OpenSearch Sink Connector for Confluent Cloud

The fully-managed OpenSearch Sink connector for Confluent Cloud moves data from an Apache Kafka® topic to a specified OpenSearch index facilitating real time analysis of data in OpenSearch. The connector supports Avro, JSON Schema, JSON (schemaless), and Protobuf data output format from Apache Kafka® topics.

Note

If you require private networking for fully-managed connectors, make sure to set up the proper networking beforehand. For more information, see Manage Networking for Confluent Cloud Connectors.

Features

The OpenSearch Sink connector includes the following features:

  • Automatic index creation: The connector supports automatic creation of indexes depending on the OpenSearch configuration.

  • Multi-indexing: The connector allows you to create and manage up to 5 indexes simultaneously.

  • Input data formats: The connector supports Avro, JSON Schema, Protobuf, or JSON (schemaless) input data formats. Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro, JSON Schema, or Protobuf). For more information, see Schema Registry Enabled Environments.

  • Dual-platform OpenSearch support: The connector supports both AWS OpenSearch and OSS OpenSearch.

  • Topic-to-index mapping: The connector supports mapping a topic to a specific OpenSearch Index.

  • Flexible write operations: The connector supports both INSERT and UPSERT write methods. With UPSERT, the Kafka record key determines the operation: the connector upserts records with a non-null key and inserts records with a null key as new documents. The default method is INSERT.

  • Schema management: The connector supports Schema Registry, Schema Context and Reference Subject Naming Strategy.

  • Topic Mutating SMTs Support: The connector also supports the following SMTs:

    • org.apache.kafka.connect.transforms.TimestampRouter

    • io.confluent.connect.transforms.MessageTimestampRouter

    • io.confluent.connect.transforms.ExtractTopic

    • io.confluent.connect.cloud.transforms.TopicRegexRouter

    For details, see the Single Message Transformations (SMT) documentation.

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

Limitations

Be sure to review the following information.

Quick Start

Use this quick start to get up and running with the Confluent Cloud OpenSearch Sink connector. The quick start provides the basics of selecting the connector and configuring it to stream events to an OpenSearch deployment.

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

To create and launch a Kafka cluster in Confluent Cloud, see Create a kafka cluster in Confluent Cloud.

Step 2: Add a connector

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

Step 3: Select your connector

Click the OpenSearch Sink connector card.

OpenSearch Sink Connector Card

Step 4: Enter the connector details

Note the following:

  • Ensure you have completed all the prerequisites.

  • An asterisk ( * ) designates a required entry.

At the Add OpenSearch Sink connector screen, complete the following:

If you’ve already populated your Kafka topics, select the topics you want to connect from the Topics list.

To create a new topic, click Add a new topic. To use the default topic settings, click Create with defaults. To modify the topic settings, click Show advanced settings, update accordingly, and then click Save & Create.

  1. Select the way you want to provide Kafka Cluster credentials. You can choose one of the following options:

    • My account: This setting allows your connector to globally access everything that you have access to. With a user account, the connector uses an API key and secret to access the Kafka cluster. This option is not recommended for production.

    • Service account: This setting limits the access for your connector by using a service account. This option is recommended for production.

    • Use an existing API key: This setting allows you to specify an API key and a secret pair. You can use an existing pair or create a new one. This method is not recommended for production environments.

    Note

    Freight clusters support only service accounts for Kafka authentication.

  1. Click Continue.

  1. Enter your OpenSearch connection details:

    • OpenSearch instance URL: The OpenSearch instance URL. For example: http://your-opensearch-instance.com/.

    • Endpoint Authentication Type: The authentication type of the endpoint.

    • SSL Enabled: Set whether to connect to the endpoint using SSL.

  2. Click Continue.

Note

Configuration properties that are not shown in the Cloud Console use the default values. See Configuration Properties for all property values and definitions.

