/*
* Copyright (C) 2020 Google LLC
*
* Licensed under the Apache License, Version 2.0 (the "License"); you may not
* use this file except in compliance with the License. You may obtain a copy of
* the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
* License for the specific language governing permissions and limitations under
* the License.
*/
package com.google.cloud.teleport.v2.templates;
import com.google.api.gax.retrying.RetrySettings;
import com.google.api.services.datastream.v1.model.SourceConfig;
import com.google.cloud.spanner.Options.RpcPriority;
import com.google.cloud.teleport.metadata.Template;
import com.google.cloud.teleport.metadata.TemplateCategory;
import com.google.cloud.teleport.metadata.TemplateParameter;
import com.google.cloud.teleport.metadata.TemplateParameter.TemplateEnumOption;
import com.google.cloud.teleport.v2.cdc.dlq.DeadLetterQueueManager;
import com.google.cloud.teleport.v2.cdc.dlq.PubSubNotifiedDlqIO;
import com.google.cloud.teleport.v2.cdc.dlq.StringDeadLetterQueueSanitizer;
import com.google.cloud.teleport.v2.coders.FailsafeElementCoder;
import com.google.cloud.teleport.v2.common.UncaughtExceptionLogger;
import com.google.cloud.teleport.v2.datastream.sources.DataStreamIO;
import com.google.cloud.teleport.v2.datastream.utils.DataStreamClient;
import com.google.cloud.teleport.v2.spanner.ddl.Ddl;
import com.google.cloud.teleport.v2.spanner.migrations.constants.Constants;
import com.google.cloud.teleport.v2.spanner.migrations.schema.ISchemaOverridesParser;
import com.google.cloud.teleport.v2.spanner.migrations.schema.NoopSchemaOverridesParser;
import com.google.cloud.teleport.v2.spanner.migrations.schema.Schema;
import com.google.cloud.teleport.v2.spanner.migrations.schema.SchemaFileOverridesParser;
import com.google.cloud.teleport.v2.spanner.migrations.schema.SchemaStringOverridesParser;
import com.google.cloud.teleport.v2.spanner.migrations.shard.ShardingContext;
import com.google.cloud.teleport.v2.spanner.migrations.transformation.CustomTransformation;
import com.google.cloud.teleport.v2.spanner.migrations.transformation.TransformationContext;
import com.google.cloud.teleport.v2.spanner.migrations.utils.DataflowWorkerMachineTypeUtils;
import com.google.cloud.teleport.v2.spanner.migrations.utils.SessionFileReader;
import com.google.cloud.teleport.v2.spanner.migrations.utils.ShardingContextReader;
import com.google.cloud.teleport.v2.spanner.migrations.utils.TransformationContextReader;
import com.google.cloud.teleport.v2.templates.DataStreamToSpanner.Options;
import com.google.cloud.teleport.v2.templates.constants.DatastreamToSpannerConstants;
import com.google.cloud.teleport.v2.templates.datastream.DatastreamConstants;
import com.google.cloud.teleport.v2.templates.spanner.ProcessInformationSchema;
import com.google.cloud.teleport.v2.templates.transform.ChangeEventTransformerDoFn;
import com.google.cloud.teleport.v2.transforms.DLQWriteTransform;
import com.google.cloud.teleport.v2.values.FailsafeElement;
import com.google.common.base.Strings;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.HashMap;
import java.util.Map;
import org.apache.beam.runners.dataflow.options.DataflowPipelineOptions;
import org.apache.beam.runners.dataflow.options.DataflowPipelineWorkerPoolOptions;
import org.apache.beam.sdk.Pipeline;
import org.apache.beam.sdk.PipelineResult;
import org.apache.beam.sdk.coders.StringUtf8Coder;
import org.apache.beam.sdk.extensions.gcp.options.GcpOptions;
import org.apache.beam.sdk.io.TextIO;
import org.apache.beam.sdk.io.gcp.spanner.SpannerConfig;
import org.apache.beam.sdk.io.gcp.spanner.SpannerServiceFactoryImpl;
import org.apache.beam.sdk.options.Default;
import org.apache.beam.sdk.options.PipelineOptions;
import org.apache.beam.sdk.options.PipelineOptionsFactory;
import org.apache.beam.sdk.options.StreamingOptions;
import org.apache.beam.sdk.options.ValueProvider;
import org.apache.beam.sdk.transforms.Flatten;
import org.apache.beam.sdk.transforms.MapElements;
import org.apache.beam.sdk.transforms.ParDo;
import org.apache.beam.sdk.transforms.Reshuffle;
import org.apache.beam.sdk.transforms.View;
import org.apache.beam.sdk.transforms.windowing.FixedWindows;
import org.apache.beam.sdk.transforms.windowing.Window;
import org.apache.beam.sdk.values.PCollection;
import org.apache.beam.sdk.values.PCollectionList;
import org.apache.beam.sdk.values.PCollectionTuple;
import org.apache.beam.sdk.values.PCollectionView;
import org.apache.beam.sdk.values.TupleTagList;
import org.joda.time.Duration;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
* This pipeline ingests DataStream data from GCS as events. The events are written to Cloud
* Spanner.
*
* <p>NOTE: Future versions will support: Pub/Sub, GCS, or Kafka as per DataStream
*
* <p>Check out <a
* href="https://github.com/GoogleCloudPlatform/DataflowTemplates/blob/main/v2/datastream-to-spanner/README_Cloud_Datastream_to_Spanner.md">README</a>
* for instructions on how to use or modify this template.
