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Escribir ejemplos

En este documento se muestran ejemplos de código que ilustran los distintos tipos de solicitudes de escritura que puedes enviar a Bigtable cuando usas las bibliotecas de cliente de Cloud Bigtable.

En los ejemplos de esta página se usan mutaciones de SetCell para enviar solicitudes de escritura a celdas no agregadas. Para ver ejemplos de cómo enviar solicitudes de adición para agregar celdas, consulta Agrega tus datos en el momento de la escritura.

Antes de probar estas muestras, asegúrate de saber cuándo debes usar cada tipo de solicitud de escritura y cuándo no.

La biblioteca de cliente de Python para Bigtable ofrece dos APIs: asyncio y una API síncrona. Si tu aplicación es asíncrona, usa asyncio.

Los ejemplos de código de esta página hacen referencia a la tabla de ejemplo de Datos para ejemplos.

Hacer una operación de escritura sencilla

En los siguientes ejemplos de código se muestra cómo hacer solicitudes de escritura sencillas a Bigtable. Este tipo de escritura hace una solicitud a la API MutateRow.

Go

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

Para autenticarte en Bigtable, configura las credenciales predeterminadas de la aplicación. Para obtener más información, consulta el artículo Configurar la autenticación para bibliotecas de cliente.

import (
	"context"
	"encoding/binary"
	"fmt"
	"io"

	"bytes"

	"cloud.google.com/go/bigtable"
)

func writeSimple(w io.Writer, projectID, instanceID string, tableName string) error {
	// projectID := "my-project-id"
	// instanceID := "my-instance-id"
	// tableName := "mobile-time-series"

	ctx := context.Background()
	client, err := bigtable.NewClient(ctx, projectID, instanceID)
	if err != nil {
		return fmt.Errorf("bigtable.NewClient: %w", err)
	}
	defer client.Close()
	tbl := client.Open(tableName)
	columnFamilyName := "stats_summary"
	timestamp := bigtable.Now()

	mut := bigtable.NewMutation()
	buf := new(bytes.Buffer)
	binary.Write(buf, binary.BigEndian, int64(1))

	mut.Set(columnFamilyName, "connected_cell", timestamp, buf.Bytes())
	mut.Set(columnFamilyName, "connected_wifi", timestamp, buf.Bytes())
	mut.Set(columnFamilyName, "os_build", timestamp, []byte("PQ2A.190405.003"))

	rowKey := "phone#4c410523#20190501"
	if err := tbl.Apply(ctx, rowKey, mut); err != nil {
		return fmt.Errorf("Apply: %w", err)
	}

	fmt.Fprintf(w, "Successfully wrote row: %s\n", rowKey)
	return nil
}

HBase

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.


import com.google.cloud.bigtable.hbase.BigtableConfiguration;
import org.apache.hadoop.hbase.TableName;
import org.apache.hadoop.hbase.client.Connection;
import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.client.Table;
import org.apache.hadoop.hbase.util.Bytes;

public class WriteSimple {

  private static final byte[] COLUMN_FAMILY_NAME = Bytes.toBytes("stats_summary");

  public static void writeSimple(String projectId, String instanceId, String tableId) {
    // String projectId = "my-project-id";
    // String instanceId = "my-instance-id";
    // String tableId = "mobile-time-series";

    try (Connection connection = BigtableConfiguration.connect(projectId, instanceId)) {
      final Table table = connection.getTable(TableName.valueOf(Bytes.toBytes(tableId)));
      long timestamp = System.currentTimeMillis();
      byte[] one = new byte[]{0, 0, 0, 0, 0, 0, 0, 1};

      String rowKey = "phone#4c410523#20190501";
      Put put = new Put(Bytes.toBytes(rowKey));

      put.addColumn(COLUMN_FAMILY_NAME, Bytes.toBytes("connected_cell"), timestamp, one);
      put.addColumn(COLUMN_FAMILY_NAME, Bytes.toBytes("connected_wifi"), timestamp, one);
      put.addColumn(
          COLUMN_FAMILY_NAME,
          Bytes.toBytes("os_build"),
          timestamp,
          Bytes.toBytes("PQ2A.190405.003"));
      table.put(put);

      System.out.printf("Successfully wrote row %s", rowKey);

    } catch (Exception e) {
      System.out.println("Error during WriteSimple: \n" + e.toString());
    }
  }
}

Java

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.


import com.google.cloud.bigtable.data.v2.BigtableDataClient;
import com.google.cloud.bigtable.data.v2.models.RowMutation;
import com.google.cloud.bigtable.data.v2.models.TableId;
import com.google.protobuf.ByteString;

public class WriteSimple {
  private static final String COLUMN_FAMILY_NAME = "stats_summary";

  public static void writeSimple(String projectId, String instanceId, String tableId) {
    // String projectId = "my-project-id";
    // String instanceId = "my-instance-id";
    // String tableId = "mobile-time-series";

    try (BigtableDataClient dataClient = BigtableDataClient.create(projectId, instanceId)) {
      long timestamp = System.currentTimeMillis() * 1000;

      String rowkey = "phone#4c410523#20190501";

      RowMutation rowMutation =
          RowMutation.create(TableId.of(tableId), rowkey)
              .setCell(
                  COLUMN_FAMILY_NAME,
                  ByteString.copyFrom("connected_cell".getBytes()),
                  timestamp,
                  1)
              .setCell(
                  COLUMN_FAMILY_NAME,
                  ByteString.copyFrom("connected_wifi".getBytes()),
                  timestamp,
                  1)
              .setCell(COLUMN_FAMILY_NAME, "os_build", timestamp, "PQ2A.190405.003");

      dataClient.mutateRow(rowMutation);
      System.out.printf("Successfully wrote row %s", rowkey);

    } catch (Exception e) {
      System.out.println("Error during WriteSimple: \n" + e.toString());
    }
  }
}

Python asyncio

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

from google.cloud.bigtable.data import BigtableDataClientAsync
from google.cloud.bigtable.data import SetCell

async def write_simple(project_id, instance_id, table_id):
    async with BigtableDataClientAsync(project=project_id) as client:
        async with client.get_table(instance_id, table_id) as table:
            family_id = "stats_summary"
            row_key = b"phone#4c410523#20190501"

            cell_mutation = SetCell(family_id, "connected_cell", 1)
            wifi_mutation = SetCell(family_id, "connected_wifi", 1)
            os_mutation = SetCell(family_id, "os_build", "PQ2A.190405.003")

            await table.mutate_row(row_key, cell_mutation)
            await table.mutate_row(row_key, wifi_mutation)
            await table.mutate_row(row_key, os_mutation)

