Trasferire flussi di dati utilizzando l'API Storage Write

Questo documento descrive come utilizzare l' API BigQuery Storage Write per inserire flussi di dati in BigQuery.

Negli scenari di streaming, i dati arrivano continuamente e devono essere disponibili per le letture con una latenza minima. Quando utilizzi l'API BigQuery Storage Write per i carichi di lavoro di streaming, considera le garanzie di cui hai bisogno:

• Se la tua applicazione ha bisogno solo della semantica "almeno una volta", utilizza il flusso predefinito.
• Se hai bisogno della semantica "esattamente una volta", crea uno o più flussi di tipo committed e utilizza gli offset del flusso per garantire le scritture "esattamente una volta".

Nel tipo committed, i dati scritti nel flusso sono disponibili per le query non appena il server riconosce la richiesta di scrittura. Il flusso predefinito utilizza anche il tipo committed, ma non fornisce garanzie "esattamente una volta".

Utilizzare il flusso predefinito per la semantica "almeno una volta"

Se la tua applicazione può accettare la possibilità che nella tabella di destinazione vengano visualizzati record duplicati, ti consigliamo di utilizzare il flusso predefinito per gli scenari di streaming.

Il seguente codice mostra come scrivere i dati nel flusso predefinito:

Java

Per scoprire come installare e utilizzare la libreria client per BigQuery, consulta Librerie client di BigQuery. Per saperne di più, consulta la documentazione di riferimento dell'API Java BigQuery.

Per eseguire l'autenticazione in BigQuery, configura le Credenziali predefinite dell'applicazione. Per saperne di più, vedi Configura l'autenticazione per le librerie client.

import com.google.api.core.ApiFuture;
import com.google.api.core.ApiFutureCallback;
import com.google.api.core.ApiFutures;
import com.google.api.gax.batching.FlowControlSettings;
import com.google.api.gax.core.FixedExecutorProvider;
import com.google.api.gax.retrying.RetrySettings;
import com.google.cloud.bigquery.BigQuery;
import com.google.cloud.bigquery.BigQueryOptions;
import com.google.cloud.bigquery.QueryJobConfiguration;
import com.google.cloud.bigquery.TableResult;
import com.google.cloud.bigquery.storage.v1.AppendRowsRequest;
import com.google.cloud.bigquery.storage.v1.AppendRowsResponse;
import com.google.cloud.bigquery.storage.v1.BigQueryWriteClient;
import com.google.cloud.bigquery.storage.v1.BigQueryWriteSettings;
import com.google.cloud.bigquery.storage.v1.Exceptions;
import com.google.cloud.bigquery.storage.v1.Exceptions.AppendSerializationError;
import com.google.cloud.bigquery.storage.v1.Exceptions.MaximumRequestCallbackWaitTimeExceededException;
import com.google.cloud.bigquery.storage.v1.Exceptions.StorageException;
import com.google.cloud.bigquery.storage.v1.Exceptions.StreamWriterClosedException;
import com.google.cloud.bigquery.storage.v1.JsonStreamWriter;
import com.google.cloud.bigquery.storage.v1.TableName;
import com.google.common.util.concurrent.MoreExecutors;
import com.google.protobuf.ByteString;
import com.google.protobuf.Descriptors.DescriptorValidationException;
import java.io.IOException;
import java.util.Map;
import java.util.concurrent.Executors;
import java.util.concurrent.Phaser;
import java.util.concurrent.atomic.AtomicInteger;
import javax.annotation.concurrent.GuardedBy;
import org.json.JSONArray;
import org.json.JSONObject;
import org.threeten.bp.Duration;

public class WriteToDefaultStream {

  public static void runWriteToDefaultStream()
      throws DescriptorValidationException, InterruptedException, IOException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "MY_PROJECT_ID";
    String datasetName = "MY_DATASET_NAME";
    String tableName = "MY_TABLE_NAME";
    writeToDefaultStream(projectId, datasetName, tableName);
  }

  private static ByteString buildByteString() {
    byte[] bytes = new byte[] {1, 2, 3, 4, 5};
    return ByteString.copyFrom(bytes);
  }

  // Create a JSON object that is compatible with the table schema.
  private static JSONObject buildRecord(int i, int j) {
    JSONObject record = new JSONObject();
    StringBuilder sbSuffix = new StringBuilder();
    for (int k = 0; k < j; k++) {
      sbSuffix.append(k);
    }
    record.put("test_string", String.format("record %03d-%03d %s", i, j, sbSuffix.toString()));
    ByteString byteString = buildByteString();
    record.put("test_bytes", byteString);
    record.put(
        "test_geo",
        "POLYGON((-124.49 47.35,-124.49 40.73,-116.49 40.73,-116.49 47.35,-124.49 47.35))");
    return record;
  }

  public static void writeToDefaultStream(String projectId, String datasetName, String tableName)
      throws DescriptorValidationException, InterruptedException, IOException {
    TableName parentTable = TableName.of(projectId, datasetName, tableName);

    DataWriter writer = new DataWriter();
    // One time initialization for the worker.
    writer.initialize(parentTable);

    // Write two batches of fake data to the stream, each with 10 JSON records.  Data may be
    // batched up to the maximum request size:
    // https://cloud.google.com/bigquery/quotas#write-api-limits
    for (int i = 0; i < 2; i++) {
      JSONArray jsonArr = new JSONArray();
      for (int j = 0; j < 10; j++) {
        JSONObject record = buildRecord(i, j);
        jsonArr.put(record);
      }

      writer.append(new AppendContext(jsonArr));
    }

    // Final cleanup for the stream during worker teardown.
    writer.cleanup();
    verifyExpectedRowCount(parentTable, 12L);
    System.out.println("Appended records successfully.");
  }

  private static void verifyExpectedRowCount(TableName parentTable, long expectedRowCount)
      throws InterruptedException {
    String queryRowCount =
        "SELECT COUNT(*) FROM `"
            + parentTable.getProject()
            + "."
            + parentTable.getDataset()
            + "."
            + parentTable.getTable()
            + "`";
    QueryJobConfiguration queryConfig = QueryJobConfiguration.newBuilder(queryRowCount).build();
    BigQuery bigquery = BigQueryOptions.getDefaultInstance().getService();
    TableResult results = bigquery.query(queryConfig);
    long countRowsActual =
        Long.parseLong(results.getValues().iterator().next().get("f0_").getStringValue());
    if (countRowsActual != expectedRowCount) {
      throw new RuntimeException(
          "Unexpected row count. Expected: " + expectedRowCount + ". Actual: " + countRowsActual);
    }
  }

  private static class AppendContext {

    JSONArray data;