*/
@Template(
name = "Cloud_Datastream_to_Spanner",
category = TemplateCategory.STREAMING,
displayName = "Datastream to Cloud Spanner",
description = {
"The Datastream to Cloud Spanner template is a streaming pipeline that reads <a"
+ " href=\"https://cloud.google.com/datastream/docs\">Datastream</a> events from a Cloud"
+ " Storage bucket and writes them to a Cloud Spanner database. It is intended for data"
+ " migration from Datastream sources to Cloud Spanner.\n",
"All tables required for migration must exist in the destination Cloud Spanner database prior"
+ " to template execution. Hence schema migration from a source database to destination"
+ " Cloud Spanner must be completed prior to data migration. Data can exist in the tables"
+ " prior to migration. This template does not propagate Datastream schema changes to the"
+ " Cloud Spanner database.\n",
"Data consistency is guaranteed only at the end of migration when all data has been written"
+ " to Cloud Spanner. To store ordering information for each record written to Cloud"
+ " Spanner, this template creates an additional table (called a shadow table) for each"
+ " table in the Cloud Spanner database. This is used to ensure consistency at the end of"
+ " migration. The shadow tables are not deleted after migration and can be used for"
+ " validation purposes at the end of migration.\n",
"Any errors that occur during operation, such as schema mismatches, malformed JSON files, or"
+ " errors resulting from executing transforms, are recorded in an error queue. The error"
+ " queue is a Cloud Storage folder which stores all the Datastream events that had"
+ " encountered errors along with the error reason in text format. The errors can be"
+ " transient or permanent and are stored in appropriate Cloud Storage folders in the"
+ " error queue. The transient errors are retried automatically while the permanent"
+ " errors are not. In case of permanent errors, you can run the pipeline in one of"
+ " two retry modes depending on your pipeline state. Use `retryDLQ` mode when the"
+ " regular pipeline is concurrently running and pointing to the same DLQ directory."
+ " This mode consumes only severe errors while the regular mode will consume the retriable errors."
+ " Use `retryAllDLQ` mode when the regular pipeline is not running or is stopped."
+ " The `retryAllDLQ` mode consumes errors from both the retry and severe buckets. Do NOT run `retryAllDLQ` concurrently"
+ " with the regular pipeline as they will conflict."
},
optionsClass = Options.class,
flexContainerName = "datastream-to-spanner",
documentation =
"https://cloud.google.com/dataflow/docs/guides/templates/provided/datastream-to-cloud-spanner",
contactInformation = "https://cloud.google.com/support",
requirements = {
"A Datastream stream in Running or Not started state.",
"A Cloud Storage bucket where Datastream events are replicated.",
"A Cloud Spanner database with existing tables. These tables can be empty or contain data.",
},
streaming = true,
supportsAtLeastOnce = true)
public class DataStreamToSpanner {
private static final Logger LOG = LoggerFactory.getLogger(DataStreamToSpanner.class);
private static final String AVRO_SUFFIX = "avro";
private static final String JSON_SUFFIX = "json";
/**
* Options supported by the pipeline.
*
* <p>Inherits standard configuration options.
*/
public interface Options
extends PipelineOptions, StreamingOptions, DataflowPipelineWorkerPoolOptions {
@TemplateParameter.GcsReadFile(
order = 1,
groupName = "Source",
optional = true,
description =
"File location for Datastream file output in Cloud Storage. Support for this feature has been disabled.",
helpText =
"The Cloud Storage file location that contains the Datastream files to replicate. Typically, "
+ "this is the root path for a stream. Support for this feature has been disabled."
+ " Please use this feature only for retrying entries that land in severe DLQ.")
String getInputFilePattern();
void setInputFilePattern(String value);
@TemplateParameter.Enum(
order = 2,
enumOptions = {@TemplateEnumOption("avro"), @TemplateEnumOption("json")},
optional = true,
description = "Datastream output file format (avro/json).",
helpText =
"The format of the output file produced by Datastream. For example `avro,json`. Defaults to `avro`.")
@Default.String("avro")
String getInputFileFormat();
void setInputFileFormat(String value);
@TemplateParameter.GcsReadFile(
order = 3,
optional = true,
description = "Session File Path in Cloud Storage",
helpText =
"Session file path in Cloud Storage that contains mapping information from"
+ " HarbourBridge")
String getSessionFilePath();
void setSessionFilePath(String value);
@TemplateParameter.Text(
order = 4,
groupName = "Target",
description = "Cloud Spanner Instance Id.",
helpText = "The Spanner instance where the changes are replicated.")
String getInstanceId();
void setInstanceId(String value);
@TemplateParameter.Text(
order = 5,
groupName = "Target",
description = "Cloud Spanner Database Id.",
helpText = "The Spanner database where the changes are replicated.")
String getDatabaseId();
void setDatabaseId(String value);
@TemplateParameter.ProjectId(
order = 6,
groupName = "Target",
optional = true,
description = "Cloud Spanner Project Id.",
helpText = "The Spanner project ID.")
