the insight mapped to.
biEngineReasons[]

object (BiEngineReason)

Output only. If present, the stage had the following reasons for being disqualified from BI Engine execution.
highCardinalityJoins[]

object (HighCardinalityJoin)

Output only. High cardinality joins in the stage.

Union field _slot_contention.

_slot_contention can be only one of the following:
slotContention

boolean

Output only. True if the stage has a slot contention issue.

Union field _insufficient_shuffle_quota.

_insufficient_shuffle_quota can be only one of the following:
insufficientShuffleQuota

boolean

Output only. True if the stage has insufficient shuffle quota.

Union field _partition_skew.

_partition_skew can be only one of the following:
partitionSkew

object (PartitionSkew)

Output only. Partition skew in the stage.

HighCardinalityJoin

JSON representation 
{
  "leftRows": string,
  "rightRows": string,
  "outputRows": string,
  "stepIndex": integer
}
Fields
leftRows

string (int64 format)

Output only. Count of left input rows.
rightRows

string (int64 format)

Output only. Count of right input rows.
outputRows

string (int64 format)

Output only. Count of the output rows.
stepIndex

integer

Output only. The index of the join operator in the ExplainQueryStep lists.

PartitionSkew

JSON representation 
{
  "skewSources": [
    {
      object (SkewSource)
    }
  ]
}
Fields
skewSources[]

object (SkewSource)

Output only. Source stages which produce skewed data.

SkewSource

JSON representation 
{
  "stageId": string,
  "outputBytesMedian": string,
  "outputBytesP95": string,
  "outputBytesMax": string
}
Fields
stageId

string (int64 format)

Output only. Stage id of the skew source stage.
outputBytesMedian

string (int64 format)

Output only. Median partition output size (in bytes) for this stage.
outputBytesP95

string (int64 format)

Output only. 95-th percentile of partition output size (in bytes) for this stage.
outputBytesMax

string (int64 format)

Output only. Max partition output size (in bytes) for this stage.

StagePerformanceChangeInsight

JSON representation 
{
  "stageId": string,

  // Union field _input_data_change can be only one of the following:
  "inputDataChange": {
    object (InputDataChange)
  }
  // End of list of possible types for union field _input_data_change.
}
Fields
stageId

string (int64 format)

Output only. The stage id that the insight mapped to.

Union field _input_data_change.

_input_data_change can be only one of the following:
inputDataChange

object (InputDataChange)

Output only. Input data change insight of the query stage.

InputDataChange

JSON representation 
{
  "recordsReadDiffPercentage": number
}
Fields
recordsReadDiffPercentage

number

Output only. Records read difference percentage compared to a previous run.

TableChangeInsight

JSON representation 
{
  "tableReference": {
    object (TableReference)
  },

  // Union field _metadata_cache_staleness_insight can be only one of the
  // following:
  "metadataCacheStalenessInsight": {
    object (MetadataCacheStalenessInsight)
  }
  // End of list of possible types for union field
  // _metadata_cache_staleness_insight.

  // Union field _metadata_cache_not_used_but_used_previously can be only one of
  // the following:
  "metadataCacheNotUsedButUsedPreviously": boolean
  // End of list of possible types for union field
  // _metadata_cache_not_used_but_used_previously.
}
Fields
tableReference

object (TableReference)

Output only. The table that was queried.

Union field _metadata_cache_staleness_insight.

_metadata_cache_staleness_insight can be only one of the following:
metadataCacheStalenessInsight

object (MetadataCacheStalenessInsight)

Output only. If present, indicates that the table's metadata column index staleness has increased significantly compared to previous jobs with the same query hash.

Union field _metadata_cache_not_used_but_used_previously.

_metadata_cache_not_used_but_used_previously can be only one of the following:
metadataCacheNotUsedButUsedPreviously

boolean

Output only. True if the table's column metadata index was not used in the current job, but was used in a previous job with the same query hash.

MetadataCacheStalenessInsight

JSON representation 
{
  "avgPreviousStalenessMs": string,
  "stalenessPercentageIncrease": number
}
Fields
avgPreviousStalenessMs

string (Duration format)

Output only. Average column metadata index staleness of previous runs with the same query hash.

A duration in seconds with up to nine fractional digits, ending with 's'. Example: "3.5s".
stalenessPercentageIncrease

number

Output only. The percent increase in staleness between the current job and the average staleness of previous jobs with the same query hash.

QueryInfo

JSON representation 
{
  "optimizationDetails": {
    object
  }
}
Fields
optimizationDetails

object (Struct format)

Output only. Information about query optimizations.

SparkStatistics

JSON representation 
{
  "endpoints": {
    string: string,
    ...
  },

  // Union field _spark_job_id can be only one of the following:
  "sparkJobId": string
  // End of list of possible types for union field _spark_job_id.

  // Union field _spark_job_location can be only one of the following:
  "sparkJobLocation": string
  // End of list of possible types for union field _spark_job_location.

  // Union field _logging_info can be only one of the following:
  "loggingInfo": {
    object (LoggingInfo)
  }
  // End of list of possible types for union field _logging_info.

  // Union field _kms_key_name can be only one of the following:
  "kmsKeyName": string
  // End of list of possible types for union field _kms_key_name.

  // Union field _gcs_staging_bucket can be only one of the following:
  "gcsStagingBucket": string
  // End of list of possible types for union field _gcs_staging_bucket.
}
Fields
endpoints

map (key: string, value: string)

Output only. Endpoints returned from Dataproc. Key list: - history_server_endpoint: A link to Spark job UI.

An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass": "1.3kg", "count": "3" }.

Union field _spark_job_id.

_spark_job_id can be only one of the following:
sparkJobId

string

Output only. Spark job ID if a Spark job is created successfully.

Union field _spark_job_location.

_spark_job_location can be only one of the following:
sparkJobLocation

string

Output only. Location where the Spark job is executed. A location is selected by BigQueury for jobs configured to run in a multi-region.

Union field _logging_info.

_logging_info can be only one of the following:
loggingInfo

object (LoggingInfo)

Output only. Logging info is used to generate a link to Cloud Logging.

Union field _kms_key_name.

_kms_key_name can be only one of the following:
kmsKeyName

string

Output only. The Cloud KMS encryption key that is used to protect the resources created by the Spark job. If the Spark procedure uses the invoker security mode, the Cloud KMS encryption key is either inferred from the provided system variable, @@spark_proc_properties.kms_key_name, or the default key of the BigQuery job's project (if the CMEK organization policy is enforced). Otherwise, the Cloud KMS key is either inferred from the Spark connection associated with the procedure (if it is provided), or from the default key of the Spark connection's project if the CMEK organization policy is enforced.

Example:

  • projects/[kms_project_id]/locations/[region]/keyRings/[key_region]/cryptoKeys/[key]

Union field _gcs_staging_bucket.