Python

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

import datetime

from google.cloud import bigtable


def write_simple(project_id, instance_id, table_id):
    client = bigtable.Client(project=project_id, admin=True)
    instance = client.instance(instance_id)
    table = instance.table(table_id)

    timestamp = datetime.datetime.utcnow()
    column_family_id = "stats_summary"

    row_key = "phone#4c410523#20190501"

    row = table.direct_row(row_key)
    row.set_cell(column_family_id, "connected_cell", 1, timestamp)
    row.set_cell(column_family_id, "connected_wifi", 1, timestamp)
    row.set_cell(column_family_id, "os_build", "PQ2A.190405.003", timestamp)

    row.commit()

    print("Successfully wrote row {}.".format(row_key))

C#

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.


using System;
using Google.Cloud.Bigtable.V2;
using Google.Cloud.Bigtable.Common.V2;

namespace Writes
{
    public class WriteSimpleSample
    {
        /// <summary>
        /// Mutate one row in an existing table and column family. Updates multiple cells within that row using one API call.
        ///</summary>
        /// <param name="projectId">Your Google Cloud Project ID.</param>
        /// <param name="instanceId">Your Google Cloud Bigtable Instance ID.</param>
        /// <param name="tableId">Your Google Cloud Bigtable table ID.</param>
        public string WriteSimple(
            string projectId = "YOUR-PROJECT-ID",
            string instanceId = "YOUR-INSTANCE-ID",
            string tableId = "YOUR-TABLE-ID")
        {
            BigtableClient bigtableClient = BigtableClient.Create();

            TableName tableName = new TableName(projectId, instanceId, tableId);
            BigtableByteString rowkey = new BigtableByteString("phone#4c410523#20190501");
            BigtableVersion timestamp = new BigtableVersion(DateTime.UtcNow);
            string COLUMN_FAMILY = "stats_summary";

            Mutation[] mutations = {
                    Mutations.SetCell(COLUMN_FAMILY, "connected_cell", 1, timestamp),
                    Mutations.SetCell(COLUMN_FAMILY, "connected_wifi", 1, timestamp),
                    Mutations.SetCell(COLUMN_FAMILY, "os_build", "PQ2A.190405.003", timestamp)
                };
            MutateRowResponse mutateRowResponse = bigtableClient.MutateRow(tableName, rowkey, mutations);
            Console.WriteLine(mutateRowResponse);
            return $"Successfully wrote row {rowkey}";
        }
    }
}

C++

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

namespace cbt = ::google::cloud::bigtable;
[](cbt::Table table) {
  auto timestamp = std::chrono::duration_cast<std::chrono::milliseconds>(
      std::chrono::system_clock::now().time_since_epoch());

  std::string row_key = "phone#4c410523#20190501";
  cbt::SingleRowMutation mutation(row_key);
  std::string column_family = "stats_summary";

  mutation.emplace_back(cbt::SetCell(column_family, "connected_cell",
                                     timestamp, std::int64_t{1}));
  mutation.emplace_back(cbt::SetCell(column_family, "connected_wifi",
                                     timestamp, std::int64_t{1}));
  mutation.emplace_back(
      cbt::SetCell(column_family, "os_build", timestamp, "PQ2A.190405.003"));
  google::cloud::Status status = table.Apply(std::move(mutation));
  if (!status.ok()) throw std::runtime_error(status.message());
  std::cout << "Successfully wrote row" << row_key << "\n";
}

Node.js

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

const {Bigtable} = require('@google-cloud/bigtable');
const bigtable = new Bigtable();

async function writeSimple() {
  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  // const instanceId = 'YOUR_INSTANCE_ID';
  // const tableId = 'YOUR_TABLE_ID';
  const instance = bigtable.instance(instanceId);
  const table = instance.table(tableId);

  const timestamp = new Date();
  const rowToInsert = {
    key: 'phone#4c410523#20190501',
    data: {
      stats_summary: {
        connected_cell: {
          value: 1,
          timestamp,
        },
        connected_wifi: {
          value: 1,
          timestamp,
        },
        os_build: {
          value: 'PQ2A.190405.003',
          timestamp,
        },
      },
    },
  };

  await table.insert(rowToInsert);

  console.log(`Successfully wrote row ${rowToInsert.key}`);
}

writeSimple();

PHP

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

use Google\Cloud\Bigtable\BigtableClient;
use Google\Cloud\Bigtable\DataUtil;
use Google\Cloud\Bigtable\Mutations;

/**
 * Write data in a table
 *
 * @param string $projectId The Google Cloud project ID
 * @param string $instanceId The ID of the Bigtable instance
 * @param string $tableId The ID of the table where the data needs to be written
 */
function write_simple(
    string $projectId,
    string $instanceId,
    string $tableId = 'mobile-time-series'
): void {
    // Connect to an existing table with an existing instance.
    $dataClient = new BigtableClient([
        'projectId' => $projectId,
    ]);
    $table = $dataClient->table($instanceId, $tableId);

    $timestampMicros = time() * 1000 * 1000;
    $columnFamilyId = 'stats_summary';
    $mutations = (new Mutations())
    ->upsert($columnFamilyId, 'connected_cell', '1', $timestampMicros)
    ->upsert($columnFamilyId, 'connected_wifi', DataUtil::intToByteString(1), $timestampMicros)
    ->upsert($columnFamilyId, 'os_build', 'PQ2A.190405.003', $timestampMicros);

    $table->mutateRow('phone#4c410523#20190501', $mutations);

    printf('Successfully wrote row.' . PHP_EOL);
}

Ruby

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

# instance_id = "my-instance"
# table_id    = "my-table"
table = bigtable.table instance_id, table_id
column_family = "stats_summary"
timestamp = (Time.now.to_f * 1_000_000).round(-3)

rowkey = "phone#4c410523#20190501"
entry = table.new_mutation_entry(rowkey)
             .set_cell(column_family, "connected_cell", 1, timestamp: timestamp)
             .set_cell(column_family, "connected_wifi", 1, timestamp: timestamp)
             .set_cell(column_family, "os_build", "PQ2A.190405.003", timestamp: timestamp)

table.mutate_row entry
puts "Successfully wrote row #{rowkey}"

