Try our Experimental-AI powered search above!

The YugabyteDB Connector is based on the Debezium Connector, and captures row-level changes in the schemas of a YugabyteDB database using the PostgreSQL replication protocol.

The first time it connects to a YugabyteDB server, the connector takes a consistent snapshot of all schemas. After that snapshot is complete, the connector continuously captures row-level changes that insert, update, and delete database content, and that were committed to a YugabyteDB database. The connector generates data change event records and streams them to Kafka topics. For each table, the default behavior is that the connector streams all generated events to a separate Kafka topic for that table. Applications and services consume data change event records from that topic.

Overview

YugabyteDB CDC using logical decoding is a mechanism that allows the extraction of changes that were committed to the transaction log and the processing of these changes in a user-friendly manner with the help of a PostgreSQL output plugin. The output plugin enables clients to consume the changes.

The YugabyteDB connector contains two main parts that work together to read and process database changes:

• You must configure a replication slot that uses your chosen output plugin before running the YugabyteDB server. The plugin can be one of the following:

  • yboutput is the plugin packaged with YugabyteDB. It is maintained by Yugabyte and is always present with the distribution.

  • pgoutput is the standard logical decoding output plugin in PostgreSQL 10+. It is maintained by the PostgreSQL community, and used by PostgreSQL itself for logical replication. YugabyteDB bundles this plugin with the standard distribution so it is always present and no additional libraries need to be installed. The YugabyteDB connector interprets the raw replication event stream directly into change events.

• Java code (the actual Kafka Connect connector) that reads the changes produced by the chosen logical decoding output plugin. It uses the streaming replication protocol, by means of the YugabyteDB JDBC driver.

The connector produces a change event for every row-level insert, update, and delete operation that was captured, and sends change event records for each table in a separate Kafka topic. Client applications read the Kafka topics that correspond to the database tables of interest, and can react to every row-level event they receive from those topics.

YugabyteDB normally purges write-ahead log (WAL) segments after some period of time. This means that the connector does not have the complete history of all changes that have been made to the database. Therefore, when the YugabyteDB connector first connects to a particular YugabyteDB database, it starts by performing a consistent snapshot of each of the configured tables. After the connector completes the snapshot, it continues streaming changes from the exact point at which the snapshot was made. This way, the connector starts with a consistent view of all of the data, and does not omit any changes that were made while the snapshot was being taken.

The connector is tolerant of failures. As the connector reads changes and produces events, it records the LSN for each event. If the connector stops for any reason (including communication failures, network problems, or crashes), upon restart the connector continues reading the WAL where it last left off.

How the connector works

To optimally configure and run a Debezium connector, it is helpful to understand how the connector performs snapshots, streams change events, determines Kafka topic names, and uses metadata.

Security

To use the Debezium connector to stream changes from a YugabyteDB database, the connector must operate with specific privileges in the database. Although one way to grant the necessary privileges is to provide the user with superuser privileges, doing so potentially exposes your YugabyteDB data to unauthorized access. Rather than granting excessive privileges to the Debezium user, it is best to create a dedicated Debezium replication user to which you grant specific privileges.

For more information about configuring privileges for the Debezium replication user, see Setting up permissions.

Snapshots

Most YugabyteDB servers are configured to not retain the complete history of the database in the WAL segments. This means that the YugabyteDB connector would be unable to see the entire history of the database by reading only the WAL. Consequently, the first time that the connector starts, it performs an initial consistent snapshot of the database.

Default workflow behavior of initial snapshots

The default behavior for performing a snapshot consists of the following steps. You can change this behavior by setting the snapshot.mode connector configuration property to a value other than initial.

1. Start a transaction.
2. Set the transaction read time to the consistent point associated with the replication slot.
3. Execute snapshot through the execution of a SELECT query.
4. Generate a READ event for each row and write to the appropriate table-specific Kafka topic.
5. Record successful completion of the snapshot in the connector offsets.

If the connector fails, is rebalanced, or stops after Step 1 begins but before Step 5 completes, upon restart the connector begins a new snapshot. After the connector completes its initial snapshot, the YugabyteDB connector continues streaming from the position that it read in Step 2. This ensures that the connector does not miss any updates. If the connector stops again for any reason, upon restart, the connector continues streaming changes from where it previously left off.

The following table describes the options for the snapshot.mode connector configuration property.

Streaming changes

The YugabyteDB connector typically spends the vast majority of its time streaming changes from the YugabyteDB server to which it is connected. This mechanism relies on PostgreSQL's replication protocol. This protocol enables clients to receive changes from the server as they are committed in the server's transaction logs.

Whenever the server commits a transaction, a separate server process invokes a callback function from the logical decoding plugin. This function processes the changes from the transaction, converts them to a specific format and writes them on an output stream, which can then be consumed by clients.

The YugabyteDB connector acts as a YugabyteDB client. When the connector receives changes it transforms the events into Debezium create, update, or delete events that include the LSN of the event. The YugabyteDB connector forwards these change events in records to the Kafka Connect framework, which is running in the same process. The Kafka Connect process asynchronously writes the change event records in the same order in which they were generated to the appropriate Kafka topic.