_gcs_staging_bucket can be only one of the following:
gcsStagingBucket

string

Output only. The Google Cloud Storage bucket that is used as the default file system by the Spark application. This field is only filled when the Spark procedure uses the invoker security mode. The gcsStagingBucket bucket is inferred from the @@spark_proc_properties.staging_bucket system variable (if it is provided). Otherwise, BigQuery creates a default staging bucket for the job and returns the bucket name in this field.

Example:

  • gs://[bucket_name]

EndpointsEntry

JSON representation 
{
  "key": string,
  "value": string
}
Fields
key

string
value

string

LoggingInfo

JSON representation 
{
  "resourceType": string,
  "projectId": string
}
Fields
resourceType

string

Output only. Resource type used for logging.
projectId

string

Output only. Project ID where the Spark logs were written.

MaterializedViewStatistics

JSON representation 
{
  "materializedView": [
    {
      object (MaterializedView)
    }
  ]
}
Fields
materializedView[]

object (MaterializedView)

Materialized views considered for the query job. Only certain materialized views are used. For a detailed list, see the child message.

If many materialized views are considered, then the list might be incomplete.

MaterializedView

JSON representation 
{

  // Union field _table_reference can be only one of the following:
  "tableReference": {
    object (TableReference)
  }
  // End of list of possible types for union field _table_reference.

  // Union field _chosen can be only one of the following:
  "chosen": boolean
  // End of list of possible types for union field _chosen.

  // Union field _estimated_bytes_saved can be only one of the following:
  "estimatedBytesSaved": string
  // End of list of possible types for union field _estimated_bytes_saved.

  // Union field _rejected_reason can be only one of the following:
  "rejectedReason": enum (RejectedReason)
  // End of list of possible types for union field _rejected_reason.
}
Fields

Union field _table_reference.

_table_reference can be only one of the following:
tableReference

object (TableReference)

The candidate materialized view.

Union field _chosen.

_chosen can be only one of the following:
chosen

boolean

Whether the materialized view is chosen for the query.

A materialized view can be chosen to rewrite multiple parts of the same query. If a materialized view is chosen to rewrite any part of the query, then this field is true, even if the materialized view was not chosen to rewrite others parts.

Union field _estimated_bytes_saved.

_estimated_bytes_saved can be only one of the following:
estimatedBytesSaved

string (int64 format)

If present, specifies a best-effort estimation of the bytes saved by using the materialized view rather than its base tables.

Union field _rejected_reason.

_rejected_reason can be only one of the following:
rejectedReason

enum (RejectedReason)

If present, specifies the reason why the materialized view was not chosen for the query.

MetadataCacheStatistics

JSON representation 
{
  "tableMetadataCacheUsage": [
    {
      object (TableMetadataCacheUsage)
    }
  ]
}
Fields
tableMetadataCacheUsage[]

object (TableMetadataCacheUsage)

Set for the Metadata caching eligible tables referenced in the query.

TableMetadataCacheUsage

JSON representation 
{
  "staleness": string,
  "tableType": string,

  // Union field _table_reference can be only one of the following:
  "tableReference": {
    object (TableReference)
  }
  // End of list of possible types for union field _table_reference.

  // Union field _unused_reason can be only one of the following:
  "unusedReason": enum (UnusedReason)
  // End of list of possible types for union field _unused_reason.

  // Union field _explanation can be only one of the following:
  "explanation": string
  // End of list of possible types for union field _explanation.

  // Union field _pruning_stats can be only one of the following:
  "pruningStats": {
    object (PruningStats)
  }
  // End of list of possible types for union field _pruning_stats.
}
Fields
staleness

string (Duration format)

Duration since last refresh as of this job for managed tables (indicates metadata cache staleness as seen by this job).

A duration in seconds with up to nine fractional digits, ending with 's'. Example: "3.5s".
tableType

string

Table type.

Union field _table_reference.

_table_reference can be only one of the following:
tableReference

object (TableReference)

Metadata caching eligible table referenced in the query.

Union field _unused_reason.

_unused_reason can be only one of the following:
unusedReason

enum (UnusedReason)

Reason for not using metadata caching for the table.

Union field _explanation.

_explanation can be only one of the following:
explanation

string

Free form human-readable reason metadata caching was unused for the job.

Union field _pruning_stats.

_pruning_stats can be only one of the following:
pruningStats

object (PruningStats)

The column metadata index pruning statistics.

PruningStats

JSON representation 
{

  // Union field _post_cmeta_pruning_partition_count can be only one of the
  // following:
  "postCmetaPruningPartitionCount": string
  // End of list of possible types for union field
  // _post_cmeta_pruning_partition_count.

  // Union field _pre_cmeta_pruning_parallel_input_count can be only one of the
  // following:
  "preCmetaPruningParallelInputCount": string
  // End of list of possible types for union field
  // _pre_cmeta_pruning_parallel_input_count.

  // Union field _post_cmeta_pruning_parallel_input_count can be only one of the
  // following:
  "postCmetaPruningParallelInputCount": string
  // End of list of possible types for union field
  // _post_cmeta_pruning_parallel_input_count.
}
Fields

Union field _post_cmeta_pruning_partition_count.

_post_cmeta_pruning_partition_count can be only one of the following:
postCmetaPruningPartitionCount

string (int64 format)

The number of partitions matched.

Union field _pre_cmeta_pruning_parallel_input_count.

_pre_cmeta_pruning_parallel_input_count can be only one of the following:
preCmetaPruningParallelInputCount

string (int64 format)

The number of parallel inputs scanned.

Union field _post_cmeta_pruning_parallel_input_count.

_post_cmeta_pruning_parallel_input_count can be only one of the following:
postCmetaPruningParallelInputCount

string (int64 format)

The number of parallel inputs matched.

IncrementalResultStats

JSON representation 
{
  "disabledReason": enum (DisabledReason),
  "disabledReasonDetails": string,
  "resultSetLastReplaceTime": string,
  "resultSetLastModifyTime": string,
  "firstIncrementalRowTime": string,
  "lastIncrementalRowTime": string,

  // Union field _incremental_row_count can be only one of the following:
  "incrementalRowCount": string
  // End of list of possible types for union field _incremental_row_count.
}
Fields
disabledReason

enum (DisabledReason)

Output only. Reason why incremental query results are/were not written by the query.
disabledReasonDetails

string

Output only. Additional human-readable clarification, if available, for DisabledReason.
resultSetLastReplaceTime

string (Timestamp format)

Output only. The time at which the result table's contents were completely replaced. May be absent if no results have been written or the query has completed.

Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z", "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30".
resultSetLastModifyTime

string (Timestamp format)

Output only. The time at which the result table's contents were modified. May be absent if no results have been written or the query has completed.

Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z", "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30".
firstIncrementalRowTime

string (Timestamp format)

Output only. The time at which the first incremental result was written. If the query needed to restart internally, this only describes the final attempt.

Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z", "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30".
lastIncrementalRowTime

string (Timestamp format)

Output only. The time at which the last incremental result was written. Does not include the final result written after query completion.

Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z", "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30".

Union field _incremental_row_count.

_incremental_row_count can be only one of the following:
incrementalRowCount

string (int64 format)

Output only. Number of rows that were in the latest result set before query completion.

GenAiStats

JSON representation 
{
  "functionStats": [
    {
      object (GenAiFunctionStats)
    }
  ],

  // Union field _error_stats can be only one of the following:
  "errorStats": {
    object (GenAiErrorStats)
  }
  // End of list of possible types for union field _error_stats.
}
Fields
functionStats[]

object (GenAiFunctionStats)

Function level stats for GenAI Functions. For more information, see Generative AI overview.

Union field _error_stats.

_error_stats can be only one of the following:
errorStats

object (GenAiErrorStats)

Job level error stats across all GenAi functions

GenAiErrorStats

JSON representation 
{
  "errors": [
    string
  ]
}
Fields
errors[]

string

A list of unique errors at query level (up to 5, truncated to 100 chars)

GenAiFunctionStats

JSON representation 
{

  // Union field _function_name can be only one of the following:
  "functionName": string
  // End of list of possible types for union field _function_name.

  // Union field _prompt can be only one of the following:
  "prompt": string
  // End of list of possible types for union field _prompt.

  // Union field _num_processed_rows can be only one of the following:
  "numProcessedRows": string
  // End of list of possible types for union field _num_processed_rows.

  // Union field _error_stats can be only one of the following:
  "errorStats": {
    object (GenAiFunctionErrorStats)
  }
  // End of list of possible types for union field _error_stats.

  // Union field _cost_optimization_stats can be only one of the following:
  "costOptimizationStats": {
    object (GenAiFunctionCostOptimizationStats)
  }
  // End of list of possible types for union field _cost_optimization_stats.

  // Union field _cache_stats can be only one of the following:
  "cacheStats": {
    object (GenAiFunctionCacheStats)
  }
  // End of list of possible types for union field _cache_stats.
}
Fields

Union field _function_name.

_function_name can be only one of the following:
functionName

string

Name of the function.

Union field _prompt.

_prompt can be only one of the following:
prompt

string

User input prompt of the function (truncated to 20 chars).

Union field _num_processed_rows.

_num_processed_rows can be only one of the following:
numProcessedRows

string (int64 format)

Number of rows processed by this GenAi function. This includes all cost_optimized, llm_inferred and failed_rows.

Union field _error_stats.

_error_stats can be only one of the following:
errorStats

object (GenAiFunctionErrorStats)

Error stats for the function.

Union field _cost_optimization_stats.

_cost_optimization_stats can be only one of the following:
costOptimizationStats

object (GenAiFunctionCostOptimizationStats)

Cost optimization stats if applied on the rows processed by the function.

Union field _cache_stats.

_cache_stats can be only one of the following:
cacheStats

object (GenAiFunctionCacheStats)

Cache stats for the function.

GenAiFunctionErrorStats

JSON representation 
{
  "errors": [
    string
  ],
  "numFailedRows": string
}
Fields
errors[]

string

A list of unique errors at function level (up to 5, truncated to 100 chars).
numFailedRows

string (int64 format)

Number of failed rows processed by the function

GenAiFunctionCostOptimizationStats

JSON representation 
{

  // Union field _num_cost_optimized_rows can be only one of the following:
  "numCostOptimizedRows": string
  // End of list of possible types for union field _num_cost_optimized_rows.

  // Union field _message can be only one of the following:
  "message": string
  // End of list of possible types for union field _message.
}
Fields

Union field _num_cost_optimized_rows.

_num_cost_optimized_rows can be only one of the following:
numCostOptimizedRows

string (int64 format)

Number of rows inferred via cost optimized workflow.

Union field _message.

_message can be only one of the following:
message

string

System generated message to provide insights into cost optimization state.

GenAiFunctionCacheStats

JSON representation 
{

  // Union field _num_cache_hit_rows can be only one of the following:
  "numCacheHitRows": string
  // End of list of possible types for union field _num_cache_hit_rows.
}
Fields

Union field _num_cache_hit_rows.

_num_cache_hit_rows can be only one of the following:
numCacheHitRows

string (int64 format)

Number of rows served from cache.

ObjectStorageStats

JSON representation 
{

  // Union field _cloud_provider can be only one of the following:
  "cloudProvider": enum (CloudProvider)
  // End of list of possible types for union field _cloud_provider.

  // Union field _object_storage_bytes_read can be only one of the following:
  "objectStorageBytesRead": string
  // End of list of possible types for union field _object_storage_bytes_read.

  // Union field _cache_bytes_read can be only one of the following:
  "cacheBytesRead": string
  // End of list of possible types for union field _cache_bytes_read.
}
Fields

Union field _cloud_provider.

_cloud_provider can be only one of the following:
cloudProvider

enum (CloudProvider)

The cloud provider for this block of statistics.

Union field _object_storage_bytes_read.

_object_storage_bytes_read can be only one of the following:
objectStorageBytesRead

string (int64 format)

Total bytes read directly from the cloud provider's storage.

Union field _cache_bytes_read.

_cache_bytes_read can be only one of the following:
cacheBytesRead

string (int64 format)

Total bytes read from the GCP Lakehouse-internal cache, avoiding an object storage read.

JobStatistics3

JSON representation 
{
  "inputFiles": string,
  "inputFileBytes": string,
  "outputRows": string,
  "outputBytes": string,
  "badRecords": string,
  "timeline": [
    {
      object (QueryTimelineSample)
    }
  ]
}
Fields
inputFiles

string (Int64Value format)

Output only. Number of source files in a load job.
inputFileBytes

string (Int64Value format)

Output only. Number of bytes of source data in a load job.
outputRows

string (Int64Value format)

Output only. Number of rows imported in a load job. Note that while an import job is in the running state, this value may change.
outputBytes

string (Int64Value format)

Output only. Size of the loaded data in bytes. Note that while a load job is in the running state, this value may change.
badRecords

string (Int64Value format)

Output only. The number of bad records encountered. Note that if the job has failed because of more bad records encountered than the maximum allowed in the load job configuration, then this number can be less than the total number of bad records present in the input data.
timeline[]

object (QueryTimelineSample)

Output only. Describes a timeline of job execution.