Incrementar un valor

En los siguientes ejemplos de código se muestra cómo enviar una solicitud de escritura que incrementa o reduce un valor numérico de una celda agregada. Este tipo de escritura hace una solicitud MutateRow con un tipo de mutación AddToCell. Los ejemplos se suman a una familia de columnas que espera el tipo de entrada Int64.

cbt

cbt addtocell TABLE_ID ROW_KEY
FAMILY_NAME:COLUMN_QUALIFER=VALUE@TIMESTAMP

Haz los cambios siguientes:

TABLE_ID: identificador permanente de la tabla
ROW_KEY: la clave de la fila
FAMILY_NAME: el nombre de la familia de columnas agregada
COLUMN_QUALIFIER: identificador de la columna
VALUE: el valor que se va a añadir a la celda
TIMESTAMP: marca de tiempo de Unix en microsegundos, como 1710868850000000

En este ejemplo, se resta 100 al valor almacenado en la columna week12 de la fila device-1:

cbt addtocell mobile-data device-1 updates:week12=-100@1710868850000000

Go

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

import (
	"context"
	"fmt"
	"io"
	"time"

	"cloud.google.com/go/bigtable"
)

func writeAggregate(w io.Writer, projectID, instanceID string, tableName string) error {
	// projectID := "my-project-id"
	// instanceID := "my-instance-id"
	// tableName := "mobile-time-series"

	ctx := context.Background()
	client, err := bigtable.NewClient(ctx, projectID, instanceID)
	if err != nil {
		return fmt.Errorf("bigtable.NewClient: %w", err)
	}
	defer client.Close()
	tbl := client.Open(tableName)
	columnFamilyName := "view_count"
	viewTimestamp, err := time.Parse(time.RFC3339, "2024-03-13T12:41:34Z")
	if err != nil {
		return err
	}
	hourlyBucket := viewTimestamp.Truncate(time.Hour)

	mut := bigtable.NewMutation()
	mut.AddIntToCell(columnFamilyName, "views", bigtable.Time(hourlyBucket), 1)

	rowKey := "page#index.html"
	if err := tbl.Apply(ctx, rowKey, mut); err != nil {
		return fmt.Errorf("Apply: %w", err)
	}

	fmt.Fprintf(w, "Successfully wrote row: %s\n", rowKey)
	return nil
}

Java

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.


import com.google.cloud.bigtable.data.v2.BigtableDataClient;
import com.google.cloud.bigtable.data.v2.models.RowMutation;
import com.google.common.primitives.Longs;
import com.google.protobuf.ByteString;
import java.time.Instant;
import java.time.temporal.ChronoUnit;

public class WriteAggregate {
  private static final String COUNT_COLUMN_FAMILY_NAME = "view_count";
  private static final long MICROS_PER_MILLI = 1000;

  public static void writeAggregate(String projectId, String instanceId, String tableId) {
    // String projectId = "my-project-id";
    // String instanceId = "my-instance-id";
    // String tableId = "page-view-counter";

    try (BigtableDataClient dataClient = BigtableDataClient.create(projectId, instanceId)) {

      String rowKey = "page#index.html";
      Instant viewTimestamp = Instant.parse("2024-03-13T12:41:34.123Z");

      // Bucket the views for an hour into a single count, giving us an hourly view count for a
      // given page.
      Instant hourlyBucket = viewTimestamp.truncatedTo(ChronoUnit.HOURS);
      long hourlyBucketMicros = hourlyBucket.toEpochMilli() * MICROS_PER_MILLI;

      RowMutation rowMutation =
          RowMutation.create(tableId, rowKey)
              .addToCell(COUNT_COLUMN_FAMILY_NAME, "views", hourlyBucketMicros, 1);

      dataClient.mutateRow(rowMutation);
      System.out.printf("Successfully wrote row %s", rowKey);

    } catch (Exception e) {
      System.out.println("Error during WriteAggregate: \n" + e.toString());
    }
  }

  public static void mergeAggregate(String projectId, String instanceId, String tableId) {
    // String projectId = "my-project-id";
    // String instanceId = "my-instance-id";
    // String tableId = "page-view-counter";

    try (BigtableDataClient dataClient = BigtableDataClient.create(projectId, instanceId)) {

      String rowKey = "page#index.html";
      Instant viewTimestamp = Instant.parse("2024-03-13T12:41:34.123Z");

      // Bucket the views for an hour into a single count, giving us an hourly view count for a
      // given page.
      Instant hourlyBucket = viewTimestamp.truncatedTo(ChronoUnit.HOURS);
      long hourlyBucketMicros = hourlyBucket.toEpochMilli() * MICROS_PER_MILLI;

      RowMutation rowMutation =
          RowMutation.create(tableId, rowKey)
              .mergeToCell(
                  COUNT_COLUMN_FAMILY_NAME,
                  "views",
                  hourlyBucketMicros,
                  ByteString.copyFrom(Longs.toByteArray(1L)));

      dataClient.mutateRow(rowMutation);
      System.out.printf("Successfully wrote row %s", rowKey);

    } catch (Exception e) {
      System.out.println("Error during mergeAggregate: \n" + e.toString());
    }
  }
}

Escribir un valor de forma condicional

En los siguientes ejemplos de código se muestra cómo enviar una solicitud de escritura condicional, que comprueba si se cumple una condición en una fila y, en función del resultado, escribe datos en esa fila. Este tipo de escritura hace una solicitud a la API CheckAndMutateRow.