  1. Select the Input Kafka record value format (data coming from the Kafka topic): AVRO, BYTES, JSON_SR, JSON (schemaless) PROTOBUF. A valid schema must be available in Schema Registry to use a schema-based message format (for example, AVRO, JSON_SR, or PROTOBUF). For more information, see Schema Registry Enabled Environments.

  2. Enter the number of indexes to push data to in the Indexes field. Note that this value should be less than or equal to 5.

  3. Configure the number of indexes you set in the Indexes field. For instance, if you entered 2 in the Indexes field, you should see 2 index configuration sections with the following fields to set:

    • Index: The index name. This name together with the OpenSearch Instance URL forms the complete HTTP(S) URL.

    • Topic: The topic from which data will be pulled for this index.

    • Behavior for null-valued records: This property determines how the connector handles records with a non-null key and a null value (also known as Kafka tombstone records) for each index.

    • Write Method: This setting defines how the connector writes documents to an index. INSERT adds only new documents. UPSERT uses the Kafka record key to determine the operation. It upserts (updates if the key exists, inserts if it does not) records with a non-null key and inserts records with a null key as new documents. The default method is INSERT.

    Note

    When the Write Method is set to UPSERT, the Kafka record key must be a string or bytes because OpenSearch only accepts string document IDs.

    Show advanced configurations

    • Schema context: Select a schema context to use for this connector, if using a schema-based data format. This property defaults to the Default context, which configures the connector to use the default schema set up for Schema Registry in your Confluent Cloud environment. A schema context allows you to use separate schemas (like schema sub-registries) tied to topics in different Kafka clusters that share the same Schema Registry environment. For example, if you select a non-default context, a Source connector uses only that schema context to register a schema and a Sink connector uses only that schema context to read from. For more information about setting up a schema context, see What are schema contexts and when should you use them?.

    Auto-restart policy

    • Enable Connector Auto-restart: Control the auto-restart behavior of the connector and its task in the event of user-actionable errors. Defaults to true, enabling the connector to automatically restart in case of user-actionable errors. Set this property to false to disable auto-restart for failed connectors. In such cases, you would need to manually restart the connector.

    Consumer configuration

    • Max poll interval(ms): Set the maximum delay between subsequent consume requests to Kafka. Use this property to improve connector performance in cases when the connector cannot send records to the sink system. The default is 300,000 milliseconds (5 minutes).

    • Max poll records: Set the maximum number of records to consume from Kafka in a single request. Use this property to improve connector performance in cases when the connector cannot send records to the sink system. The default is 500 records.

    • Max poll interval (ms): The maximum delay between subsequent consume requests to Kafka. This configuration property can be used to improve the performance of the connector, if the connector cannot send records to the sink system. Defaults to 300000 milliseconds (5 minutes).

    • Max poll records: The maximum number of records to consume from Kafka in a single request. This configuration property can be used to improve the performance of the connector, if the connector cannot send records to the sink system. Defaults to 500 records.

    • Behavior on Errors: Behavior setting for handling error responses from HTTP requests. storage connectors. Must be configured to one of the following: IGNORE or FAIL.

    • Retry Backoff Policy: The backoff policy to use in terms of a retry. Must be configured to CONSTANT_VALUE OR EXPONENTIAL_WITH_JITTER.

    • Retry Backoff (ms): The time in milliseconds to wait following an error before the connector retries the task.

    • Retry HTTP Status Codes: The HTTP response status codes returned that prompt the connector to retry the request. Enter a comma- separated list of codes or range of codes. Ranges are specified with a start and optional end code. Range boundaries are inclusive. For example: 400- includes all codes greater than or equal to 400 and 400-500 includes codes from 400 to 500, including 500. Multiple ranges and single codes can be specified together to achieve fine-grained control over retry behavior. For example: 404,408,500- prompts the connector to retry on 404 NOT FOUND, 408 REQUEST TIMEOUT, and all 5xx error codes. Note that some status codes are always retried, such as unauthorized, timeouts, and too many requests.

