Cloud Bigtable Client Libraries

This page shows how to get started with the Cloud Client Libraries for the Cloud Bigtable API. Read more about the client libraries for Cloud APIs in Client Libraries Explained.

Installing the client library


See the GitHub README for details about this client library's requirements and install dependencies.


For more information, see Setting Up a C# Development Environment.
Install-Package Google.Cloud.Bigtable.V2 -Pre
Install-Package Google.Cloud.Bigtable.Admin.V2 -Pre


go get -u


For more information, see Setting Up a Java Development Environment. Maven을 사용하는 경우 pom.xml 파일에 다음을 추가합니다.

Gradle을 사용하는 경우 종속 항목에 다음을 추가합니다.
compile ''
SBT를 사용하는 경우 종속 항목에 다음을 추가합니다.
libraryDependencies += "" % "google-cloud-bigtable" % "1.5.0"


The Cloud Bigtable HBase client for Java includes the following Maven artifacts that you can use in your project. All of the artifacts are based on HBase 1.x:

The Cloud Bigtable Maven artifacts include the netty-tcnative-boringssl-static library, which requires that you use Linux, macOS, or Windows on an x86 64-bit processor.

If your application runs in the App Engine standard environment, you must use a current version of the Java runtime. The Java 7 runtime is deprecated and does not support the HBase client for Java.

The following examples assume that you are using the bigtable-hbase-1.x artifact.

Maven을 사용하는 경우 pom.xml 파일에 다음을 추가합니다.
Gradle을 사용하는 경우 종속 항목에 다음을 추가합니다.
compile ''
SBT를 사용하는 경우 종속 항목에 다음을 추가합니다.
libraryDependencies += "" % "bigtable-hbase-1.x" % "1.11.0"


For more information, see Setting Up a Node.js Development Environment.
npm install --save @google-cloud/bigtable


Install and enable the gRPC extension for PHP, then run the following command:
composer require google/cloud-bigtable


For more information, see Setting Up a Python Development Environment.
pip install --upgrade google-cloud-bigtable


For more information, see Setting Up a Ruby Development Environment.
gem install google-cloud-bigtable

Setting up authentication

To run the client library, you must first set up authentication by creating a service account and setting an environment variable. Complete the following steps to set up authentication. For other ways to authenticate, see the GCP authentication documentation.

GCP Console

  1. GCP Console에서 서비스 계정 키 만들기 페이지로 이동합니다.

    서비스 계정 키 만들기 페이지로 이동
  2. 서비스 계정 목록에서 새 서비스 계정을 선택합니다.
  3. 서비스 계정 이름 필드에 이름을 입력합니다.
  4. 역할 목록에서 프로젝트 > 소유자를 선택합니다.

    참고: 역할 필드가 리소스에 액세스할 수 있도록 서비스 계정을 승인합니다. 나중에 GCP Console을 사용하여 이 필드를 보고 변경할 수 있습니다. 프로덕션 애플리케이션을 개발하는 경우 프로젝트 > 소유자보다 세부적인 권한을 지정합니다. 자세한 내용은 서비스 계정에 역할 부여를 참조하세요.
  5. 만들기를 클릭합니다. 키가 포함된 JSON 파일이 컴퓨터에 다운로드됩니다.


로컬 머신 또는 Cloud Shell에서 Cloud SDK를 사용하여 다음 명령어를 실행할 수 있습니다.

