Couchbase Sink Connector for Confluent Cloud¶
The fully-managed Couchbase Sink connector for Confluent Cloud maps and persists events from Apache Kafka® topics directly to a Couchbase database collection. The connector supports AVRO, BYTES, JSON Schema, PROTOBUF, or JSON (schemaless) data from Apache Kafka® topics. The connector ingests events from Kafka topics directly into a Couchbase database, exposing the data to services for querying, enrichment, and analytics.
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 connector provides the following features:
At least once delivery: The connector guarantees that records are written at least once to Couchbase unless the record is intentionally discarded by a custom sink handler.
Database authentication: Uses password authentication.
Client-side field level encryption (CSFLE) support: The connector supports CSFLE for sensitive data. For more information about CSFLE setup, see the connector configuration.
Input data formats: The connector supports AVRO, BYTES, JSON_SR, PROTOBUF, or JSON (schemaless) input data formats. Schema Registry must be enabled to use a Schema Registry-based format (for example, AVRO, JSON_SR (JSON Schema), or PROTOBUF). For more information, see Schema Registry Enabled Environments.
Select sink behavior:
"couchbase.default.collection": Specifies the default Couchbase collection for records from Kafka topics not explicitly mapped."couchbase.topic.to.collection": Provides granular data routing by mapping specific Kafka topics to Couchbase collections."couchbase.topic.to.document.id": Enables per-topic overrides for Couchbase document ID formatting."couchbase.sink.handler": Defines how Kafka records are transformed into actions on Couchbase documents, supporting built-in and custom handlers.
For details about all property values and definitions, see Configuration Properties.
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.
- For connector limitations, see Couchbase Sink limitations.
- If you plan to use one or more Single Message Transforms (SMTs), see SMT Limitations.
- If you plan to use Confluent Cloud Schema Registry, see Schema Registry Enabled Environments.
Quick Start¶
Use this quick start to get up and running with the Confluent Cloud Couchbase Sink connector. The quick start provides the basics of selecting the connector and configuring it to consume data from Kafka and persist the data to a Couchbase database.
- Prerequisites
- Authorized access to a Confluent Cloud cluster on Amazon Web Services (AWS), Microsoft Azure (Azure), or Google Cloud.
- The Confluent CLI installed and configured for the cluster. For more information, see Install the Confluent CLI.
- Schema Registry must be enabled to use a Schema Registry-based format (for example, AVRO, JSON_SR (JSON Schema), or PROTOBUF). For more information, see Schema Registry Enabled Environments.
- Access to a Couchbase database.
- The Couchbase database service endpoint and the Kafka cluster must be in the same region.
- For networking considerations, see Networking and DNS. To use a set of public egress IP addresses, see Public Egress IP Addresses for Confluent Cloud Connectors.
- If you have a VPC-peered cluster in Confluent Cloud, consider configuring a PrivateLink Connection between Couchbase and the VPC.
- 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 4: Enter the connector details¶
Note
- Ensure you have all your prerequisites completed.
- An asterisk ( * ) designates a required entry.
At the Add Couchbase DB 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 new topic.
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.
Click Continue.
- Add the following database connection details:
- Couchbase Seed Nodes: A comma-separated addresses of Couchbase Server nodes.
If a custom port is specified, it must be the KV port (which is normally
11210for insecure connections, or11207for secure connections). - Couchbase Username: The name of the Couchbase user connecting to the Couchbase database.
- Couchbase Password: The password of the Couchbase user connecting to the Couchbase database.
- Couchbase Bucket: Name of the Couchbase bucket to use. This property is required
unless using the experimental
AnalyticsSinkHandler.
- Couchbase Seed Nodes: A comma-separated addresses of Couchbase Server nodes.
If a custom port is specified, it must be the KV port (which is normally
- Click Continue.
Note
See Configuration Properties for all property values and definitions.
Configure the following:
- Input Kafka record value format: Select the input Kafka record value format (data coming from the Kafka topic). Valid entires are AVRO, BYTES, JSON_SR (JSON Schema), PROTOBUF, or JSON (schemaless). A valid schema must be available in Schema Registry to use a schema-based message format (for example, AVRO, JSON_SR, or PROTOBUF). See Schema Registry Enabled Environments for additional information.