    • Maximum Retries: The maximum number of times the connector retries a request when an error occurs, before the task fails.

    Transforms

  4. Click Continue.

Based on the number of topic partitions you select, you will be provided with a recommended number of tasks.

  1. To change the number of recommended tasks, enter the number of tasks for the connector to use in the Tasks field.

  2. Click Continue.

  1. Verify the connection details.

  2. Click Launch.

    The status for the connector should go from Provisioning to Running.

Step 5: Check the results in OpenSearch

Verify that new records are being added to your OpenSearch deployment.

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

Tip

When you launch a connector, a Dead Letter Queue topic is automatically created. See View Connector Dead Letter Queue Errors in Confluent Cloud for details.

Using the Confluent CLI

Complete the following steps to set up and run the connector using the Confluent CLI. Ensure you have completed all the prerequisites.

Step 1: List the available connectors

Enter the following command to list available connectors:

confluent connect plugin list

Step 2: List the connector configuration properties

Enter the following command to show the connector configuration properties:

confluent connect plugin describe <connector-plugin-name>

The command output shows the required and optional configuration properties.

Step 3: Create the connector configuration file

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

{
  "connector.class": "OpenSearchSink",
  "input.data.format": "JSON",
  "kafka.auth.mode": "KAFKA_API_KEY",
  "kafka.api.key": "<my-kafka-api-key",
  "kafka.api.secret": "<my-kafka-api-secret",
  "name": "os_sink_connectors3ss2a",
  "instance.url": "https://your-opensearch-endpoint.example",
  "topics": "inventory,orders,users",
  "request.method": "POST",
  "tasks.max": "1",
  "indexes.num": "3",
  "auth.type": "BASIC",
  "connection.user": "username",
  "connection.password": "password",
  "index1.name" : "users_index",
  "index1.topic": "users",
  "index1.write.method": "INSERT",
  "index2.name" : "inventory_index",
  "index2.topic": "inventory",
  "index2.write.method": "UPSERT",
  "index3.name" : "orders",
  "index3.topic": "orders_index",
  "index3.write.method": "INSERT"
}

Note the following property definitions:

  • "connector.class": Identifies the connector plugin name.

  • "input.data.format": Sets the input Kafka record value format (data coming from the Kafka topic). Valid entries are AVRO, JSON_SR, PROTOBUF, or JSON. You must have Confluent Cloud Schema Registry configured if using a schema-based message format (for example, Avro, JSON Schema, JSON, or Protobuf).

  • "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

  • "name": Sets a name for your new connector.

  • "instance.url": The OpenSearch instance URL. The URL you enter should look like this: http://your-opensearch-instance.com/.

  • "topics": Identifies the topic name or a comma-separated list of topic names.

  • "request.method": Enter an HTTP API Request Method. Only POST requests are supported.

  • "tasks.max": Enter the maximum number of tasks for the connector to use. More tasks might improve performance.

  • "indexes.num": The number of indexes to push data to.

  • "indexN.write.method": Sets how documents are written. Set to INSERT to add only new documents. Set to UPSERT to use the Kafka record key to determine the operation. It upserts (updates if the key exists, inserts if it does not) records with a non-null key and inserts records with a null key as new documents. When you use UPSERT method, the Kafka record key must be a string or bytes because OpenSearch accepts only string document IDs. The default is INSERT.

Single Message Transforms: For details about adding SMTs using the CLI, see the Single Message Transforms (SMT) documentation. For a list of SMTs that are not supported with this connector, see Unsupported transformations.

For all property values and definitions, see Configuration Properties.

Step 4: Load the configuration file and create the connector

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

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

For example:

confluent connect cluster create --config-file opensearch-sink-config.json

Example output:

Created connector os_sink_connectors3ss2a lcc-ix4dl

Step 5: Check the connector status

Enter the following Confluent CLI command to check the connector status:

confluent connect cluster list

Example output:

ID          |       Name                 | Status  | Type
+-----------+----------------------------+---------+------+
lcc-ix4dl   | os_sink_connectors3ss2a    | RUNNING | sink

Step 6: Check the results in OpenSearch

Verify new records are being added to the OpenSearch deployment.