    AppendContext(JSONArray data) {
      this.data = data;
    }
  }

  private static class DataWriter {

    private static final int MAX_RECREATE_COUNT = 3;

    private BigQueryWriteClient client;

    // Track the number of in-flight requests to wait for all responses before shutting down.
    private final Phaser inflightRequestCount = new Phaser(1);
    private final Object lock = new Object();
    private JsonStreamWriter streamWriter;

    @GuardedBy("lock")
    private RuntimeException error = null;

    private AtomicInteger recreateCount = new AtomicInteger(0);

    private JsonStreamWriter createStreamWriter(String tableName)
        throws DescriptorValidationException, IOException, InterruptedException {
      // Configure in-stream automatic retry settings.
      // Error codes that are immediately retried:
      // * ABORTED, UNAVAILABLE, CANCELLED, INTERNAL, DEADLINE_EXCEEDED
      // Error codes that are retried with exponential backoff:
      // * RESOURCE_EXHAUSTED
      RetrySettings retrySettings =
          RetrySettings.newBuilder()
              .setInitialRetryDelay(Duration.ofMillis(500))
              .setRetryDelayMultiplier(1.1)
              .setMaxAttempts(5)
              .setMaxRetryDelay(Duration.ofMinutes(1))
              .build();

      // Use the JSON stream writer to send records in JSON format. Specify the table name to write
      // to the default stream.
      // For more information about JsonStreamWriter, see:
      // https://googleapis.dev/java/google-cloud-bigquerystorage/latest/com/google/cloud/bigquery/storage/v1/JsonStreamWriter.html
      return JsonStreamWriter.newBuilder(tableName, client)
          .setExecutorProvider(FixedExecutorProvider.create(Executors.newScheduledThreadPool(10)))
          .setChannelProvider(
              BigQueryWriteSettings.defaultGrpcTransportProviderBuilder()
                  .setKeepAliveTime(org.threeten.bp.Duration.ofMinutes(1))
                  .setKeepAliveTimeout(org.threeten.bp.Duration.ofMinutes(1))
                  .setKeepAliveWithoutCalls(true)
                  .setChannelsPerCpu(2)
                  .build())
          .setEnableConnectionPool(true)
          // This will allow connection pool to scale up better.
          .setFlowControlSettings(
              FlowControlSettings.newBuilder().setMaxOutstandingElementCount(100L).build())
          // If value is missing in json and there is a default value configured on bigquery
          // column, apply the default value to the missing value field.
          .setDefaultMissingValueInterpretation(
              AppendRowsRequest.MissingValueInterpretation.DEFAULT_VALUE)
          .setRetrySettings(retrySettings)
          .build();
    }

    public void initialize(TableName parentTable)
        throws DescriptorValidationException, IOException, InterruptedException {
      // Initialize client without settings, internally within stream writer a new client will be
      // created with full settings.
      client = BigQueryWriteClient.create();

      streamWriter = createStreamWriter(parentTable.toString());
    }

    public void append(AppendContext appendContext)
        throws DescriptorValidationException, IOException, InterruptedException {
      synchronized (this.lock) {
        if (!streamWriter.isUserClosed()
            && streamWriter.isClosed()
            && recreateCount.getAndIncrement() < MAX_RECREATE_COUNT) {
          streamWriter = createStreamWriter(streamWriter.getStreamName());
          this.error = null;
        }
        // If earlier appends have failed, we need to reset before continuing.
        if (this.error != null) {
          throw this.error;
        }
      }
      // Append asynchronously for increased throughput.
      ApiFuture<AppendRowsResponse> future = streamWriter.append(appendContext.data);
      ApiFutures.addCallback(
          future, new AppendCompleteCallback(this, appendContext), MoreExecutors.directExecutor());

      // Increase the count of in-flight requests.
      inflightRequestCount.register();
    }

    public void cleanup() {
      // Wait for all in-flight requests to complete.
      inflightRequestCount.arriveAndAwaitAdvance();

      client.close();
      // Close the connection to the server.
      streamWriter.close();

      // Verify that no error occurred in the stream.
      synchronized (this.lock) {
        if (this.error != null) {
          throw this.error;
        }
      }
    }

    static class AppendCompleteCallback implements ApiFutureCallback<AppendRowsResponse> {

      private final DataWriter parent;
      private final AppendContext appendContext;

      public AppendCompleteCallback(DataWriter parent, AppendContext appendContext) {
        this.parent = parent;
        this.appendContext = appendContext;
      }

      public void onSuccess(AppendRowsResponse response) {
        System.out.format("Append success\n");
        this.parent.recreateCount.set(0);
        done();
      }

      public void onFailure(Throwable throwable) {
        if (throwable instanceof AppendSerializationError) {
          AppendSerializationError ase = (AppendSerializationError) throwable;
          Map<Integer, String> rowIndexToErrorMessage = ase.getRowIndexToErrorMessage();
          if (rowIndexToErrorMessage.size() > 0) {
            // Omit the faulty rows
            JSONArray dataNew = new JSONArray();
            for (int i = 0; i < appendContext.data.length(); i++) {
              if (!rowIndexToErrorMessage.containsKey(i)) {
                dataNew.put(appendContext.data.get(i));
              } else {
                // process faulty rows by placing them on a dead-letter-queue, for instance
              }
            }