Sink behavior
Default Collection: Qualified name (
scope.collectionorbucket.scope.collection) of the destination collection for messages from topics that do not have an entry in thecouchbase.topic.to.collectionmap.- If the bucket component contains a dot (.), escape it by enclosing it in backticks.
- If the bucket component is omitted, it defaults to the value of the
couchbase.bucketproperty. - Default value:
_default._default.
Topic to Collection Map: A comma-delimited map from Kafka topic to Couchbase collection. Topic and collection are joined by an equals sign (=). A collection name is of the form
bucket.scope.collectionorscope.collection. If the bucket component is omitted, it defaults to the value of thecouchbase.bucketproperty. If the bucket component contains a dot (.), escape it by enclosing it in backticks. Defaults to an empty map, with all documents going to the collection specified by thecouchbase.default.collectionproperty.For example, if you want to write messages from topic topic1 to collection scope-a.invoices in the default bucket, and topic2 to collection scope-a.widgets in bucket other-bucket, you would write
topic1=scope-a.invoices,topic2=other-bucket.scope-a.widgets.Topic to Document ID Map: A comma-delimited map of per-topic overrides for the
couchbase.document.idconfiguration property. Topic and document ID format are joined by an equals sign (=). Defaults to an empty map, which means thecouchbase.document.idproperty applies to documents from all topics.For example, if documents from topic topic1 should match their id field, and documents from topic topic2 should match their identifier field, you would write
topic1=${/id},topic2=${/identifier}.Sink Handler Class: The fully-qualified class name of the sink handler to use. The handler determines how the Kafka record is translated into actions on Couchbase documents. The built-in handlers are:
com.couchbase.connect.kafka.handler.sink.UpsertSinkHandlercom.couchbase.connect.kafka.handler.sink.N1qlSinkHandlercom.couchbase.connect.kafka.handler.sink.SubDocumentSinkHandler
You can customize the sink connector’s behavior by implementing your own
SinkHandler. Default_value iscom.couchbase.connect.kafka.handler.sink.UpsertSinkHandler.Document ID: Format string for the Couchbase document ID. This overrides the message key. This may refer to document fields via placeholders, for example,
${/path/to/field}.Remove Document ID: Whether to remove the ID identified by
couchbase.documentIdfrom the document before storing in Couchbase. Default value isfalse.Document Expiration: Document expiration time, specified as an integer followed by a time unit (s = seconds, m = minutes, h = hours, d = days). For example, set this value to
30mto have documents expire after 30 minutes. Default value is0that means documents never expireRetry Timeout: Time limit for retrying failed writes to Couchbase. If this deadline is reached, the connector terminates. This retry timeout is distinct from the KV timeout (set via
couchbase.env.*), which affects individual write attempts. The retry timeout spans multiple attempts, making the connector resilient to transient failures. Do not confuse this with the Kafka Connect framework’s built-inerrors.retry.timeoutproperty, which applies only to failures occurring before the framework delivers the record to the Couchbase connector. Default value is0that means the connector terminates immediately on a write failure.
Durability
- Durability: The preferred way to specify an enhanced durability requirement when using
Couchbase Server
6.5or later.- If you set this to anything other than
NONE, then you must not setcouchbase.persist.toorcouchbase.replicate.toproperty. - Default value is
NONEthat means a write is successful as soon as it reaches the memory of the active node.
- If you set this to anything other than
- Persist To: Default value is
NONE.- For Couchbase Server versions prior to
6.5, this property specifies that the connector must verify a write is persisted to disk on a certain number of replicas before considering the write successful. - If you’re using Couchbase Server
6.5or later, Confluent recommends using thecouchbase.durabilityproperty instead.
- For Couchbase Server versions prior to
- Replicate To: Default value is
NONE.- For Couchbase Server versions prior to
6.5, this property specifies that the connector must verify a write has reached the memory of a certain number of replicas before considering the write successful.. - If you’re using Couchbase Server
6.5or later, Confluent recommends using thecouchbase.durabilityproperty instead.
