Oracle Database Sink Connector for Confluent Cloud

Note

If you are installing the connector locally for Confluent Platform, see JDBC Connector (Source and Sink) for Confluent Platform.

The managed Oracle Database Sink connector for Confluent Cloud allows you to export data from Apache Kafka® topics to an Oracle database (JDBC). The connector polls data from Kafka to write to the database based on the topic subscription. It is possible to achieve idempotent writes with upserts. Auto-creation of tables and limited auto-evolution is also supported.

Features

The Oracle Database Sink connector supports the following features:

  • Idempotent writes: The default insert.mode is INSERT. If it is configured as UPSERT, the connector will use upsert semantics rather than plain insert statements. Upsert semantics refer to automically adding a new row or updating the existing row if there is a primary key constraint violation, which provides idempotence.

    Important

    When a target table includes columns with CLOB, INSERT or UPSERT performance may be degraded. Try to use VARCHAR or VARCHAR2 instead.

  • SSL support: Supports one-way SSL.

  • Schemas: The connector supports Avro, JSON Schema, and Protobuf input value formats. The connector supports Avro, JSON Schema, Protobuf, and String input key formats. Schema Registry must be enabled to use a Schema Registry-based format.

  • Primary key support: Supported PK modes are kafka, none, record_key, and record_value. Used in conjunction with the PK Fields property.

  • Table and column auto-creation: auto.create and auto-evolve are supported. If tables or columns are missing, they can be created automatically. Table names are created based on Kafka topic names.

  • At least once delivery: This connector guarantees that records from the Kafka topic are delivered at least once.

  • Supports multiple tasks: The connector supports running one or more tasks. More tasks may improve performance.

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 Oracle Database Sink connector. The quick start provides the basics of selecting the connector and configuring it to stream events

Prerequisites
  • Authorized access to a Confluent Cloud cluster on Amazon Web Services (AWS), Microsoft Azure (Azure), or Google Cloud Platform (GCP).
  • Authorized access to an Oracle database.
  • The Oracle Database version must be 11.2.0.4 or later.
  • The database and Kafka cluster should be in the same region. If you use a different region, be aware that you may incur additional data transfer charges.
  • For networking considerations, see Networking and DNS Considerations. To use static egress IPs, see Static Egress IP Addresses.
  • The Confluent CLI installed and configured for the cluster. 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). See Environment Limitations for additional information.
  • At least one source Kafka topic must exist in your Confluent Cloud cluster before creating the sink connector.
  • See Database considerations for additional information.

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 Oracle Database Sink connector icon.

Oracle Database Sink Connector Icon

Step 4: Enter the connector details.

Note

  • Ensure you have all your prerequisites completed.
  • An asterisk ( * ) designates a required entry.

At the Add Oracle Database Sink Connector screen, complete the following:

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

To create a new topic, click +Add new topic.

Step 5: Check for records.

Verify that rows are populating the database.

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

Tip

When you launch a connector, a Dead Letter Queue topic is automatically created. See Dead Letter Queue 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.
  • 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 OracleDatabaseSink

Example output:

Following are the required configs:
connector.class: OracleDatabaseSink
input.data.format
name
kafka.auth.mode
kafka.api.key
kafka.api.secret
connection.host
connection.port
connection.user
connection.password
db.name
ssl.server.cert.dn
ssl.rootcertfile
tasks.max
topics

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. See the Configuration Properties for configuration property values and descriptions.

{
  "connector.class": "OracleDatabaseSink",
  "input.data.format": "AVRO",
  "name": "OracleDatabaseSink_0",
  "kafka.auth.mode": "KAFKA_API_KEY",
  "kafka.api.key": "<my-kafka-api-key>",
  "kafka.api.secret": "<my-kafka-api-secret>",
  "connection.host ": "<connection-host",
  "connection.port": "1521",
  "connection.user": "<user-name>",
  "connection.password": "<user-password>",
  "db.name": "<database-name>",
  "ssl.server.cert.dn": "<distinquished-database-server-name>",
  "ssl.rootcertfile": "<certificate-text>",
  "tasks.max": "1",
  "topics": "<topic-name>",
}

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, and PROTOBUF. You must have Confluent Cloud Schema Registry configured if using a schema-based message format (for example, Avro, JSON_SR (JSON Schema), or Protobuf). See input.key.format in the Configuration Properties for additional options.
  • "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_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
    
  • "connection.<...>": The database connection properties. The connection.host entry will look similar to database-1.<id>.us-west-2.rds.amazonaws.com. For details, see Database Connection Details.