Periodically, Kafka Connect records the most recent offset in another Kafka topic. The offset indicates source-specific position information that Debezium includes with each event. For the YugabyteDB connector, the LSN recorded in each change event is the offset.

When Kafka Connect gracefully shuts down, it stops the connectors, flushes all event records to Kafka, and records the last offset received from each connector. When Kafka Connect restarts, it reads the last recorded offset for each connector, and starts each connector at its last recorded offset. When the connector restarts, it sends a request to the YugabyteDB server to send the events starting just after that position.

Logical decoding plugin support

As of YugabyteDB v2024.1.1 and later, YugabyteDB supports the yboutput plugin, a native output plugin for logical decoding.

Additionally, YugabyteDB also supports the PostgreSQL pgoutput plugin natively. This means that the YugabyteDB connector can work with an existing setup configured using pgoutput.

Topic names

By default, the YugabyteDB connector writes change events for all INSERT, UPDATE, and DELETE operations that occur in a table to a single Apache Kafka topic that is specific to that table. The connector names change event topics as topicPrefix.schemaName.tableName.

The components of a topic name are as follows:

• topicPrefix - the topic prefix as specified by the topic.prefix configuration property.
• schemaName - the name of the database schema in which the change event occurred.
• tableName - the name of the database table in which the change event occurred.

For example, suppose that dbserver is the topic prefix in the configuration for a connector that is capturing changes in a YugabyteDB installation that has a yugabyte database and an inventory schema that contains four tables: products, products_on_hand, customers, and orders. The connector would stream records to these four Kafka topics:

• dbserver.inventory.products
• dbserver.inventory.products_on_hand
• dbserver.inventory.customers
• dbserver.inventory.orders

Now suppose that the tables are not part of a specific schema but were created in the default public YugabyteDB schema. The names of the Kafka topics would be:

• dbserver.public.products
• dbserver.public.products_on_hand
• dbserver.public.customers
• dbserver.public.orders

The connector applies similar naming conventions to label its transaction metadata topics.

If the default topic names don't meet your requirements, you can configure custom topic names. To configure custom topic names, you specify regular expressions in the logical topic routing SMT. For more information about using the logical topic routing SMT to customize topic naming, see the Debezium documentation on Topic routing.

Transaction metadata

Debezium can generate events that represent transaction boundaries and that enrich data change event messages.

For every transaction BEGIN and END, Debezium generates an event containing the following fields:

• status - BEGIN or END.
• id - String representation of the unique transaction identifier composed of YugabyteDB transaction ID itself and LSN of given operation separated by colon, that is, the format is txID:LSN.
• ts_ms - The time of a transaction boundary event (BEGIN or END event) at the data source. If the data source does not provide Debezium with the event time, then the field instead represents the time at which Debezium processes the event.
• event_count (for END events) - total number of events emitted by the transaction.
• data_collections (for END events) - an array of pairs of data_collection and event_count that provides the number of events emitted by changes originating from given data collection.

For example:

{
  "status": "BEGIN",
  "id": "571:53195829",
  "ts_ms": 1486500577125,
  "event_count": null,
  "data_collections": null
}

{
  "status": "END",
  "id": "571:53195832",
  "ts_ms": 1486500577691,
  "event_count": 2,
  "data_collections": [
    {
      "data_collection": "s1.a",
      "event_count": 1
    },
    {
      "data_collection": "s2.a",
      "event_count": 1
    }
  ]
}

Unless overridden via the transaction.topic option, transaction events are written to the topic and named <topic.prefix>.transaction.

Change data event enrichment

When transaction metadata is enabled the data message Envelope is enriched with a new transaction field. This field provides information about every event in the form of a composite of fields:

• id - string representation of unique transaction identifier
• total_order - absolute position of the event among all events generated by the transaction
• data_collection_order - the per-data collection position of the event among all events emitted by the transaction

Following is an example of a message:

{
  "before": null,
  "after": {
    "pk": "2",
    "aa": "1"
  },
  "source": {
   ...
  },
  "op": "c",
  "ts_ms": "1580390884335",
  "transaction": {
    "id": "571:53195832",
    "total_order": "1",
    "data_collection_order": "1"
  }
}

Data change events

The YugabyteDB connector generates a data change event for each row-level INSERT, UPDATE, and DELETE operation. Each event contains a key and a value. The structure of the key and the value depends on the table that was changed.

Debezium and Kafka Connect are designed around continuous streams of event messages. However, the structure of these events may change over time, which can be difficult for consumers to handle. To address this, each event contains the schema for its content or, if you are using a schema registry, a schema ID that a consumer can use to obtain the schema from the registry. This makes each event self-contained.

The following skeleton JSON shows the basic four parts of a change event. However, how you configure the Kafka Connect converter that you choose to use in your application determines the representation of these four parts in change events. A schema field is in a change event only when you configure the converter to produce it. Likewise, the event key and event payload are in a change event only if you configure a converter to produce it. If you use the JSON converter and you configure it to produce all four basic change event parts, change events have this structure:

{
 "schema": { --> 1
   ...
  },
 "payload": { --> 2
   ...
 },
 "schema": { --> 3
   ...
  },
 "payload": { --> 4
   ...
 }
}

The following table describes the content of the change events.