- For Couchbase Server versions prior to
Data encryption
- (Optional) Enable Client-Side Field Level Encryption for data decryption. Specify a Service Account to
access the Schema Registry and associated encryption rules or keys with that schema. Select the connector behavior
(
ERRORorNONE) on data decryption failure. If set toERROR, the connector fails and writes the encrypted data in the DLQ. If set toNONE, the connector writes the encrypted data in the target system without decryption. For more information on CSFLE setup, see Manage CSFLE for connectors.
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?.
Additional configurations
To add an additional configuration, see Additional Connector Configuration Reference for Confluent Cloud.
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 tofalseto 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.
Transforms
Single Message Transforms: To add a new SMT, see Add transforms. For more information about unsupported SMTs, see Unsupported transformations.
Processing position
Set offsets: Click Set offsets to define a specific offset for this connector to begin procession data from. For more information on managing offsets, see Manage offsets.
Click Continue.
Based on the number of topic partitions you select, you will be provided with a recommended number of tasks. One task can handle up to 100 partitions.
- To change the number of recommended tasks, enter the number of tasks for the connector to use in the Tasks field.
- Click Continue.
Verify the connection details by previewing the running configuration.
After you’ve validated that the properties are configured to your satisfaction, click Launch.
Tip
For information about previewing your connector output, see Data Previews for Confluent Cloud Connectors.
Verify the connection details and click Launch.
The status for the connector should go from Provisioning to Running. It may take a few minutes.
Step 5: Check Couchbase database¶
After the connector is running, verify that messages are being added to your Couchbase database.
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.
Note
Make sure you have all your prerequisites completed.
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 the required connector properties.
{
"connector.class": "CouchbaseSink",
"name": "CouchbaseSinkConnector_0",
"kafka.auth.mode": "KAFKA_API_KEY",
"kafka.api.key": "<my-kafka-api-key",
"kafka.api.secret": "<my-kafka-api-secret>",
"input.data.format" : "JSON",
"couchbase.seed.nodes": "<couchbase-node-address>",
"couchbase.bucket": "<bucket-name>",
"topics": "dlq-bcc-devcjd1abc",
"couchbase.username": "<database-username>",
"couchbase.password": "<database-password>",
"couchbase.default.collection": "_default._default",
"couchbase.sink.handler": "com.couchbase.connect.kafka.handler.sink.UpsertSinkHandler",
"couchbase.remove.document.id": "false",
"couchbase.document.expiration": "0",
"couchbase.retry.timeout": "0",
"couchbase.durability": "NONE",
"couchbase.persist.to": "NONE",
"couchbase.replicate.to": "NONE",
"tasks.max": "1"
}
Note the following property definitions:
"connector.class": Identifies the connector plugin name."name": Sets a name for your new connector.
"kafka.auth.mode": Identifies the connector authentication mode you want to use. There are two options:SERVICE_ACCOUNTorKAFKA_API_KEY(the default). To use an API key and secret, specify the configuration propertieskafka.api.keyandkafka.api.secret, as shown in the example configuration (above). To use a service account, specify the Resource ID in the propertykafka.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
"input.data.format": Sets the input Kafka record value format (data coming from the Kafka topic). Valid entires are AVRO, BYTES, JSON_SR (JSON Schema), PROTOBUF, or JSON (schemaless). You must have Confluent Cloud Schema Registry configured if using a schema-based message format (for example, AVRO, JSON_SR (JSON Schema), or PROTOBUF)."couchbase.seed.nodes": A comma-separated addresses of Couchbase Server nodes. If a custom port is specified, it must be the KV port (which is normally11210for insecure connections, or11207for secure connections)."couchbase.bucket": Name of the Couchbase bucket to use. This property is required unless using the experimentalAnalyticsSinkHandler."couchbase.username": The name of the Couchbase user connecting to the Couchbase database."couchbase.password": The password of the Couchbase user connecting to the Couchbase database."couchbase.source.handler": The source handler determines how the Couchbase document is converted into a Kafka record. When using a custom source handler that filters out certain messages, consider also configuringcouchbase.black.hole.topicproperty.Enter the number of tasks for the connector. For more information, see Confluent Cloud connector limitations.