String getProjectId();
void setProjectId(String projectId);
@TemplateParameter.Text(
order = 7,
groupName = "Target",
optional = true,
description = "The Cloud Spanner Endpoint to call",
helpText = "The Cloud Spanner endpoint to call in the template.",
example = "https://batch-spanner.googleapis.com")
@Default.String("https://batch-spanner.googleapis.com")
String getSpannerHost();
void setSpannerHost(String value);
@TemplateParameter.PubsubSubscription(
order = 8,
optional = true,
description = "The Pub/Sub subscription being used in a Cloud Storage notification policy.",
helpText =
"The Pub/Sub subscription being used in a Cloud Storage notification policy. For the name,"
+ " use the format `projects/<PROJECT_ID>/subscriptions/<SUBSCRIPTION_NAME>`.")
String getGcsPubSubSubscription();
void setGcsPubSubSubscription(String value);
@TemplateParameter.Text(
order = 9,
groupName = "Source",
optional = true,
description = "Datastream stream name.",
helpText =
"The name or template for the stream to poll for schema information and source type.")
String getStreamName();
void setStreamName(String value);
@TemplateParameter.Text(
order = 10,
optional = true,
description = "Cloud Spanner shadow table prefix.",
helpText = "The prefix used to name shadow tables. Default: `shadow_`.")
@Default.String("shadow_")
String getShadowTablePrefix();
void setShadowTablePrefix(String value);
@TemplateParameter.Boolean(
order = 11,
optional = true,
description = "If true, create shadow tables in Cloud Spanner.",
helpText =
"This flag indicates whether shadow tables must be created in Cloud Spanner database.")
@Default.Boolean(true)
Boolean getShouldCreateShadowTables();
void setShouldCreateShadowTables(Boolean value);
@TemplateParameter.DateTime(
order = 12,
optional = true,
description =
"The starting DateTime used to fetch from Cloud Storage "
+ "(https://tools.ietf.org/html/rfc3339).",
helpText =
"The starting DateTime used to fetch from Cloud Storage "
+ "(https://tools.ietf.org/html/rfc3339).")
@Default.String("1970-01-01T00:00:00.00Z")
String getRfcStartDateTime();
void setRfcStartDateTime(String value);
@TemplateParameter.Integer(
order = 13,
optional = true,
description = "File read concurrency",
helpText = "The number of concurrent DataStream files to read.")
@Default.Integer(30)
Integer getFileReadConcurrency();
void setFileReadConcurrency(Integer value);
@TemplateParameter.Text(
order = 14,
optional = true,
description = "Dead letter queue directory.",
helpText =
"The file path used when storing the error queue output. "
+ "The default file path is a directory under the Dataflow job's temp location.")
@Default.String("")
String getDeadLetterQueueDirectory();
void setDeadLetterQueueDirectory(String value);
@TemplateParameter.Integer(
order = 15,
optional = true,
description = "Dead letter queue retry minutes",
helpText = "The number of minutes between dead letter queue retries. Defaults to `10`.")
@Default.Integer(10)
Integer getDlqRetryMinutes();
void setDlqRetryMinutes(Integer value);
@TemplateParameter.Integer(
order = 16,
optional = true,
description = "Dead letter queue maximum retry count",
helpText =
"The max number of times temporary errors can be retried through DLQ. Defaults to `500`.")
@Default.Integer(500)
Integer getDlqMaxRetryCount();
void setDlqMaxRetryCount(Integer value);
// DataStream API Root Url (only used for testing)
@TemplateParameter.Text(
order = 17,
optional = true,
description = "Datastream API Root URL (only required for testing)",
helpText = "Datastream API Root URL.")
@Default.String("https://datastream.googleapis.com/")
String getDataStreamRootUrl();
void setDataStreamRootUrl(String value);
@TemplateParameter.Text(
order = 18,
optional = true,
description = "Datastream source type (only required for testing)",
helpText =
"This is the type of source database that Datastream connects to. Example -"
+ " mysql/oracle. Need to be set when testing without an actual running"
+ " Datastream.")
String getDatastreamSourceType();
void setDatastreamSourceType(String value);
@TemplateParameter.Boolean(
order = 19,
optional = true,
description =
"If true, rounds the decimal values in json columns to a number that can be stored"
+ " without loss of precision.",
helpText =
"This flag if set, rounds the decimal values in json columns to a number that can be"
+ " stored without loss of precision.")
@Default.Boolean(false)
Boolean getRoundJsonDecimals();
void setRoundJsonDecimals(Boolean value);
@TemplateParameter.Enum(
order = 20,
optional = true,
description = "Run mode - currently supported are : regular, retryDLQ, or retryAllDLQ",
enumOptions = {
@TemplateEnumOption(Constants.RUN_MODE_REGULAR),
@TemplateEnumOption(Constants.RUN_MODE_RETRY_DLQ),
@TemplateEnumOption(Constants.RUN_MODE_RETRY_ALL_DLQ)
},
helpText =
"This is the run mode type. Default is regular. Use `retryDLQ` mode to process exclusively severe error files concurrently with your live migration pipeline. Use `retryAllDLQ` mode only when the regular pipeline is stopped. This mode processes both retry and severe directories. Do NOT run `retryAllDLQ` concurrently with any active pipeline as it will cause conflicts.")