Go

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

import (
	"context"
	"fmt"
	"io"

	"cloud.google.com/go/bigtable"
)

func writeConditionally(w io.Writer, projectID, instanceID string, tableName string) error {
	// projectID := "my-project-id"
	// instanceID := "my-instance-id"
	// tableName := "mobile-time-series"

	ctx := context.Background()
	client, err := bigtable.NewClient(ctx, projectID, instanceID)
	if err != nil {
		return fmt.Errorf("bigtable.NewAdminClient: %w", err)
	}
	defer client.Close()
	tbl := client.Open(tableName)
	columnFamilyName := "stats_summary"
	timestamp := bigtable.Now()

	mut := bigtable.NewMutation()
	mut.Set(columnFamilyName, "os_name", timestamp, []byte("android"))

	filter := bigtable.ChainFilters(
		bigtable.FamilyFilter(columnFamilyName),
		bigtable.ColumnFilter("os_build"),
		bigtable.ValueFilter("PQ2A\\..*"))
	conditionalMutation := bigtable.NewCondMutation(filter, mut, nil)

	rowKey := "phone#4c410523#20190501"
	if err := tbl.Apply(ctx, rowKey, conditionalMutation); err != nil {
		return fmt.Errorf("Apply: %w", err)
	}

	fmt.Fprintln(w, "Successfully updated row's os_name")
	return nil
}

HBase

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.


import com.google.cloud.bigtable.hbase.BigtableConfiguration;
import org.apache.hadoop.hbase.TableName;
import org.apache.hadoop.hbase.client.Connection;
import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.client.RowMutations;
import org.apache.hadoop.hbase.client.Table;
import org.apache.hadoop.hbase.filter.CompareFilter.CompareOp;
import org.apache.hadoop.hbase.util.Bytes;

public class WriteConditionally {

  private static final byte[] COLUMN_FAMILY_NAME = Bytes.toBytes("stats_summary");

  public static void writeConditionally(String projectId, String instanceId, String tableId) {
    // String projectId = "my-project-id";
    // String instanceId = "my-instance-id";
    // String tableId = "mobile-time-series";

    try (Connection connection = BigtableConfiguration.connect(projectId, instanceId)) {
      Table table = connection.getTable(TableName.valueOf(Bytes.toBytes(tableId)));
      long timestamp = System.currentTimeMillis();

      String rowKey = "phone#4c410523#20190501";
      RowMutations mutations = new RowMutations(Bytes.toBytes(rowKey));

      Put put = new Put(Bytes.toBytes(rowKey));
      put.addColumn(
          COLUMN_FAMILY_NAME, Bytes.toBytes("os_name"), timestamp, Bytes.toBytes("android"));
      mutations.add(put);

      table.checkAndMutate(
          Bytes.toBytes(rowKey),
          COLUMN_FAMILY_NAME,
          Bytes.toBytes("os_build"),
          CompareOp.GREATER_OR_EQUAL,
          Bytes.toBytes("PQ2A.190405"),
          mutations);

      System.out.print("Successfully updated row's os_name");

    } catch (Exception e) {
      System.out.println("Error during WriteConditionally: \n" + e.toString());
      e.printStackTrace();
    }
  }
}

Java

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.


import static com.google.cloud.bigtable.data.v2.models.Filters.FILTERS;

import com.google.cloud.bigtable.data.v2.BigtableDataClient;
import com.google.cloud.bigtable.data.v2.models.ConditionalRowMutation;
import com.google.cloud.bigtable.data.v2.models.Filters.Filter;
import com.google.cloud.bigtable.data.v2.models.Mutation;
import com.google.cloud.bigtable.data.v2.models.TableId;

public class WriteConditionally {
  private static final String COLUMN_FAMILY_NAME = "stats_summary";

  public static void writeConditionally(String projectId, String instanceId, String tableId) {
    // String projectId = "my-project-id";
    // String instanceId = "my-instance-id";
    // String tableId = "mobile-time-series";

    try (BigtableDataClient dataClient = BigtableDataClient.create(projectId, instanceId)) {
      long timestamp = System.currentTimeMillis() * 1000;

      String rowkey = "phone#4c410523#20190501";

      Mutation mutation =
          Mutation.create().setCell(COLUMN_FAMILY_NAME, "os_name", timestamp, "android");

      Filter filter =
          FILTERS
              .chain()
              .filter(FILTERS.family().exactMatch(COLUMN_FAMILY_NAME))
              .filter(FILTERS.qualifier().exactMatch("os_build"))
              .filter(FILTERS.value().regex("PQ2A\\..*"));

      ConditionalRowMutation conditionalRowMutation =
          ConditionalRowMutation.create(TableId.of(tableId), rowkey)
              .condition(filter)
              .then(mutation);

      boolean success = dataClient.checkAndMutateRow(conditionalRowMutation);

      System.out.printf("Successfully updated row's os_name: %b", success);

    } catch (Exception e) {
      System.out.println("Error during WriteConditionally: \n" + e.toString());
      e.printStackTrace();
    }
  }
}

Python asyncio

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

from google.cloud.bigtable.data import BigtableDataClientAsync
from google.cloud.bigtable.data import row_filters
from google.cloud.bigtable.data import SetCell

async def write_conditional(project_id, instance_id, table_id):
    async with BigtableDataClientAsync(project=project_id) as client:
        async with client.get_table(instance_id, table_id) as table:
            family_id = "stats_summary"
            row_key = "phone#4c410523#20190501"

            row_filter = row_filters.RowFilterChain(
                filters=[
                    row_filters.FamilyNameRegexFilter(family_id),
                    row_filters.ColumnQualifierRegexFilter("os_build"),
                    row_filters.ValueRegexFilter("PQ2A\\..*"),
                ]
            )

            if_true = SetCell(family_id, "os_name", "android")
            result = await table.check_and_mutate_row(
                row_key,
                row_filter,
                true_case_mutations=if_true,
                false_case_mutations=None,
            )
            if result is True:
                print("The row os_name was set to android")

Python

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

import datetime

from google.cloud import bigtable
from google.cloud.bigtable import row_filters


def write_conditional(project_id, instance_id, table_id):
    client = bigtable.Client(project=project_id, admin=True)
    instance = client.instance(instance_id)
    table = instance.table(table_id)

    timestamp = datetime.datetime.utcnow()
    column_family_id = "stats_summary"

    row_key = "phone#4c410523#20190501"

    row_filter = row_filters.RowFilterChain(
        filters=[
            row_filters.FamilyNameRegexFilter(column_family_id),
            row_filters.ColumnQualifierRegexFilter("os_build"),
            row_filters.ValueRegexFilter("PQ2A\\..*"),
        ]
    )
    row = table.conditional_row(row_key, filter_=row_filter)
    row.set_cell(column_family_id, "os_name", "android", timestamp)
    row.commit()

    print("Successfully updated row's os_name.")