Note
(Optional) To enable CSFLE for data encryption, specify the following properties:
csfle.enabled: Flag to indicate whether the connector honors CSFLE rules.sr.service.account.id: A Service Account to access the Schema Registry and associated encryption rules or keys with that schema.csfle.onFailure: Configures the connector behavior (ERRORorNONE) on data decryption failure. If set toERROR, the connector fails and writes the encrypted data in the DLQ. If set toNONE, the connector writes the encrypted data in the target system without decryption.
Warning
Security Risk: Dead Letter Queue (DLQ) with CSFLE
When using CSFLE with connectors that route failed messages to a Dead Letter Queue (DLQ), be aware that data sent to the DLQ is written in plaintext (unencrypted). This poses a significant security risk as sensitive data that should be encrypted may be exposed in the DLQ.
Do not use DLQ with CSFLE in the current version. If you need error handling for CSFLE-enabled data, use alternative approaches such as:
- Setting the connector behavior to
ERRORto throw exceptions instead of routing to DLQ - Implementing custom error handling in your applications
- Using
NONEto pass encrypted data through without decryption
For more information on CSFLE setup, see Manage CSFLE for connectors.
Single Message Transforms: For more information about adding SMTs using the CLI, see Single Message Transforms (SMT) documentation.
See Configuration Properties for all property values and definitions.
Step 4: Load the properties file and create the connector¶
Enter the following 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 CouchbaseSink.json
Example output:
Created connector confluent-CouchbaseSink lcc-ix4dl
Step 5: Check the connector status¶
Enter the following command to check the connector status:
confluent connect cluster list
Example output:
ID | Name | Status | Type
+-----------+-------------------------+---------+------+
lcc-ix4dl | confluent-CouchbaseSink | RUNNING | sink
Step 6: Check Couchbase¶
After the connector is running, verify that records are populating your Couchbase database.
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 fully-managed connector. For self-managed connector property definitions and other details, see the connector docs in Self-managed connectors for Confluent Platform.
How should we connect to your data?¶
nameSets a name for your connector.
- Type: string
- Valid Values: A string at most 64 characters long
- Importance: high
Schema Config¶
schema.context.nameAdd 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
Kafka Cluster credentials¶
kafka.auth.modeKafka 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.keyKafka API Key. Required when kafka.auth.mode==KAFKA_API_KEY.
- Type: password
- Importance: high
kafka.service.account.idThe Service Account that will be used to generate the API keys to communicate with Kafka Cluster.
- Type: string
- Importance: high
kafka.api.secretSecret associated with Kafka API key. Required when kafka.auth.mode==KAFKA_API_KEY.
- Type: password
- Importance: high
Connection¶
couchbase.seed.nodesAddresses of Couchbase Server nodes, delimited by commas. If a custom port is specified, it must be the KV port (which is normally 11210 for insecure connections, or 11207 for secure connections).
- Type: string
- Importance: high
couchbase.usernameName of the Couchbase user to authenticate as.
- Type: string
- Importance: high
couchbase.passwordPassword of the Couchbase user.
- Type: password
- Importance: high
couchbase.bucketName of the Couchbase bucket to use. This property is required unless using the experimental AnalyticsSinkHandler.
- Type: string
- Default: “”
- Importance: high
Sink Behavior¶
couchbase.default.collectionQualified name (scope.collection or bucket.scope.collection) of the destination collection for messages from topics that don’t have an entry in the couchbase.topic.to.collection map. If the bucket component contains a dot, escape it by enclosing it in backticks. If the bucket component is omitted, it defaults to the value of the couchbase.bucket property.
- Type: string
- Default: _default._default
- Importance: medium
couchbase.topic.to.collectionA map from Kafka topic to Couchbase collection. Topic and collection are joined by an equals sign. Map entries are delimited by commas. A collection name is of the form bucket.scope.collection or scope.collection. If the bucket component is omitted, it defaults to the value of the couchbase.bucket property. If the bucket component contains a dot, escape it by enclosing it in backticks. For example, if you want to write messages from topic “topic1” to collection “scope-a.invoices” in the default bucket, and messages from topic “topic2” to collection “scope-a.widgets” in bucket “other-bucket” you would write: “topic1=scope-a.invoices,topic2=other-bucket.scope-a.widgets”. Defaults to an empty map, with all documents going to the collection specified by couchbase.default.collection.