            // Retry the remaining valid rows, but using a separate thread to
            // avoid potentially blocking while we are in a callback.
            if (dataNew.length() > 0) {
              try {
                this.parent.append(new AppendContext(dataNew));
              } catch (DescriptorValidationException e) {
                throw new RuntimeException(e);
              } catch (IOException e) {
                throw new RuntimeException(e);
              } catch (InterruptedException e) {
                throw new RuntimeException(e);
              }
            }
            // Mark the existing attempt as done since we got a response for it
            done();
            return;
          }
        }

        boolean resendRequest = false;
        if (throwable instanceof MaximumRequestCallbackWaitTimeExceededException) {
          resendRequest = true;
        } else if (throwable instanceof StreamWriterClosedException) {
          if (!parent.streamWriter.isUserClosed()) {
            resendRequest = true;
          }
        }
        if (resendRequest) {
          // Retry this request.
          try {
            this.parent.append(new AppendContext(appendContext.data));
          } catch (DescriptorValidationException e) {
            throw new RuntimeException(e);
          } catch (IOException e) {
            throw new RuntimeException(e);
          } catch (InterruptedException e) {
            throw new RuntimeException(e);
          }
          // Mark the existing attempt as done since we got a response for it
          done();
          return;
        }

        synchronized (this.parent.lock) {
          if (this.parent.error == null) {
            StorageException storageException = Exceptions.toStorageException(throwable);
            this.parent.error =
                (storageException != null) ? storageException : new RuntimeException(throwable);
          }
        }
        done();
      }

      private void done() {
        // Reduce the count of in-flight requests.
        this.parent.inflightRequestCount.arriveAndDeregister();
      }
    }
  }
}

Node.js

Per scoprire come installare e utilizzare la libreria client per BigQuery, consulta Librerie client di BigQuery.

Per eseguire l'autenticazione in BigQuery, configura le Credenziali predefinite dell'applicazione. Per saperne di più, vedi Configura l'autenticazione per le librerie client.

const {adapt, managedwriter} = require('@google-cloud/bigquery-storage');
const {WriterClient, JSONWriter} = managedwriter;

async function appendJSONRowsDefaultStream() {
  /**
   * TODO(developer): Uncomment the following lines before running the sample.
   */
  // projectId = 'my_project';
  // datasetId = 'my_dataset';
  // tableId = 'my_table';

  const destinationTable = `projects/${projectId}/datasets/${datasetId}/tables/${tableId}`;
  const writeClient = new WriterClient({projectId});

  try {
    const writeStream = await writeClient.getWriteStream({
      streamId: `${destinationTable}/streams/_default`,
      view: 'FULL',
    });
    const protoDescriptor = adapt.convertStorageSchemaToProto2Descriptor(
      writeStream.tableSchema,
      'root',
    );

    const connection = await writeClient.createStreamConnection({
      streamId: managedwriter.DefaultStream,
      destinationTable,
    });
    const streamId = connection.getStreamId();

    const writer = new JSONWriter({
      streamId,
      connection,
      protoDescriptor,
    });

    let rows = [];
    const pendingWrites = [];

    // Row 1
    let row = {
      row_num: 1,
      customer_name: 'Octavia',
    };
    rows.push(row);

    // Row 2
    row = {
      row_num: 2,
      customer_name: 'Turing',
    };
    rows.push(row);

    // Send batch.
    let pw = writer.appendRows(rows);
    pendingWrites.push(pw);

    rows = [];

    // Row 3
    row = {
      row_num: 3,
      customer_name: 'Bell',
    };
    rows.push(row);

    // Send batch.
    pw = writer.appendRows(rows);
    pendingWrites.push(pw);

    const results = await Promise.all(
      pendingWrites.map(pw => pw.getResult()),
    );
    console.log('Write results:', results);
  } catch (err) {
    console.log(err);
  } finally {
    writeClient.close();
  }
}

Python

Questo esempio mostra come inserire un record con due campi utilizzando il flusso predefinito:

from google.cloud import bigquery_storage_v1
from google.cloud.bigquery_storage_v1 import types
from google.cloud.bigquery_storage_v1 import writer
from google.protobuf import descriptor_pb2
import logging
import json

import sample_data_pb2

# The list of columns from the table's schema to search in the given data to write to BigQuery.
TABLE_COLUMNS_TO_CHECK = [
    "name",
    "age"
    ]

# Function to create a batch of row data to be serialized.
def create_row_data(data):
    row = sample_data_pb2.SampleData()
    for field in TABLE_COLUMNS_TO_CHECK:
      # Optional fields will be passed as null if not provided
      if field in data:
        setattr(row, field, data[field])
    return row.SerializeToString()

class BigQueryStorageWriteAppend(object):

    # The stream name is: projects/{project}/datasets/{dataset}/tables/{table}/_default
    def append_rows_proto2(
        project_id: str, dataset_id: str, table_id: str, data: dict
    ):

        write_client = bigquery_storage_v1.BigQueryWriteClient()
        parent = write_client.table_path(project_id, dataset_id, table_id)
        stream_name = f'{parent}/_default'
        write_stream = types.WriteStream()

        # Create a template with fields needed for the first request.
        request_template = types.AppendRowsRequest()

        # The request must contain the stream name.
        request_template.write_stream = stream_name

        # Generating the protocol buffer representation of the message descriptor.
        proto_schema = types.ProtoSchema()
        proto_descriptor = descriptor_pb2.DescriptorProto()
        sample_data_pb2.SampleData.DESCRIPTOR.CopyToProto(proto_descriptor)
        proto_schema.proto_descriptor = proto_descriptor
        proto_data = types.AppendRowsRequest.ProtoData()
        proto_data.writer_schema = proto_schema
        request_template.proto_rows = proto_data

        # Construct an AppendRowsStream to send an arbitrary number of requests to a stream.
        append_rows_stream = writer.AppendRowsStream(write_client, request_template)

        # Append proto2 serialized bytes to the serialized_rows repeated field using create_row_data.
        proto_rows = types.ProtoRows()
        for row in data:
            proto_rows.serialized_rows.append(create_row_data(row))

        # Appends data to the given stream.
        request = types.AppendRowsRequest()
        proto_data = types.AppendRowsRequest.ProtoData()
        proto_data.rows = proto_rows
        request.proto_rows = proto_data

        append_rows_stream.send(request)

        print(f"Rows to table: '{parent}' have been written.")

if __name__ == "__main__":

    ###### Uncomment the below block to provide additional logging capabilities ######
    #logging.basicConfig(
    #    level=logging.DEBUG,
    #    format="%(asctime)s [%(levelname)s] %(message)s",
    #    handlers=[
    #        logging.StreamHandler()
    #    ]
    #)
    ###### Uncomment the above block to provide additional logging capabilities ######

    with open('entries.json', 'r') as json_file:
        data = json.load(json_file)
    # Change this to your specific BigQuery project, dataset, table details
    BigQueryStorageWriteAppend.append_rows_proto2("PROJECT_ID","DATASET_ID", "TABLE_ID ",data=data)

Questo esempio di codice dipende dal modulo del protocollo compilato sample_data_pb2.py. Per creare il modulo compilato, esegui il protoc --python_out=. sample_data.proto comando, dove protoc è il compilatore del buffer di protocollo. Il file sample_data.proto definisce il formato dei messaggi utilizzati nell'esempio Python. Per installare il compilatore protoc, segui le istruzioni riportate in Protocol Buffers - Google's data interchange format.