@Default.String(Constants.RUN_MODE_REGULAR)
String getRunMode();
void setRunMode(String value);
@TemplateParameter.GcsReadFile(
order = 21,
optional = true,
helpText =
"Transformation context file path in cloud storage used to populate data used in"
+ " transformations performed during migrations Eg: The shard id to db name to"
+ " identify the db from which a row was migrated",
description = "Transformation context file path in cloud storage")
String getTransformationContextFilePath();
void setTransformationContextFilePath(String value);
@TemplateParameter.Integer(
order = 22,
optional = true,
description = "Directory watch duration in minutes. Default: 10 minutes",
helpText =
"The Duration for which the pipeline should keep polling a directory in GCS. Datastream"
+ "output files are arranged in a directory structure which depicts the timestamp "
+ "of the event grouped by minutes. This parameter should be approximately equal to"
+ "maximum delay which could occur between event occurring in source database and "
+ "the same event being written to GCS by Datastream. 99.9 percentile = 10 minutes")
@Default.Integer(10)
Integer getDirectoryWatchDurationInMinutes();
void setDirectoryWatchDurationInMinutes(Integer value);
@TemplateParameter.Enum(
order = 23,
enumOptions = {
@TemplateEnumOption("LOW"),
@TemplateEnumOption("MEDIUM"),
@TemplateEnumOption("HIGH")
},
optional = true,
description = "Priority for Spanner RPC invocations",
helpText =
"The request priority for Cloud Spanner calls. The value must be one of:"
+ " [`HIGH`,`MEDIUM`,`LOW`]. Defaults to `HIGH`.")
@Default.Enum("HIGH")
RpcPriority getSpannerPriority();
void setSpannerPriority(RpcPriority value);
@TemplateParameter.PubsubSubscription(
order = 24,
optional = true,
description =
"The Pub/Sub subscription being used in a Cloud Storage notification policy for DLQ"
+ " retry directory when running in regular mode.",
helpText =
"The Pub/Sub subscription being used in a Cloud Storage notification policy for DLQ"
+ " retry directory when running in regular mode. For the name, use the format"
+ " `projects/<PROJECT_ID>/subscriptions/<SUBSCRIPTION_NAME>`. When set, the"
+ " deadLetterQueueDirectory and dlqRetryMinutes are ignored.")
String getDlqGcsPubSubSubscription();
void setDlqGcsPubSubSubscription(String value);
@TemplateParameter.GcsReadFile(
order = 25,
optional = true,
description = "Custom jar location in Cloud Storage",
helpText =
"Custom JAR file location in Cloud Storage for the file that contains the custom transformation logic for processing records"
+ " in forward migration.")
@Default.String("")
String getTransformationJarPath();
void setTransformationJarPath(String value);
@TemplateParameter.Text(
order = 26,
optional = true,
description = "Custom class name",
helpText =
"Fully qualified class name having the custom transformation logic. It is a"
+ " mandatory field in case transformationJarPath is specified")
@Default.String("")
String getTransformationClassName();
void setTransformationClassName(String value);
@TemplateParameter.Text(
order = 27,
optional = true,
description = "Custom parameters for transformation",
helpText =
"String containing any custom parameters to be passed to the custom transformation class.")
@Default.String("")
String getTransformationCustomParameters();
void setTransformationCustomParameters(String value);
@TemplateParameter.Text(
order = 28,
optional = true,
description = "Filtered events directory",
helpText =
"This is the file path to store the events filtered via custom transformation. Default is a directory"
+ " under the Dataflow job's temp location. The default value is enough under most"
+ " conditions.")
@Default.String("")
String getFilteredEventsDirectory();
void setFilteredEventsDirectory(String value);
@TemplateParameter.GcsReadFile(
order = 29,
optional = true,
helpText =
"Sharding context file path in cloud storage is used to populate the shard id in spanner database for each source shard."
+ "It expects a JSON file with the format: {\\\"StreamToDbAndShardMap\\\": Map<stream_name, Map<db_name, shard_id>>}",
description = "Sharding context file path in cloud storage")
String getShardingContextFilePath();
void setShardingContextFilePath(String value);
@TemplateParameter.Text(
order = 30,
optional = true,
description = "Table name overrides from source to spanner",
regexes =
"^\\[([[:space:]]*\\{[[:space:]]*[[:graph:]]+[[:space:]]*,[[:space:]]*[[:graph:]]+[[:space:]]*\\}[[:space:]]*(,[[:space:]]*)*)*\\]$",
example = "[{Singers, Vocalists}, {Albums, Records}]",
helpText =
"These are the table name overrides from source to spanner. They are written in the"
+ "following format: [{SourceTableName1, SpannerTableName1}, {SourceTableName2, SpannerTableName2}]"
+ "This example shows mapping Singers table to Vocalists and Albums table to Records.")
@Default.String("")
String getTableOverrides();
void setTableOverrides(String value);
@TemplateParameter.Text(
order = 31,
optional = true,
regexes =
"^\\[([[:space:]]*\\{[[:space:]]*[[:graph:]]+\\.[[:graph:]]+[[:space:]]*,[[:space:]]*[[:graph:]]+\\.[[:graph:]]+[[:space:]]*\\}[[:space:]]*(,[[:space:]]*)*)*\\]$",
description = "Column name overrides from source to spanner",
example =
"[{Singers.SingerName, Singers.TalentName}, {Albums.AlbumName, Albums.RecordName}]",
helpText =
"These are the column name overrides from source to spanner. They are written in the"
+ "following format: [{SourceTableName1.SourceColumnName1, SourceTableName1.SpannerColumnName1}, {SourceTableName2.SourceColumnName1, SourceTableName2.SpannerColumnName1}]"
+ "Note that the SourceTableName should remain the same in both the source and spanner pair. To override table names, use tableOverrides."
