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Chapter 2. Installing Debezium connectors on RHEL

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Install Debezium connectors through AMQ Streams by extending Kafka Connect with connector plugins. Following a deployment of AMQ Streams, you can deploy Debezium as a connector configuration through Kafka Connect.

2.1. Kafka topic creation recommendations

Debezium stores data in multiple Apache Kafka topics. The topics must either be created in advance by an administrator, or you can configure Kafka Connect to configure topics automatically.

The following list describes limitations and recommendations to consider when creating topics:

Database schema history topics for the Debezium Db2, MySQL, Oracle, and SQL Server connectors

For each of the preceding connectors a database schema history topic is required. Whether you manually create the database schema history topic, use the Kafka broker to create the topic automatically, or use Kafka Connect to create the topic, ensure that the topic is configured with the following settings:

  • Infinite or very long retention.
  • Replication factor of at least three in production environments.
  • Single partition.
Other topics
  • When you enable Kafka log compaction so that only the last change event for a given record is saved, set the following topic properties in Apache Kafka:

    • min.compaction.lag.ms
    • delete.retention.ms

      To ensure that topic consumers have enough time to receive all events and delete markers, specify values for the preceding properties that are larger than the maximum downtime that you expect for your sink connectors. For example, consider the downtime that might occur when you apply updates to sink connectors.

  • Replicated in production.
  • Single partition.

    You can relax the single partition rule, but your application must handle out-of-order events for different rows in the database. Events for a single row are still totally ordered. If you use multiple partitions, the default behavior is that Kafka determines the partition by hashing the key. Other partition strategies require the use of single message transformations (SMTs) to set the partition number for each record.

2.2. Planning the Debezium connector configuration

Before you deploy a Debezium connector, determine how you want to configure the connector. The configuration provides information that specifies the behavior of the connector and enables Debezium to connect to the source database.

You specify the connector configuration as JSON, and when you are ready to register the connector, you use curl to submit the configuration to the Kafka Connect API endpoint.

Prerequisites

  • A source database is deployed and the Debezium connector can access the database.
  • You know the following information, which the connector requires to access the source database:

    • Name or IP address of the database host.
    • Port number for connecting to the database.
    • Name of the account that the connector can use to sign in to the database.
    • Password of the database user account.
    • Name of the database.
    • The names of the tables from which you want the connector to capture information.
    • The name of the Kafka broker to which you want the connector to emit change events.
    • The name of the Kafka topic to which you want the connector to send database history information.

Procedure

  • Specify the configuration that you want to apply to the Debezium connector in JSON format.

    The following example shows a simple configuration for a Debezium MySQL connector:

    {
      "name": "inventory-connector",  1
      "config": {
        "connector.class": "io.debezium.connector.mysql.MySqlConnector", 2
        "tasks.max": "1",  3
        "database.hostname": "mysql",  4
        "database.port": "3306", 5
        "database.user": "debezium", 6
        "database.password": "dbz", 7
        "database.server.id": "184054",  8
        "topic.prefix": "dbserver1",   9
        "table.include.list": "public.inventory",  10
        "schema.history.internal.kafka.bootstrap.servers": "kafka:9092",  11
        "schema.history.internal.kafka.topic": "dbhistory.inventory"  12
      }
    }
    1
    The name of the connector to register with the Kafka Connect cluster.
    2
    The name of the connector class.
    3
    The number of tasks that can operate concurrently. Only one task should operate at a time.
    4
    The host name or IP address of the host database instance.
    5
    The port number of the database instance.
    6
    The name of the user account through which Debezium connects to the database.
    7
    The password for the database user account.
    8
    A unique numeric ID for the connector.
    This property is used for the MySQL connector only.
    9
    A string that serves as the logical identifier for the database server or cluster of servers from which the connector captures changes. The specified string designates a namespace. Debezium prefixes this name to each Kafka topic that the connector writes to, as well as to the names of Kafka Connect schemas, and the namespaces of the corresponding Avro schema, when the Avro converter is used.
    10
    The list of tables from which the connector captures change events.
    11
    The name of the Kafka broker where the connector sends the database schema history. The specified broker also receives the change events that the connector emits.
    12
    The name of the Kafka topic that stores the schema history.
    After a connector restart, the connector resumes reading the database log from the point at which it stopped, emitting events for any transactions that occurred while it was offline. Before the connector writes change events for an unread transaction to Kafka, it checks the schema history and then applies the schema that was in effect when the original transaction occurred.

Additional information

  • For information about the configuration properties that you can set for each type of connector, see the deployment documentation for the connector in the Debezium User Guide.