  1. 서비스 계정을 만듭니다. [NAME]을 서비스 계정 이름으로 바꿉니다.

    gcloud iam service-accounts create [NAME]
  2. 서비스 계정에 권한을 부여합니다. [PROJECT_ID]를 프로젝트 ID로 바꿉니다.

    gcloud projects add-iam-policy-binding [PROJECT_ID] --member "serviceAccount:[NAME]@[PROJECT_ID]" --role "roles/owner"
    참고: 역할 필드가 리소스에 액세스할 수 있도록 서비스 계정을 승인합니다. 이 필드는 나중에 GCP Console을 사용하여 보고 변경할 수 있습니다. 프로덕션 애플리케이션을 개발하는 경우 프로젝트 > 소유자보다 세부적인 권한을 지정합니다. 자세한 내용은 서비스 계정에 역할 부여를 참조하세요.
  3. 키 파일을 생성합니다. [FILE_NAME]을 키 파일 이름으로 바꿉니다.

    gcloud iam service-accounts keys create [FILE_NAME].json --iam-account [NAME]@[PROJECT_ID]

환경 변수 GOOGLE_APPLICATION_CREDENTIALS를 설정하여 애플리케이션 코드에 사용자 인증 정보를 제공합니다. [PATH]를 서비스 계정 키가 포함된 JSON 파일의 파일 경로로 바꾸고 [FILE_NAME]을 파일 이름으로 바꿉니다. 이 변수는 현재 셸 세션에만 적용되므로 새 세션을 연 경우 변수를 다시 설정합니다.

Linux 또는 macOS



export GOOGLE_APPLICATION_CREDENTIALS="/home/user/Downloads/[FILE_NAME].json"






명령 프롬프트:


Using the client library

The following example shows how to use the client library. The example connects to a Cloud Bigtable instance and reads a row from a table.

If you haven't stored any data in Cloud Bigtable yet, you can use the cbt command-line tool to create a table and add some data. See the quickstart using cbt for instructions.


#include "google/cloud/bigtable/table.h"

int main(int argc, char* argv[]) try {
  if (argc != 4) {
    std::string const cmd = argv[0];
    auto last_slash = std::string(cmd).find_last_of('/');
    std::cerr << "Usage: " << cmd.substr(last_slash + 1)
              << " <project_id> <instance_id> <table_id>\n";
    return 1;

  std::string const project_id = argv[1];
  std::string const instance_id = argv[2];
  std::string const table_id = argv[3];

  // Create a namespace alias to make the code easier to read.
  namespace cbt = google::cloud::bigtable;

  cbt::Table table(cbt::CreateDefaultDataClient(project_id, instance_id,

  std::string row_key = "r1";
  std::string column_family = "cf1";

  std::cout << "Getting a single row by row key:" << std::flush;
  google::cloud::StatusOr<std::pair<bool, cbt::Row>> result =
      table.ReadRow(row_key, cbt::Filter::FamilyRegex(column_family));
  if (!result) {
    throw std::runtime_error(result.status().message());
  if (!result->first) {
    std::cout << "Cannot find row " << row_key << " in the table: " << table_id
              << "\n";
    return 0;

  cbt::Cell const& cell = result->second.cells().front();
  std::cout << cell.family_name() << ":" << cell.column_qualifier() << "    @ "
            << cell.timestamp().count() << "us\n"
            << '"' << cell.value() << '"' << "\n";

  return 0;
} catch (std::exception const& ex) {
  std::cerr << "Standard C++ exception raised: " << ex.what() << "\n";
  return 1;


using System;
using Google.Cloud.Bigtable.Common.V2;
// Imports the Google Cloud client library
using Google.Cloud.Bigtable.V2;

namespace GoogleCloudSamples.Bigtable
    public class QuickStart
        public static int Main(string[] args)
            // Your Google Cloud Platform project ID
            const string projectId = "YOUR-PROJECT-ID";
            // The name of the Cloud Bigtable instance
            const string instanceId = "YOUR-INSTANCE-ID";
            // The name of the Cloud Bigtable table
            const string tableId = "my-table";

                // Creates a Bigtable client
                BigtableClient bigtableClient = BigtableClient.Create();

