Data Catalog client libraries

This page shows how to get started with the Cloud Client Libraries for the Data Catalog API. Read more about the client libraries for Cloud APIs, including the older Google API Client Libraries, in Client Libraries Explained.

Installing the client library


For more information, see Setting Up a C# Development Environment.


For more information, see Setting Up a Go Development Environment.


For more information, see Setting Up a Java Development Environment.

If you are using Maven, add this to your pom.xml file:

    <version>insert datacatalog-library-version here</version>
If you are using Gradle, add this to your dependencies:
compile group: '', name: 'google-cloud-datacatalog', version: 'insert datacatalog-library-version here'


For more information, see Setting Up a Node.js Development Environment.

npm install --save @google-cloud/datacatalog


For more information, see Using PHP on Google Cloud.


For more information, see Setting Up a Python Development Environment.

pip install --upgrade google-cloud-datacatalog


For more information, see Setting Up a Ruby Development Environment.

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.

Cloud Console

Create a service account:

  1. In the Cloud Console, go to the Create service account page.

    Go to Create service account
  2. Select a project.
  3. In the Service account name field, enter a name. The Cloud Console fills in the Service account ID field based on this name.

    In the Service account description field, enter a description. For example, Service account for quickstart.

  4. Click Create.
  5. Click the Select a role field.

    Under Quick access, click Basic, then click Owner.

  6. Click Continue.
  7. Click Done to finish creating the service account.

    Do not close your browser window. You will use it in the next step.

Create a service account key:

  1. In the Cloud Console, click the email address for the service account that you created.
  2. Click Keys.
  3. Click Add key, then click Create new key.
  4. Click Create. A JSON key file is downloaded to your computer.
  5. Click Close.

Command line

You can run the following commands using the Cloud SDK on your local machine, or in Cloud Shell.

  1. Create the service account. Replace NAME with a name for the service account.

    gcloud iam service-accounts create NAME
  2. Grant permissions to the service account. Replace PROJECT_ID with your project ID.

    gcloud projects add-iam-policy-binding PROJECT_ID --member="" --role="roles/owner"
  3. Generate the key file. Replace FILE_NAME with a name for the key file.

    gcloud iam service-accounts keys create FILE_NAME.json

Provide authentication credentials to your application code by setting the environment variable GOOGLE_APPLICATION_CREDENTIALS. This variable only applies to your current shell session, so if you open a new session, set the variable again.

Linux or macOS


Replace KEY_PATH with the path of the JSON file that contains your service account key.

For example:

export GOOGLE_APPLICATION_CREDENTIALS="/home/user/Downloads/service-account-file.json"


For PowerShell:


Replace KEY_PATH with the path of the JSON file that contains your service account key.

For example:


For command prompt:


Replace KEY_PATH with the path of the JSON file that contains your service account key.

Using the client library

The following example shows how to use the client library.


For more information, see the Data Catalog Java API reference documentation.


public class LookupEntryBigQueryDataset {

   * Lookup the Data Catalog entry referring to a BigQuery Dataset
   * @param projectId The project ID to which the Dataset belongs, e.g. 'my-project'
   * @param datasetId The dataset ID to which the Catalog Entry refers, e.g. 'my_dataset'
  public static void lookupEntry(String projectId, String datasetId) {
    // String projectId = "my-project"
    // String datasetId = "my_dataset"

    // Get an entry by the resource name from the source Google Cloud Platform service.
    String linkedResource =
        String.format("//", projectId, datasetId);
    LookupEntryRequest request =

    // Alternatively, lookup by the SQL name of the entry would have the same result:
    // String sqlResource = String.format("bigquery.dataset.`%s`.`%s`", projectId, datasetId);
    // LookupEntryRequest request =
    // LookupEntryRequest.newBuilder().setSqlResource(sqlResource).build();

    // 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 (DataCatalogClient dataCatalogClient = DataCatalogClient.create()) {
      Entry entry = dataCatalogClient.lookupEntry(request);
      System.out.printf("Entry name: %s\n", entry.getName());
    } catch (Exception e) {
      System.out.print("Error during lookupEntryBigQueryDataset:\n" + e.toString());


For more information, see the Data Catalog Node.js API reference documentation.

// -------------------------------
// Import required modules.
// -------------------------------
const {DataCatalogClient} = require('@google-cloud/datacatalog').v1;
const datacatalog = new DataCatalogClient();

const lookup = async () => {
  // TODO(developer): Uncomment the following lines before running the sample.
  // const projectId = 'my-project'
  // const datasetId = 'my_dataset'
  const resourceName = `//${projectId}/datasets/${datasetId}`;
  const request = {linkedResource: resourceName};
  const [result] = await datacatalog.lookupEntry(request);
  return result;

const response = await lookup();


For more information, see the Data Catalog Python API reference documentation.

"""Retrieves Data Catalog entry for the given BigQuery Dataset."""
from import datacatalog_v1

datacatalog = datacatalog_v1.DataCatalogClient()

resource_name = '//{}/datasets/{}'\
    .format(project_id, dataset_id)

return datacatalog.lookup_entry(request={'linked_resource': resource_name})

Additional resources