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

Tip

When you launch a connector, a Dead Letter Queue topic is automatically created. See View Connector Dead Letter Queue Errors in Confluent Cloud for details.

Configuration Properties

Use the following configuration properties with the OpenSearch Sink connector.

Which topics do you want to get data from?

topics

Identifies the topic name or a comma-separated list of topic names.

  • Type: list

  • Importance: high

errors.deadletterqueue.topic.name

The name of the topic to be used as the dead letter queue (DLQ) for messages that result in an error when processed by this sink connector, or its transformations or converters. Defaults to ‘dlq-${connector}’ if not set. The DLQ topic will be created automatically if it does not exist. You can provide ${connector} in the value to use it as a placeholder for the logical cluster ID.

  • Type: string

  • Default: dlq-${connector}

  • Importance: low

reporter.result.topic.name

The name of the topic to produce records to after successfully processing a sink record. Defaults to ‘success-${connector}’ if not set. You can provide ${connector} in the value to use it as a placeholder for the logical cluster ID.

  • Type: string

  • Default: success-${connector}

  • Importance: low

reporter.error.topic.name

The name of the topic to produce records to after each unsuccessful record sink attempt. Defaults to ‘error-${connector}’ if not set. You can provide ${connector} in the value to use it as a placeholder for the logical cluster ID.

  • Type: string

  • Default: error-${connector}

  • Importance: low

Schema Config

schema.context.name

Add a schema context name. A schema context represents an independent scope in Schema Registry. It is a separate sub-schema tied to topics in different Kafka clusters that share the same Schema Registry instance. If not used, the connector uses the default schema configured for Schema Registry in your Confluent Cloud environment.

  • Type: string

  • Default: default

  • Importance: medium

Input messages

input.data.format

Sets the input Kafka record value format. Valid entries are AVRO, JSON_SR, PROTOBUF, JSON or BYTES. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO, JSON_SR, and PROTOBUF.

  • Type: string

  • Default: JSON

  • Importance: high

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

Kafka API Key. Required when kafka.auth.mode==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

Secret associated with Kafka API key. Required when kafka.auth.mode==KAFKA_API_KEY.

  • Type: password

  • Importance: high

Consumer configuration

max.poll.interval.ms

The maximum delay between subsequent consume requests to Kafka. This configuration property may be used to improve the performance of the connector, if the connector cannot send records to the sink system. Defaults to 300000 milliseconds (5 minutes).

  • Type: long

  • Default: 300000 (5 minutes)

  • Valid Values: [60000,…,1800000] for non-dedicated clusters and [60000,…] for dedicated clusters

  • Importance: low

max.poll.records

The maximum number of records to consume from Kafka in a single request. This configuration property may be used to improve the performance of the connector, if the connector cannot send records to the sink system. Defaults to 500 records.

  • Type: long

  • Default: 500

  • Valid Values: [1,…,500] for non-dedicated clusters and [1,…] for dedicated clusters

  • Importance: low

Number of tasks for this connector

tasks.max

Maximum number of tasks for the connector.

  • Type: int

  • Valid Values: [1,…]

  • Importance: high

Authentication

instance.url

The OpenSearch instance URL. For example: https://your-opensearch-instance.com/.

  • Type: string

  • Importance: high

auth.type

Authentication type of the endpoint. Valid values are NONE, BASIC.

  • Type: string

  • Default: BASIC

  • Importance: high

connection.user

The username to be used with an endpoint requiring basic authentication.

  • Type: string

  • Importance: medium

connection.password

The password to be used with an endpoint requiring basic authentication.