By default, the connector streams change event records to Kafka topics with names that are the same as the event's originating table.

Change event keys

For a given table, the change event's key has a structure that contains a field for each column in the primary key of the table at the time the event was created. Alternatively, if the table has REPLICA IDENTITY set to FULL there is a field for each unique key constraint.

Consider a customers table defined in the public database schema and the example of a change event key for that table.

Example table:

CREATE TABLE customers (
  id SERIAL,
  first_name VARCHAR(255) NOT NULL,
  last_name VARCHAR(255) NOT NULL,
  email VARCHAR(255) NOT NULL,
  PRIMARY KEY(id)
);

Example change event key

If the topic.prefix connector configuration property has the value YugabyteDB_server, every change event for the customers table while it has this definition has the same key structure, which in JSON looks like this:

{
  "schema": { --> 1
    "type": "struct",
    "name": "YugabyteDB_server.public.customers.Key", --> 2
    "optional": false, --> 3
    "fields": [ --> 4
          {
              "name": "id",
              "index": "0",
              "schema": {
                  "type": "INT32",
                  "optional": "false"
              }
          }
      ]
  },
  "payload": { --> 5
      "id": "1"
  },
}

Description of a change event key:

Change event values

The value in a change event is a bit more complicated than the key. Like the key, the value has a schema section and a payload section. The schema section contains the schema that describes the Envelope structure of the payload section, including its nested fields. Change events for operations that create, update or delete data all have a value payload with an envelope structure.

Consider the same sample table that was used to show an example of a change event key:

CREATE TABLE customers (
  id SERIAL,
  first_name VARCHAR(255) NOT NULL,
  last_name VARCHAR(255) NOT NULL,
  email VARCHAR(255) NOT NULL,
  PRIMARY KEY(id)
);

The value portion of a change event for a change to this table varies according to the REPLICA IDENTITY setting and the operation that the event is for.

Replica Identity

REPLICA IDENTITY is a YugabyteDB-specific table-level setting that determines the amount of information that is available to the logical decoding plugin for UPDATE and DELETE events. More specifically, the setting of REPLICA IDENTITY controls what (if any) information is available for the previous values of the table columns involved, whenever an UPDATE or DELETE event occurs.

There are 4 possible values for REPLICA IDENTITY:

• CHANGE - Emitted events for UPDATE operations will only contain the value of the changed column along with the primary key column with no previous values present. DELETE operations will only contain the previous value of the primary key column in the table.
• DEFAULT - The default behavior is that only DELETE events contain the previous values for the primary key columns of a table. For an UPDATE event, no previous values will be present and the new values will be present for all the columns in the table.
• FULL - Emitted events for UPDATE and DELETE operations contain the previous values of all columns in the table.
• NOTHING - Emitted events for UPDATE and DELETE operations do not contain any information about the previous value of any table column.

Message formats for replica identities

Consider the following employee table into which a row is inserted, subsequently updated, and deleted:

CREATE TABLE employee (
  employee_id INT PRIMARY KEY,
  employee_name VARCHAR,
  employee_dept TEXT);

INSERT INTO employee VALUES (1001, 'Alice', 'Packaging');

UPDATE employee SET employee_name = 'Bob' WHERE employee_id = 1001;

DELETE FROM employee WHERE employee_id = 1001;

• CHANGE
• DEFAULT
• FULL
• NOTHING

{
  "before": null,
  "after": {
    "employee_id": {
        "value": 1001,
        "set": true
    },
    "employee_name": {
      "value": "Alice",
      "set": true
    },
    "employee_dept": {
        "value": "Packaging",
        "set": true
    }
  }
  "op": "c"
}

{
  "before": null,
  "after": {
    "employee_id": {
        "value": 1001,
        "set": true
    },
    "employee_name": {
      "value": "Bob",
      "set": true
    },
    "employee_dept": null
  }
  "op": "u"
}

{
  "before": {
    "employee_id": {
      "value": 1001,
      "set": true
    },
    "employee_name": null,
    "employee_dept": null
  },
  "after": null,
  "op": "d"
}

{
  "before": null,
  "after": {
    "employee_id": {
        "value": 1001,
        "set": true
    },
    "employee_name": {
      "value": "Alice",
      "set": true
    },
    "employee_dept": {
        "value": "Packaging",
        "set": true
    }
  }
  "op": "c"
}

{
  "before": null,
  "after": {
    "employee_id": {
        "value": 1001,
        "set": true
    },
    "employee_name": {
      "value": "Bob",
      "set": true
    },
    "employee_dept": null
  }
  "op": "u"
}

{
  "before": {
    "employee_id": {
      "value": 1001,
      "set": true
    },
    "employee_name": null,
    "employee_dept": null
  },
  "after": null,
  "op": "d"
}

{
  "before": null,
  "after": {
    "employee_id": 1001,
    "employee_name": "Alice",
    "employee_dept": "Packaging"
  }
  "op": "c"
}

{
  "before": null,
  "after": {
    "employee_id": 1001,
    "employee_name": "Bob",
    "employee_dept": "Packaging"
  }
  "op": "u"
}