                // Read a row from my-table using a row key
                Row row = bigtableClient.ReadRow(
                    new TableName(projectId, instanceId, tableId), "r1", RowFilters.CellsPerRowLimit(1));
                // Print the row key and data (column value, labels, timestamp)
                Console.WriteLine($"{"Row key:",-30}{row.Key.ToStringUtf8()}\n" +
                                  $"{"  Column Family:",-30}{row.Families[0].Name}\n" +
                                  $"{"    Column Qualifyer:",-30}{row.Families[0].Columns[0].Qualifier.ToStringUtf8()}\n" +
                                  $"{"      Value:",-30}{row.Families[0].Columns[0].Cells[0].Value.ToStringUtf8()}\n" +
                                  $"{"      Labels:",-30}{row.Families[0].Columns[0].Cells[0].Labels}\n" +
                                  $"{"      Timestamp:",-30}{row.Families[0].Columns[0].Cells[0].TimestampMicros}\n");
            catch (Exception ex)
                // Handle error performing the read operation
                Console.WriteLine($"Error reading row r1: {ex.Message}");
            return 0;


// Quickstart is a sample program demonstrating use of the Cloud Bigtable client
// library to read a row from an existing table.
package main

import (


func main() {
	projectID := "my-project-id"   // The Google Cloud Platform project ID
	instanceID := "my-instance-id" // The Google Cloud Bigtable instance ID
	tableID := "my-table"          // The Google Cloud Bigtable table

	ctx := context.Background()

	// Set up Bigtable data operations client.
	client, err := bigtable.NewClient(ctx, projectID, instanceID)
	if err != nil {
		log.Fatalf("Could not create data operations client: %v", err)

	tbl := client.Open(tableID)

	// Read data in a row using a row key
	rowKey := "r1"
	columnFamilyName := "cf1"

	log.Printf("Getting a single row by row key:")
	row, err := tbl.ReadRow(ctx, rowKey)
	if err != nil {
		log.Fatalf("Could not read row with key %s: %v", rowKey, err)
	log.Printf("Row key: %s\n", rowKey)
	log.Printf("Data: %s\n", string(row[columnFamilyName][0].Value))

	if err = client.Close(); err != nil {
		log.Fatalf("Could not close data operations client: %v", err)



public class Quickstart {

  public static void quickstart(String projectId, String instanceId, String tableId) {
    // String projectId = "my-project-id";
    // String instanceId = "my-instance-id";
    // String tableId = "my-table-id";

    BigtableDataSettings settings =

    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (BigtableDataClient dataClient = BigtableDataClient.create(settings)) {
      System.out.println("\nReading a single row by row key");
      Row row = dataClient.readRow(tableId, "r1");
      System.out.println("Row: " + row.getKey().toStringUtf8());
      for (RowCell cell : row.getCells()) {
            "Family: %s    Qualifier: %s    Value: %s%n",
            cell.getFamily(), cell.getQualifier().toStringUtf8(), cell.getValue().toStringUtf8());
    } catch (NotFoundException e) {
      System.err.println("Failed to read from a non-existent table: " + e.getMessage());
    } catch (Exception e) {
      System.out.println("Error during quickstart: \n" + e.toString());


Read more in the API Reference Documentation for the Cloud Bigtable HBase Client for Java.



import org.apache.hadoop.hbase.TableName;
import org.apache.hadoop.hbase.client.Connection;
import org.apache.hadoop.hbase.client.Get;
import org.apache.hadoop.hbase.client.Result;
import org.apache.hadoop.hbase.client.Table;
import org.apache.hadoop.hbase.util.Bytes;

 * A quickstart application that shows connecting to a Cloud Bigtable instance
 * using the native HBase API to read a row from a table.
public class Quickstart {

  public static void main(String... args) {

    String projectId = args[0];  // my-gcp-project-id
    String instanceId = args[1]; // my-bigtable-instance-id
    String tableId = args[2];    // my-bigtable-table-id

    // Create a connection to the Cloud Bigtable instance.
    // Use try-with-resources to make sure the connection is closed correctly
    try (Connection connection = BigtableConfiguration.connect(projectId, instanceId)) {