Ecco i contenuti del file sample_data.proto:

message SampleData {
  required string name = 1;
  required int64 age = 2;
}

Questo script utilizza il file entries.json, che contiene dati di riga di esempio da inserire nella tabella BigQuery:

{"name": "Jim", "age": 35}
{"name": "Jane", "age": 27}

Utilizzare il multiplexing

Puoi attivare il multiplexing solo a livello di writer di flusso per il flusso predefinito. Per attivare il multiplexing in Java, chiama il setEnableConnectionPool metodo quando crei un StreamWriter o JsonStreamWriter oggetto.

Dopo aver attivato il pool di connessioni, la libreria client Java gestisce le connessioni in background, aumentando il numero di connessioni se quelle esistenti sono considerate troppo occupate. Per la scalabilità automatica, ti consigliamo di ridurre il limite maxInflightRequests.

// One possible way for constructing StreamWriter
StreamWriter.newBuilder(streamName)
              .setWriterSchema(protoSchema)
              .setEnableConnectionPool(true)
              .setMaxInflightRequests(100)
              .build();
// One possible way for constructing JsonStreamWriter
JsonStreamWriter.newBuilder(tableName, bigqueryClient)
              .setEnableConnectionPool(true)
              .setMaxInflightRequests(100)
              .build();

Per attivare il multiplexing in Go, consulta Condivisione delle connessioni (multiplexing).

Utilizzare il tipo committed per la semantica "esattamente una volta"

Se hai bisogno della semantica di scrittura "esattamente una volta", crea un flusso di scrittura di tipo committed. Nel tipo committed, i record sono disponibili per le query non appena il client riceve la conferma dal backend.

Il tipo committed fornisce la consegna "esattamente una volta" all'interno di un flusso tramite l'utilizzo degli offset dei record. Utilizzando gli offset dei record, l'applicazione specifica l'offset di accodamento successivo in ogni chiamata a AppendRows. L'operazione di scrittura viene eseguita solo se il valore dell'offset corrisponde all'offset di accodamento successivo. Per saperne di più, consulta Gestire gli offset dei flussi per ottenere la semantica "esattamente una volta".

Se non fornisci un offset, i record vengono aggiunti alla fine corrente del flusso. In questo caso, se una richiesta di accodamento restituisce un errore, il nuovo tentativo potrebbe comportare la visualizzazione del record più di una volta nel flusso.

Per utilizzare il tipo committed, segui questi passaggi:

Java

1. Chiama CreateWriteStream per creare uno o più flussi di tipo committed.
2. Per ogni flusso, chiama AppendRows in un loop per scrivere batch di record.
3. Chiama FinalizeWriteStream per ogni flusso per rilasciarlo. Dopo aver chiamato questo metodo, non puoi scrivere altre righe nel flusso. Questo passaggio è facoltativo nel tipo committed, ma aiuta a evitare di superare il limite dei flussi attivi. Per saperne di più, consulta Limitare la frequenza di creazione dei flussi.

Node.js

1. Chiama createWriteStreamFullResponse per creare uno o più flussi di tipo committed.
2. Per ogni flusso, chiama appendRows in un loop per scrivere batch di record.
3. Chiama finalize per ogni flusso per rilasciarlo. Dopo aver chiamato questo metodo, non puoi scrivere altre righe nel flusso. Questo passaggio è facoltativo nel tipo committed, ma aiuta a evitare di superare il limite dei flussi attivi. Per saperne di più, consulta Limitare la frequenza di creazione dei flussi.

Non puoi eliminare un flusso in modo esplicito. I flussi seguono la durata (TTL) definita dal sistema:

• Un flusso committed ha una TTL di tre giorni se non è presente traffico sul flusso.
• Per impostazione predefinita, un flusso con buffer ha una TTL di sette giorni se non è presente traffico sul flusso.

Il seguente codice mostra come utilizzare il tipo committed:

Java

Per scoprire come installare e utilizzare la libreria client per BigQuery, consulta Librerie client di BigQuery. Per saperne di più, consulta la documentazione di riferimento dell'API Java BigQuery.

Per eseguire l'autenticazione in BigQuery, configura le Credenziali predefinite dell'applicazione. Per saperne di più, vedi Configura l'autenticazione per le librerie client.

import com.google.api.core.ApiFuture;
import com.google.api.core.ApiFutureCallback;
import com.google.api.core.ApiFutures;
import com.google.api.gax.retrying.RetrySettings;
import com.google.cloud.bigquery.storage.v1.AppendRowsResponse;
import com.google.cloud.bigquery.storage.v1.BigQueryWriteClient;
import com.google.cloud.bigquery.storage.v1.CreateWriteStreamRequest;
import com.google.cloud.bigquery.storage.v1.Exceptions;
import com.google.cloud.bigquery.storage.v1.Exceptions.StorageException;
import com.google.cloud.bigquery.storage.v1.FinalizeWriteStreamResponse;
import com.google.cloud.bigquery.storage.v1.JsonStreamWriter;
import com.google.cloud.bigquery.storage.v1.TableName;
import com.google.cloud.bigquery.storage.v1.WriteStream;
import com.google.common.util.concurrent.MoreExecutors;
import com.google.protobuf.Descriptors.DescriptorValidationException;
import java.io.IOException;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.Phaser;
import javax.annotation.concurrent.GuardedBy;
import org.json.JSONArray;
import org.json.JSONObject;
import org.threeten.bp.Duration;

public class WriteCommittedStream {

  public static void runWriteCommittedStream()
      throws DescriptorValidationException, InterruptedException, IOException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "MY_PROJECT_ID";
    String datasetName = "MY_DATASET_NAME";
    String tableName = "MY_TABLE_NAME";

    writeCommittedStream(projectId, datasetName, tableName);
  }

  public static void writeCommittedStream(String projectId, String datasetName, String tableName)
      throws DescriptorValidationException, InterruptedException, IOException {
    BigQueryWriteClient client = BigQueryWriteClient.create();
    TableName parentTable = TableName.of(projectId, datasetName, tableName);

