本頁面由 Cloud Translation API 翻譯而成。

寫入樣本

本文提供程式碼範例，說明使用 Cloud Bigtable 用戶端程式庫時，可以傳送至 Bigtable 的各種類型寫入要求。

本頁面的範例會使用 SetCell 突變，將寫入要求傳送至非匯總儲存格。如需如何傳送新增要求來匯總儲存格的範例，請參閱「在寫入時匯總資料」。

嘗試這些範例之前，請確定您已經瞭解何時該與不該使用每種類型寫入要求。

Bigtable 的 Python 用戶端程式庫提供兩種 API，即 asyncio 和同步 API。如果應用程式是非同步，請使用 asyncio。

本頁面的程式碼範例會參照「範例資料」中的範例資料表。

執行簡易寫入作業作業

下列程式碼範例示範如何向 Bigtable 發出簡易寫入要求。這種類型的寫入會產生 MutateRow API 要求。

Go

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。


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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。


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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

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#

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。


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++

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

# 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}"

遞增值

下列程式碼範例示範如何傳送可讓匯總儲存格中的現有數值逐步增加或減少的寫入要求。這種類型的寫入會產生 MutateRow 要求，並包含 AddToCell 異動類型。這些範例會將值加到資料欄系列中的總和，而該系列預期輸入的類型為 Int64。

cbt

cbt addtocell TABLE_ID ROW_KEY
FAMILY_NAME:COLUMN_QUALIFER=VALUE@TIMESTAMP

更改下列內容：

TABLE_ID：資料表的永久 ID
ROW_KEY：資料列索引鍵
FAMILY_NAME：匯總資料欄系列的名稱
COLUMN_QUALIFIER：資料欄的 ID
VALUE：要新增至儲存格的值
TIMESTAMP：以微秒為單位的 Unix 時間戳記，例如 1710868850000000

這個範例會將 device-1 資料列中 week12 資料欄儲存的值減少 100：

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

Go

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。


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());
    }
  }
}

條件式寫入資料值

下列程式碼範例示範如何傳送條件式寫入請求，針對特定條件檢查資料列，然後根據結果將數據寫入該資料列。這種類型的寫入會產生 CheckAndMutateRow API 要求。

Go

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。


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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。


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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

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#

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。


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++

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

/**
 * 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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

# 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}"

執行批次寫入作業

下列程式碼範例示範如何向 Bigtable 發出批次寫入要求。這種類型的寫入會產生 MutateRows API 要求。

Go

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。


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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。


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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

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#

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。


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++

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

/**
 * 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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

# 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"

啟用批次寫入流量控制

下列程式碼片段示範如何向 Bigtable 傳送批次寫入時，啟用批次寫入流程控制。這項功能適用於 Bigtable Beam 連接器 (BigtableIO) 和 Bigtable HBase Beam 連接器 (CloudBigtableIO)。如要查看完整範例 (包括匯入陳述式)，請按一下，然後按一下「在 GitHub 上查看」。

BigtableIO

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

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

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

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()));

寫入授權檢視表

以下範例說明如何將寫入要求傳送至授權檢視畫面。語法與寫入資料表類似，但您也必須提供授權檢視 ID。

Java

如要瞭解如何安裝及使用 Bigtable 的用戶端程式庫，請參閱這篇文章。

如要向 Bigtable 進行驗證，請設定應用程式預設憑證。詳情請參閱「設定用戶端程式庫的驗證機制」。

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());
  }
}

寫入樣本

執行簡易寫入作業作業

Go

HBase

Java

Python asyncio

Python

C#

C++

Node.js

PHP

Ruby

遞增值

cbt

Go

Java

條件式寫入資料值

Go

HBase

Java

Python asyncio

Python

C#

C++

Node.js

PHP

Ruby

執行批次寫入作業

Go

HBase

Java

Python asyncio

Python

C#

C++

Node.js

PHP

Ruby

啟用批次寫入流量控制

BigtableIO

CloudBigtableIO

寫入授權檢視表

Java

後續步驟