{
  "before": {
    "employee_id": 1001
  },
  "after": null,
  "op": "d"
}

{
  "before": null,
  "after": {
    "employee_id": {
        "value": 1001,
        "set": true
    },
    "employee_name": {
      "value": "Alice",
      "set": true
    },
    "employee_dept": {
        "value": "Packaging",
        "set": true
    }
  }
  "op": "c"
}

{
  "before": {
    "employee_id": {
        "value": 1001,
        "set": true
    },
    "employee_name": {
      "value": "Alice",
      "set": true
    },
    "employee_dept": {
      "value": "Packaging",
      "set": true
    }
  },
  "after": {
    "employee_id": {
        "value": 1001,
        "set": true
    },
    "employee_name": {
      "value": "Bob",
      "set": true
    },
    "employee_dept": {
      "value": "Packaging",
      "set": true
    }
  }
  "op": "u"
}

{
  "before": {
    "employee_id": {
    "employee_id": {
        "value": 1001,
        "set": true
    },
    "employee_name": {
      "value": "Bob",
      "set": true
    },
    "employee_dept": {
      "value": "Packaging",
      "set": true
    }
  },
  "after": null,
  "op": "d"
}

{
  "before": null,
  "after": {
    "employee_id": 1001,
    "employee_name": "Alice",
    "employee_dept": "Packaging",
    }
  }
  "op": "c"
}

{
  "before": {
    "employee_id": 1001,
    "employee_name": "Alice",
    "employee_dept": "Packaging"
  },
  "after": {
    "employee_id": 1001,
    "employee_name": "Bob",
    "employee_dept": "Packaging"
  }
  "op": "u"
}

{
  "before": {
    "employee_id": 1001,
    "employee_name": "Bob",
    "employee_dept": "Packaging"
  },
  "after": null,
  "op": "d"
}

{
  "before": null,
  "after": {
    "employee_id": {
        "value": 1001,
        "set": true
    },
    "employee_name": {
      "value": "Alice",
      "set": true
    },
    "employee_dept": {
        "value": "Packaging",
        "set": true
    }
  }
  "op": "c"
}

{
  "before": null,
  "after": {
    "employee_id": 1001,
    "employee_name": "Alice",
    "employee_dept": "Packaging",
  }
  "op": "c"
}

create events

The following example shows the value portion of a change event that the connector generates for an operation that creates data in the customers table:

{
    "schema": { --> 1
        "type": "struct",
        "fields": [
            {
                "type": "struct",
                "fields": [
                    {
                        "type": "int32",
                        "optional": false,
                        "field": "id"
                    },
                    {
                        "type": "string",
                        "optional": false,
                        "field": "first_name"
                    },
                    {
                        "type": "string",
                        "optional": false,
                        "field": "last_name"
                    },
                    {
                        "type": "string",
                        "optional": false,
                        "field": "email"
                    }
                ],
                "optional": true,
                "name": "YugabyteDB_server.inventory.customers.Value", --> 2
                "field": "before"
            },
            {
                "type": "struct",
                "fields": [
                    {
                        "type": "int32",
                        "optional": false,
                        "field": "id"
                    },
                    {
                        "type": "string",
                        "optional": false,
                        "field": "first_name"
                    },
                    {
                        "type": "string",
                        "optional": false,
                        "field": "last_name"
                    },
                    {
                        "type": "string",
                        "optional": false,
                        "field": "email"
                    }
                ],
                "optional": true,
                "name": "YugabyteDB_server.inventory.customers.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": "boolean",
                        "optional": true,
                        "default": false,
                        "field": "snapshot"
                    },
                    {
                        "type": "string",
                        "optional": false,
                        "field": "db"
                    },
                    {
                        "type": "string",
                        "optional": false,
                        "field": "schema"
                    },
                    {
                        "type": "string",
                        "optional": false,
                        "field": "table"
                    },
                    {
                        "type": "int64",
                        "optional": true,
                        "field": "txId"
                    },
                    {
                        "type": "int64",
                        "optional": true,
                        "field": "lsn"
                    },
                    {
                        "type": "int64",
                        "optional": true,
                        "field": "xmin"
                    }
                ],
                "optional": false,
                "name": "io.debezium.connector.postgresql.Source", --> 3
                "field": "source"
            },
            {
                "type": "string",
                "optional": false,
                "field": "op"
            },
            {
                "type": "int64",
                "optional": true,
                "field": "ts_ms"
            }
        ],
        "optional": false,
        "name": "YugabyteDB_server.public.customers.Envelope" --> 4
    },
    "payload": { --> 5
        "before": null, --> 6 
        "after": { --> 7
            "id": 1,
            "first_name": "Anne",
            "last_name": "Kretchmar",
            "email": "annek@noanswer.org"
        },
        "source": { --> 8
            "version": "2.5.2.Final",
            "connector": "YugabyteDB",
            "name": "YugabyteDB_server",
            "ts_ms": 1559033904863,
            "snapshot": true,
            "db": "postgres",
            "sequence": "[\"24023119\",\"24023128\"]",
            "schema": "public",
            "table": "customers",
            "txId": 555,
            "lsn": 24023128,
            "xmin": null
        },
        "op": "c", --> 9
        "ts_ms": 1559033904863 --> 10
    }
}

