Google Pub/Sub Source Connector for Confluent Cloud

Note

If you are installing the connector locally for Confluent Platform, see Google Pub/Sub Source Connector for Confluent Platform.

The Kafka Connect Google Pub/Sub Source connector for Confluent Cloud can obtain a snapshot of the existing data in a Google Pub/Sub database and then monitor and record all subsequent row-level changes to that data. All of the events for each table are recorded in a separate Apache Kafka® topic. The events can then be easily consumed by applications and services. Note that deleted records are not captured.

Features

The Google Pub/Sub Source connector provides the following features:

  • Topics created automatically: The connector can automatically create Kafka topics.
  • Fetches records from a Pub/Sub topic through a subscription.
  • Select configuration properties:
    • gcp.pubsub.max.retry.time=5
    • gcp.pubsub.message.max.count=10000

For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect section.

Limitations

Be sure to review the following information.

Quick Start

Use this quick start to get up and running with the Confluent Cloud Google Pub/Sub source connector. The quick start provides the basics of selecting the connector and configuring it to obtain a snapshot of the existing data in a Google Pub/Sub database and then monitoring and recording all subsequent row-level changes.

Prerequisites
  • Kafka cluster credentials. The following lists the different ways you can provide credentials.
    • Enter an existing service account resource ID.
    • Create a Confluent Cloud service account for the connector. Make sure to review the ACL entries required in the service account documentation. Some connectors have specific ACL requirements.
    • Create a Confluent Cloud API key and secret. To create a key and secret, you can use confluent api-key create or you can autogenerate the API key and secret directly in the Cloud Console when setting up the connector.

Using the Confluent Cloud Console

Step 1: Launch your Confluent Cloud cluster.

See the Quick Start for Apache Kafka using Confluent Cloud for installation instructions.

Step 2: Add a connector.

In the left navigation menu, click Data integration, and then click Connectors. If you already have connectors in your cluster, click + Add connector.

Step 3: Select your connector.

Click the Google Cloud Pub/Sub Source connector icon.

Google Cloud Pub/Sub Source Connector Icon

Step 4: Set up the connection.

Complete the following and click Continue.

Note

  • Make sure you have all your prerequisites completed.
  • An asterisk ( * ) designates a required entry.
  1. Enter a connector name.
  2. Select the way you want to provide Kafka Cluster credentials. You can either select a service account resource ID or you can enter an API key and secret (or generate these in the Cloud Console).
  3. Enter the Kafka topic name where you want data sent. The connector can create a topic automatically if no topics exist.
  4. Upload your GCP credentials JSON file.
  5. Enter your Google Pub/Sub Project, Topic, and Subscription IDs.
  6. Enter the connection details:
    • Maximum number of messages polled: 10000
    • Maximum time in seconds to retry on errors: 5
  7. Enter the number of tasks for the connector.
  8. Transforms and Predicates: See the Single Message Transforms (SMT) documentation for details.

See Configuration Properties for all property values and definitions.

Step 5: Launch the connector.

Verify the connection details by previewing the running configuration. Once you’ve validated that the properties are configured to your satisfaction, click Launch.

Tip

For information about previewing your connector output, see Connector Data Previews.

Launch the connector

Step 6: Check the connector status.

The status for the connector should go from Provisioning to Running. It may take a few minutes.

Check the connector status

Step 7: Check the Kafka topic.

After the connector is running, verify that messages are populating your Kafka topic.

For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect section.

See also

For an example that shows fully-managed Confluent Cloud connectors in action with Confluent Cloud ksqlDB, see the Cloud ETL Demo. This example also shows how to use Confluent CLI to manage your resources in Confluent Cloud.

../_images/topology.png

Using the Confluent CLI

Complete the following steps to set up and run the connector using the Confluent CLI.

Note

  • Make sure you have all your prerequisites completed.
  • The example commands use Confluent CLI version 2. For more information see, Confluent CLI v2.

Step 1: List the available connectors.

Enter the following command to list available connectors:

confluent connect plugin list

Step 2: Show the required connector configuration properties.

