Debezium Connector for Oracle

Overview

Debezium ingests change events from Oracle using the XStream API. In order to use this API and hence this connector, you need to have a license for the GoldenGate product (though it is not required that GoldenGate itself is installed). We are currently exploring alternatives to using XStream for a future Debezium release, e.g. based on LogMiner and/or alternative solutions. Please track the DBZ-137 JIRA issue and join the discussion if you are aware of potential other ways for ingesting change events from Oracle.

Setting up Oracle

The following steps need to be performed in order to prepare the database so the Debezium connector can be used. This assumes the multi-tenancy configuration (with a container database and at least one pluggable database); if you’re not using this model, adjust the steps accordingly.

You can find a template for setting up Oracle in a virtual machine (via Vagrant) in the oracle-vagrant-box/ repository.

Preparing the Database

Enable GoldenGate replication and archive log mode:

ORACLE_SID=ORCLCDB dbz_oracle sqlplus /nolog
CONNECT sys/top_secret AS SYSDBA
alter system set db_recovery_file_dest_size = 5G;
alter system set db_recovery_file_dest = '/opt/oracle/oradata/recovery_area' scope=spfile;
alter system set enable_goldengate_replication=true;
shutdown immediate
startup mount
alter database archivelog;
alter database open;
-- Should show "Database log mode: Archive Mode"
archive log list
exit;

Furthermore, in order to capture the before state of changed rows, supplemental logging must be enabled for the captured tables or the database in general. E.g. like so for a specific table:

ALTER TABLE inventory.customers ADD SUPPLEMENTAL LOG DATA (ALL) COLUMNS;

Creating an XStream Admin User and a User For the Connector

Create an XStream admin user in the container database (used per Oracle’s recommendation for administering XStream):

sqlplus sys/top_secret@//localhost:1521/ORCLCDB as sysdba
CREATE TABLESPACE xstream_adm_tbs DATAFILE '/opt/oracle/oradata/ORCLCDB/xstream_adm_tbs.dbf'
  SIZE 25M REUSE AUTOEXTEND ON MAXSIZE UNLIMITED;
exit;

sqlplus sys/top_secret@//localhost:1521/ORCLPDB1 as sysdba
CREATE TABLESPACE xstream_adm_tbs DATAFILE '/opt/oracle/oradata/ORCLCDB/ORCLPDB1/xstream_adm_tbs.dbf'
  SIZE 25M REUSE AUTOEXTEND ON MAXSIZE UNLIMITED;
exit;

sqlplus sys/top_secret@//localhost:1521/ORCLCDB as sysdba
CREATE USER c##xstrmadmin IDENTIFIED BY xsa
  DEFAULT TABLESPACE xstream_adm_tbs
  QUOTA UNLIMITED ON xstream_adm_tbs
  CONTAINER=ALL;
GRANT CREATE SESSION, SET CONTAINER TO c##xstrmadmin CONTAINER=ALL;
BEGIN
   DBMS_XSTREAM_AUTH.GRANT_ADMIN_PRIVILEGE(
      grantee                 => 'c##xstrmadmin',
      privilege_type          => 'CAPTURE',
      grant_select_privileges => TRUE,
      container               => 'ALL'
   );
END;
/
exit;

Create XStream user (used by the Debezium connector to connect to the XStream outbound server):

sqlplus sys/top_secret@//localhost:1521/ORCLCDB as sysdba
CREATE TABLESPACE xstream_tbs DATAFILE '/opt/oracle/oradata/ORCLCDB/xstream_tbs.dbf'
  SIZE 25M REUSE AUTOEXTEND ON MAXSIZE UNLIMITED;
exit;

sqlplus sys/top_secret@//localhost:1521/ORCLPDB1 as sysdba
CREATE TABLESPACE xstream_tbs DATAFILE '/opt/oracle/oradata/ORCLCDB/ORCLPDB1/xstream_tbs.dbf'
  SIZE 25M REUSE AUTOEXTEND ON MAXSIZE UNLIMITED;
exit;

sqlplus sys/top_secret@//localhost:1521/ORCLCDB as sysdba
CREATE USER c##xstrm IDENTIFIED BY xs
  DEFAULT TABLESPACE xstream_tbs
  QUOTA UNLIMITED ON xstream_tbs
  CONTAINER=ALL;
GRANT CREATE SESSION TO c##xstrm CONTAINER=ALL;
GRANT SET CONTAINER TO c##xstrm CONTAINER=ALL;
GRANT SELECT ON V_$DATABASE to c##xstrm CONTAINER=ALL;
GRANT FLASHBACK ANY TABLE TO c##xstrm CONTAINER=ALL;
exit;

Create an XStream Outbound Server

Create an XStream Outbound server (given the right privileges, this may be done automatically by the connector going forward, see DBZ-721):

sqlplus c##xstrmadmin/xsa@//localhost:1521/ORCLCDB
DECLARE
  tables  DBMS_UTILITY.UNCL_ARRAY;
  schemas DBMS_UTILITY.UNCL_ARRAY;
BEGIN
    tables(1)  := NULL;
    schemas(1) := 'debezium';
  DBMS_XSTREAM_ADM.CREATE_OUTBOUND(
    server_name     =>  'dbzxout',
    table_names     =>  tables,
    schema_names    =>  schemas);
END;
/
exit;

Alter the XStream Outbound server to allow the xstrm user to connect to it:

sqlplus sys/top_secret@//localhost:1521/ORCLCDB as sysdba
BEGIN
  DBMS_XSTREAM_ADM.ALTER_OUTBOUND(
    server_name  => 'dbzxout',
    connect_user => 'c##xstrm');
END;
/
exit;

Note that a given outbound server must not be used by multiple connector instances at the same time. If you wish to set up multiple instances of the Debezium Oracle connector, a specific XStreamOutbound server is needed for each of them.