C#

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.


using System;
using Google.Cloud.Bigtable.V2;
using Google.Cloud.Bigtable.Common.V2;

namespace Writes
{
    public class WriteConditionalSample
    {
        /// <summary>
        /// Check if a row has a certain value then mutate the row if it does.
        ///</summary>
        /// <param name="projectId">Your Google Cloud Project ID.</param>
        /// <param name="instanceId">Your Google Cloud Bigtable Instance ID.</param>
        /// <param name="tableId">Your Google Cloud Bigtable table ID.</param>
        public string WriteConditional(
            string projectId = "YOUR-PROJECT-ID",
            string instanceId = "YOUR-INSTANCE-ID",
            string tableId = "YOUR-TABLE-ID")
        {
            BigtableClient bigtableClient = BigtableClient.Create();

            TableName tableName = new TableName(projectId, instanceId, tableId);
            BigtableByteString rowkey = new BigtableByteString("phone#4c410523#20190501");
            BigtableVersion timestamp = new BigtableVersion(DateTime.UtcNow);
            string COLUMN_FAMILY = "stats_summary";

            CheckAndMutateRowResponse checkAndMutateRowResponse = bigtableClient.CheckAndMutateRow(
                tableName,
                rowkey,
                RowFilters.Chain(
                    RowFilters.FamilyNameExact(COLUMN_FAMILY),
                    RowFilters.ColumnQualifierExact("os_build"),
                    RowFilters.ValueRegex("PQ2A\\..*")),
                Mutations.SetCell(COLUMN_FAMILY, "os_name", "android", timestamp));

            return $"Successfully updated row's os_name: {checkAndMutateRowResponse.PredicateMatched}";
        }
    }
}

C++

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

namespace cbt = ::google::cloud::bigtable;
[](cbt::Table table) {
  auto timestamp = std::chrono::duration_cast<std::chrono::milliseconds>(
      std::chrono::system_clock::now().time_since_epoch());

  std::string row_key = "phone#4c410523#20190501";
  cbt::SingleRowMutation mutation(row_key);
  std::string column_family = "stats_summary";
  cbt::Filter predicate = cbt::Filter::Chain(
      cbt::Filter::ColumnName(column_family, "os_build"),
      cbt::Filter::Latest(1), cbt::Filter::ValueRegex("PQ2A\\..*"));

  google::cloud::StatusOr<cbt::MutationBranch> branch =
      table.CheckAndMutateRow(
          row_key, std::move(predicate),
          {cbt::SetCell(column_family, "os_name", timestamp, "android")}, {});

  if (!branch) throw std::move(branch).status();
  if (*branch == cbt::MutationBranch::kPredicateMatched) {
    std::cout << "Successfully updated row\n";
  } else {
    std::cout << "The predicate was not matched\n";
  }
}

Node.js

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

/**
 * TODO(developer): Uncomment these variables before running the sample.
 */
// const instanceId = 'YOUR_INSTANCE_ID';
// const tableId = 'YOUR_TABLE_ID';

const {Bigtable} = require('@google-cloud/bigtable');

const bigtable = new Bigtable();

async function writeConditionally() {
  const instance = bigtable.instance(instanceId);
  const table = instance.table(tableId);

  const timestamp = new Date();
  const row = table.row('phone#4c410523#20190501');
  const filter = [
    {
      column: 'os_build',
      value: {
        start: 'PQ2A',
        end: 'PQ2A',
      },
    },
  ];

  const config = {
    onMatch: [
      {
        method: 'insert',
        data: {
          stats_summary: {
            os_name: 'android',
            timestamp,
          },
        },
      },
    ],
  };

  await row.filter(filter, config);

  console.log("Successfully updated row's os_name");
}

writeConditionally();

PHP

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

use Google\Cloud\Bigtable\BigtableClient;
use Google\Cloud\Bigtable\Filter;
use Google\Cloud\Bigtable\Mutations;

/**
 * Write data conditionally in a table
 *
 * @param string $projectId The Google Cloud project ID
 * @param string $instanceId The ID of the Bigtable instance
 * @param string $tableId The ID of the table where the data needs to be written
 */
function write_conditionally(
    string $projectId,
    string $instanceId,
    string $tableId = 'mobile-time-series'
): void {
    // Connect to an existing table with an existing instance.
    $dataClient = new BigtableClient([
        'projectId' => $projectId,
    ]);
    $table = $dataClient->table($instanceId, $tableId);

    $timestampMicros = time() * 1000 * 1000;
    $columnFamilyId = 'stats_summary';

    $mutations = (new Mutations())->upsert($columnFamilyId, 'os_name', 'android', $timestampMicros);
    $predicateFilter = Filter::chain()
    ->addFilter(Filter::family()->exactMatch($columnFamilyId))
    ->addFilter(Filter::qualifier()->exactMatch('os_build'))
    ->addFilter(Filter::value()->regex('PQ2A.*'));
    $options = ['predicateFilter' => $predicateFilter, 'trueMutations' => $mutations];

    $table->checkAndMutateRow('phone#4c410523#20190501', $options);

    printf('Successfully updated row\'s os_name' . PHP_EOL);
}

Ruby

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

# instance_id = "my-instance"
# table_id    = "my-table"
table = bigtable.table instance_id, table_id
column_family = "stats_summary"
timestamp = (Time.now.to_f * 1_000_000).round(-3)

rowkey = "phone#4c410523#20190501"
predicate_filter = Google::Cloud::Bigtable::RowFilter.chain
                                                     .family(column_family)
                                                     .qualifier("os_build")
                                                     .value("PQ2A\\..*")

on_match_mutations = Google::Cloud::Bigtable::MutationEntry.new
on_match_mutations.set_cell(
  column_family,
  "os_name",
  "android",
  timestamp: timestamp
)

response = table.check_and_mutate_row(
  rowkey,
  predicate_filter,
  on_match: on_match_mutations
)

puts "Successfully updated row's os_name: #{response}"

Hacer operaciones de escritura por lotes

En los siguientes ejemplos de código se muestra cómo hacer solicitudes de escritura por lotes en Bigtable. Este tipo de escritura hace una solicitud a la API MutateRows.