- Type: string
- Default: “”
- Importance: medium
couchbase.topic.to.document.idA map of per-topic overrides for the couchbase.document.id configuration property. Topic and document ID format are joined by an equals sign. Map entries are delimited by commas. For example, if documents from topic “topic1” should be assigned document IDs that match their “id” field, and documents from topic “topic2” should be assigned documents IDs that match their “identifier” field, you would write: “topic1=${/id},topic2=${/identifier}”. Defaults to an empty map, which means the value of the couchbase.document.id configuration property is applied to documents from all topics.
- Type: string
- Default: “”
- Importance: medium
couchbase.sink.handlerThe fully-qualified class name of the sink handler to use. The sink handler determines how the Kafka record is translated into actions on Couchbase documents. The built-in handlers are: com.couchbase.connect.kafka.handler.sink.UpsertSinkHandler, com.couchbase.connect.kafka.handler.sink.N1qlSinkHandler, and com.couchbase.connect.kafka.handler.sink.SubDocumentSinkHandler. You can customize the sink connector’s behavior by implementing your own SinkHandler.
- Type: string
- Default: com.couchbase.connect.kafka.handler.sink.UpsertSinkHandler
- Valid Values: com.couchbase.connect.kafka.handler.sink.AnalyticsSinkHandler, com.couchbase.connect.kafka.handler.sink.N1qlSinkHandler, com.couchbase.connect.kafka.handler.sink.SubDocumentSinkHandler, com.couchbase.connect.kafka.handler.sink.UpsertSinkHandler
- Importance: medium
couchbase.document.idFormat string to use for the Couchbase document ID (overriding the message key). May refer to document fields via placeholders like ${/path/to/field}
- Type: string
- Default: “”
- Importance: medium
couchbase.remove.document.idWhether to remove the ID identified by ‘couchbase.documentId’ from the document before storing in Couchbase.
- Type: boolean
- Default: false
- Importance: medium
couchbase.document.expirationDocument expiration time specified as an integer followed by a time unit (s = seconds, m = minutes, h = hours, d = days). For example, to have documents expire after 30 minutes, set this value to “30m”. A value of “0” (the default) means documents never expire.
- Type: string
- Default: 0
- Valid Values: Must match the regex
^0$|^[1-9]\d*(ms|s|m|h|d)$ - Importance: medium
couchbase.retry.timeoutRetry failed writes to Couchbase until this deadline is reached. If time runs out, the connector terminates. A value of 0 (the default) means the connector will terminate immediately when a write fails. This retry timeout is distinct from the KV timeout (which you can set via couchbase.env.*). The KV timeout affects an individual write attempt, while the retry timeout spans multiple attempts and makes the connector resilient to more kinds of transient failures. Try not to confuse this with the Kafka Connect framework’s built-in errors.retry.timeout config property, which applies only to failures occurring before the framework delivers the record to the Couchbase connector.
- Type: string
- Default: 0
- Valid Values: Must match the regex
^0$|^[1-9]\d*(ms|s|m|h|d)$ - Importance: medium
Durability¶
couchbase.durabilityThe preferred way to specify an enhanced durability requirement when using Couchbase Server 6.5 or later. The default value of NONE means a write is considered successful as soon as it reaches the memory of the active node. If you set this to anything other than NONE, then you must not set couchbase.persist.to or couchbase.replicate.to.
- Type: string
- Default: NONE
- Valid Values: MAJORITY, MAJORITY_AND_PERSIST_TO_ACTIVE, NONE, PERSIST_TO_MAJORITY
- Importance: medium
couchbase.persist.toFor Couchbase Server versions prior to 6.5, this is how you require the connector to verify a write is persisted to disk on a certain number of replicas before considering the write successful. If you’re using Couchbase Server 6.5 or later, we recommend using the couchbase.durability property instead.
- Type: string
- Default: NONE
- Valid Values: ACTIVE, FOUR, NONE, ONE, THREE, TWO
- Importance: medium
couchbase.replicate.toFor Couchbase Server versions prior to 6.5, this is how you require the connector to verify a write has reached the memory of a certain number of replicas before considering the write successful. If you’re using Couchbase Server 6.5 or later, we recommend using the couchbase.durability property instead.