      System.out.println("--- Connection established with Bigtable Instance ---");
      // Create a connection to the table that already exists
      // Use try-with-resources to make sure the connection to the table is closed correctly
      try (Table table = connection.getTable(TableName.valueOf(tableId))) {

        // Read a row
        String rowKey = "r1";
        System.out.printf("--- Reading for row-key: %s for provided table: %s ---\n",
            rowKey, tableId);

        // Retrieve the result
        Result result = table.get(new Get(Bytes.toBytes(rowKey)));

        // Convert row data to string
        String rowValue = Bytes.toString(result.value());

        System.out.printf("Scanned value for Row r1: %s \n", rowValue);

        System.out.println(" --- Finished reading row --- ");

      }  catch (IOException e) {
        // handle exception while connecting to a table
        throw e;
    } catch (IOException e) {
      System.err.println("Exception while running quickstart: " + e.getMessage());


// Imports the Google Cloud client library
const Bigtable = require('@google-cloud/bigtable');

const bigtable = Bigtable();

async function quickstart() {
  // Connect to an existing instance:my-bigtable-instance
  const instance = bigtable.instance(INSTANCE_ID);

  // Connect to an existing table:my-table
  const table = instance.table(TABLE_ID);

  // Read a row from my-table using a row key
  const [singleRow] = await table.row('r1').get();

  // Print the row key and data (column value, labels, timestamp)
  const rowData = JSON.stringify(, null, 4);
  console.log(`Row key: ${}\nData: ${rowData}`);


use Google\Cloud\Bigtable\BigtableClient;

/** Uncomment and populate these variables in your code */
// $project_id = 'The Google project ID';
// $instance_id = 'The Bigtable instance ID';
// $table_id = 'The Bigtable table ID';

// Connect to an existing table with an existing instance.
$dataClient = new BigtableClient([
    'projectId' => $project_id,
$table = $dataClient->table($instance_id, $table_id);
$key = 'r1';
// Read a row from my-table using a row key
$row = $table->readRow($key);

$column_family_id = 'cf1';
$column_id = 'c1';
// Get the Value from the Row, using the column_family_id and column_id

$value = $row[$column_family_id][$column_id][0]['value'];

printf("Row key: %s\nData: %s\n", $key, $value);


import argparse

from import bigtable

def main(project_id="project-id", instance_id="instance-id",
    # Create a Cloud Bigtable client.
    client = bigtable.Client(project=project_id)

    # Connect to an existing Cloud Bigtable instance.
    instance = client.instance(instance_id)

    # Open an existing table.
    table = instance.table(table_id)

    row_key = 'r1'
    row = table.read_row(row_key.encode('utf-8'))

    column_family_id = 'cf1'
    column_id = 'c1'.encode('utf-8')
    value = row.cells[column_family_id][column_id][0].value.decode('utf-8')

    print('Row key: {}\nData: {}'.format(row_key, value))

if __name__ == '__main__':
    parser = argparse.ArgumentParser(
    parser.add_argument('project_id', help='Your Cloud Platform project ID.')
        'instance_id', help='ID of the Cloud Bigtable instance to connect to.')
        help='Existing table used in the quickstart.',

    args = parser.parse_args()
    main(args.project_id, args.instance_id, args.table)


# Import google bigtable client lib
require "google-cloud-bigtable"

# The name of the Cloud Bigtable instance
INSTANCE_NAME = "my-bigtable-instance"

#  The name of the Cloud Bigtable table
TABLE_NAME = "my-table"

gcloud =
bigtable = gcloud.bigtable

# Get table client
table = bigtable.table(INSTANCE_NAME, TABLE_NAME)

# Read and print row
pp table.read_row("user00000001")

Additional resources

Third-party Cloud Bigtable API client libraries


The Scio client library provides a Scala API for Dataflow, which can read from and write to Cloud Bigtable. The Scio repository provides sample code for a Dataflow pipeline that uses Cloud Bigtable.