Go

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

import (
	"bytes"
	"context"
	"encoding/binary"
	"fmt"
	"io"

	"cloud.google.com/go/bigtable"
)

func writeBatch(w io.Writer, projectID, instanceID string, tableName string) error {
	// projectID := "my-project-id"
	// instanceID := "my-instance-id"
	// tableName := "mobile-time-series"

	ctx := context.Background()
	client, err := bigtable.NewClient(ctx, projectID, instanceID)
	if err != nil {
		return fmt.Errorf("bigtable.NewAdminClient: %w", err)
	}
	defer client.Close()
	tbl := client.Open(tableName)
	columnFamilyName := "stats_summary"
	timestamp := bigtable.Now()

	var muts []*bigtable.Mutation

	binary1 := new(bytes.Buffer)
	binary.Write(binary1, binary.BigEndian, int64(1))

	mut := bigtable.NewMutation()
	mut.Set(columnFamilyName, "connected_wifi", timestamp, binary1.Bytes())
	mut.Set(columnFamilyName, "os_build", timestamp, []byte("12155.0.0-rc1"))
	muts = append(muts, mut)

	mut = bigtable.NewMutation()
	mut.Set(columnFamilyName, "connected_wifi", timestamp, binary1.Bytes())
	mut.Set(columnFamilyName, "os_build", timestamp, []byte("12145.0.0-rc6"))
	muts = append(muts, mut)

	rowKeys := []string{"tablet#a0b81f74#20190501", "tablet#a0b81f74#20190502"}
	if _, err := tbl.ApplyBulk(ctx, rowKeys, muts); err != nil {
		return fmt.Errorf("ApplyBulk: %w", err)
	}

	fmt.Fprintf(w, "Successfully wrote 2 rows: %s\n", rowKeys)
	return nil
}

HBase

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.


import com.google.cloud.bigtable.hbase.BigtableConfiguration;
import java.util.ArrayList;
import java.util.List;
import org.apache.hadoop.hbase.TableName;
import org.apache.hadoop.hbase.client.Connection;
import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.client.Table;
import org.apache.hadoop.hbase.util.Bytes;

public class WriteBatch {

  private static final byte[] COLUMN_FAMILY_NAME = Bytes.toBytes("stats_summary");

  public static void writeBatch(String projectId, String instanceId, String tableId) {
    // String projectId = "my-project-id";
    // String instanceId = "my-instance-id";
    // String tableId = "mobile-time-series";

    try (Connection connection = BigtableConfiguration.connect(projectId, instanceId)) {
      final Table table = connection.getTable(TableName.valueOf(Bytes.toBytes(tableId)));
      long timestamp = System.currentTimeMillis();
      byte[] one = new byte[]{0, 0, 0, 0, 0, 0, 0, 1};

      List<Put> puts = new ArrayList<Put>();
      puts.add(new Put(Bytes.toBytes("tablet#a0b81f74#20190501")));
      puts.add(new Put(Bytes.toBytes("tablet#a0b81f74#20190502")));

      puts.get(0).addColumn(COLUMN_FAMILY_NAME, Bytes.toBytes("connected_wifi"), timestamp, one);
      puts.get(0)
          .addColumn(
              COLUMN_FAMILY_NAME,
              Bytes.toBytes("os_build"),
              timestamp,
              Bytes.toBytes("12155.0.0-rc1"));

      puts.get(1).addColumn(COLUMN_FAMILY_NAME, Bytes.toBytes("connected_wifi"), timestamp, one);
      puts.get(1)
          .addColumn(
              COLUMN_FAMILY_NAME,
              Bytes.toBytes("os_build"),
              timestamp,
              Bytes.toBytes("12145.0.0-rc6"));

      table.put(puts);

      System.out.print("Successfully wrote 2 rows");
    } catch (Exception e) {
      System.out.println("Error during WriteBatch: \n" + e.toString());
    }
  }
}

Java

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.


import com.google.api.core.ApiFuture;
import com.google.api.gax.batching.Batcher;
import com.google.api.gax.batching.BatchingException;
import com.google.cloud.bigtable.data.v2.BigtableDataClient;
import com.google.cloud.bigtable.data.v2.models.RowMutationEntry;
import com.google.cloud.bigtable.data.v2.models.TableId;
import com.google.protobuf.ByteString;
import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.ExecutionException;

public class WriteBatch {
  private static final String COLUMN_FAMILY_NAME = "stats_summary";

  public static void writeBatch(String projectId, String instanceId, String tableId) {
    // String projectId = "my-project-id";
    // String instanceId = "my-instance-id";
    // String tableId = "mobile-time-series";

    try (BigtableDataClient dataClient = BigtableDataClient.create(projectId, instanceId)) {
      List<ApiFuture<Void>> batchFutures = new ArrayList<>();
      try (Batcher<RowMutationEntry, Void> batcher =
          dataClient.newBulkMutationBatcher(TableId.of(tableId))) {
        long timestamp = System.currentTimeMillis() * 1000;
        batchFutures.add(
            batcher.add(
                RowMutationEntry.create("tablet#a0b81f74#20190501")
                    .setCell(
                        COLUMN_FAMILY_NAME, ByteString.copyFromUtf8("connected_wifi"), timestamp, 1)
                    .setCell(COLUMN_FAMILY_NAME, "os_build", timestamp, "12155.0.0-rc1")));
        batchFutures.add(
            batcher.add(
                RowMutationEntry.create("tablet#a0b81f74#20190502")
                    .setCell(
                        COLUMN_FAMILY_NAME, ByteString.copyFromUtf8("connected_wifi"), timestamp, 1)
                    .setCell(COLUMN_FAMILY_NAME, "os_build", timestamp, "12155.0.0-rc6")));

        // Blocks until mutations are applied on all submitted row entries.
        // flush will be called automatically when a batch is full.
        batcher.flush();
        // Before batcher is closed, all remaining (if any) mutations are applied.
      } catch (BatchingException batchingException) {
        System.out.println(
            "At least one entry failed to apply. Summary of the errors: \n" + batchingException);
        // get individual entry error details
        for (ApiFuture<Void> future : batchFutures) {
          try {
            future.get();
          } catch (ExecutionException entryException) {
            System.out.println("Entry failure: " + entryException.getCause());
          } catch (InterruptedException e) {
            // handle interrupted exception
          }
        }
      }
      System.out.println("Successfully wrote 2 rows");
    } catch (Exception e) {
      System.out.println("Error during WriteBatch: \n" + e);
    }
  }
}