- Type: string
- Default: NONE
- Valid Values: NONE, ONE, THREE, TWO
- Importance: medium
N1ql Sink Handler¶
couchbase.n1ql.operationThe type of update to use when couchbase.sink.handler is set to com.couchbase.connect.kafka.handler.sink.N1qlSinkHandler. This property is specific to N1qlSinkHandler.
- Type: string
- Default: UPDATE
- Valid Values: UPDATE, UPDATE_WHERE
- Importance: medium
couchbase.n1ql.where.fieldsWhen using the UPDATE_WHERE operation, this is the list of document fields that must match the Kafka message in order for the document to be updated with the remaining message fields. To match against a literal value instead of a message field, use a colon to delimit the document field name and the target value. For example, “type:widget,color” matches documents whose ‘type’ field is ‘widget’ and whose ‘color’ field matches the ‘color’ field of the Kafka message. This property is specific to N1qlSinkHandler.
- Type: string
- Default: “”
- Importance: medium
couchbase.n1ql.create.documentControls whether to create the document if it does not exist. This property is specific to N1qlSinkHandler.
- Type: boolean
- Default: true
- Importance: medium
Sub Document Sink Handler¶
couchbase.subdocument.pathJSON Pointer to the property of the Kafka message whose value is the subdocument path to use when modifying the Couchbase document. This property is specific to SubDocumentSinkHandler.
- Type: string
- Default: “”
- Importance: medium
couchbase.subdocument.operationSetting to indicate the type of update to a sub-document. This property is specific to SubDocumentSinkHandler.
- Type: string
- Default: UPSERT
- Valid Values: ARRAY_APPEND, ARRAY_PREPEND, UPSERT
- Importance: medium
couchbase.subdocument.create.pathWhether to add the parent paths if they are missing in the document. This property is specific to SubDocumentSinkHandler.
- Type: boolean
- Default: true
- Importance: medium
couchbase.subdocument.create.documentThis property controls whether to create the document if it does not exist. This property is specific to SubDocumentSinkHandler.
- Type: boolean
- Default: true
- Importance: medium
Analytics Sink Handler¶
couchbase.analytics.max.records.in.batchEvery Batch consists of an UPSERT or a DELETE statement, based on mutations. This property determines the maximum number of records in the UPSERT or DELETE statement in the batch. Users can configure this parameter based on the capacity of their analytics cluster. This property is specific to AnalyticsSinkHandler. UNCOMMITTED; this feature may change in a patch release without notice. Since: 4.1.14
- Type: int
- Default: 100
- Importance: medium
couchbase.analytics.max.size.in.batchEvery Batch consists of an UPSERT or a DELETE statement, based on mutations. This property defines the max size of all docs in bytes in an UPSERT statement in a batch. Users can configure this parameter based on the capacity of their analytics cluster. This property is specific to AnalyticsSinkHandler. UNCOMMITTED; this feature may change in a patch release without notice. Since: 4.2.0
- Type: string
- Default: 5m
- Valid Values: Must match the regex
^[1-9]\d*(b|k|m|g)$ - Importance: medium
couchbase.analytics.query.timeoutThis property determines the time period after which client cancels the Query request for Analytics. This property is specific to AnalyticsSinkHandler. UNCOMMITTED; this feature may change in a patch release without notice. Since: 4.2.0
- Type: string
- Default: 5m
- Valid Values: Must match the regex
^[1-9]\d*(ms|s|m|h|d)$ - Importance: medium
Additional Configs¶
consumer.override.auto.offset.resetDefines 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.levelControls 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.converterThe 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.keysAllow optional string map key when converting from Connect Schema to Avro Schema. Applicable for Avro Converters.
- Type: boolean
- Importance: low
value.converter.auto.register.schemasSpecify if the Serializer should attempt to register the Schema.
- Type: boolean
- Importance: low
value.converter.connect.meta.dataAllow the Connect converter to add its metadata to the output schema. Applicable for Avro Converters.
- Type: boolean
- Importance: low
value.converter.enhanced.avro.schema.supportEnable enhanced schema support to preserve package information and Enums. Applicable for Avro Converters.
- Type: boolean
- Importance: low
value.converter.enhanced.protobuf.schema.supportEnable enhanced schema support to preserve package information. Applicable for Protobuf Converters.