Enter the following command to show the required connector properties:

confluent connect plugin describe <connector-catalog-name>

For example:

confluent connect plugin describe PubSubSource

Example output:

Following are the required configs:
connector.class
name
kafka.auth.mode
kafka.api.key
kafka.api.secret
kafka.topic
gcp.pubsub.credentials.json
gcp.pubsub.project.id
gcp.pubsub.topic.id
gcp.pubsub.subscription.id
tasks.max

Step 3: Create the connector configuration file.

Create a JSON file that contains the connector configuration properties. The following example shows the required connector properties.

{
    "name" : "confluent-pubsub-source",
    "connector.class": "PubSubSource",
    "kafka.auth.mode": "KAFKA_API_KEY",
    "kafka.api.key": "<my-kafka-api-key>",
    "kafka.api.secret" : "<my-kafka-api-secret>",
    "kafka.topic" : "customers",
    "gcp.pubsub.credentials.json" : "omitted",
    "gcp.pubsub.project.id": "<gcp-project-ID>",
    "gcp.pubsub.topic.id":"<pubsub-topic-ID>",
    "gcp.pubsub.subscription.id": "<pubsub-subscription-ID>",
    "tasks.max" : "1"
}

Note the following property definitions:

  • "name": Sets a name for your new connector.
  • "connector.class": Identifies the connector plugin name.
  • "kafka.auth.mode": Identifies the connector authentication mode you want to use. There are two options: SERVICE_ACCOUNT or KAFKA_API_KEY (the default). To use an API key and secret, specify the configuration properties kafka.api.key and kafka.api.secret, as shown in the example configuration (above). To use a service account, specify the Resource ID in the property kafka.service.account.id=<service-account-resource-ID>. To list the available service account resource IDs, use the following command:

    confluent iam service-account list
    

    For example:

    confluent iam service-account list
    
       Id     | Resource ID |       Name        |    Description
    +---------+-------------+-------------------+-------------------
       123456 | sa-l1r23m   | sa-1              | Service account 1
       789101 | sa-l4d56p   | sa-2              | Service account 2
    
  • "gcp.pubsub.credentials.json": This contains the contents of the downloaded JSON file. See Formatting credentials for details about how to format and use the contents of the downloaded credentials file.

Single Message Transforms: See the Single Message Transforms (SMT) documentation for details about adding SMTs using the CLI.

See Configuration Properties for all property values and definitions.

Formatting credentials

The contents of the downloaded credentials file must be converted to string format before it can be used in the connector configuration.

  1. Convert the JSON file contents into string format. You can use an online converter tool to do this. For example: JSON to String Online Converter.

  2. Add an escape character (\) before all \n entries in the Private Key section so that each section begins with \\n (see the highlighted lines below). The example below has been formatted so that the \\n entries are easier to see. Most of the credentials key has been omitted.

    Tip

    A script is available that converts the credentials to a string and also adds the additional \ escape character where needed. See Stringify GCP Credentials.

      {
          "name" : "confluent-pubsub-source",
          "connector.class" : "PubSubSource",
          "kafka.api.key" : "<my-kafka-api-keyk>",
          "kafka.api.secret" : "<my-kafka-api-secret>",
          "gcp.pubsub.credentials.json" : "{\"type\":\"service_account\",\"project_id\":\"connect-
          1234567\",\"private_key_id\":\"omitted\",
          \"private_key\":\"-----BEGIN PRIVATE KEY-----
          \\nMIIEvAIBADANBgkqhkiG9w0BA
          \\n6MhBA9TIXB4dPiYYNOYwbfy0Lki8zGn7T6wovGS5pzsIh
          \\nOAQ8oRolFp\rdwc2cC5wyZ2+E+bhwn
          \\nPdCTW+oZoodY\\nOGB18cCKn5mJRzpiYsb5eGv2fN\/J
          \\n...rest of key omitted...
          \\n-----END PRIVATE KEY-----\\n\",
          \"client_email\":\"pub-sub@connect-123456789.iam.gserviceaccount.com\",
          \"client_id\":\"123456789\",\"auth_uri\":\"https:\/\/accounts.google.com\/o\/oauth2\/
          auth\",\"token_uri\":\"https:\/\/oauth2.googleapis.com\/
          token\",\"auth_provider_x509_cert_url\":\"https:\/\/
          www.googleapis.com\/oauth2\/v1\/
          certs\",\"client_x509_cert_url\":\"https:\/\/www.googleapis.com\/
          robot\/v1\/metadata\/x509\/pub-sub%40connect-
          123456789.iam.gserviceaccount.com\"}",
          "gcp.pubsub.project.id": "<gcp-project-ID>",
          "gcp.pubsub.topic.id":"<pubsub-topic-ID>",
          "gcp.pubsub.subscription.id": "<pubsub-subscription-ID>",
          "tasks.max" : "1"
      }
    