  • Type: password

  • Importance: medium

opensearch.ssl.enabled

Whether or not to connect to the endpoint via SSL.

  • Type: boolean

  • Default: false

  • Importance: medium

opensearch.ssl.keystorefile

The keystore that contains the client certificate and private key. Supported formats are JKS or PKCS12. File system paths are not supported.

  • Type: password

  • Default: [hidden]

  • Importance: low

opensearch.ssl.keystore.password

The store password for the key store file.

  • Type: password

  • Importance: high

opensearch.ssl.key.password

The password for the private key in the key store file.

  • Type: password

  • Importance: high

opensearch.ssl.truststorefile

The truststore that contains the server CA certificate(s). Supported formats are JKS or PKCS12. File system paths are not supported.

  • Type: password

  • Default: [hidden]

  • Importance: high

opensearch.ssl.truststore.password

The trust store password containing a server CA certificate.

  • Type: password

  • Importance: high

opensearch.ssl.protocol

The protocol to use for SSL connections

  • Type: string

  • Default: TLSv1.3

  • Importance: medium

Behavior on error

behavior.on.error

Error handling behavior setting for handling error response from HTTP requests.

  • Type: string

  • Default: FAIL

  • Importance: low

Indexes

indexes.num

The number of indexes to push data to. This value should be less than or equal to 5

  • Type: int

  • Default: 1

  • Valid Values: [1,…,5]

  • Importance: high

Retry configurations

retry.backoff.policy

The backoff policy to use in terms of retry - CONSTANT_VALUE or EXPONENTIAL_WITH_JITTER

  • Type: string

  • Default: EXPONENTIAL_WITH_JITTER

  • Importance: medium

retry.backoff.ms

The initial duration in milliseconds to wait following an error before a retry attempt is made. Subsequent backoff attempts can be a constant value or exponential with jitter (can be configured using api*.retry.backoff.policy parameter). Jitter adds randomness to the exponential backoff algorithm to prevent synchronized retries.

  • Type: int

  • Default: 3000 (3 seconds)

  • Valid Values: [100,…]

  • Importance: medium

retry.on.status.codes

Comma-separated list of HTTP status codes or range of codes to retry on. Ranges are specified with start and optional end code. Range boundaries are inclusive. For instance, 400- includes all codes greater than or equal to 400. 400-500 includes codes from 400 to 500, including 500. Multiple ranges and single codes can be specified together to achieve fine-grained control over retry behavior. For example, 404,408,500- will retry on 404 NOT FOUND, 408 REQUEST TIMEOUT, and all 5xx error codes. Note that some status codes will always be retried, such as unauthorized, timeouts and too many requests.

  • Type: string

  • Default: 400-

  • Importance: medium

max.retries

The maximum number of times to retry on errors before failing the task.

  • Type: int

  • Default: 3

  • Importance: medium

Index 1 configuration

index1.name

The index name together with the OpenSearch Instance URL will form the complete HTTP(S) URL. This path can be templated with offset information.

  • Type: string

  • Importance: high

index1.topic

Topic from where data will be pulled for this Index

  • Type: string

  • Default: “”

  • Importance: high

index1.behavior.on.null.values

How to handle records with a non-null key and a null value (i.e. Kafka tombstone records). Valid options are IGNORE, DELETE and FAIL

  • Type: string

  • Default: IGNORE

  • Importance: low

index1.batch.size

Size of the batch of records to be sent to the OpenSearch. Note that Basic and Standard Clusters may experience throughput limitations, even with a higher batch size.

  • Type: int

  • Default: 1

  • Importance: low

index1.report.only.status.code.to.success.topic

Whether to report only the status code to the success topic. If the API response payload is huge, it is recommended to set this to true, for better throughput.

  • Type: boolean

  • Default: false

  • Importance: medium

index1.write.method

The write method determines how you add data to an index. The INSERT method inserts only new documents, while the UPSERT method updates existing documents or inserts new ones if they don’t exist.