JobStatistics4

JSON representation 
{
  "destinationUriFileCounts": [
    string
  ],
  "inputBytes": string,
  "timeline": [
    {
      object (QueryTimelineSample)
    }
  ]
}
Fields
destinationUriFileCounts[]

string (int64 format)

Output only. Number of files per destination URI or URI pattern specified in the extract configuration. These values will be in the same order as the URIs specified in the 'destinationUris' field.
inputBytes

string (Int64Value format)

Output only. Number of user bytes extracted into the result. This is the byte count as computed by BigQuery for billing purposes and doesn't have any relationship with the number of actual result bytes extracted in the desired format.
timeline[]

object (QueryTimelineSample)

Output only. Describes a timeline of job execution.

CopyJobStatistics

JSON representation 
{
  "copiedRows": string,
  "copiedLogicalBytes": string,
  "remoteDestinationRegion": string
}
Fields
copiedRows

string (Int64Value format)

Output only. Number of rows copied to the destination table.
copiedLogicalBytes

string (Int64Value format)

Output only. Number of logical bytes copied to the destination table.
remoteDestinationRegion

string

Output only. Destination region for a cross-region copy job. Not set for in-region copy jobs.

ScriptStatistics

JSON representation 
{
  "evaluationKind": enum (EvaluationKind),
  "stackFrames": [
    {
      object (ScriptStackFrame)
    }
  ]
}
Fields
evaluationKind

enum (EvaluationKind)

Whether this child job was a statement or expression.
stackFrames[]

object (ScriptStackFrame)

Stack trace showing the line/column/procedure name of each frame on the stack at the point where the current evaluation happened. The leaf frame is first, the primary script is last. Never empty.

ScriptStackFrame

JSON representation 
{
  "startLine": integer,
  "startColumn": integer,
  "endLine": integer,
  "endColumn": integer,
  "procedureId": string,
  "text": string
}
Fields
startLine

integer

Output only. One-based start line.
startColumn

integer

Output only. One-based start column.
endLine

integer

Output only. One-based end line.
endColumn

integer

Output only. One-based end column.
procedureId

string

Output only. Name of the active procedure, empty if in a top-level script.
text

string

Output only. Text of the current statement/expression.

RowLevelSecurityStatistics

JSON representation 
{
  "rowLevelSecurityApplied": boolean
}
Fields
rowLevelSecurityApplied

boolean

Whether any accessed data was protected by row access policies.

DataMaskingStatistics

JSON representation 
{
  "dataMaskingApplied": boolean
}
Fields
dataMaskingApplied

boolean

Whether any accessed data was protected by the data masking.

TransactionInfo

JSON representation 
{
  "transactionId": string
}
Fields
transactionId

string

Output only. [Alpha] Id of the transaction.

SessionInfo

JSON representation 
{
  "sessionId": string
}
Fields
sessionId

string

Output only. The id of the session.

JobStatus

JSON representation 
{
  "errorResult": {
    object (ErrorProto)
  },
  "errors": [
    {
      object (ErrorProto)
    }
  ],
  "state": string
}
Fields
errorResult

object (ErrorProto)

Output only. Final error result of the job. If present, indicates that the job has completed and was unsuccessful.
errors[]

object (ErrorProto)

Output only. The first errors encountered during the running of the job. The final message includes the number of errors that caused the process to stop. Errors here do not necessarily mean that the job has not completed or was unsuccessful.
state

string

Output only. Running state of the job. Valid states include 'PENDING', 'RUNNING', and 'DONE'.

ErrorProto

JSON representation 
{
  "reason": string,
  "location": string,
  "debugInfo": string,
  "message": string
}
Fields
reason

string

A short error code that summarizes the error.
location

string

Specifies where the error occurred, if present.
debugInfo

string

Debugging information. This property is internal to Google and should not be used.
message

string

A human-readable description of the error.

JobCreationReason

JSON representation 
{
  "code": enum (Code)
}
Fields
code

enum (Code)

Output only. Specifies the high level reason why a Job was created.

FileSetSpecType

This enum defines how to interpret source URIs for load jobs and external tables.

Enums
FILE_SET_SPEC_TYPE_FILE_SYSTEM_MATCH This option expands source URIs by listing files from the object store. It is the default behavior if FileSetSpecType is not set.
FILE_SET_SPEC_TYPE_NEW_LINE_DELIMITED_MANIFEST This option indicates that the provided URIs are newline-delimited manifest files, with one URI per line. Wildcard URIs are not supported.

RoundingMode

Rounding mode options that can be used when storing NUMERIC or BIGNUMERIC values.

Enums
ROUNDING_MODE_UNSPECIFIED Unspecified will default to using ROUND_HALF_AWAY_FROM_ZERO.
ROUND_HALF_AWAY_FROM_ZERO ROUND_HALF_AWAY_FROM_ZERO rounds half values away from zero when applying precision and scale upon writing of NUMERIC and BIGNUMERIC values. For Scale: 0 1.1, 1.2, 1.3, 1.4 => 1 1.5, 1.6, 1.7, 1.8, 1.9 => 2
ROUND_HALF_EVEN ROUND_HALF_EVEN rounds half values to the nearest even value when applying precision and scale upon writing of NUMERIC and BIGNUMERIC values. For Scale: 0 1.1, 1.2, 1.3, 1.4 => 1 1.5 => 2 1.6, 1.7, 1.8, 1.9 => 2 2.5 => 2

GeneratedMode

Dictates when system generated values are used to populate the field.

Enums
GENERATED_MODE_UNSPECIFIED Unspecified GeneratedMode will default to GENERATED_ALWAYS.
GENERATED_ALWAYS Field can only have system generated values. Users cannot manually insert values into the field.
GENERATED_BY_DEFAULT Use system generated values only if the user does not explicitly provide a value.

TypeSystem

External systems, such as query engines or table formats, that have their own data types.

Enums
TYPE_SYSTEM_UNSPECIFIED TypeSystem not specified.
HIVE Represents Hive data types.

DecimalTargetType

The data types that could be used as a target type when converting decimal values.

Enums
DECIMAL_TARGET_TYPE_UNSPECIFIED Invalid type.
NUMERIC Decimal values could be converted to NUMERIC type.
BIGNUMERIC Decimal values could be converted to BIGNUMERIC type.
STRING Decimal values could be converted to STRING type.

JsonExtension

Used to indicate that a JSON variant, rather than normal JSON, is being used as the source_format. This should only be used in combination with the JSON source format.

Enums
JSON_EXTENSION_UNSPECIFIED The default if provided value is not one included in the enum, or the value is not specified. The source format is parsed without any modification.
GEOJSON Use GeoJSON variant of JSON. See https://tools.ietf.org/html/rfc7946.

MapTargetType

Indicates the map target type. Only applies to parquet maps.

Enums
MAP_TARGET_TYPE_UNSPECIFIED In this mode, the map will have the following schema: struct map_field_name { repeated struct key_value { key value } }.
ARRAY_OF_STRUCT In this mode, the map will have the following schema: repeated struct map_field_name { key value }.

ObjectMetadata

Supported Object Metadata Types.