Python asyncio

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

from google.cloud.bigtable.data import BigtableDataClientAsync
from google.cloud.bigtable.data.mutations import SetCell
from google.cloud.bigtable.data.mutations import RowMutationEntry
from google.cloud.bigtable.data.exceptions import MutationsExceptionGroup

async def write_batch(project_id, instance_id, table_id):
    async with BigtableDataClientAsync(project=project_id) as client:
        async with client.get_table(instance_id, table_id) as table:
            family_id = "stats_summary"
            try:
                async with table.mutations_batcher() as batcher:
                    mutation_list = [
                        SetCell(family_id, "connected_cell", 1),
                        SetCell(family_id, "connected_wifi", 1),
                        SetCell(family_id, "os_build", "12155.0.0-rc1"),
                    ]
                    # awaiting the batcher.append method adds the RowMutationEntry
                    # to the batcher's queue to be written in the next flush.
                    await batcher.append(
                        RowMutationEntry("tablet#a0b81f74#20190501", mutation_list)
                    )
                    await batcher.append(
                        RowMutationEntry("tablet#a0b81f74#20190502", mutation_list)
                    )
            except MutationsExceptionGroup as e:
                # MutationsExceptionGroup contains a FailedMutationEntryError for
                # each mutation that failed.
                for sub_exception in e.exceptions:
                    failed_entry: RowMutationEntry = sub_exception.entry
                    cause: Exception = sub_exception.__cause__
                    print(
                        f"Failed mutation: {failed_entry.row_key} with error: {cause!r}"
                    )

Python

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

import datetime

from google.cloud import bigtable
from google.cloud.bigtable.batcher import MutationsBatcher


def write_batch(project_id, instance_id, table_id):
    client = bigtable.Client(project=project_id, admin=True)
    instance = client.instance(instance_id)
    table = instance.table(table_id)

    with MutationsBatcher(table=table) as batcher:
        timestamp = datetime.datetime.utcnow()
        column_family_id = "stats_summary"

        rows = [
            table.direct_row("tablet#a0b81f74#20190501"),
            table.direct_row("tablet#a0b81f74#20190502"),
        ]

        rows[0].set_cell(column_family_id, "connected_wifi", 1, timestamp)
        rows[0].set_cell(column_family_id, "os_build", "12155.0.0-rc1", timestamp)
        rows[1].set_cell(column_family_id, "connected_wifi", 1, timestamp)
        rows[1].set_cell(column_family_id, "os_build", "12145.0.0-rc6", timestamp)

        batcher.mutate_rows(rows)

    print("Successfully wrote 2 rows.")

C#

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.


using System;
using Google.Cloud.Bigtable.V2;
using Google.Cloud.Bigtable.Common.V2;

namespace Writes
{
    public class WriteBatchSample
    {
        /// <summary>
        /// Mutate multiple rows in an existing table and column family. Updates multiple cells within each row.
        ///</summary>
        /// <param name="projectId">Your Google Cloud Project ID.</param>
        /// <param name="instanceId">Your Google Cloud Bigtable Instance ID.</param>
        /// <param name="tableId">Your Google Cloud Bigtable table ID.</param>
        public string WriteBatch(
            string projectId = "YOUR-PROJECT-ID",
            string instanceId = "YOUR-INSTANCE-ID",
            string tableId = "YOUR-TABLE-ID")
        {
            BigtableClient bigtableClient = BigtableClient.Create();

            TableName tableName = new TableName(projectId, instanceId, tableId);
            BigtableVersion timestamp = new BigtableVersion(DateTime.UtcNow);
            string COLUMN_FAMILY = "stats_summary";

            MutateRowsRequest.Types.Entry mutations1 = Mutations.CreateEntry(new BigtableByteString("tablet#a0b81f74#20190501"),
                Mutations.SetCell(COLUMN_FAMILY, "connected_cell", 1, timestamp),
                Mutations.SetCell(COLUMN_FAMILY, "os_build", "12155.0.0-rc1", timestamp)
            );
            MutateRowsRequest.Types.Entry mutations2 = Mutations.CreateEntry(new BigtableByteString("tablet#a0b81f74#20190502"),
                Mutations.SetCell(COLUMN_FAMILY, "connected_cell", 1, timestamp),
                Mutations.SetCell(COLUMN_FAMILY, "os_build", "12145.0.0-rc6", timestamp)
            );
            MutateRowsRequest.Types.Entry[] entries = {
                    mutations1,
                    mutations2
                };
            MutateRowsResponse mutateRowResponse = bigtableClient.MutateRows(tableName, entries);
            foreach (MutateRowsResponse.Types.Entry entry in mutateRowResponse.Entries)
            {
                if (entry.Status.Code == 0)
                {
                    Console.WriteLine($"Row {entry.Index} written successfully");
                }
                else
                {
                    Console.WriteLine($"\tFailed to write row {entry.Index}");
                    Console.WriteLine(entry.Status.Message);
                    return entry.Status.Message;
                }
            }
            return "Successfully wrote 2 rows";
        }
    }
}

C++

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

namespace cbt = ::google::cloud::bigtable;
[](cbt::Table table) {
  auto timestamp = std::chrono::duration_cast<std::chrono::milliseconds>(
      std::chrono::system_clock::now().time_since_epoch());
  std::string column_family = "stats_summary";

  cbt::BulkMutation bulk;
  bulk.emplace_back(cbt::SingleRowMutation(
      "tablet#a0b81f74#20190501",
      cbt::SetCell(column_family, "connected_cell", timestamp,
                   std::int64_t{1}),
      cbt::SetCell(column_family, "os_build", timestamp, "12155.0.0-rc1")));
  bulk.emplace_back(cbt::SingleRowMutation(
      "tablet#a0b81f74#20190502",
      cbt::SetCell(column_family, "connected_cell", timestamp,
                   std::int64_t{1}),
      cbt::SetCell(column_family, "os_build", timestamp, "12145.0.0-rc6")));

  std::vector<cbt::FailedMutation> failures =
      table.BulkApply(std::move(bulk));
  if (failures.empty()) {
    std::cout << "Successfully wrote 2 rows.\n";
    return;
  }
  std::cerr << "The following mutations failed:\n";
  for (auto const& f : failures) {
    std::cerr << "rowkey[" << f.original_index() << "]=" << f.status()
              << "\n";
  }
}