+ "The example shows mapping SingerName to TalentName and AlbumName to RecordName in Singers and Albums table respectively.")
@Default.String("")
String getColumnOverrides();
void setColumnOverrides(String value);
@TemplateParameter.Text(
order = 32,
optional = true,
description = "File based overrides from source to spanner",
helpText =
"A file which specifies the table and the column name overrides from source to spanner.")
@Default.String("")
String getSchemaOverridesFilePath();
void setSchemaOverridesFilePath(String value);
@TemplateParameter.Text(
order = 33,
optional = true,
groupName = "Target",
description = "Cloud Spanner Shadow Table Instance Id.",
helpText =
"Optional separate instance for shadow tables. If not specified, shadow tables will be created in the main instance. If specified, ensure shadowTableSpannerDatabaseId is specified as well.")
@Default.String("")
String getShadowTableSpannerInstanceId();
void setShadowTableSpannerInstanceId(String value);
@TemplateParameter.Text(
order = 33,
optional = true,
groupName = "Target",
description = "Cloud Spanner Shadow Table Database Id.",
helpText =
"Optional separate database for shadow tables. If not specified, shadow tables will be created in the main database. If specified, ensure shadowTableSpannerInstanceId is specified as well.")
@Default.String("")
String getShadowTableSpannerDatabaseId();
void setShadowTableSpannerDatabaseId(String value);
@TemplateParameter.Text(
order = 34,
optional = true,
description = "Failure injection parameter",
helpText = "Failure injection parameter. Only used for testing.")
@Default.String("")
String getFailureInjectionParameter();
void setFailureInjectionParameter(String value);
}
private static void validateSourceType(Options options) {
boolean isRetryMode = Constants.RUN_MODE_RETRY_DLQ.equals(options.getRunMode());
if (isRetryMode) {
// retry mode does not read from Datastream
return;
}
String sourceType = getSourceType(options);
if (!DatastreamConstants.SUPPORTED_DATASTREAM_SOURCES.contains(sourceType)) {
throw new IllegalArgumentException(
"Unsupported source type found: "
+ sourceType
+ ". Specify one of the following source types: "
+ DatastreamConstants.SUPPORTED_DATASTREAM_SOURCES);
}
options.setDatastreamSourceType(sourceType);
}
static String getSourceType(Options options) {
if (options.getDatastreamSourceType() != null) {
return options.getDatastreamSourceType();
}
if (options.getStreamName() == null) {
throw new IllegalArgumentException("Stream name cannot be empty.");
}
GcpOptions gcpOptions = options.as(GcpOptions.class);
DataStreamClient datastreamClient;
SourceConfig sourceConfig;
try {
datastreamClient = new DataStreamClient(gcpOptions.getGcpCredential());
sourceConfig = datastreamClient.getSourceConnectionProfile(options.getStreamName());
} catch (IOException e) {
LOG.error("IOException Occurred: DataStreamClient failed initialization.");
throw new IllegalArgumentException("Unable to initialize DatastreamClient: " + e);
}
if (sourceConfig.getMysqlSourceConfig() != null) {
return DatastreamConstants.MYSQL_SOURCE_TYPE;
} else if (sourceConfig.getOracleSourceConfig() != null) {
return DatastreamConstants.ORACLE_SOURCE_TYPE;
} else if (sourceConfig.getPostgresqlSourceConfig() != null) {
return DatastreamConstants.POSTGRES_SOURCE_TYPE;
}
LOG.error("Source Connection Profile Type Not Supported");
throw new IllegalArgumentException("Unsupported source connection profile type in Datastream");
}
/**
* Main entry point for executing the pipeline.
*
* @param args The command-line arguments to the pipeline.
*/
public static void main(String[] args) {
UncaughtExceptionLogger.register();
LOG.info("Starting DataStream to Cloud Spanner");
Options options = PipelineOptionsFactory.fromArgs(args).withValidation().as(Options.class);
boolean isRetryDLQMode = Constants.RUN_MODE_RETRY_DLQ.equals(options.getRunMode());
options.setStreaming(!isRetryDLQMode);
validateSourceType(options);
run(options);
}
/**
* Runs the pipeline with the supplied options.
*
* @param options The execution parameters to the pipeline.
* @return The result of the pipeline execution.
*/
public static PipelineResult run(Options options) {
long startTime = System.currentTimeMillis();
/*
* Stages:
* 1) Ingest and Normalize Data to FailsafeElement with JSON Strings
* 2) Write JSON Strings to Cloud Spanner
* 3) Write Failures to GCS Dead Letter Queue
*/
Pipeline pipeline = Pipeline.create(options);
String workerMachineType =
pipeline.getOptions().as(DataflowPipelineWorkerPoolOptions.class).getWorkerMachineType();
DataflowWorkerMachineTypeUtils.validateMachineSpecs(workerMachineType, 4);
DeadLetterQueueManager dlqManager = buildDlqManager(options);
// Ingest session file into schema object.
Schema schema = SessionFileReader.read(options.getSessionFilePath());
/*
* Stage 1: Ingest/Normalize Data to FailsafeElement with JSON Strings and
* read Cloud Spanner information schema.