Enums
OBJECT_METADATA_UNSPECIFIED Unspecified by default.
DIRECTORY A synonym for SIMPLE.
SIMPLE Directory listing of objects.

MetadataCacheMode

MetadataCacheMode identifies if the table should use metadata caching for files from external source (eg Google Cloud Storage).

Enums
METADATA_CACHE_MODE_UNSPECIFIED Unspecified metadata cache mode.
AUTOMATIC Set this mode to trigger automatic background refresh of metadata cache from the external source. Queries will use the latest available cache version within the table's maxStaleness interval.
MANUAL Set this mode to enable triggering manual refresh of the metadata cache from external source. Queries will use the latest manually triggered cache version within the table's maxStaleness interval.

TypeKind

The kind of the datatype.

Enums
TYPE_KIND_UNSPECIFIED Invalid type.
INT64 Encoded as a string in decimal format.
BOOL Encoded as a boolean "false" or "true".
FLOAT64 Encoded as a number, or string "NaN", "Infinity" or "-Infinity".
STRING Encoded as a string value.
BYTES Encoded as a base64 string per RFC 4648, section 4.
TIMESTAMP Encoded as an RFC 3339 timestamp with mandatory "Z" time zone string: 1985-04-12T23:20:50.52Z
DATE Encoded as RFC 3339 full-date format string: 1985-04-12
TIME Encoded as RFC 3339 partial-time format string: 23:20:50.52
DATETIME Encoded as RFC 3339 full-date "T" partial-time: 1985-04-12T23:20:50.52
INTERVAL Encoded as fully qualified 3 part: 0-5 15 2:30:45.6
GEOGRAPHY Encoded as WKT
NUMERIC Encoded as a decimal string.
BIGNUMERIC Encoded as a decimal string.
JSON Encoded as a string.
ARRAY Encoded as a list with types matching Type.array_type.
STRUCT Encoded as a list with fields of type Type.struct_type[i]. List is used because a JSON object cannot have duplicate field names.
RANGE Encoded as a pair with types matching range_element_type. Pairs must begin with "[", end with ")", and be separated by ", ".
UUID Encoded as a string.

NullValue

Represents a JSON null.

NullValue is a sentinel, using an enum with only one value to represent the null value for the Value type union.

A field of type NullValue with any value other than 0 is considered invalid. Most ProtoJSON serializers will emit a Value with a null_value set as a JSON null regardless of the integer value, and so will round trip to a 0 value.

Enums
NULL_VALUE Null value.

KeyResultStatementKind

KeyResultStatementKind controls how the key result is determined.

Enums
KEY_RESULT_STATEMENT_KIND_UNSPECIFIED Default value.
LAST The last result determines the key result.
FIRST_SELECT The first SELECT statement determines the key result.

DeserializationOption

DeserializationOption defines the TProtocol implementation that will be used to deserialize Thrift data.

Enums
DESERIALIZATION_OPTION_UNSPECIFIED Default value. This value is unused.
THRIFT_BINARY_PROTOCOL_OPTION Use TBinaryProtocol to deserialize the data..

FramingOption

Framing in Apache Thrift means 4 bytes added in front of the serialized record or data blocks to inidicate the size of the followed record or data block. Please see TFramedTransport for more details. One thing to note is that the 4-byte record size added by TFramedTransport is in big endian. A TFramedTransport framed block looks like:

| 4-byte size (big endian) | serialized record ... |

We also support framing with little endian record or data block size.

Enums
FRAMING_OPTION_UNSPECIFIED Default value. This value is unused.
NOT_FRAMED Records or data blocks are not framed.
FRAMED_WITH_BIG_ENDIAN Records or data blocks are framed with a 4-byte record size in big endian.
FRAMED_WITH_LITTLE_ENDIAN Records or data blocks are framed with a 4-byte record size in little endian.

ColumnNameCharacterMap

Indicates the character map used for column names.

Enums
COLUMN_NAME_CHARACTER_MAP_UNSPECIFIED Unspecified column name character map.
STRICT Support flexible column name and reject invalid column names.
V1 Support alphanumeric + underscore characters and names must start with a letter or underscore. Invalid column names will be normalized.
V2 Support flexible column name. Invalid column names will be normalized.

SourceColumnMatch

Indicates the strategy used to match loaded columns to the schema.

Enums
SOURCE_COLUMN_MATCH_UNSPECIFIED Uses sensible defaults based on how the schema is provided. If autodetect is used, then columns are matched by name. Otherwise, columns are matched by position. This is done to keep the behavior backward-compatible.
POSITION Matches by position. This assumes that the columns are ordered the same way as the schema.
NAME Matches by name. This reads the header row as column names and reorders columns to match the field names in the schema.

OperationType

Indicates different operation types supported in table copy job.

Enums
OPERATION_TYPE_UNSPECIFIED Unspecified operation type.
COPY The source and destination table have the same table type.
SNAPSHOT The source table type is TABLE and the destination table type is SNAPSHOT.
RESTORE The source table type is SNAPSHOT and the destination table type is TABLE.
CLONE The source and destination table have the same table type, but only bill for unique data.

ComputeMode

Indicates the type of compute mode.

Enums
COMPUTE_MODE_UNSPECIFIED ComputeMode type not specified.
BIGQUERY This stage was processed using BigQuery slots.
BI_ENGINE This stage was processed using BI Engine compute.

DmlMode

Enum to specify the DML mode used.

Enums
DML_MODE_UNSPECIFIED Default value. This value is unused.
COARSE_GRAINED_DML Coarse-grained DML was used.
FINE_GRAINED_DML Fine-grained DML was used.

FineGrainedDmlUnusedReason

Reason for disabling fine-grained DML. Additional values may be added in the future.

Enums
FINE_GRAINED_DML_UNUSED_REASON_UNSPECIFIED Default value. This value is unused.
MAX_PARTITION_SIZE_EXCEEDED Max partition size threshold exceeded. Fine-grained DML Limitations
TABLE_NOT_ENROLLED The table is not enrolled for fine-grained DML.
DML_IN_MULTI_STATEMENT_TRANSACTION The DML statement is part of a multi-statement transaction.

SeasonalPeriodType

Seasonal period type.

Enums
SEASONAL_PERIOD_TYPE_UNSPECIFIED Unspecified seasonal period.
NO_SEASONALITY No seasonality
DAILY Daily period, 24 hours.
WEEKLY Weekly period, 7 days.
MONTHLY Monthly period, 30 days or irregular.
QUARTERLY Quarterly period, 90 days or irregular.
YEARLY Yearly period, 365 days or irregular.
HOURLY Hourly period, 1 hour.

ModelType

Indicates the type of the Model.