The following table describes the create event value fields.

update events

The value of a change event for an update in the sample customers table has the same schema as a create event for that table. Likewise, the event value's payload has the same structure. However, the event value payload contains different values in an update event. The following is an example of a change event value in an event that the connector generates for an update in the customers table:

{
    "schema": { ... },
    "payload": {
        "before": null, --> 1
        "after": { --> 2
            "id": 1,
            "first_name": "Anne Marie",
            "last_name": "Kretchmar",
            "email": "annek@noanswer.org"
        },
        "source": { --> 3
            "version": "2.5.2.Final",
            "connector": "YugabyteDB",
            "name": "YugabyteDB_server",
            "ts_ms": 1559033904863,
            "snapshot": false,
            "db": "postgres",
            "schema": "public",
            "table": "customers",
            "txId": 556,
            "lsn": 24023128,
            "xmin": null
        },
        "op": "u", --> 4
        "ts_ms": 1465584025523 --> 5
    }
}

The following table describes the update event value fields.

Primary key updates

An UPDATE operation that changes a row's primary key field(s) is known as a primary key change. For a primary key change, in place of sending an UPDATE event record, the connector sends a DELETE event record for the old key and a CREATE event record for the new (updated) key.

delete events

The value in a delete change event has the same schema portion as create and update events for the same table. The payload portion in a delete event for the sample customers table looks like this:

{
    "schema": { ... },
    "payload": {
        "before": { --> 1
            "id": 1
        },
        "after": null, --> 2
        "source": { --> 3
            "version": "2.5.4.Final",
            "connector": "YugabyteDB",
            "name": "YugabyteDB_server",
            "ts_ms": 1559033904863,
            "snapshot": false,
            "db": "postgres",
            "schema": "public",
            "table": "customers",
            "txId": 556,
            "lsn": 46523128,
            "xmin": null
        },
        "op": "d", --> 4
        "ts_ms": 1465581902461 --> 5
    }
}

The following table describes the delete event value fields.

A delete change event record provides a consumer with the information it needs to process the removal of this row.

YugabyteDB connector events are designed to work with Kafka log compaction. Log compaction enables removal of some older messages as long as at least the most recent message for every key is kept. This lets Kafka reclaim storage space while ensuring that the topic contains a complete data set and can be used for reloading key-based state.

Tombstone events

When a row is deleted, the delete event value still works with log compaction, because Kafka can remove all earlier messages that have that same key. However, for Kafka to remove all messages that have that same key, the message value must be null. To make this possible, the YugabyteDB connector follows a delete event with a special tombstone event that has the same key but a null value.

Data type mappings

The YugabyteDB connector represents changes to rows with events that are structured like the table in which the row exists. The event contains a field for each column value. How that value is represented in the event depends on the YugabyteDB data type of the column. The following sections describe how the connector maps YugabyteDB data types to a literal type and a semantic type in event fields.

• literal type describes how the value is literally represented using Kafka Connect schema types: INT8, INT16, INT32, INT64, FLOAT32, FLOAT64, BOOLEAN, STRING, BYTES, ARRAY, MAP, and STRUCT.
• semantic type describes how the Kafka Connect schema captures the meaning of the field using the name of the Kafka Connect schema for the field.

If the default data type conversions do not meet your needs, you can create a custom converter for the connector.

Basic types

Temporal types

Other than YugabyteDB's TIMESTAMPTZ and TIMETZ data types, which contain time zone information, how temporal types are mapped depends on the value of the time.precision.mode connector configuration property. The following sections describe these mappings:

• time.precision.mode=adaptive
• time.precision.mode=adaptive_time_microseconds
• time.precision.mode=connect

time.precision.mode=adaptive

When the time.precision.mode property is set to adaptive, the default, the connector determines the literal type and semantic type based on the column's data type definition. This ensures that events exactly represent the values in the database.

time.precision.mode=adaptive_time_microseconds

When the time.precision.mode configuration property is set to adaptive_time_microseconds, the connector determines the literal type and semantic type for temporal types based on the column's data type definition. This ensures that events exactly represent the values in the database, except all TIME fields are captured as microseconds.

time.precision.mode=connect

When the time.precision.mode configuration property is set to connect, the connector uses Kafka Connect logical types. This may be useful when consumers can handle only the built-in Kafka Connect logical types and are unable to handle variable-precision time values. However, because YugabyteDB supports microsecond precision, the events generated by a connector with the connect time precision mode results in a loss of precision when the database column has a fractional second precision value that is greater than 3.

TIMESTAMP type

The TIMESTAMP type represents a timestamp without time zone information. Such columns are converted into an equivalent Kafka Connect value based on UTC. For example, the TIMESTAMP value "2018-06-20 15:13:16.945104" is represented by an io.debezium.time.MicroTimestamp with the value "1529507596945104" when time.precision.mode is not set to connect.

The timezone of the JVM running Kafka Connect and Debezium does not affect this conversion.