* a) Prepare spanner config and process information schema
* b) Read DataStream data from GCS into JSON String FailsafeElements
* c) Reconsume Dead Letter Queue data from GCS into JSON String FailsafeElements
* d) Flatten DataStream and DLQ Streams
*/
// Prepare Spanner config
SpannerConfig spannerConfig =
SpannerConfig.create()
.withProjectId(ValueProvider.StaticValueProvider.of(options.getProjectId()))
.withHost(ValueProvider.StaticValueProvider.of(options.getSpannerHost()))
.withInstanceId(ValueProvider.StaticValueProvider.of(options.getInstanceId()))
.withDatabaseId(ValueProvider.StaticValueProvider.of(options.getDatabaseId()))
.withRpcPriority(ValueProvider.StaticValueProvider.of(options.getSpannerPriority()))
.withCommitRetrySettings(
RetrySettings.newBuilder()
.setTotalTimeout(org.threeten.bp.Duration.ofMinutes(4))
.setInitialRetryDelay(org.threeten.bp.Duration.ofMinutes(0))
.setRetryDelayMultiplier(1)
.setMaxRetryDelay(org.threeten.bp.Duration.ofMinutes(0))
.setInitialRpcTimeout(org.threeten.bp.Duration.ofMinutes(4))
.setRpcTimeoutMultiplier(1)
.setMaxRpcTimeout(org.threeten.bp.Duration.ofMinutes(4))
.setMaxAttempts(1)
.build());
SpannerConfig shadowTableSpannerConfig = getShadowTableSpannerConfig(options);
/* Process information schema
* 1) Read information schema from destination Cloud Spanner database
* 2) Check if shadow tables are present and create if necessary
* 3) Return new information schema
*/
PCollectionTuple ddlTuple =
pipeline.apply(
"Process Information Schema",
new ProcessInformationSchema(
spannerConfig,
shadowTableSpannerConfig,
options.getShouldCreateShadowTables(),
options.getShadowTablePrefix(),
options.getDatastreamSourceType()));
PCollectionView<Ddl> ddlView =
ddlTuple
.get(ProcessInformationSchema.MAIN_DDL_TAG)
.apply("Cloud Spanner Main DDL as view", View.asSingleton());
PCollectionView<Ddl> shadowTableDdlView =
ddlTuple
.get(ProcessInformationSchema.SHADOW_TABLE_DDL_TAG)
.apply("Cloud Spanner shadow tables DDL as view", View.asSingleton());
PCollection<FailsafeElement<String, String>> jsonRecords = null;
// Elements sent to the Dead Letter Queue are to be reconsumed.
// A DLQManager is to be created using PipelineOptions, and it is in charge
// of building pieces of the DLQ.
PCollectionTuple reconsumedElements = null;
boolean isRegularMode = Constants.RUN_MODE_REGULAR.equals(options.getRunMode());
if (isRegularMode && (!Strings.isNullOrEmpty(options.getDlqGcsPubSubSubscription()))) {
reconsumedElements =
dlqManager.getReconsumerDataTransformForFiles(
pipeline.apply(
"Read retry from PubSub",
new PubSubNotifiedDlqIO(
options.getDlqGcsPubSubSubscription(),
// file paths to ignore when re-consuming for retry
new ArrayList<String>(
Arrays.asList("/severe/", "/tmp_retry", "/tmp_severe/", ".temp")))));
} else {
if (isRegularMode) {
reconsumedElements =
dlqManager.getReconsumerDataTransform(
pipeline.apply(dlqManager.dlqReconsumer(options.getDlqRetryMinutes())));
} else { // retryDLQ or retryAllDLQ mode
PCollection<String> oneShotRecords =
pipeline.apply("Read severe from OneShot", dlqManager.dlqOneShotReconsumer(startTime));
if (Constants.RUN_MODE_RETRY_DLQ.equals(options.getRunMode())) {
reconsumedElements = dlqManager.getReconsumerDataTransform(oneShotRecords);
} else {
// retryAllDLQ mode: Drain both the severe (one-shot) and retry (continuous) buckets
PCollection<String> continuousRecords =
pipeline.apply(
"Read retry from Continuous",
dlqManager.dlqReconsumer(options.getDlqRetryMinutes()));
PCollection<String> allRecords =
PCollectionList.of(continuousRecords)
.and(oneShotRecords)
.apply("Flatten DLQ Records", Flatten.pCollections());
reconsumedElements = dlqManager.getReconsumerDataTransform(allRecords);
}
}
}
PCollection<FailsafeElement<String, String>> dlqJsonRecords =
reconsumedElements
.get(DeadLetterQueueManager.RETRYABLE_ERRORS)
.setCoder(FailsafeElementCoder.of(StringUtf8Coder.of(), StringUtf8Coder.of()));
if (isRegularMode) {
LOG.info("Regular Datastream flow");
PCollection<FailsafeElement<String, String>> datastreamJsonRecords =
pipeline.apply(
new DataStreamIO(
options.getStreamName(),
options.getInputFilePattern(),
options.getInputFileFormat(),
options.getGcsPubSubSubscription(),
options.getRfcStartDateTime())
.withFileReadConcurrency(options.getFileReadConcurrency())
.withoutDatastreamRecordsReshuffle()
.withDirectoryWatchDuration(
Duration.standardMinutes(options.getDirectoryWatchDurationInMinutes()))
.withDatastreamSourceType(options.getDatastreamSourceType()));
int maxNumWorkers = options.getMaxNumWorkers() != 0 ? options.getMaxNumWorkers() : 1;
jsonRecords =
PCollectionList.of(datastreamJsonRecords)
.and(dlqJsonRecords)
.apply(Flatten.pCollections())
.apply(
"Reshuffle",
Reshuffle.<FailsafeElement<String, String>>viaRandomKey()
.withNumBuckets(
maxNumWorkers * DatastreamToSpannerConstants.MAX_DOFN_PER_WORKER));
} else {
LOG.info("DLQ retry flow");
jsonRecords =
PCollectionList.of(dlqJsonRecords)
.apply(Flatten.pCollections())
.apply("Reshuffle", Reshuffle.viaRandomKey());
}
/*
* Stage 2: Transform records
*/
// Ingest transformation context file into memory.