2.3. Deploying Debezium with AMQ Streams on Red Hat Enterprise Linux

This procedure describes how to set up connectors for Debezium on Red Hat Enterprise Linux. Connectors are deployed to an AMQ Streams cluster using Apache Kafka Connect, a framework for streaming data between Apache Kafka and external systems. Kafka Connect must be run in distributed mode rather than standalone mode.

Prerequisites

Note

If you are running an earlier version of AMQ Streams, you must first upgrade to AMQ Streams 2.6. For information about the upgrade process, see AMQ Streams and Kafka upgrades.

  • You have administrative privileges (sudo access) on the host.
  • Apache ZooKeeper and the Apache Kafka broker are running.
  • Kafka Connect is running in distributed mode, and not in standalone mode.
  • You know the credentials of the kafka user that was created when AMQ Streams was installed.
  • A source database is deployed and the host where you deploy Debezium has access to the database.
  • You know how you want to configure the connector.

Procedure

  1. Download the Debezium connector or connectors that you want to use from the Red Hat Integration download site. For example, to use Debezium with a MySQL database, download the Debezium 2.5.4 MySQL Connector.
  2. On the Red Hat Enterprise Linux host where you deployed AMQ Streams, open a terminal window and create a connector-plugins directory in /opt/kafka, if it does not already exist:

    $ sudo mkdir /opt/kafka/connector-plugins
  3. Enter the following command to extract the contents of the Debezium connector archive that you downloaded to the /opt/kafka/connector-plugins directory.

    $ sudo unzip debezium-connector-mysql-2.5.4.Final.zip -d /opt/kafka/connector-plugins
  4. Repeat Steps 1 -3 for each connector that you want to install.
  5. From a terminal window, sign in as the kafka user:

    $ su - kafka
    $ Password:
  6. Stop the Kafka Connect process if it is running.

    1. Check whether Kafka Connect is running in distributed mode by entering the following command:

      $ jcmd | grep ConnectDistributed

      If the process is running, the command returns the process ID, for example:

      18514 org.apache.kafka.connect.cli.ConnectDistributed /opt/kafka/config/connect-distributed.properties
    2. Stop the process by entering the kill command with the process ID, for example,

      $ kill 18514
  7. Edit the connect-distributed.properties file in /opt/kafka/config/ and set the value of plugin.path to the location of the parent directory for the Debezium connector plug-ins:

    plugin.path=/opt/kafka/connector-plugins
  8. Start Kafka Connect in distributed mode.

    $ /opt/kafka/bin/connect-distributed.sh /opt/kafka/config/connect-distributed.properties
  9. After Kafka Connect is running, use the Kafka Connect API to register the connector.
    Enter a curl command to submit a POST request that sends the connector configuration JSON that you specified in Section 2.2, “Planning the Debezium connector configuration” to the Kafka Connect REST API endpoint at localhost:8083/connectors.
    For example:

    curl -i -X POST -H "Accept:application/json" -H "Content-Type:application/json" http://localhost:8083/connectors/ -d '{"name": "inventory-connector", "config":
    {"connector.class": "io.debezium.connector.mysql.MySqlConnector",
    "tasks.max": "1",
    "database.hostname": "mysql",
    "database.port": "3306",
    "database.user": "debezium",
    "database.password": "dbz",
    "database.server.id": "184054",
    "topic.prefix": "dbserver1",
    "table.include.list": "public.inventory",
    "schema.history.internal.kafka.bootstrap.servers": "kafka:9092", "schema.history.internal.kafka.topic": "dbhistory.inventory" }
    }'

    To register multiple connectors, submit a separate request for each one.

  10. Restart Kafka Connect to implement your changes.

    As Kafka Connect starts, it loads the configured Debezium connectors from the connector-plugins directory.

    After you complete the configuration, the deployed connector connects to the source database and produces events for each inserted, updated, or deleted row or document.

  11. Repeat Steps 5–10 for each Kafka Connect worker node.

Additional resources

2.4. Verifying the deployment

After the connector starts, it performs a snapshot of the configured database, and creates topics for each table that you specify.

Prerequisites

  • You deployed a connector on Red Hat Enterprise Linux, based on the instructions in Section 2.3, “Deploying Debezium with AMQ Streams on Red Hat Enterprise Linux”. .Procedure

    1. From a terminal window on the host, enter the following command to request the list of connectors from the Kafka Connect API:

      $ curl -H "Accept:application/json" localhost:8083/connectors/

      The query returns the name of the deployed connector, for example:

      ["inventory-connector"]
    2. From a terminal window on the host, enter the following command to view the tasks that the connector is running:

      $ curl -i -X GET -H "Accept:application/json" localhost:8083/connectors/inventory-connector

      The command returns output that is similar to the following example:

      HTTP/1.1 200 OK
      Date: Thu, 06 Feb 2020 22:12:03 GMT
      Content-Type: application/json
      Content-Length: 531
      Server: Jetty(9.4.20.v20190813)
      
      {
        "name": "inventory-connector",
        ...
        "tasks": [
          {
            "connector": "inventory-connector",
            "task": 0
          }
        ]
      }
    3. Display a list of topics in the Kafka cluster.
      From a terminal window, navigate to /opt/kafka/bin/ and run the following shell script:

      ./kafka-topics.sh --bootstrap-server=localhost:9092 --list

      The Kafka broker returns a list of topics that the connector creates. The available topics depends on the settings of the connector’s snapshot.mode,snapshot.include.collection.list, and table.include.list configuration properties. By default, the connector creates a topic for each non-system table in the database.