  • Type: string

  • Default: INSERT

  • Valid Values: INSERT, UPSERT

  • Importance: high

Index 2 configuration

index2.name

The index name together with the OpenSearch Instance URL will form the complete HTTP(S) URL. This path can be templated with offset information.

  • Type: string

  • Importance: high

index2.topic

Topic from where data will be pulled for this Index

  • Type: string

  • Default: “”

  • Importance: high

index2.behavior.on.null.values

How to handle records with a non-null key and a null value (i.e. Kafka tombstone records). Valid options are IGNORE, DELETE and FAIL

  • Type: string

  • Default: IGNORE

  • Importance: low

index2.batch.size

Size of the batch of records to be sent to the OpenSearch. Note that Basic and Standard Clusters may experience throughput limitations, even with a higher batch size.

  • Type: int

  • Default: 1

  • Importance: low

index2.report.only.status.code.to.success.topic

Whether to report only the status code to the success topic. If the API response payload is huge, it is recommended to set this to true, for better throughput.

  • Type: boolean

  • Default: false

  • Importance: medium

index2.write.method

The write method determines how you add data to an index. The INSERT method inserts only new documents, while the UPSERT method updates existing documents or inserts new ones if they don’t exist.

  • Type: string

  • Default: INSERT

  • Valid Values: INSERT, UPSERT

  • Importance: high

Index 3 configuration

index3.name

The index name together with the OpenSearch Instance URL will form the complete HTTP(S) URL. This path can be templated with offset information.

  • Type: string

  • Importance: high

index3.topic

Topic from where data will be pulled for this Index

  • Type: string

  • Default: “”

  • Importance: high

index3.behavior.on.null.values

How to handle records with a non-null key and a null value (i.e. Kafka tombstone records). Valid options are IGNORE, DELETE and FAIL

  • Type: string

  • Default: IGNORE

  • Importance: low

index3.batch.size

Size of the batch of records to be sent to the OpenSearch. Note that Basic and Standard Clusters may experience throughput limitations, even with a higher batch size.

  • Type: int

  • Default: 1

  • Importance: low

index3.report.only.status.code.to.success.topic

Whether to report only the status code to the success topic. If the API response payload is huge, it is recommended to set this to true, for better throughput.

  • Type: boolean

  • Default: false

  • Importance: medium

index3.write.method

The write method determines how you add data to an index. The INSERT method inserts only new documents, while the UPSERT method updates existing documents or inserts new ones if they don’t exist.

  • Type: string

  • Default: INSERT

  • Valid Values: INSERT, UPSERT

  • Importance: high

Index 4 configuration

index4.name

The index name together with the OpenSearch Instance URL will form the complete HTTP(S) URL. This path can be templated with offset information.

  • Type: string

  • Importance: high

index4.topic

Topic from where data will be pulled for this Index

  • Type: string

  • Default: “”

  • Importance: high

index4.behavior.on.null.values

How to handle records with a non-null key and a null value (i.e. Kafka tombstone records). Valid options are IGNORE, DELETE and FAIL

  • Type: string

  • Default: IGNORE

  • Importance: low

index4.batch.size

Size of the batch of records to be sent to the OpenSearch. Note that Basic and Standard Clusters may experience throughput limitations, even with a higher batch size.

  • Type: int

  • Default: 1

  • Importance: low

index4.report.only.status.code.to.success.topic

Whether to report only the status code to the success topic. If the API response payload is huge, it is recommended to set this to true, for better throughput.

  • Type: boolean

  • Default: false

  • Importance: medium

index4.write.method

The write method determines how you add data to an index. The INSERT method inserts only new documents, while the UPSERT method updates existing documents or inserts new ones if they don’t exist.

  • Type: string

  • Default: INSERT

  • Valid Values: INSERT, UPSERT

  • Importance: high

Index 5 configuration

index5.name

The index name together with the OpenSearch Instance URL will form the complete HTTP(S) URL. This path can be templated with offset information.