TransformationContext transformationContext =
TransformationContextReader.getTransformationContext(
options.getTransformationContextFilePath());
// Ingest sharding context file into memory.
ShardingContext shardingContext =
ShardingContextReader.getShardingContext(options.getShardingContextFilePath());
CustomTransformation customTransformation =
CustomTransformation.builder(
options.getTransformationJarPath(), options.getTransformationClassName())
.setCustomParameters(options.getTransformationCustomParameters())
.build();
// Create the overrides mapping.
ISchemaOverridesParser schemaOverridesParser = configureSchemaOverrides(options);
ChangeEventTransformerDoFn changeEventTransformerDoFn =
ChangeEventTransformerDoFn.create(
schema,
schemaOverridesParser,
transformationContext,
shardingContext,
options.getDatastreamSourceType(),
customTransformation,
options.getRoundJsonDecimals(),
ddlView,
spannerConfig);
PCollectionTuple transformedRecords =
jsonRecords.apply(
"Apply Transformation to events",
ParDo.of(changeEventTransformerDoFn)
.withSideInputs(ddlView)
.withOutputTags(
DatastreamToSpannerConstants.TRANSFORMED_EVENT_TAG,
TupleTagList.of(
Arrays.asList(
DatastreamToSpannerConstants.FILTERED_EVENT_TAG,
DatastreamToSpannerConstants.PERMANENT_ERROR_TAG))));
/*
* Stage 3: Write filtered records to GCS
*/
String tempLocation =
options.as(DataflowPipelineOptions.class).getTempLocation().endsWith("/")
? options.as(DataflowPipelineOptions.class).getTempLocation()
: options.as(DataflowPipelineOptions.class).getTempLocation() + "/";
String filterEventsDirectory =
options.getFilteredEventsDirectory().isEmpty()
? tempLocation + "filteredEvents/"
: options.getFilteredEventsDirectory();
LOG.info("Filtered events directory: {}", filterEventsDirectory);
transformedRecords
.get(DatastreamToSpannerConstants.FILTERED_EVENT_TAG)
.apply(Window.into(FixedWindows.of(Duration.standardMinutes(1))))
.apply(
"Write Filtered Events To GCS",
TextIO.write().to(filterEventsDirectory).withSuffix(".json").withWindowedWrites());
spannerConfig =
SpannerServiceFactoryImpl.createSpannerService(
spannerConfig, options.getFailureInjectionParameter());
shadowTableSpannerConfig =
SpannerServiceFactoryImpl.createSpannerService(
shadowTableSpannerConfig, options.getFailureInjectionParameter());
/*
* Stage 4: Write transformed records to Cloud Spanner
*/
SpannerTransactionWriter.Result spannerWriteResults =
transformedRecords
.get(DatastreamToSpannerConstants.TRANSFORMED_EVENT_TAG)
.apply(
"Write events to Cloud Spanner",
new SpannerTransactionWriter(
spannerConfig,
shadowTableSpannerConfig,
ddlView,
shadowTableDdlView,
options.getShadowTablePrefix(),
options.getDatastreamSourceType(),
isRegularMode));
/*
* Stage 5: Write failures to GCS Dead Letter Queue
* a) Retryable errors are written to retry GCS Dead letter queue
* b) Severe errors are written to severe GCS Dead letter queue
*/
// We will write only the original payload from the failsafe event to the DLQ. We are doing
// that in
// StringDeadLetterQueueSanitizer.
spannerWriteResults
.retryableErrors()
.apply(
"DLQ: Write retryable Failures to GCS",
MapElements.via(new StringDeadLetterQueueSanitizer()))
.setCoder(StringUtf8Coder.of())
.apply(
"Write To DLQ",
DLQWriteTransform.WriteDLQ.newBuilder()
.withDlqDirectory(dlqManager.getRetryDlqDirectoryWithDateTime())
.withTmpDirectory(options.getDeadLetterQueueDirectory() + "/tmp_retry/")
.setIncludePaneInfo(true)
.build());
PCollection<FailsafeElement<String, String>> dlqErrorRecords =
reconsumedElements
.get(DeadLetterQueueManager.PERMANENT_ERRORS)
.setCoder(FailsafeElementCoder.of(StringUtf8Coder.of(), StringUtf8Coder.of()));
// TODO: Write errors from transformer and spanner writer into separate folders
PCollection<FailsafeElement<String, String>> permanentErrors =
PCollectionList.of(dlqErrorRecords)
.and(spannerWriteResults.permanentErrors())
.and(transformedRecords.get(DatastreamToSpannerConstants.PERMANENT_ERROR_TAG))
.apply(Flatten.pCollections());
// increment the metrics
permanentErrors
.apply("Update metrics", ParDo.of(new MetricUpdaterDoFn(isRegularMode)))
.apply(
"DLQ: Write Severe errors to GCS",
MapElements.via(new StringDeadLetterQueueSanitizer()))
.setCoder(StringUtf8Coder.of())
.apply(
"Write To DLQ",
DLQWriteTransform.WriteDLQ.newBuilder()
.withDlqDirectory(dlqManager.getSevereDlqDirectoryWithDateTime())
.withTmpDirectory((options).getDeadLetterQueueDirectory() + "/tmp_severe/")
.setIncludePaneInfo(true)
.build());
// Execute the pipeline and return the result.