    4. View the contents of a topic.
      From a terminal window, navigate to /opt/kafka/bin/, and run the kafka-console-consumer.sh shell script to display the contents of one of the topics returned by the preceding command:

      For example:

      ./kafka-console-consumer.sh \
      >     --bootstrap-server localhost:9092 \
      >     --from-beginning \
      >     --property print.key=true \
      >     --topic=dbserver1.inventory.products_on_hand

      For each event in the topic, the command returns information that is similar to the following output:

      Example 2.1. Content of a Debezium change event

      {"schema":{"type":"struct","fields":[{"type":"int32","optional":false,"field":"product_id"}],"optional":false,"name":"dbserver1.inventory.products_on_hand.Key"},"payload":{"product_id":101}}	{"schema":{"type":"struct","fields":[{"type":"struct","fields":[{"type":"int32","optional":false,"field":"product_id"},{"type":"int32","optional":false,"field":"quantity"}],"optional":true,"name":"dbserver1.inventory.products_on_hand.Value","field":"before"},{"type":"struct","fields":[{"type":"int32","optional":false,"field":"product_id"},{"type":"int32","optional":false,"field":"quantity"}],"optional":true,"name":"dbserver1.inventory.products_on_hand.Value","field":"after"},{"type":"struct","fields":[{"type":"string","optional":false,"field":"version"},{"type":"string","optional":false,"field":"connector"},{"type":"string","optional":false,"field":"name"},{"type":"int64","optional":false,"field":"ts_ms"},{"type":"string","optional":true,"name":"io.debezium.data.Enum","version":1,"parameters":{"allowed":"true,last,false"},"default":"false","field":"snapshot"},{"type":"string","optional":false,"field":"db"},{"type":"string","optional":true,"field":"sequence"},{"type":"string","optional":true,"field":"table"},{"type":"int64","optional":false,"field":"server_id"},{"type":"string","optional":true,"field":"gtid"},{"type":"string","optional":false,"field":"file"},{"type":"int64","optional":false,"field":"pos"},{"type":"int32","optional":false,"field":"row"},{"type":"int64","optional":true,"field":"thread"},{"type":"string","optional":true,"field":"query"}],"optional":false,"name":"io.debezium.connector.mysql.Source","field":"source"},{"type":"string","optional":false,"field":"op"},{"type":"int64","optional":true,"field":"ts_ms"},{"type":"struct","fields":[{"type":"string","optional":false,"field":"id"},{"type":"int64","optional":false,"field":"total_order"},{"type":"int64","optional":false,"field":"data_collection_order"}],"optional":true,"field":"transaction"}],"optional":false,"name":"dbserver1.inventory.products_on_hand.Envelope"},"payload":{"before":null,"after":{"product_id":101,"quantity":3},"source":{"version":"2.5.4.Final-redhat-00001","connector":"mysql","name":"inventory_connector_mysql","ts_ms":1638985247805,"snapshot":"true","db":"inventory","sequence":null,"table":"products_on_hand","server_id":0,"gtid":null,"file":"mysql-bin.000003","pos":156,"row":0,"thread":null,"query":null},"op":"r","ts_ms":1638985247805,"transaction":null}}

      In the preceding example, the payload value shows that the connector snapshot generated a read ("op" ="r") event from the table inventory.products_on_hand. The "before" state of the product_id record is null, indicating that no previous value exists for the record. The "after" state shows a quantity of 3 for the item with product_id 101.

Next Steps

For information about the configuration settings that are available for each connector, and to learn how to configure source databases to enable change data capture, see the Debezium User Guide.

2.5. Updating Debezium connector plug-ins in the Kafka Connect cluster

To replace the version of a Debezium connector that is deployed on Red Hat Enterprise Linux, you update the connector plug-in.

Procedure

  1. Download a copy of the Debezium connector plug-in that you want to replace from the Red Hat Integration download site.
  2. Extract the contents of the Debezium connector archive to the /opt/kafka/connector-plugins directory.

    $ sudo unzip debezium-connector-mysql-2.5.4.Final.zip -d /opt/kafka/connector-plugins
  3. Restart Kafka Connect.
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