Enums
MODEL_TYPE_UNSPECIFIED Default value.
LINEAR_REGRESSION Linear regression model.
LOGISTIC_REGRESSION Logistic regression based classification model.
KMEANS K-means clustering model.
MATRIX_FACTORIZATION Matrix factorization model.
DNN_CLASSIFIER DNN classifier model.
TENSORFLOW An imported TensorFlow model.
DNN_REGRESSOR DNN regressor model.
XGBOOST An imported XGBoost model.
BOOSTED_TREE_REGRESSOR Boosted tree regressor model.
BOOSTED_TREE_CLASSIFIER Boosted tree classifier model.
ARIMA ARIMA model.
AUTOML_REGRESSOR AutoML Tables regression model.
AUTOML_CLASSIFIER AutoML Tables classification model.
PCA Prinpical Component Analysis model.
DNN_LINEAR_COMBINED_CLASSIFIER Wide-and-deep classifier model.
DNN_LINEAR_COMBINED_REGRESSOR Wide-and-deep regressor model.
AUTOENCODER Autoencoder model.
ARIMA_PLUS New name for the ARIMA model.
ARIMA_PLUS_XREG ARIMA with external regressors.
RANDOM_FOREST_REGRESSOR Random forest regressor model.
RANDOM_FOREST_CLASSIFIER Random forest classifier model.
TENSORFLOW_LITE An imported TensorFlow Lite model.
ONNX An imported ONNX model.
TRANSFORM_ONLY Model to capture the columns and logic in the TRANSFORM clause along with statistics useful for ML analytic functions.
CONTRIBUTION_ANALYSIS The contribution analysis model.

TrainingType

Training type.

Enums
TRAINING_TYPE_UNSPECIFIED Unspecified training type.
SINGLE_TRAINING Single training with fixed parameter space.
HPARAM_TUNING Hyperparameter tuning training.

LossType

Loss metric to evaluate model training performance.

Enums
LOSS_TYPE_UNSPECIFIED Default value.
MEAN_SQUARED_LOSS Mean squared loss, used for linear regression.
MEAN_LOG_LOSS Mean log loss, used for logistic regression.

DataSplitMethod

Indicates the method to split input data into multiple tables.

Enums
DATA_SPLIT_METHOD_UNSPECIFIED Default value.
RANDOM Splits data randomly.
CUSTOM Splits data with the user provided tags.
SEQUENTIAL Splits data sequentially.
NO_SPLIT Data split will be skipped.
AUTO_SPLIT Splits data automatically: Uses NO_SPLIT if the data size is small. Otherwise uses RANDOM.

LearnRateStrategy

Indicates the learning rate optimization strategy to use.

Enums
LEARN_RATE_STRATEGY_UNSPECIFIED Default value.
CONSTANT Use a constant learning rate.

DistanceType

Distance metric used to compute the distance between two points.

Enums
DISTANCE_TYPE_UNSPECIFIED Default value.
EUCLIDEAN Eculidean distance.
COSINE Cosine distance.

OptimizationStrategy

Indicates the optimization strategy used for training.

Enums
OPTIMIZATION_STRATEGY_UNSPECIFIED Default value.
BATCH_GRADIENT_DESCENT Uses an iterative batch gradient descent algorithm.
NORMAL_EQUATION Uses a normal equation to solve linear regression problem.

BoosterType

Booster types supported. Refer to booster parameter in XGBoost.

Enums
BOOSTER_TYPE_UNSPECIFIED Unspecified booster type.
GBTREE Gbtree booster.
DART Dart booster.

DartNormalizeType

Type of normalization algorithm for boosted tree models using dart booster. Refer to normalize_type in XGBoost.

Enums
DART_NORMALIZE_TYPE_UNSPECIFIED Unspecified dart normalize type.
TREE New trees have the same weight of each of dropped trees.
FOREST New trees have the same weight of sum of dropped trees.

TreeMethod

Tree construction algorithm used in boosted tree models. Refer to tree_method in XGBoost.

Enums
TREE_METHOD_UNSPECIFIED Unspecified tree method.
AUTO Use heuristic to choose the fastest method.
EXACT Exact greedy algorithm.
APPROX Approximate greedy algorithm using quantile sketch and gradient histogram.
HIST Fast histogram optimized approximate greedy algorithm.

FeedbackType

Indicates the training algorithm to use for matrix factorization models.

Enums
FEEDBACK_TYPE_UNSPECIFIED Default value.
IMPLICIT Use weighted-als for implicit feedback problems.
EXPLICIT Use nonweighted-als for explicit feedback problems.

KmeansInitializationMethod

Indicates the method used to initialize the centroids for KMeans clustering algorithm.

Enums
KMEANS_INITIALIZATION_METHOD_UNSPECIFIED Unspecified initialization method.
RANDOM Initializes the centroids randomly.
CUSTOM Initializes the centroids using data specified in kmeans_initialization_column.
KMEANS_PLUS_PLUS Initializes with kmeans++.

DataFrequency

Type of supported data frequency for time series forecasting models.

Enums
DATA_FREQUENCY_UNSPECIFIED Default value.
AUTO_FREQUENCY Automatically inferred from timestamps.
YEARLY Yearly data.
QUARTERLY Quarterly data.
MONTHLY Monthly data.
WEEKLY Weekly data.
DAILY Daily data.
HOURLY Hourly data.
PER_MINUTE Per-minute data.

HolidayRegion

Type of supported holiday regions for time series forecasting models.

Enums
HOLIDAY_REGION_UNSPECIFIED Holiday region unspecified.
GLOBAL Global.
NA North America.
JAPAC Japan and Asia Pacific: Korea, Greater China, India, Australia, and New Zealand.
EMEA Europe, the Middle East and Africa.
LAC Latin America and the Caribbean.
AE United Arab Emirates
AR Argentina
AT Austria
AU Australia
BE Belgium
BR Brazil
CA Canada
CH Switzerland
CL Chile
CN China
CO Colombia
CS Czechoslovakia
CZ Czech Republic
DE Germany
DK Denmark
DZ Algeria
EC Ecuador
EE Estonia
EG Egypt
ES Spain
FI Finland
FR France
GB Great Britain (United Kingdom)
GR Greece
HK Hong Kong
HU Hungary
ID Indonesia
IE Ireland
IL Israel
IN India
IR Iran
IT Italy
JP Japan
KR Korea (South)
LV Latvia
MA Morocco
MX Mexico
MY Malaysia
NG Nigeria
NL Netherlands
NO Norway
NZ New Zealand
PE Peru
PH Philippines
PK Pakistan
PL Poland
PT Portugal
RO Romania
RS Serbia
RU Russian Federation
SA Saudi Arabia
SE Sweden
SG Singapore
SI Slovenia
SK Slovakia
TH Thailand
TR Turkey
TW Taiwan
UA Ukraine
US United States
VE Venezuela
VN Vietnam
ZA South Africa

HparamTuningObjective

Available evaluation metrics used as hyperparameter tuning objectives.