  • Type: string

  • Importance: high

index5.topic

Topic from where data will be pulled for this Index

  • Type: string

  • Default: “”

  • Importance: high

index5.behavior.on.null.values

How to handle records with a non-null key and a null value (i.e. Kafka tombstone records). Valid options are IGNORE, DELETE and FAIL

  • Type: string

  • Default: IGNORE

  • Importance: low

index5.batch.size

Size of the batch of records to be sent to the OpenSearch. Note that Basic and Standard Clusters may experience throughput limitations, even with a higher batch size.

  • Type: int

  • Default: 1

  • Importance: low

index5.report.only.status.code.to.success.topic

Whether to report only the status code to the success topic. If the API response payload is huge, it is recommended to set this to true, for better throughput.

  • Type: boolean

  • Default: false

  • Importance: medium

index5.write.method

The write method determines how you add data to an index. The INSERT method inserts only new documents, while the UPSERT method updates existing documents or inserts new ones if they don’t exist.

  • Type: string

  • Default: INSERT

  • Valid Values: INSERT, UPSERT

  • Importance: high

Additional Configs

consumer.override.auto.offset.reset

Defines the behavior of the consumer when there is no committed position (which occurs when the group is first initialized) or when an offset is out of range. You can choose either to reset the position to the “earliest” offset (the default) or the “latest” offset. You can also select “none” if you would rather set the initial offset yourself and you are willing to handle out of range errors manually. More details: https://docs.confluent.io/platform/current/installation/configuration/consumer-configs.html#auto-offset-reset

  • Type: string

  • Importance: low

consumer.override.isolation.level

Controls how to read messages written transactionally. If set to read_committed, consumer.poll() will only return transactional messages which have been committed. If set to read_uncommitted (the default), consumer.poll() will return all messages, even transactional messages which have been aborted. Non-transactional messages will be returned unconditionally in either mode. More details: https://docs.confluent.io/platform/current/installation/configuration/consumer-configs.html#isolation-level

  • Type: string

  • Importance: low

header.converter

The converter class for the headers. This is used to serialize and deserialize the headers of the messages.

  • Type: string

  • Importance: low

value.converter.allow.optional.map.keys

Allow optional string map key when converting from Connect Schema to Avro Schema. Applicable for Avro Converters.

  • Type: boolean

  • Importance: low

value.converter.auto.register.schemas

Specify if the Serializer should attempt to register the Schema.

  • Type: boolean

  • Importance: low

value.converter.connect.meta.data

Allow the Connect converter to add its metadata to the output schema. Applicable for Avro Converters.

  • Type: boolean

  • Importance: low

value.converter.enhanced.avro.schema.support

Enable enhanced schema support to preserve package information and Enums. Applicable for Avro Converters.

  • Type: boolean

  • Importance: low

value.converter.enhanced.protobuf.schema.support

Enable enhanced schema support to preserve package information. Applicable for Protobuf Converters.

  • Type: boolean

  • Importance: low

value.converter.flatten.unions

Whether to flatten unions (oneofs). Applicable for Protobuf Converters.

  • Type: boolean

  • Importance: low

value.converter.generate.index.for.unions

Whether to generate an index suffix for unions. Applicable for Protobuf Converters.

  • Type: boolean

  • Importance: low

value.converter.generate.struct.for.nulls

Whether to generate a struct variable for null values. Applicable for Protobuf Converters.

  • Type: boolean

  • Importance: low

value.converter.int.for.enums

Whether to represent enums as integers. Applicable for Protobuf Converters.

  • Type: boolean

  • Importance: low

value.converter.latest.compatibility.strict

Verify latest subject version is backward compatible when use.latest.version is true.

  • Type: boolean

  • Importance: low

value.converter.object.additional.properties

Whether to allow additional properties for object schemas. Applicable for JSON_SR Converters.