    DataWriter writer = new DataWriter();
    // One time initialization.
    writer.initialize(parentTable, client);

    try {
      // Write two batches of fake data to the stream, each with 10 JSON records.  Data may be
      // batched up to the maximum request size:
      // https://cloud.google.com/bigquery/quotas#write-api-limits
      long offset = 0;
      for (int i = 0; i < 2; i++) {
        // Create a JSON object that is compatible with the table schema.
        JSONArray jsonArr = new JSONArray();
        for (int j = 0; j < 10; j++) {
          JSONObject record = new JSONObject();
          record.put("col1", String.format("batch-record %03d-%03d", i, j));
          jsonArr.put(record);
        }
        writer.append(jsonArr, offset);
        offset += jsonArr.length();
      }
    } catch (ExecutionException e) {
      // If the wrapped exception is a StatusRuntimeException, check the state of the operation.
      // If the state is INTERNAL, CANCELLED, or ABORTED, you can retry. For more information, see:
      // https://grpc.github.io/grpc-java/javadoc/io/grpc/StatusRuntimeException.html
      System.out.println("Failed to append records. \n" + e);
    }

    // Final cleanup for the stream.
    writer.cleanup(client);
    System.out.println("Appended records successfully.");
  }

  // A simple wrapper object showing how the stateful stream writer should be used.
  private static class DataWriter {

    private JsonStreamWriter streamWriter;
    // Track the number of in-flight requests to wait for all responses before shutting down.
    private final Phaser inflightRequestCount = new Phaser(1);

    private final Object lock = new Object();

    @GuardedBy("lock")
    private RuntimeException error = null;

    void initialize(TableName parentTable, BigQueryWriteClient client)
        throws IOException, DescriptorValidationException, InterruptedException {
      // Initialize a write stream for the specified table.
      // For more information on WriteStream.Type, see:
      // https://googleapis.dev/java/google-cloud-bigquerystorage/latest/com/google/cloud/bigquery/storage/v1/WriteStream.Type.html
      WriteStream stream = WriteStream.newBuilder().setType(WriteStream.Type.COMMITTED).build();

      CreateWriteStreamRequest createWriteStreamRequest =
          CreateWriteStreamRequest.newBuilder()
              .setParent(parentTable.toString())
              .setWriteStream(stream)
              .build();
      WriteStream writeStream = client.createWriteStream(createWriteStreamRequest);

      // Configure in-stream automatic retry settings.
      // Error codes that are immediately retried:
      // * ABORTED, UNAVAILABLE, CANCELLED, INTERNAL, DEADLINE_EXCEEDED
      // Error codes that are retried with exponential backoff:
      // * RESOURCE_EXHAUSTED
      RetrySettings retrySettings =
          RetrySettings.newBuilder()
              .setInitialRetryDelay(Duration.ofMillis(500))
              .setRetryDelayMultiplier(1.1)
              .setMaxAttempts(5)
              .setMaxRetryDelay(Duration.ofMinutes(1))
              .build();

      // Use the JSON stream writer to send records in JSON format.
      // For more information about JsonStreamWriter, see:
      // https://googleapis.dev/java/google-cloud-bigquerystorage/latest/com/google/cloud/bigquery/storage/v1/JsonStreamWriter.html
      streamWriter =
          JsonStreamWriter.newBuilder(writeStream.getName(), writeStream.getTableSchema(), client)
              .setRetrySettings(retrySettings)
              .build();
    }

    public void append(JSONArray data, long offset)
        throws DescriptorValidationException, IOException, ExecutionException {
      synchronized (this.lock) {
        // If earlier appends have failed, we need to reset before continuing.
        if (this.error != null) {
          throw this.error;
        }
      }
      // Append asynchronously for increased throughput.
      ApiFuture<AppendRowsResponse> future = streamWriter.append(data, offset);
      ApiFutures.addCallback(
          future, new DataWriter.AppendCompleteCallback(this), MoreExecutors.directExecutor());
      // Increase the count of in-flight requests.
      inflightRequestCount.register();
    }

    public void cleanup(BigQueryWriteClient client) {
      // Wait for all in-flight requests to complete.
      inflightRequestCount.arriveAndAwaitAdvance();

      // Close the connection to the server.
      streamWriter.close();

      // Verify that no error occurred in the stream.
      synchronized (this.lock) {
        if (this.error != null) {
          throw this.error;
        }
      }

      // Finalize the stream.
      FinalizeWriteStreamResponse finalizeResponse =
          client.finalizeWriteStream(streamWriter.getStreamName());
      System.out.println("Rows written: " + finalizeResponse.getRowCount());
    }

    public String getStreamName() {
      return streamWriter.getStreamName();
    }

    static class AppendCompleteCallback implements ApiFutureCallback<AppendRowsResponse> {

      private final DataWriter parent;

      public AppendCompleteCallback(DataWriter parent) {
        this.parent = parent;
      }

      public void onSuccess(AppendRowsResponse response) {
        System.out.format("Append %d success\n", response.getAppendResult().getOffset().getValue());
        done();
      }

      public void onFailure(Throwable throwable) {
        synchronized (this.parent.lock) {
          if (this.parent.error == null) {
            StorageException storageException = Exceptions.toStorageException(throwable);
            this.parent.error =
                (storageException != null) ? storageException : new RuntimeException(throwable);
          }
        }
        System.out.format("Error: %s\n", throwable.toString());
        done();
      }

      private void done() {
        // Reduce the count of in-flight requests.
        this.parent.inflightRequestCount.arriveAndDeregister();
      }
    }
  }
}

Node.js

Per scoprire come installare e utilizzare la libreria client per BigQuery, consulta Librerie client di BigQuery.