- Type: boolean
- Importance: low
value.converter.flatten.unionsWhether to flatten unions (oneofs). Applicable for Protobuf Converters.
- Type: boolean
- Importance: low
value.converter.generate.index.for.unionsWhether to generate an index suffix for unions. Applicable for Protobuf Converters.
- Type: boolean
- Importance: low
value.converter.generate.struct.for.nullsWhether to generate a struct variable for null values. Applicable for Protobuf Converters.
- Type: boolean
- Importance: low
value.converter.int.for.enumsWhether to represent enums as integers. Applicable for Protobuf Converters.
- Type: boolean
- Importance: low
value.converter.latest.compatibility.strictVerify latest subject version is backward compatible when use.latest.version is true.
- Type: boolean
- Importance: low
value.converter.object.additional.propertiesWhether to allow additional properties for object schemas. Applicable for JSON_SR Converters.
- Type: boolean
- Importance: low
value.converter.optional.for.nullablesWhether nullable fields should be specified with an optional label. Applicable for Protobuf Converters.
- Type: boolean
- Importance: low
value.converter.optional.for.proto2Whether proto2 optionals are supported. Applicable for Protobuf Converters.
- Type: boolean
- Importance: low
value.converter.scrub.invalid.namesWhether 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.versionUse latest version of schema in subject for serialization when auto.register.schemas is false.
- Type: boolean
- Importance: low
value.converter.use.optional.for.nonrequiredWhether to set non-required properties to be optional. Applicable for JSON_SR Converters.
- Type: boolean
- Importance: low
value.converter.wrapper.for.nullablesWhether nullable fields should use primitive wrapper messages. Applicable for Protobuf Converters.
- Type: boolean
- Importance: low
value.converter.wrapper.for.raw.primitivesWhether a wrapper message should be interpreted as a raw primitive at root level. Applicable for Protobuf Converters.
- Type: boolean
- Importance: low
errors.toleranceUse 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.strategyHow to construct the subject name for key schema registration.
- Type: string
- Default: TopicNameStrategy
- Importance: low
key.converter.replace.null.with.defaultWhether 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 Key Converter.
- Type: boolean
- Default: true
- Importance: low
key.converter.schemas.enableInclude schemas within each of the serialized keys. Input message keys must contain schema and payload fields and may not contain additional fields. For plain JSON data, set this to false. Applicable for JSON Key Converter.
- Type: boolean
- Default: false
- Importance: low
value.converter.decimal.formatSpecify 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.unionsWhether to flatten singleton unions. Applicable for Avro and JSON_SR Converters.
- Type: boolean
- Default: false
- Importance: low
value.converter.ignore.default.for.nullablesWhen 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.strategySet 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.defaultWhether 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.enableInclude 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.strategyDetermines how to construct the subject name under which the value schema is registered with Schema Registry.
- Type: string
- Default: TopicNameStrategy
- Importance: low
Consumer configuration¶
max.poll.interval.msThe 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.recordsThe 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
Input messages¶
input.data.formatSets 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
input.key.formatSets the input Kafka record key format. Valid entries are AVRO, BYTES, JSON, JSON_SR, PROTOBUF, or STRING. 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
- Valid Values: AVRO, BYTES, JSON, JSON_SR, PROTOBUF, STRING
- Importance: high
Number of tasks for this connector¶
tasks.maxMaximum number of tasks for the connector.
- Type: int
- Valid Values: [1,…]
- Importance: high
Which topics do you want to get data from?¶
topics.regexA regular expression that matches the names of the topics to consume from. This is useful when you want to consume from multiple topics that match a certain pattern without having to list them all individually.
- Type: string
- Importance: low
topicsIdentifies the topic name or a comma-separated list of topic names.
- Type: list
- Importance: high
errors.deadletterqueue.topic.nameThe 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
Auto-restart policy¶
auto.restart.on.user.errorEnable connector to automatically restart on user-actionable errors.
- Type: boolean
- Default: true
- Importance: medium
Next Steps¶
For an example that shows fully-managed Confluent Cloud connectors in action with Confluent Cloud for Apache Flink, see the Cloud ETL Demo. This example also shows how to use Confluent CLI to manage your resources in Confluent Cloud.