  • Type: boolean

  • Importance: low

value.converter.optional.for.nullables

Whether nullable fields should be specified with an optional label. Applicable for Protobuf Converters.

  • Type: boolean

  • Importance: low

value.converter.optional.for.proto2

Whether proto2 optionals are supported. Applicable for Protobuf Converters.

  • Type: boolean

  • Importance: low

value.converter.scrub.invalid.names

Whether to scrub invalid names by replacing invalid characters with valid characters. Applicable for Avro and Protobuf Converters.

  • Type: boolean

  • Importance: low

value.converter.use.latest.version

Use latest version of schema in subject for serialization when auto.register.schemas is false.

  • Type: boolean

  • Importance: low

value.converter.use.optional.for.nonrequired

Whether to set non-required properties to be optional. Applicable for JSON_SR Converters.

  • Type: boolean

  • Importance: low

value.converter.wrapper.for.nullables

Whether nullable fields should use primitive wrapper messages. Applicable for Protobuf Converters.

  • Type: boolean

  • Importance: low

value.converter.wrapper.for.raw.primitives

Whether a wrapper message should be interpreted as a raw primitive at root level. Applicable for Protobuf Converters.

  • Type: boolean

  • Importance: low

errors.tolerance

Use this property if you would like to configure the connector’s error handling behavior. WARNING: This property should be used with CAUTION for SOURCE CONNECTORS as it may lead to dataloss. If you set this property to ‘all’, the connector will not fail on errant records, but will instead log them (and send to DLQ for Sink Connectors) and continue processing. If you set this property to ‘none’, the connector task will fail on errant records.

  • Type: string

  • Default: all

  • Importance: low

key.converter.key.subject.name.strategy

How to construct the subject name for key schema registration.

  • Type: string

  • Default: TopicNameStrategy

  • Importance: low

value.converter.decimal.format

Specify the JSON/JSON_SR serialization format for Connect DECIMAL logical type values with two allowed literals:

BASE64 to serialize DECIMAL logical types as base64 encoded binary data and

NUMERIC to serialize Connect DECIMAL logical type values in JSON/JSON_SR as a number representing the decimal value.

  • Type: string

  • Default: BASE64

  • Importance: low

value.converter.flatten.singleton.unions

Whether to flatten singleton unions. Applicable for Avro and JSON_SR Converters.

  • Type: boolean

  • Default: false

  • Importance: low

value.converter.ignore.default.for.nullables

When set to true, this property ensures that the corresponding record in Kafka is NULL, instead of showing the default column value. Applicable for AVRO,PROTOBUF and JSON_SR Converters.

  • Type: boolean

  • Default: false

  • Importance: low

value.converter.reference.subject.name.strategy

Set the subject reference name strategy for value. Valid entries are DefaultReferenceSubjectNameStrategy or QualifiedReferenceSubjectNameStrategy. Note that the subject reference name strategy can be selected only for PROTOBUF format with the default strategy being DefaultReferenceSubjectNameStrategy.

  • Type: string

  • Default: DefaultReferenceSubjectNameStrategy

  • Importance: low

value.converter.replace.null.with.default

Whether to replace fields that have a default value and that are null to the default value. When set to true, the default value is used, otherwise null is used. Applicable for JSON Converter.

  • Type: boolean

  • Default: true

  • Importance: low

value.converter.schemas.enable

Include schemas within each of the serialized values. Input messages must contain schema and payload fields and may not contain additional fields. For plain JSON data, set this to false. Applicable for JSON Converter.

  • Type: boolean

  • Default: false

  • Importance: low

value.converter.value.subject.name.strategy

Determines how to construct the subject name under which the value schema is registered with Schema Registry.

  • Type: string

  • Default: TopicNameStrategy

  • Importance: low

Auto-restart policy

auto.restart.on.user.error

Enable connector to automatically restart on user-actionable errors.

  • Type: boolean

  • Default: true

  • Importance: medium

Next Steps

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