YugabyteDB supports using +/-infinite values in TIMESTAMP columns. These special values are converted to timestamps with value 9223372036825200000 in case of positive infinity or -9223372036832400000 in case of negative infinity. This behavior mimics the standard behavior of the YugabyteDB JDBC driver. For reference, see the org.postgresql.PGStatement interface.

Decimal types

The setting of the YugabyteDB connector configuration property decimal.handling.mode determines how the connector maps decimal types.

decimal.handling.mode=double

When the decimal.handling.mode property is set to double, the connector represents all DECIMAL, NUMERIC and MONEY values as Java double values and encodes them as shown in the following table.

decimal.handling.mode=string

The last possible setting for the decimal.handling.mode configuration property is string. In this case, the connector represents DECIMAL, NUMERIC and MONEY values as their formatted string representation, and encodes them as shown in the following table.

HSTORE types

The setting of the YugabyteDB connector configuration property hstore.handling.mode determines how the connector maps HSTORE values.

When the hstore.handling.mode property is set to json (the default), the connector represents HSTORE values as string representations of JSON values and encodes them as shown in the following table. When the hstore.handling.mode property is set to map, the connector uses the MAP schema type for HSTORE values.

Domain types

YugabyteDB supports user-defined types that are based on other underlying types. When such column types are used, Debezium exposes the column's representation based on the full type hierarchy.

Network address types

YugabyteDB has data types that can store IPv4, IPv6, and MAC addresses. It is better to use these types instead of plain text types to store network addresses. Network address types offer input error checking and specialized operators and functions.

Setting up YugabyteDB

Setting up permissions

Setting up a YugabyteDB server to run a Debezium connector requires a database user that can perform replications. Replication can be performed only by a database user that has appropriate permissions and only for a configured number of hosts.

Although, by default, superusers have the necessary REPLICATION and LOGIN roles, as mentioned in Security, it is best not to provide the Debezium replication user with elevated privileges. Instead, create a Debezium user that has the minimum required privileges.

Prerequisites:

• YugabyteDB administrative permissions.

Procedure:

To provide a user with replication permissions, define a YugabyteDB role that has at least the REPLICATION and LOGIN permissions, and then grant that role to the user. For example:

CREATE ROLE <name> REPLICATION LOGIN;

Setting privileges to enable Debezium to create YugabyteDB publications when you use pgoutput or yboutput

If you use pgoutput or yboutput as the logical decoding plugin, Debezium must operate in the database as a user with specific privileges.

Debezium streams change events for YugabyteDB source tables from publications that are created for the tables. Publications contain a filtered set of change events that are generated from one or more tables. The data in each publication is filtered based on the publication specification. The specification can be created by the YugabyteDB database administrator or by the Debezium connector. To permit the Debezium connector to create publications and specify the data to replicate to them, the connector must operate with specific privileges in the database.

There are several options for determining how publications are created. In general, it is best to manually create publications for the tables that you want to capture, before you set up the connector. However, you can configure your environment in a way that permits Debezium to create publications automatically, and to specify the data that is added to them.

Debezium uses include list and exclude list properties to specify how data is inserted in the publication. For more information about the options for enabling Debezium to create publications, see publication.autocreate.mode.

For Debezium to create a YugabyteDB publication, it must run as a user that has the following privileges:

• Replication privileges in the database to add the table to a publication.
• CREATE privileges on the database to add publications.
• SELECT privileges on the tables to copy the initial table data. Table owners automatically have SELECT permission for the table.

To add tables to a publication, the user must be an owner of the table. But because the source table already exists, you need a mechanism to share ownership with the original owner. To enable shared ownership, create a YugabyteDB replication group, then add the existing table owner and the replication user to the group.

Procedure

1. Create a replication group.

   CREATE ROLE <replication_group>;
   

2. Add the original owner of the table to the group.

   GRANT REPLICATION_GROUP TO <original_owner>;
   

3. Add the Debezium replication user to the group.

   GRANT REPLICATION_GROUP TO <replication_user>;
   

4. Transfer ownership of the table to <replication_group>.

   ALTER TABLE <table_name> OWNER TO REPLICATION_GROUP;
   

For Debezium to specify the capture configuration, the value of publication.autocreate.mode must be set to filtered.

Configuring YugabyteDB to allow replication with the Debezium connector host

To enable Debezium to replicate YugabyteDB data, you must configure the database to permit replication with the host that runs the YugabyteDB connector. To specify the clients that are permitted to replicate with the database, add entries to the YugabyteDB host-based authentication file, ysql_hba.conf. For more information about the pg_hba.conf file, see the YugabyteDB documentation.

Procedure

• Add entries to the ysql_hba.conf file to specify the Debezium connector hosts that can replicate with the database host. For example,

--ysql_hba_conf_csv="local replication <yourUser> trust, local replication <yourUser> 127.0.0.1/32 trust, host replication <yourUser> ::1/128 trust"

Supported YugabyteDB topologies

As mentioned in the beginning, YugabyteDB (for all versions > 2024.1.1) supports logical replication slots. The YugabyteDB connector can communicate with the server by connecting to any node using the YugabyteDB Java driver. Should any node fail, the connector receives an error and restarts. Upon restart, the connector connects to any available node and continues streaming from that node.