Enums
HPARAM_TUNING_OBJECTIVE_UNSPECIFIED Unspecified evaluation metric.
MEAN_ABSOLUTE_ERROR Mean absolute error. mean_absolute_error = AVG(ABS(label - predicted))
MEAN_SQUARED_ERROR Mean squared error. mean_squared_error = AVG(POW(label - predicted, 2))
MEAN_SQUARED_LOG_ERROR Mean squared log error. mean_squared_log_error = AVG(POW(LN(1 + label) - LN(1 + predicted), 2))
MEDIAN_ABSOLUTE_ERROR Mean absolute error. median_absolute_error = APPROX_QUANTILES(absolute_error, 2)[OFFSET(1)]
R_SQUARED R^2 score. This corresponds to r2_score in ML.EVALUATE. r_squared = 1 - SUM(squared_error)/(COUNT(label)*VAR_POP(label))
EXPLAINED_VARIANCE Explained variance. explained_variance = 1 - VAR_POP(label_error)/VAR_POP(label)
PRECISION Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier.
RECALL Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric.
ACCURACY Accuracy is the fraction of predictions given the correct label. For multiclass this is a globally micro-averaged metric.
F1_SCORE The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric.
LOG_LOSS Logarithmic Loss. For multiclass this is a macro-averaged metric.
ROC_AUC Area Under an ROC Curve. For multiclass this is a macro-averaged metric.
DAVIES_BOULDIN_INDEX Davies-Bouldin Index.
MEAN_AVERAGE_PRECISION Mean Average Precision.
NORMALIZED_DISCOUNTED_CUMULATIVE_GAIN Normalized Discounted Cumulative Gain.
AVERAGE_RANK Average Rank.

EncodingMethod

Supported encoding methods for categorical features.

Enums
ENCODING_METHOD_UNSPECIFIED Unspecified encoding method.
ONE_HOT_ENCODING Applies one-hot encoding.
LABEL_ENCODING Applies label encoding.
DUMMY_ENCODING Applies dummy encoding.

ColorSpace

Enums for color space, used for processing images in Object Table. See more details at https://www.tensorflow.org/io/tutorials/colorspace.

Enums
COLOR_SPACE_UNSPECIFIED Unspecified color space
RGB RGB
HSV HSV
YIQ YIQ
YUV YUV
GRAYSCALE GRAYSCALE

PcaSolver

Enums for supported PCA solvers.

Enums
UNSPECIFIED Default value.
FULL Full eigen-decoposition.
RANDOMIZED Randomized SVD.
AUTO Auto.

ModelRegistry

Enums for supported model registries.

Enums
MODEL_REGISTRY_UNSPECIFIED Default value.
VERTEX_AI Vertex AI.

ReservationAffinityType

Supported reservation affinity types to configure a Vertex AI resource.

Enums
RESERVATION_AFFINITY_TYPE_UNSPECIFIED Default value.
NO_RESERVATION No reservation.
ANY_RESERVATION Any reservation.
SPECIFIC_RESERVATION Specific reservation.

TrialStatus

Current status of the trial.

Enums
TRIAL_STATUS_UNSPECIFIED Default value.
NOT_STARTED Scheduled but not started.
RUNNING Running state.
SUCCEEDED The trial succeeded.
FAILED The trial failed.
INFEASIBLE The trial is infeasible due to the invalid params.
STOPPED_EARLY Trial stopped early because it's not promising.

BiEngineMode

Indicates the type of BI Engine acceleration.

Enums
ACCELERATION_MODE_UNSPECIFIED BiEngineMode type not specified.
DISABLED BI Engine disabled the acceleration. bi_engine_reasons specifies a more detailed reason.
PARTIAL Part of the query was accelerated using BI Engine. See bi_engine_reasons for why parts of the query were not accelerated.
FULL All of the query was accelerated using BI Engine.

BiEngineAccelerationMode

Indicates the type of BI Engine acceleration.

Enums
BI_ENGINE_ACCELERATION_MODE_UNSPECIFIED BiEngineMode type not specified.
BI_ENGINE_DISABLED BI Engine acceleration was attempted but disabled. bi_engine_reasons specifies a more detailed reason.
PARTIAL_INPUT Some inputs were accelerated using BI Engine. See bi_engine_reasons for why parts of the query were not accelerated.
FULL_INPUT All of the query inputs were accelerated using BI Engine.
FULL_QUERY All of the query was accelerated using BI Engine.

Code

Indicates the high-level reason for no/partial acceleration

Enums
CODE_UNSPECIFIED BiEngineReason not specified.
NO_RESERVATION No reservation available for BI Engine acceleration.
INSUFFICIENT_RESERVATION Not enough memory available for BI Engine acceleration.
UNSUPPORTED_SQL_TEXT This particular SQL text is not supported for acceleration by BI Engine.
INPUT_TOO_LARGE Input too large for acceleration by BI Engine.
OTHER_REASON Catch-all code for all other cases for partial or disabled acceleration.
TABLE_EXCLUDED One or more tables were not eligible for BI Engine acceleration.

IndexUsageMode

Indicates the type of search index usage in the entire search query. In this context, "usage" means that an index lookup is attempted to prune base table data, with effectiveness depending on the selectivity of the search term.

Enums
INDEX_USAGE_MODE_UNSPECIFIED Index usage mode not specified.
UNUSED No search indexes were used in the search query. See indexUnusedReasons for detailed reasons.
PARTIALLY_USED Part of the search query used search indexes. See indexUnusedReasons for why other parts of the query did not use search indexes.
FULLY_USED The entire search query used search indexes.

Code

Indicates the high-level reason for the scenario when no search index was used.

Enums
CODE_UNSPECIFIED Code not specified.
INDEX_CONFIG_NOT_AVAILABLE Indicates the search index configuration has not been created.
PENDING_INDEX_CREATION Indicates the search index creation has not been completed.
BASE_TABLE_TRUNCATED Indicates the base table has been truncated (rows have been removed from table with TRUNCATE TABLE statement) since the last time the search index was refreshed.
INDEX_CONFIG_MODIFIED Indicates the search index configuration has been changed since the last time the search index was refreshed.
TIME_TRAVEL_QUERY Indicates the search query accesses data at a timestamp before the last time the search index was refreshed.
NO_PRUNING_POWER Indicates the usage of search index will not contribute to any pruning improvement for the search function, e.g. when the search predicate is in a disjunction with other non-search predicates.
UNINDEXED_SEARCH_FIELDS Indicates the search index does not cover all fields in the search function.
UNSUPPORTED_SEARCH_PATTERN Indicates the search index does not support the given search query pattern.
OPTIMIZED_WITH_MATERIALIZED_VIEW Indicates the query has been optimized by using a materialized view.
SECURED_BY_DATA_MASKING Indicates the query has been secured by data masking, and thus search indexes are not applicable.
MISMATCHED_TEXT_ANALYZER Indicates that the search index and the search function call do not have the same text analyzer.
BASE_TABLE_TOO_SMALL Indicates the base table is too small (below a certain threshold). The index does not provide noticeable search performance gains when the base table is too small.
BASE_TABLE_TOO_LARGE