return pipeline.run();
}
static SpannerConfig getShadowTableSpannerConfig(Options options) {
// Validate shadow table Spanner config - both instance and database must be specified together
String shadowTableSpannerInstanceId = options.getShadowTableSpannerInstanceId();
String shadowTableSpannerDatabaseId = options.getShadowTableSpannerDatabaseId();
LOG.info(
"Input Shadow table db - instance {} and database {}",
shadowTableSpannerInstanceId,
shadowTableSpannerDatabaseId);
if ((Strings.isNullOrEmpty(shadowTableSpannerInstanceId)
&& !Strings.isNullOrEmpty(shadowTableSpannerDatabaseId))
|| (!Strings.isNullOrEmpty(shadowTableSpannerInstanceId)
&& Strings.isNullOrEmpty(shadowTableSpannerDatabaseId))) {
throw new IllegalArgumentException(
"Both shadowTableSpannerInstanceId and shadowTableSpannerDatabaseId must be specified together");
}
// If not specified, use main instance and main database values. The shadow table database
// stores the shadow tables and by default, is the same as the main database for backward
// compatibility.
if (Strings.isNullOrEmpty(shadowTableSpannerInstanceId)
&& Strings.isNullOrEmpty(shadowTableSpannerDatabaseId)) {
shadowTableSpannerInstanceId = options.getInstanceId();
shadowTableSpannerDatabaseId = options.getDatabaseId();
LOG.info(
"Overwrote shadow table instance - {} and db- {}",
shadowTableSpannerInstanceId,
shadowTableSpannerDatabaseId);
}
return SpannerConfig.create()
.withProjectId(ValueProvider.StaticValueProvider.of(options.getProjectId()))
.withHost(ValueProvider.StaticValueProvider.of(options.getSpannerHost()))
.withInstanceId(ValueProvider.StaticValueProvider.of(shadowTableSpannerInstanceId))
.withDatabaseId(ValueProvider.StaticValueProvider.of(shadowTableSpannerDatabaseId))
.withRpcPriority(ValueProvider.StaticValueProvider.of(options.getSpannerPriority()))
.withCommitRetrySettings(
RetrySettings.newBuilder()
.setTotalTimeout(org.threeten.bp.Duration.ofMinutes(4))
.setInitialRetryDelay(org.threeten.bp.Duration.ofMinutes(0))
.setRetryDelayMultiplier(1)
.setMaxRetryDelay(org.threeten.bp.Duration.ofMinutes(0))
.setInitialRpcTimeout(org.threeten.bp.Duration.ofMinutes(4))
.setRpcTimeoutMultiplier(1)
.setMaxRpcTimeout(org.threeten.bp.Duration.ofMinutes(4))
.setMaxAttempts(1)
.build());
}
private static DeadLetterQueueManager buildDlqManager(Options options) {
String tempLocation =
options.as(DataflowPipelineOptions.class).getTempLocation().endsWith("/")
? options.as(DataflowPipelineOptions.class).getTempLocation()
: options.as(DataflowPipelineOptions.class).getTempLocation() + "/";
String dlqDirectory =
options.getDeadLetterQueueDirectory().isEmpty()
? tempLocation + "dlq/"
: options.getDeadLetterQueueDirectory();
LOG.info("Dead-letter queue directory: {}", dlqDirectory);
options.setDeadLetterQueueDirectory(dlqDirectory);
return DeadLetterQueueManager.create(dlqDirectory, options.getDlqMaxRetryCount(), true);
}
static ISchemaOverridesParser configureSchemaOverrides(Options options) {
// incorrect configuration
if (!options.getSchemaOverridesFilePath().isEmpty()
&& (!options.getTableOverrides().isEmpty() || !options.getColumnOverrides().isEmpty())) {
throw new IllegalArgumentException(
"Only one of file based or string based overrides must be configured! Please correct the configuration and re-run the job");
}
// string based overrides
if (!options.getTableOverrides().isEmpty() || !options.getColumnOverrides().isEmpty()) {
Map<String, String> userOptionsOverrides = new HashMap<>();
if (!options.getTableOverrides().isEmpty()) {
userOptionsOverrides.put("tableOverrides", options.getTableOverrides());
}
if (!options.getColumnOverrides().isEmpty()) {
userOptionsOverrides.put("columnOverrides", options.getColumnOverrides());
}
return new SchemaStringOverridesParser(userOptionsOverrides);
}
// file based overrides
if (!options.getSchemaOverridesFilePath().isEmpty()) {
return new SchemaFileOverridesParser(options.getSchemaOverridesFilePath());
}
// no overrides
return new NoopSchemaOverridesParser();
}
}