  3. Add all the converted string content to the "keyfile" credentials section of your configuration file as shown in the example above.

Step 4: Load the configuration file and create the connector.

Enter the following command to load the configuration and start the connector:

confluent connect create --config <file-name>.json

For example:

confluent connect create --config pubsub-source-config.json

Example output:

Created connector confluent-pubsub-source lcc-ix4dl

Step 5: Check the connector status.

Enter the following command to check the connector status:

confluent connect list

Example output:

ID          |       Name              | Status  | Type
+-----------+-------------------------+---------+-------+
lcc-ix4dl   | confluent-pubsub-source | RUNNING | source

Step 6: Check the Kafka topic.

After the connector is running, verify that messages are populating your Kafka topic.

For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect section.

Configuration Properties

Use the following configuration properties with this connector.

How should we connect to your data?

name

Sets a name for your connector.

  • Type: string
  • Valid Values: A string at most 64 characters long
  • Importance: high

Kafka Cluster credentials

kafka.auth.mode

Kafka Authentication mode. It can be one of KAFKA_API_KEY or SERVICE_ACCOUNT. It defaults to KAFKA_API_KEY mode.

  • Type: string
  • Default: KAFKA_API_KEY
  • Valid Values: KAFKA_API_KEY, SERVICE_ACCOUNT
  • Importance: high
kafka.api.key
  • Type: password
  • Importance: high
kafka.service.account.id

The Service Account that will be used to generate the API keys to communicate with Kafka Cluster.

  • Type: string
  • Importance: high
kafka.api.secret
  • Type: password
  • Importance: high

Which topic do you want to send data to?

kafka.topic

Identifies the topic name to write the data to.

  • Type: list
  • Importance: high

GCP credentials

gcp.pubsub.credentials.json

GCP service account JSON file with read permissions for Pub/Sub.

  • Type: password
  • Importance: high

GCP Pub/Sub details

gcp.pubsub.project.id

ID for the GCP project where the Pub/Sub is located.

  • Type: string
  • Importance: high
gcp.pubsub.topic.id

The Pub/Sub topic containing messages that have to be polled.

  • Type: string
  • Importance: high
gcp.pubsub.subscription.id

The subscription ID for the Pub/Sub topic.

  • Type: string
  • Importance: high

Connection details

gcp.pubsub.message.max.count

The maximum number of messages to be polled in a single Pub/Sub pull request.

  • Type: int
  • Default: 10000
  • Valid Values: [1000,…]
  • Importance: low
gcp.pubsub.max.retry.time

The maximum time in seconds that the Pub/Sub client will try polling records from Pub/Sub topic.

  • Type: int
  • Default: 5
  • Valid Values: [5,…]
  • Importance: low

Number of tasks for this connector

tasks.max
  • Type: int
  • Valid Values: [1,…]
  • Importance: high

Next Steps

See also

For an example that shows fully-managed Confluent Cloud connectors in action with Confluent Cloud ksqlDB, see the Cloud ETL Demo. This example also shows how to use Confluent CLI to manage your resources in Confluent Cloud.

../_images/topology.png