Per eseguire l'autenticazione in BigQuery, configura le Credenziali predefinite dell'applicazione. Per saperne di più, vedi Configura l'autenticazione per le librerie client.

const {adapt, managedwriter} = require('@google-cloud/bigquery-storage');
const {WriterClient, JSONWriter} = managedwriter;

async function appendJSONRowsCommittedStream() {
  /**
   * TODO(developer): Uncomment the following lines before running the sample.
   */
  // projectId = 'my_project';
  // datasetId = 'my_dataset';
  // tableId = 'my_table';

  const destinationTable = `projects/${projectId}/datasets/${datasetId}/tables/${tableId}`;
  const streamType = managedwriter.CommittedStream;
  const writeClient = new WriterClient({projectId});

  try {
    const writeStream = await writeClient.createWriteStreamFullResponse({
      streamType,
      destinationTable,
    });
    const streamId = writeStream.name;
    console.log(`Stream created: ${streamId}`);

    const protoDescriptor = adapt.convertStorageSchemaToProto2Descriptor(
      writeStream.tableSchema,
      'root',
    );

    const connection = await writeClient.createStreamConnection({
      streamId,
    });

    const writer = new JSONWriter({
      streamId,
      connection,
      protoDescriptor,
    });

    let rows = [];
    const pendingWrites = [];

    // Row 1
    let row = {
      row_num: 1,
      customer_name: 'Octavia',
    };
    rows.push(row);

    // Row 2
    row = {
      row_num: 2,
      customer_name: 'Turing',
    };
    rows.push(row);

    // Send batch.
    let pw = writer.appendRows(rows);
    pendingWrites.push(pw);

    rows = [];

    // Row 3
    row = {
      row_num: 3,
      customer_name: 'Bell',
    };
    rows.push(row);

    // Send batch.
    pw = writer.appendRows(rows);
    pendingWrites.push(pw);

    const results = await Promise.all(
      pendingWrites.map(pw => pw.getResult()),
    );
    console.log('Write results:', results);

    const {rowCount} = await connection.finalize();
    console.log(`Row count: ${rowCount}`);
  } catch (err) {
    console.log(err);
  } finally {
    writeClient.close();
  }
}

Utilizzare il formato Apache Arrow per importare i dati

Il seguente codice mostra come importare i dati utilizzando il formato Apache Arrow.

Python

Questo esempio mostra come importare una tabella PyArrow serializzata utilizzando il flusso predefinito. Per un esempio end-to-end più dettagliato, consulta l'esempio PyArrow su GitHub.

from google.cloud.bigquery_storage_v1 import types as gapic_types
from google.cloud.bigquery_storage_v1.writer import AppendRowsStream
from google.cloud import bigquery_storage_v1

def append_rows_with_pyarrow(
  pyarrow_table: pyarrow.Table,
  project_id: str,
  dataset_id: str,
  table_id: str,
):
  bqstorage_write_client = bigquery_storage_v1.BigQueryWriteClient()

  # Create request_template.
  request_template = gapic_types.AppendRowsRequest()
  request_template.write_stream = (
      f"projects/{project_id}/datasets/{dataset_id}/tables/{table_id}/_default"
  )
  arrow_data = gapic_types.AppendRowsRequest.ArrowData()
  arrow_data.writer_schema.serialized_schema = (
      pyarrow_table.schema.serialize().to_pybytes()
  )
  request_template.arrow_rows = arrow_data

  # Create AppendRowsStream.
  append_rows_stream = AppendRowsStream(
      bqstorage_write_client,
      request_template,
  )

  # Create request with table data.
  request = gapic_types.AppendRowsRequest()
  request.arrow_rows.rows.serialized_record_batch = (
      pyarrow_table.to_batches()[0].serialize().to_pybytes()
  )

  # Send request.
  future = append_rows_stream.send(request)

  # Wait for result.
  future.result()

Java

Per scoprire come installare e utilizzare la libreria client per BigQuery, consulta Librerie client di BigQuery. Per saperne di più, consulta la documentazione di riferimento dell'API Java BigQuery.

Per eseguire l'autenticazione in BigQuery, configura le Credenziali predefinite dell'applicazione. Per saperne di più, vedi Configura l'autenticazione per le librerie client.

import com.google.api.core.ApiFuture;
import com.google.api.core.ApiFutureCallback;
import com.google.api.core.ApiFutures;
import com.google.api.gax.core.FixedExecutorProvider;
import com.google.api.gax.retrying.RetrySettings;
import com.google.cloud.bigquery.BigQuery;
import com.google.cloud.bigquery.BigQueryOptions;
import com.google.cloud.bigquery.QueryJobConfiguration;
import com.google.cloud.bigquery.TableResult;
import com.google.cloud.bigquery.storage.v1.AppendRowsRequest;
import com.google.cloud.bigquery.storage.v1.AppendRowsResponse;
import com.google.cloud.bigquery.storage.v1.BigQueryWriteClient;
import com.google.cloud.bigquery.storage.v1.BigQueryWriteSettings;
import com.google.cloud.bigquery.storage.v1.Exceptions;
import com.google.cloud.bigquery.storage.v1.Exceptions.AppendSerializationError;
import com.google.cloud.bigquery.storage.v1.Exceptions.MaximumRequestCallbackWaitTimeExceededException;
import com.google.cloud.bigquery.storage.v1.Exceptions.StorageException;
import com.google.cloud.bigquery.storage.v1.Exceptions.StreamWriterClosedException;
import com.google.cloud.bigquery.storage.v1.StreamWriter;
import com.google.cloud.bigquery.storage.v1.TableName;
import com.google.common.collect.ImmutableList;
import com.google.common.util.concurrent.MoreExecutors;
import com.google.protobuf.Descriptors.DescriptorValidationException;
import java.io.IOException;
import java.util.List;
import java.util.Map;
import java.util.concurrent.Executors;
import java.util.concurrent.Phaser;
import java.util.concurrent.atomic.AtomicInteger;
import javax.annotation.concurrent.GuardedBy;
import org.apache.arrow.memory.BufferAllocator;
import org.apache.arrow.memory.RootAllocator;
import org.apache.arrow.vector.BigIntVector;
import org.apache.arrow.vector.VarCharVector;
import org.apache.arrow.vector.VectorSchemaRoot;
import org.apache.arrow.vector.VectorUnloader;
import org.apache.arrow.vector.compression.CompressionCodec;
import org.apache.arrow.vector.compression.CompressionUtil;
import org.apache.arrow.vector.compression.NoCompressionCodec;
import org.apache.arrow.vector.ipc.message.ArrowRecordBatch;
import org.apache.arrow.vector.types.pojo.ArrowType;
import org.apache.arrow.vector.types.pojo.Field;
import org.apache.arrow.vector.types.pojo.FieldType;
import org.apache.arrow.vector.types.pojo.Schema;
import org.threeten.bp.Duration;

