写入示例

本文档提供了一些代码示例,演示了在使用 Cloud Bigtable 客户端库时可以发送到 Bigtable 的各种类型的写入请求。

本页中的示例使用 SetCell 更改将写入请求发送到非汇总单元格。如需有关如何向汇总单元格发送添加请求的示例,请参阅在写入时汇总数据

在试用这些示例之前,请确保您了解每种类型的写入请求的适用情形和不适用情形。

Bigtable 的 Python 客户端库提供两个 API,asyncio 和同步 API。如果您的应用是异步的,请使用 asyncio

执行简单的写入

以下代码示例演示了如何向 Bigtable 发出简单的写入请求。这类写入会发出 MutateRow API 请求。

Go

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证


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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证


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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

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#

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证


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++

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

# 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}"

递增值

以下代码示例演示了如何发送用于递增或递减汇总单元格中现有数值的写入请求。这类写入会发出 MutateRow 请求,并使用 AddToCell 更新类型。这些示例会相加,并计入预期输入类型为 Int64 的列族中的总和。

cbt

cbt addtocell TABLE_ID ROW_KEY
FAMILY_NAME:COLUMN_QUALIFER=VALUE@TIMESTAMP

替换以下内容:

  • TABLE_ID:表的永久标识符
  • ROW_KEY:行键
  • FAMILY_NAME:汇总列族的名称
  • COLUMN_QUALIFIER:列的标识符
  • VALUE:要添加到单元格的值
  • TIMESTAMP:以微秒为单位的 Unix 时间戳,例如 1710868850000000

以下示例会将 device-1 行中 week12 列中存储的值递减 100:

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

Go

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证


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());
    }
  }
}

有条件地写入值

以下代码示例演示了如何发送条件写入请求,该请求检查某行是否符合条件,然后根据结果向该行写入数据。这类写入会发出 CheckAndMutateRow API 请求。

Go

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证


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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证


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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

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#

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证


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++

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

/**
 * 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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

# 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}"

执行批量写入

以下代码示例演示了如何向 Bigtable 发出批量写入请求。这类写入会发出 MutateRows API 请求。

Go

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证


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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证


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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

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#

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证


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++

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

/**
 * 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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

# 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"

启用批量写入流控制

以下代码段演示了如何在向 Bigtable 发送批量写入时启用批量写入流控制。此功能适用于 Bigtable Beam 连接器 (BigtableIO)Bigtable HBase Beam 连接器 (CloudBigtableIO)。如需查看整个示例(包括导入语句),请点击 ,然后点击在 GitHub 上查看

BigtableIO

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

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

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

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()));

写入已获授权的视图

以下示例展示了如何向已获授权的视图发送写入请求。语法与写入表格类似,但您还必须提供已获授权的视图 ID。

Java

如需了解如何安装和使用 Bigtable 的客户端库,请参阅 Bigtable 客户端库

如需向 Bigtable 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

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());
  }
}

后续步骤