Node.js

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

/**
 * TODO(developer): Uncomment these variables before running the sample.
 */
// const instanceId = 'YOUR_INSTANCE_ID';
// const tableId = 'YOUR_TABLE_ID';

const {Bigtable} = require('@google-cloud/bigtable');

const bigtable = new Bigtable();

async function writeBatch() {
  const instance = bigtable.instance(instanceId);
  const table = instance.table(tableId);

  const timestamp = new Date();
  const rowsToInsert = [
    {
      key: 'tablet#a0b81f74#20190501',
      data: {
        stats_summary: {
          connected_wifi: {
            value: 1,
            timestamp,
          },
          os_build: {
            value: '12155.0.0-rc1',
            timestamp,
          },
        },
      },
    },
    {
      key: 'tablet#a0b81f74#20190502',
      data: {
        stats_summary: {
          connected_wifi: {
            value: 1,
            timestamp,
          },
          os_build: {
            value: '12145.0.0-rc6',
            timestamp,
          },
        },
      },
    },
  ];

  await table.insert(rowsToInsert);

  console.log(
    `Successfully wrote 2 rows: ${rowsToInsert[0].key} and ${rowsToInsert[1].key}`,
  );
}

writeBatch();

PHP

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

use Google\Cloud\Bigtable\BigtableClient;
use Google\Cloud\Bigtable\Mutations;

/**
 * Write data in batches in a table
 *
 * @param string $projectId The Google Cloud project ID
 * @param string $instanceId The ID of the Bigtable instance
 * @param string $tableId The ID of the table where the batch data needs to be written
 */
function write_batch(
    string $projectId,
    string $instanceId,
    string $tableId = 'mobile-time-series'
): void {
    // Connect to an existing table with an existing instance.
    $dataClient = new BigtableClient([
        'projectId' => $projectId,
    ]);
    $table = $dataClient->table($instanceId, $tableId);

    $timestampMicros = time() * 1000 * 1000;
    $columnFamilyId = 'stats_summary';
    $mutations = [
        (new Mutations())
            ->upsert($columnFamilyId, 'connected_wifi', '1', $timestampMicros)
            ->upsert($columnFamilyId, 'os_build', '12155.0.0-rc1', $timestampMicros),
        (new Mutations())
            ->upsert($columnFamilyId, 'connected_wifi', '1', $timestampMicros)
            ->upsert($columnFamilyId, 'os_build', '12145.0.0-rc6', $timestampMicros)];

    $table->mutateRows([
        'tablet#a0b81f74#20190501' => $mutations[0],
        'tablet#a0b81f74#20190502' => $mutations[1]
    ]);

    printf('Successfully wrote 2 rows.' . PHP_EOL);
}

Ruby

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

# instance_id = "my-instance"
# table_id    = "my-table"
table = bigtable.table instance_id, table_id
column_family = "stats_summary"
timestamp = (Time.now.to_f * 1_000_000).round(-3)

entries = []
entries << table.new_mutation_entry("tablet#a0b81f74#20190501")
                .set_cell(column_family, "connected_cell", 1, timestamp: timestamp)
                .set_cell(column_family, "os_build", "12155.0.0-rc1", timestamp: timestamp)
entries << table.new_mutation_entry("tablet#a0b81f74#20190502")
                .set_cell(column_family, "connected_cell", 1, timestamp: timestamp)
                .set_cell(column_family, "os_build", "12155.0.0-rc6", timestamp: timestamp)

results = table.mutate_rows entries
puts "Successfully wrote #{results.length} rows"

Habilitar el control de flujo de escritura por lotes

En los siguientes fragmentos de código se muestra cómo habilitar el control de flujo de escritura por lotes cuando envías escrituras por lotes a Bigtable. Esta función está disponible en el conector Bigtable Beam (BigtableIO) y en el conector Bigtable HBase Beam (CloudBigtableIO). Para ver el ejemplo completo, incluidos los comandos de importación, haz clic en y, a continuación, en Ver en GitHub.

BigtableIO

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

mutations.apply(
    String.format("Write data to table %s via BigtableIO", options.getBigtableTableId()),
    BigtableIO.write()
        .withProjectId(options.getProject())
        .withInstanceId(options.getBigtableInstanceId())
        .withTableId(options.getBigtableTableId())
        .withFlowControl(true) // This enables batch write flow control
);

CloudBigtableIO

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

mutations.apply(
    String.format("Write data to table %s via CloudBigtableIO", options.getBigtableTableId()),
    CloudBigtableIO.writeToTable(
        new CloudBigtableTableConfiguration.Builder()
            .withProjectId(options.getProject())
            .withInstanceId(options.getBigtableInstanceId())
            .withTableId(options.getBigtableTableId())
            .withConfiguration(
                BigtableOptionsFactory.BIGTABLE_ENABLE_BULK_MUTATION_FLOW_CONTROL, "true")
            .build()));

Escribir en una vista autorizada

En el siguiente ejemplo se muestra cómo enviar una solicitud de escritura a una vista autorizada. La sintaxis es similar a la de la escritura en una tabla, pero también debes proporcionar el ID de la vista autorizada.

Java

Para saber cómo instalar y usar la biblioteca de cliente de Bigtable, consulta el artículo Bibliotecas de cliente de Bigtable.

try {
  System.out.println("\nWriting to authorized view");
  String[] names = {"World", "Bigtable", "Java"};
  for (int i = 0; i < names.length; i++) {
    String greeting = "Hello " + names[i] + "!";
    RowMutation rowMutation =
        RowMutation.create(AuthorizedViewId.of(tableId, authorizedViewId), ROW_KEY_PREFIX + i)
            .setCell(COLUMN_FAMILY, COLUMN_QUALIFIER_NAME, names[i])
            .setCell(COLUMN_FAMILY, COLUMN_QUALIFIER_GREETING, greeting);
    dataClient.mutateRow(rowMutation);
    System.out.println(greeting);
  }
} catch (Exception e) {
  if (e instanceof NotFoundException) {
    System.err.println("Failed to write to non-existent authorized view: " + e.getMessage());
  } else if (e instanceof PermissionDeniedException) {
    System.err.println(
        "Failed to apply mutations outside of the authorized view: " + e.getMessage());
  }
}

Escribir ejemplos

Hacer una operación de escritura sencilla

Go

HBase

Java

Python asyncio

Python

C#

C++

Node.js

PHP

Ruby

Incrementar un valor

cbt

Go

Java

Escribir un valor de forma condicional

Go

HBase

Java

Python asyncio

Python

C#

C++

Node.js

PHP

Ruby

Hacer operaciones de escritura por lotes

Go

HBase

Java

Python asyncio

Python

C#

C++

Node.js

PHP

Ruby

Habilitar el control de flujo de escritura por lotes

BigtableIO

CloudBigtableIO

Escribir en una vista autorizada

Java

Siguientes pasos