  • "ssl.rootcertfile": The default ssl.mode is verify-full. Use the property ssl.rootcertfile and add the contents of the text certificate file for the property value. For example, "ssl.rootcertfile": "<certificate-text>". See the Configuration Properties for additional ssl.mode options.

  • "ssl.server.cert.dn": The default ssl.mode is verify-full. With this mode, you must provide the distinguished server name. See the Configuration Properties for additional ssl.mode options.

  • "tasks.max": Enter the maximum number of tasks for the connector to use. More tasks may improve performance (that is, consumer lag is reduced with multiple tasks running).

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

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 descriptions.

Step 4: Load the properties 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 oracle-db-sink-config.json

Example output:

Created connector OracleDatabaseSink_0 lcc-do6vzd

Step 5: Check the connector status.

Enter the following command to check the connector status:

confluent connect list

Example output:

ID           |             Name         | Status  | Type | Trace
+------------+--------------------------+---------+------+-------+
lcc-do6vzd   | OracleDatabaseSink_0     | RUNNING | sink |       |

Step 6: Check for records.

Verify that rows are populating the database.

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

Tip

When you launch a connector, a Dead Letter Queue topic is automatically created. See Dead Letter Queue for details.

Configuration Properties

Use the following configuration properties with this 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

Input messages

input.data.format

Sets the input Kafka record value format. Valid entries are AVRO, JSON_SR, or PROTOBUF. 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
  • Importance: high
input.key.format

Sets the input Kafka record key format. This need to be set to a proper format if using pk.mode=record_key. Valid entries are AVRO, JSON_SR, PROTOBUF, 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
  • Importance: high
delete.enabled

Whether to treat null record values as deletes. Requires pk.mode to be record_key.

  • Type: boolean
  • Default: false
  • Importance: low

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

How should we connect to your database?

connection.host

JDBC connection host.

  • Type: string
  • Importance: high
connection.port

JDBC connection port.

  • Type: int
  • Valid Values: [0,…,65535]
  • Importance: high
connection.user

JDBC connection user.

  • Type: string
  • Importance: high
connection.password

JDBC connection password.

  • Type: password
  • Importance: high
db.name

JDBC database name.

  • Type: string
  • Valid Values: Must match the regex ^[a-zA-Z][a-zA-Z0-9$#_]*$
  • Importance: high
ssl.mode

What SSL mode should we use to connect to your database. disabled disables SSL entirely. verify-ca uses SSL for encryption and performs authentication of the server CA. verify-ca option requires a Java truststore containing the server CA and the truststore password to be provided.

  • Type: string
  • Default: verify-full
  • Importance: high
ssl.truststorefile

The trust store containing server CA certificate. Only required if using verify-ca or verify-full ssl mode.

  • Type: password
  • Default: [hidden]
  • Importance: low
ssl.truststorepassword

The trust store password containing server CA certificate. Only required if using verify-ca or verify-full ssl mode.

  • Type: password
  • Default: [hidden]
  • Importance: low
ssl.server.cert.dn

Use this paramter to specify the distinguished name (DN) of the database server. Only required if using verify-full ssl mode.

  • Type: string
  • Importance: low

Database details

insert.mode

The insertion mode to use.

  • Type: string
  • Default: INSERT
  • Importance: high
table.name.format

A format string for the destination table name, which may contain ${topic} as a placeholder for the originating topic name.

For example, kafka_${topic} for the topic ‘orders’ will map to the table name ‘kafka_orders’.

  • Type: string
  • Default: ${topic}
  • Importance: medium
table.types

The comma-separated types of database tables to which the sink connector can write. By default this is TABLE, but any combination of TABLE and VIEW is allowed. Not all databases support writing to views, and when they do the sink connector will fail if the view definition does not match the records’ schemas (regardless of auto.evolve).

  • Type: list
  • Default: TABLE
  • Importance: low
fields.whitelist

List of comma-separated record value field names. If empty, all fields from the record value are utilized, otherwise used to filter to the desired fields.

  • Type: list
  • Importance: medium
db.timezone

Name of the JDBC timezone used in the connector when querying with time-based criteria. Defaults to UTC.

  • Type: string
  • Default: UTC
  • Importance: medium

Primary Key

pk.mode

The primary key mode, also refer to pk.fields documentation for interplay. Supported modes are:

none: No keys utilized.

kafka: Apache Kafka® coordinates are used as the PK.

record_value: Field(s) from the record value are used, which must be a struct.

record_key: Field(s) from the record key are used, which must be a struct.