Setting up multiple connectors for same database server

Debezium uses replication slots to stream changes from a database. These replication slots maintain the current position in form of a LSN. This helps YugabyteDB keep the WAL available until it is processed by Debezium. A single replication slot can exist only for a single consumer or process - as different consumer might have different state and may need data from different position.

Because a replication slot can only be used by a single connector, it is essential to create a unique replication slot for each Debezium connector. Although when a connector is not active, YugabyteDB may allow other connectors to consume the replication slot - which could be dangerous as it may lead to data loss as a slot will emit each change just once.

In addition to replication slot, Debezium uses publication to stream events when using the pgoutputor yboutput plugin. Similar to replication slot, publication is at database level and is defined for a set of tables. Thus, you'll need a unique publication for each connector, unless the connectors work on same set of tables. For more information about the options for enabling Debezium to create publications, see publication.autocreate.mode.

See slot.name and publication.name on how to set a unique replication slot name and publication name for each connector.

Deployment

To deploy the connector, you install the connector archive, configure the connector, and start the connector by adding its configuration to Kafka Connect.

Prerequisites

• Zookeeper, Kafka, and Kafka Connect are installed.
• YugabyteDB is installed and is set up to run the Debezium connector.

Procedure

1. Download the YugabyteDB connector plugin archive.
2. Extract the files into your Kafka Connect environment.
3. Add the directory with the JAR files to the Kafka Connect plugin.path.
4. Restart your Kafka Connect process to pick up the new JAR files.

Creating Kafka topics

If auto creation of topics is not enabled in the Kafka Connect cluster then you will need to create the following topics manually:

• Topic for each table in the format <topic.prefix>.<schemaName>.<tableName>
• Heartbeat topic in the format <topic.heartbeat.prefix>.<topic.prefix>. The topic.heartbeat.prefix has a default value of __debezium-heartbeat.

Connector configuration example

Following is an example of the configuration for a YugabyteDB connector that connects to a YugabyteDB server on port 5433 at 192.168.99.100, whose topic prefix is fulfillment. Typically, you configure the YugabyteDB connector in a JSON file by setting the configuration properties available for the connector.

You can choose to produce events for a subset of the schemas and tables in a database. Optionally, you can ignore, mask, or truncate columns that contain sensitive data, are larger than a specified size, or that you do not need.

{
  "name": "fulfillment-connector",  --> 1
  "config": {
    "connector.class": "io.debezium.connector.postgresql.YugabyteDBConnector", --> 2
    "database.hostname": "192.168.99.100:5433,192.168.1.10:5433,192.168.1.68:5433", --> 3
    "database.port": "5432", --> 4
    "database.user": "postgres", --> 5
    "database.password": "postgres", --> 6
    "database.dbname" : "postgres", --> 7
    "topic.prefix": "fulfillment", --> 8
    "table.include.list": "public.inventory" --> 9
  }
}

1. The name of the connector when registered with a Kafka Connect service.
2. The name of this YugabyteDB connector class.
3. The addresses of the YugabyteDB YB-TServer nodes. This can take a value of multiple addresses in the format IP1:PORT1,IP2:PORT2,IP3:PORT3.
4. The port number of the YugabyteDB server.
5. The name of the YugabyteDB user that has the required privileges.
6. The password for the YugabyteDB user that has the required privileges.
7. The name of the YugabyteDB database to connect to
8. The topic prefix for the YugabyteDB server/cluster, which forms a namespace and is used in all the names of the Kafka topics to which the connector writes, the Kafka Connect schema names, and the namespaces of the corresponding Avro schema when the Avro converter is used.
9. A list of all tables hosted by this server that this connector will monitor. This is optional, and there are other properties for listing the schemas and tables to include or exclude from monitoring.

See the complete list of YugabyteDB connector properties that can be specified in these configurations.

You can send this configuration with a POST command to a running Kafka Connect service. The service records the configuration and starts one connector task that performs the following actions:

• Connects to the YugabyteDB database.
• Reads the transaction log.
• Streams change event records to Kafka topics.

Adding connector configuration

To run a the connector, create a connector configuration and add the configuration to your Kafka Connect cluster.

Prerequisites

• YugabyteDB is configured to support logical replication.
• The YugabyteDB connector is installed.

Procedure

1. Create a configuration for the YugabyteDB connector.
2. Use the Kafka Connect REST API to add that connector configuration to your Kafka Connect cluster.

Results

After the connector starts, it performs a consistent snapshot of the YugabyteDB server databases that the connector is configured for. The connector then starts generating data change events for row-level operations and streaming change event records to Kafka topics.

Connector properties

The connector has many configuration properties that you can use to achieve the right connector behavior for your application. Many properties have default values. Information about the properties is organized as follows:

• Required configuration properties
• Advanced configuration properties
• Pass-through configuration properties

The following configuration properties are required unless a default value is available.

Required configuration properties

Advanced configuration properties

The following advanced configuration properties have defaults that work in most situations and therefore rarely need to be specified in the connector's configuration.

Pass-through configuration properties

The connector also supports pass-through configuration properties that are used when creating the Kafka producer and consumer.

Be sure to consult the Kafka documentation for all of the configuration properties for Kafka producers and consumers. The YugabyteDB connector does use the new consumer configuration properties.