/**
 * This class demonstrates how to ingest data using Arrow format into BigQuery via the default
 * stream. It initiates a DataWriter to establish a connection to BigQuery and reuses this
 * connection to continuously ingest data.
 */
public class WriteToDefaultStreamWithArrow {
  public static void main(String[] args)
      throws DescriptorValidationException, InterruptedException, IOException {
    if (args.length < 3) {
      System.out.println(
          "Usage: WriteToDefaultStreamWithArrow <projectId> <datasetName> <tableName>");
      return;
    }
    String projectId = args[0];
    String datasetName = args[1];
    String tableName = args[2];
    // Table schema should contain 3 fields:
    // ['test_string': STRING, 'test_int': INTEGER, 'test_geo':GEOGRAPHY]
    writeToDefaultStreamWithArrow(projectId, datasetName, tableName);
  }

  private static Schema createArrowSchema() {
    List<Field> fields =
        ImmutableList.of(
            new Field("test_string", FieldType.nullable(new ArrowType.Utf8()), null),
            new Field("test_int", FieldType.nullable(new ArrowType.Int(64, true)), null),
            new Field("test_geo", FieldType.nullable(new ArrowType.Utf8()), null));
    return new Schema(fields, null);
  }

  // Create an ArrowRecordBatch object that is compatible with the table schema.
  private static ArrowRecordBatch buildRecordBatch(VectorSchemaRoot root, int rowCount) {
    VarCharVector testString = (VarCharVector) root.getVector("test_string");
    BigIntVector testInt = (BigIntVector) root.getVector("test_int");
    VarCharVector testGeo = (VarCharVector) root.getVector("test_geo");

    testString.allocateNew(rowCount);
    testInt.allocateNew(rowCount);
    testGeo.allocateNew(rowCount);

    for (int i = 0; i < rowCount; i++) {
      testString.set(i, ("A" + i).getBytes());
      testInt.set(i, i + 100);
      testGeo.set(
          i,
          "POLYGON((-124.49 47.35,-124.49 40.73,-116.49 40.73,-113.49 47.35,-124.49 47.35))"
              .getBytes());
    }
    root.setRowCount(rowCount);

    CompressionCodec codec =
        NoCompressionCodec.Factory.INSTANCE.createCodec(CompressionUtil.CodecType.NO_COMPRESSION);
    VectorUnloader vectorUnloader =
        new VectorUnloader(root, /* includeNullCount= */ true, codec, /* alignBuffers= */ true);
    return vectorUnloader.getRecordBatch();
  }

  public static void writeToDefaultStreamWithArrow(
      String projectId, String datasetName, String tableName)
      throws DescriptorValidationException, InterruptedException, IOException {
    TableName parentTable = TableName.of(projectId, datasetName, tableName);
    Schema arrowSchema = createArrowSchema();
    DataWriter writer = new DataWriter();
    // One time initialization for the worker.
    writer.initialize(parentTable, arrowSchema);
    long initialRowCount = getRowCount(parentTable);
    try (BufferAllocator allocator = new RootAllocator()) {
      // A writer should be used to ingest as much data as possible before teardown.
      // Append 100 batches.
      for (int i = 0; i < 100; i++) {
        try (VectorSchemaRoot root = VectorSchemaRoot.create(arrowSchema, allocator)) {
          // Each batch has 10 rows.
          ArrowRecordBatch batch = buildRecordBatch(root, 10);

          // Asynchronous append.
          writer.append(new ArrowData(arrowSchema, batch));
        }
      }
    }
    // Final cleanup for the stream during worker teardown.
    // It's blocked until all append requests' response are received.
    writer.cleanup();

    verifyExpectedRowCount(parentTable, initialRowCount + 1000);
    System.out.println("Appended records successfully.");
  }

  private static long getRowCount(TableName parentTable) throws InterruptedException {
    String queryRowCount =
        "SELECT COUNT(*) FROM `"
            + parentTable.getProject()
            + "."
            + parentTable.getDataset()
            + "."
            + parentTable.getTable()
            + "`";
    QueryJobConfiguration queryConfig = QueryJobConfiguration.newBuilder(queryRowCount).build();
    BigQuery bigquery =
        BigQueryOptions.newBuilder().setProjectId(parentTable.getProject()).build().getService();
    TableResult results = bigquery.query(queryConfig);
    return Long.parseLong(results.getValues().iterator().next().get("f0_").getStringValue());
  }

  private static void verifyExpectedRowCount(TableName parentTable, long expectedRowCount)
      throws InterruptedException {
    String queryRowCount =
        "SELECT COUNT(*) FROM `"
            + parentTable.getProject()
            + "."
            + parentTable.getDataset()
            + "."
            + parentTable.getTable()
            + "`";
    QueryJobConfiguration queryConfig = QueryJobConfiguration.newBuilder(queryRowCount).build();
    BigQuery bigquery =
        BigQueryOptions.newBuilder().setProjectId(parentTable.getProject()).build().getService();
    TableResult results = bigquery.query(queryConfig);
    long countRowsActual =
        Long.parseLong(results.getValues().iterator().next().get("f0_").getStringValue());
    if (countRowsActual != expectedRowCount) {
      throw new RuntimeException(
          "Unexpected row count. Expected: " + expectedRowCount + ". Actual: " + countRowsActual);
    }
  }

  private static class ArrowData {
    Schema arrowSchema;
    ArrowRecordBatch data;

    ArrowData(Schema arrowSchema, ArrowRecordBatch data) {
      this.arrowSchema = arrowSchema;
      this.data = data;
    }
  }

  private static class DataWriter {

    private static final int MAX_RECREATE_COUNT = 3;

    private BigQueryWriteClient client;