Indicates that the total size of indexed base tables in your organization exceeds your region's limit and the index is not used in the query. To index larger base tables, you can use your own reservation for index-management jobs.
ESTIMATED_PERFORMANCE_GAIN_TOO_LOW Indicates that the estimated performance gain from using the search index is too low for the given search query.
COLUMN_METADATA_INDEX_NOT_USED Indicates that the column metadata index (which the search index depends on) is not used. User can refer to the column metadata index usage for more details on why it was not used.
NOT_SUPPORTED_IN_STANDARD_EDITION Indicates that search indexes can not be used for search query with STANDARD edition.
INDEX_SUPPRESSED_BY_FUNCTION_OPTION Indicates that an option in the search function that cannot make use of the index has been selected.
QUERY_CACHE_HIT Indicates that the query was cached, and thus the search index was not used.
STALE_INDEX The index cannot be used in the search query because it is stale.
INTERNAL_ERROR Indicates an internal error that causes the search index to be unused.
OTHER_REASON Indicates that the reason search indexes cannot be used in the query is not covered by any of the other IndexUnusedReason options.

IndexUsageMode

Indicates the type of vector index usage in the entire vector search query.

Enums
INDEX_USAGE_MODE_UNSPECIFIED Index usage mode not specified.
UNUSED No vector indexes were used in the vector search query. See indexUnusedReasons for detailed reasons.
PARTIALLY_USED Part of the vector search query used vector indexes. See indexUnusedReasons for why other parts of the query did not use vector indexes.
FULLY_USED The entire vector search query used vector indexes.

Code

Indicates the high-level reason for the scenario when stored columns cannot be used in the query.

Enums
CODE_UNSPECIFIED Default value.
STORED_COLUMNS_COVER_INSUFFICIENT If stored columns do not fully cover the columns.
BASE_TABLE_HAS_RLS If the base table has RLS (Row Level Security).
BASE_TABLE_HAS_CLS If the base table has CLS (Column Level Security).
UNSUPPORTED_PREFILTER If the provided prefilter is not supported.
INTERNAL_ERROR If an internal error is preventing stored columns from being used.
OTHER_REASON Indicates that the reason stored columns cannot be used in the query is not covered by any of the other StoredColumnsUnusedReason options.

RejectedReason

Reason why a materialized view was not chosen for a query. For more information, see Understand why materialized views were rejected.

Enums
REJECTED_REASON_UNSPECIFIED Default unspecified value.
NO_DATA View has no cached data because it has not refreshed yet.
COST

The estimated cost of the view is more expensive than another view or the base table.

Note: The estimate cost might not match the billed cost.
BASE_TABLE_TRUNCATED View has no cached data because a base table is truncated.
BASE_TABLE_DATA_CHANGE View is invalidated because of a data change in one or more base tables. It could be any recent change if the maxStaleness option is not set for the view, or otherwise any change outside of the staleness window.
BASE_TABLE_PARTITION_EXPIRATION_CHANGE View is invalidated because a base table's partition expiration has changed.
BASE_TABLE_EXPIRED_PARTITION View is invalidated because a base table's partition has expired.
BASE_TABLE_INCOMPATIBLE_METADATA_CHANGE View is invalidated because a base table has an incompatible metadata change.
TIME_ZONE View is invalidated because it was refreshed with a time zone other than that of the current job.
OUT_OF_TIME_TRAVEL_WINDOW View is outside the time travel window.
BASE_TABLE_FINE_GRAINED_SECURITY_POLICY View is inaccessible to the user because of a fine-grained security policy on one of its base tables.
BASE_TABLE_TOO_STALE One of the view's base tables is too stale. For example, the cached metadata of a BigLake external table needs to be updated.

UnusedReason

Reasons for not using metadata caching.

Enums
UNUSED_REASON_UNSPECIFIED Unused reasons not specified.
EXCEEDED_MAX_STALENESS Metadata cache was outside the table's maxStaleness.
METADATA_CACHING_NOT_ENABLED Metadata caching feature is not enabled. Update BigLake tables to enable the metadata caching.
OTHER_REASON Other unknown reason.

DisabledReason

Reason why incremental query results are/were not written by the query.

Enums
DISABLED_REASON_UNSPECIFIED Disabled reason not specified.
OTHER Incremental results are/were disabled for reasons not covered by the other enum values, e.g. runtime issues.
UNSUPPORTED_OPERATOR Query includes an operation that is not supported.

CloudProvider

The cloud provider hosting the object storage.

Enums
CLOUD_PROVIDER_UNSPECIFIED Unspecified cloud provider.
GCP Google Cloud Platform.
AWS Amazon Web Services.
AZURE Microsoft Azure.

EvaluationKind

Describes how the job is evaluated.

Enums
EVALUATION_KIND_UNSPECIFIED Default value.
STATEMENT The statement appears directly in the script.
EXPRESSION The statement evaluates an expression that appears in the script.

ReservationEdition

The type of editions. Different features and behaviors are provided to different editions Capacity commitments and reservations are linked to editions.

Enums
RESERVATION_EDITION_UNSPECIFIED Default value, which will be treated as ENTERPRISE.
STANDARD Standard edition.
ENTERPRISE Enterprise edition.
ENTERPRISE_PLUS Enterprise Plus edition.

Code

Indicates the high level reason why a job was created.

Enums
CODE_UNSPECIFIED Reason is not specified.
REQUESTED Job creation was requested.
LONG_RUNNING The query request ran beyond a system defined timeout specified by the timeoutMs field in the QueryRequest. As a result it was considered a long running operation for which a job was created.
LARGE_RESULTS The results from the query cannot fit in the response.
OTHER BigQuery has determined that the query needs to be executed as a Job.

Tool Annotations

Tool annotations are sent to MCP clients to describe the basic risk of a given tool. Most clients treat these hints as untrusted, but they can be used to decide when a confirmation prompt might be sent to a user.

Along with the title string, the following boolean hints are defined as follows:

  • readOnlyHint: If true, the tool doesn't modify its environment. Default: false.
  • destructiveHint: If true, then the tool can perform destructive actions. If false, then the tool can only perform additive actions. Default: true.
  • idempotentHint: If true, then calling the tool repeatedly with the same arguments will have no additional effect on its environment. Default: false.
  • openWorldHint: If true, then the tool can interact with an 'open world' of external entities. If false, then the tool can only interact with internal entities. For example, a web search tool would be open world, while a memory tool would not be open world.

Destructive Hint: ✅ | Idempotent Hint: ✅ | Read Only Hint: ❌ | Open World Hint: ❌