  • Type: string
  • Valid Values: kafka, none, record_key, record_value
  • Importance: high
pk.fields

List of comma-separated primary key field names. The runtime interpretation of this config depends on the pk.mode:

none: Ignored as no fields are used as primary key in this mode.

kafka: Must be a trio representing the Kafka coordinates, defaults to __connect_topic,__connect_partition,__connect_offset if empty.

record_value: If empty, all fields from the value struct will be used, otherwise used to extract the desired fields.

  • Type: list
  • Importance: high

SQL/DDL Support

auto.create

Whether to automatically create the destination table if it is missing.

  • Type: boolean
  • Default: false
  • Importance: medium
auto.evolve

Whether to automatically add columns in the table if they are missing.

  • Type: boolean
  • Default: false
  • Importance: medium
quote.sql.identifiers

When to quote table names, column names, and other identifiers in SQL statements. For backward compatibility, the default is ‘always’.

  • Type: string
  • Default: ALWAYS
  • Valid Values: ALWAYS, NEVER
  • Importance: medium

Connection details

batch.sizes

Maximum number of rows to include in a single batch when polling for new data. This setting can be used to limit the amount of data buffered internally in the connector.

  • Type: int
  • Default: 3000
  • Valid Values: [1,…,5000]
  • Importance: low

Number of tasks for this connector

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

Database considerations

Note the following issues to keep in mind.

  1. String type is mapped to CLOB when auto.create=true. For example, you have the following Avro schema:

    {
      "connect.name": "ksql.ratings",
      "fields": [
        {
          "name": "rating_id",
          "type": "long"
        },
        {
          "name": "user_id",
          "type": "int"
        },
        ...
        {
          "name": "channel",
          "type": "string"
        },
        {
          "name": "message",
          "type": "string"
        }
      ],
      "name": "ratings",
      "namespace": "ksql",
      "type": "record"
    }
    

    These values are mapped to CLOB in the table schema:

    Name        Null?    Type
    ----------- -------- ----------
    rating_id   NOT NULL NUMBER(19)
    user_id     NOT NULL NUMBER(10)
    stars       NOT NULL NUMBER(10)
    route_id    NOT NULL NUMBER(10)
    rating_time NOT NULL NUMBER(19)
    channel     NOT NULL CLOB
    message     NOT NULL CLOB
    

    Since String is mapped to CLOB when auto.create=true, a field using the String type cannot be used as a primary key. If you want to use a String type field as a primary key, you should create a table in the database first and then use auto.create=false. If not, an exception occurs containing the following line:

    ...
    "stringValue": "Exception chain:\njava.sql.SQLException: ORA-02329:
    column of datatype LOB cannot be unique or a primary key
    ...
    
  2. The table name and column names are case sensitive. For example, you have the following Avro schema:

    {
      "connect.name": "ksql.pageviews",
      "fields": [
        {
          "name": "viewtime",
          "type": "long"
        },
        {
          "name": "userid",
          "type": "string"
        },
        {
          "name": "pageid",
          "type": "string"
        }
      ],
      "name": "pageviews",
      "namespace": "ksql",
      "type": "record"
    }
    

    A table named PAGEVIEWS is created, which causes the exception where pageviews is not found.

    create table pageviews (
      userid VARCHAR(10) NOT NULL PRIMARY KEY,
      pageid VARCHAR(50),
      viewtime VARCHAR(50)
      );
    
    Table PAGEVIEWS created.
    
    DESC pageviews;
    Name     Null?    Type
    -------- -------- ------------
    USERID   NOT NULL VARCHAR2(10)
    PAGEID            VARCHAR2(50)
    VIEWTIME          VARCHAR2(50)
    

    An exception message similar to the following one will be in the DLQ:

    {
      "key": "__connect.errors.exception.message",
      "stringValue": "Table \"pageviews\" is missing and auto-creation
      is disabled"
    }
    

    To resolve this issue, create a table in Oracle Database first and use auto.create=false.

    create table "pageviews" (
      "userid" VARCHAR(10) NOT NULL PRIMARY KEY,
      "pageid" VARCHAR(50),
      "viewtime" VARCHAR(50)
      );
    
    Table "pageviews" created.
    
    
    DESC "pageviews";
    
    Name     Null?    Type
    -------- -------- ------------
    userid   NOT NULL VARCHAR2(10)
    pageid            VARCHAR2(50)
    viewtime          VARCHAR2(50)
    

    Note

    Note that SQL standards define databases to be case insensitive for identifiers and keywords unless they are quoted. What this means is that CREATE TABLE test_case creates a table named TEST_CASE and CREATE TABLE "test_case" creates a table named test_case. This is also true of table column identifiers. For additional information about identifier quoting, see Database Identifiers, Quoting, and Case Sensitivity.

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