    // Track the number of in-flight requests to wait for all responses before shutting down.
    private final Phaser inflightRequestCount = new Phaser(1);
    private final Object lock = new Object();

    private Schema arrowSchema;
    private StreamWriter streamWriter;

    @GuardedBy("lock")
    private RuntimeException error = null;

    private final AtomicInteger recreateCount = new AtomicInteger(0);

    private StreamWriter createStreamWriter(String streamName, Schema arrowSchema)
        throws IOException {
      // Configure in-stream automatic retry settings.
      // Error codes that are immediately retried:
      // * ABORTED, UNAVAILABLE, CANCELLED, INTERNAL, DEADLINE_EXCEEDED
      // Error codes that are retried with exponential backoff:
      // * RESOURCE_EXHAUSTED
      RetrySettings retrySettings =
          RetrySettings.newBuilder()
              .setInitialRetryDelay(Duration.ofMillis(500))
              .setRetryDelayMultiplier(1.1)
              .setMaxAttempts(5)
              .setMaxRetryDelay(Duration.ofMinutes(1))
              .build();

      // Use the Stream writer to send records in Arrow format. Specify the table name to write
      // to the default stream.
      // For more information about StreamWriter, see:
      // https://cloud.google.com/java/docs/reference/google-cloud-bigquerystorage/latest/com.google.cloud.bigquery.storage.v1.StreamWriter
      return StreamWriter.newBuilder(streamName, client)
          .setExecutorProvider(FixedExecutorProvider.create(Executors.newScheduledThreadPool(10)))
          .setChannelProvider(
              BigQueryWriteSettings.defaultGrpcTransportProviderBuilder()
                  .setKeepAliveTime(org.threeten.bp.Duration.ofMinutes(1))
                  .setKeepAliveTimeout(org.threeten.bp.Duration.ofMinutes(1))
                  .setKeepAliveWithoutCalls(true)
                  .setChannelsPerCpu(2)
                  .build())
          .setEnableConnectionPool(true)
          // If value is missing in ArrowRecordBatch and there is a default value configured on
          // bigquery column, apply the default value to the missing value field.
          .setDefaultMissingValueInterpretation(
              AppendRowsRequest.MissingValueInterpretation.DEFAULT_VALUE)
          .setMaxRetryDuration(java.time.Duration.ofSeconds(5))
          // Set the StreamWriter with Arrow Schema, this would only allow the StreamWriter to
          // append data in Arrow format.
          .setWriterSchema(arrowSchema)
          .setRetrySettings(retrySettings)
          .build();
    }

    public void initialize(TableName parentTable, Schema arrowSchema)
        throws DescriptorValidationException, IOException, InterruptedException {
      // Initialize client without settings, internally within stream writer a new client will be
      // created with full settings.
      client = BigQueryWriteClient.create();

      streamWriter = createStreamWriter(parentTable.toString() + "/_default", arrowSchema);
    }

    public void append(ArrowData arrowData)
        throws DescriptorValidationException, IOException, InterruptedException {
      synchronized (this.lock) {
        if (!streamWriter.isUserClosed()
            && streamWriter.isClosed()
            && recreateCount.getAndIncrement() < MAX_RECREATE_COUNT) {
          streamWriter = createStreamWriter(streamWriter.getStreamName(), arrowData.arrowSchema);
          this.error = null;
        }
        // If earlier appends have failed, we need to reset before continuing.
        if (this.error != null) {
          throw this.error;
        }
      }
      // Append asynchronously for increased throughput.
      ApiFuture<AppendRowsResponse> future = streamWriter.append(arrowData.data);
      ApiFutures.addCallback(
          future, new AppendCompleteCallback(this, arrowData), MoreExecutors.directExecutor());

      // Increase the count of in-flight requests.
      inflightRequestCount.register();
    }

    public void cleanup() {
      // Wait for all in-flight requests to complete.
      inflightRequestCount.arriveAndAwaitAdvance();

      client.close();
      // Close the connection to the server.
      streamWriter.close();

      // Verify that no error occurred in the stream.
      synchronized (this.lock) {
        if (this.error != null) {
          throw this.error;
        }
      }
    }

    static class AppendCompleteCallback implements ApiFutureCallback<AppendRowsResponse> {

      private final DataWriter parent;
      private final ArrowData arrowData;

      public AppendCompleteCallback(DataWriter parent, ArrowData arrowData) {
        this.parent = parent;
        this.arrowData = arrowData;
      }

      public void onSuccess(AppendRowsResponse response) {
        System.out.format("Append success\n");
        this.parent.recreateCount.set(0);
        done();
      }

      public void onFailure(Throwable throwable) {
        System.out.format("Append failed: " + throwable.toString());
        if (throwable instanceof AppendSerializationError) {
          AppendSerializationError ase = (AppendSerializationError) throwable;
          Map<Integer, String> rowIndexToErrorMessage = ase.getRowIndexToErrorMessage();
          if (rowIndexToErrorMessage.size() > 0) {
            System.out.format("row level errors: " + rowIndexToErrorMessage.toString());
            // The append returned failure with indices for faulty rows.
            // Fix the faulty rows or remove them from the appended data and retry the append.
            done();
            return;
          }
        }

        boolean resendRequest = false;
        if (throwable instanceof MaximumRequestCallbackWaitTimeExceededException) {
          resendRequest = true;
        } else if (throwable instanceof StreamWriterClosedException) {
          if (!parent.streamWriter.isUserClosed()) {
            resendRequest = true;
          }
        }
        if (resendRequest) {
          // Retry this request.
          try {
            this.parent.append(new ArrowData(arrowData.arrowSchema, arrowData.data));
          } catch (DescriptorValidationException e) {
            throw new RuntimeException(e);
          } catch (IOException e) {
            throw new RuntimeException(e);
          } catch (InterruptedException e) {
            throw new RuntimeException(e);
          }
          // Mark the existing attempt as done since we got a response for it
          done();
          return;
        }

        synchronized (this.parent.lock) {
          if (this.parent.error == null) {
            StorageException storageException = Exceptions.toStorageException(throwable);
            this.parent.error =
                (storageException != null) ? storageException : new RuntimeException(throwable);
          }
        }
        done();
      }

      private void done() {
        // Reduce the count of in-flight requests.
        this.parent.inflightRequestCount.arriveAndDeregister();
      }
    }
  }
}