Monitoring

The YugabyteDB connector provides two metrics in addition to the built-in support for JMX metrics that Zookeeper, Kafka, and Kafka Connect provide:

• Snapshot metrics provide information about connector operation while performing a snapshot.
• Streaming metrics provide information about connector operation when the connector is capturing changes and streaming change event records.

Debezium monitoring documentation provides details for how to expose these metrics by using JMX.

Snapshot metrics

The MBean is debezium.postgres:type=connector-metrics,context=snapshot,server=<topic.prefix>.

Snapshot metrics are not exposed unless a snapshot operation is active, or if a snapshot has occurred since the last connector start.

The following table lists the snapshot metrics that are available.

Streaming metrics

The MBean is debezium.postgres:type=connector-metrics,context=streaming,server=<topic.prefix>.

The following table lists the streaming metrics that are available.

Behavior when things go wrong

Debezium is a distributed system that captures all changes in multiple upstream databases; it never misses or loses an event. When the system is operating normally or being managed carefully then Debezium provides exactly once delivery of every change event record. If a fault does happen then the system does not lose any events. However, while it is recovering from the fault, it's possible that the connector might emit some duplicate change events. In these abnormal situations, Debezium, like Kafka, provides at least once delivery of change events.

The rest of this section describes how Debezium handles various kinds of faults and problems.

Configuration and startup errors

In the following situations, the connector fails when trying to start, reports an error/exception in the log, and stops running:

• The connector's configuration is invalid.
• The connector cannot successfully connect to YugabyteDB by using the specified connection parameters.
• The connector is restarting from a previously-recorded LSN and YugabyteDB no longer has that history available.

In these cases, the error message has details about the problem and possibly a suggested workaround. After you correct the configuration or address the YugabyteDB problem, restart the connector.

YB-TServer becomes unavailable

When the connector is running, the YB-TServer that it is connected to could become unavailable for any number of reasons. If this happens, the connector fails with an error and retries to connect to the YugabyteDB server. Because the connector uses the YugabyteDB Java driver, the connection is handled internally and the connector restores the connection to another running node.

The YugabyteDB connector externally stores the last processed offset in the form of a YugabyteDB LSN. After a connector restarts and connects to a server instance, the connector communicates with the server to continue streaming from that particular offset. This offset is available as long as the Debezium replication slot remains intact.

Cluster failures

When the connector is running, it is possible that the YugabyteDB server becomes unavailable for any number of reasons. If that happens, the connector fails with and error and initiates retries but as the complete YugabyteDB server is unavailable, all the retries will fail.

When the YugabyteDB server is back up, restart the connector to continue streaming where it left off.

Kafka Connect process stops gracefully

Suppose that Kafka Connect is being run in distributed mode and a Kafka Connect process is stopped gracefully. Prior to shutting down that process, Kafka Connect migrates the process's connector tasks to another Kafka Connect process in that group. The new connector tasks start processing exactly where the prior tasks stopped. There is a short delay in processing while the connector tasks are stopped gracefully and restarted on the new processes.

Kafka Connect process crashes

If the Kafka Connector process stops unexpectedly, any connector tasks it was running terminate without recording their most recently processed offsets. When Kafka Connect is being run in distributed mode, Kafka Connect restarts those connector tasks on other processes. However, YugabyteDB connectors resume from the last offset that was recorded by the earlier processes. This means that the new replacement tasks might generate some of the same change events that were processed just prior to the crash. The number of duplicate events depends on the offset flush period and the volume of data changes just before the crash.

Because there is a chance that some events might be duplicated during a recovery from failure, consumers should always anticipate some duplicate events. Debezium changes are idempotent, so a sequence of events always results in the same state.

In each change event record, Debezium connectors insert source-specific information about the origin of the event, including the YugabyteDB server's time of the event, the ID of the server transaction, and the position in the write-ahead log where the transaction changes were written. Consumers can keep track of this information, especially the LSN, to determine whether an event is a duplicate.

Kafka becomes unavailable

As the connector generates change events, the Kafka Connect framework records those events in Kafka by using the Kafka producer API. Periodically, at a frequency that you specify in the Kafka Connect configuration, Kafka Connect records the latest offset that appears in those change events. If the Kafka brokers become unavailable, the Kafka Connect process that is running the connectors repeatedly tries to reconnect to the Kafka brokers. In other words, the connector tasks pause until a connection can be re-established, at which point the connectors resume exactly where they left off.

Connector is stopped for a duration

If the connector is gracefully stopped, the database can continue to be used. Any changes are recorded in the YugabyteDB WAL. When the connector restarts, it resumes streaming changes where it left off. That is, it generates change event records for all database changes that were made while the connector was stopped.

A properly configured Kafka cluster is able to handle massive throughput. Kafka Connect is written according to Kafka best practices, and given enough resources a Kafka Connect connector can also handle very large numbers of database change events. Because of this, after being stopped for a while, when a Debezium connector restarts, it is very likely to catch up with the database changes that were made while it was stopped. How quickly this happens depends on the capabilities and performance of Kafka and the volume of changes being made to the data in YugabyteDB.