Supported Configurations

So far, the connector has been tested with the pluggable database set-up (CDB/PDB model). It should monitor a single PDB in this model. It should also work with traditional (non-CDB) set-ups, though this could not be tested so far.

How the Oracle Connector Works

Database Schema History

tbd.

Snapshots

Most Oracle servers are configured to not retain the complete history of the database in the redo logs, so the Debezium Oracle connector would be unable to see the entire history of the database by simply reading the logs. So, by default (snapshotting mode initial) the connector will upon first startup perform an initial consistent snapshot of the database (meaning the structure and data within any tables to be captured as per the connector’s filter configuration).

Each snapshot consists of the following steps:

1. Determine the tables to be captured

2. Obtain an IN EXCLUSIVE MODE lock on each of the monitored tables to ensure that no structural changes can occur to any of the tables.

3. Read the current SCN (“system change number”) position in the server’s redo log.

4. Capture the structure of all relevant tables.

5. Release the locks obtained in step 2, i.e. the locks are held only for a short period of time.

6. Scan all of the relevant database tables and schemas as valid at the SCN position read in step 3 (SELECT * FROM …​ AS OF SCN 123), and generate a READ event for each row and write that event to the appropriate table-specific Kafka topic.

7. Record the successful completion of the snapshot in the connector offsets.

If the connector fails, is rebalanced, or stops after step 1 begins but before step 7 completes, upon restart the connector will begin a new snapshot. Once the Oracle connector does complete its initial snapshot, it continues streaming from the position read during step 3, ensuring that it does not miss any updates that occurred while the snapshot was taken. If the connector stops again for any reason, upon restart it will simply continue streaming changes from where it previously left off.

A second snapshotting mode is schema_only. In this case, step 6 from the snapshotting routine described above is not applied. In other words, the connector still captures the structure of the relevant tables, but it does not create any READ events representing the complete dataset at the point of connector start-up. This can be useful if you are interested in data changes only from now onwards but not the complete current state of all records.

Reading the Redo Log

Upon first start-up, the connector takes a snapshot of the structure of the captured tables (DDL) and persists this information in its internal database history topic. It then proceeds to listen for change events right from the SCN at which the schema structure was captured. Processed SCNs are passed as offsets to Kafka Connect and regularly acknowledged with the database server (allowing it to discard older log files). After restart, the connector will resume from the offset (SCN) where it left off before.

Topics Names

Schema Change Topic

The user-facing schema change topic is not implemented yet (see DBZ-753).

Events

All data change events produced by the Oracle connector have a key and a value, although the structure of the key and value depend on the table from which the change events originated (see Topic names).

Debezium and Kafka Connect are designed around continuous streams of event messages, and the structure of these events may change over time. This could be difficult for consumers to deal with, so to make it easy Kafka Connect makes each event self-contained. Every message key and value has two parts: a schema and payload. The schema describes the structure of the payload, while the payload contains the actual data.

Change Event Keys

For a given table, the change event’s key will have a structure that contains a field for each column in the primary key (or unique key constraint) of the table at the time the event was created.

Consider a customers table defined in the inventory database schema:

CREATE TABLE customers (
  id NUMBER(9) GENERATED BY DEFAULT ON NULL AS IDENTITY (START WITH 1001) NOT NULL PRIMARY KEY,
  first_name VARCHAR2(255) NOT NULL,
  last_name VARCHAR2(255) NOT NULL,
  email VARCHAR2(255) NOT NULL UNIQUE
);

If the database.server.name configuration property has the value server1, every change event for the customers table while it has this definition will feature the same key structure, which in JSON looks like this:

{
    "schema": {
        "type": "struct",
        "fields": [
            {
                "type": "int32",
                "optional": false,
                "field": "ID"
            }
        ],
        "optional": false,
        "name": "server1.INVENTORY.CUSTOMERS.Key"
    },
    "payload": {
        "ID": 1004
    }
}

The schema portion of the key contains a Kafka Connect schema describing what is in the key portion, and in our case that means that the payload value is not optional, is a structure defined by a schema named server1.DEBEZIUM.CUSTOMERS.Key, and has one required field named id of type int32. If you look at the value of the key’s payload field, you can see that it is indeed a structure (which in JSON is just an object) with a single id field, whose value is 1004.

Therefore, you can interpret this key as describing the row in the inventory.customers table (output from the connector named server1) whose id primary key column had a value of 1004.

Change Event Values

Like the message key, the value of a change event message has a schema section and payload section. The payload section of every change event value produced by the Oracle connector has an envelope structure with the following fields:

• op is a mandatory field that contains a string value describing the type of operation. Values for the Oracle connector are c for create (or insert), u for update, d for delete, and r for read (in the case of a snapshot).

• before is an optional field that if present contains the state of the row before the event occurred. The structure will be described by the server1.INVENTORY.CUSTOMERS.Value Kafka Connect schema, which the server1 connector uses for all rows in the inventory.customers table.

• after is an optional field that if present contains the state of the row after the event occurred. The structure is described by the same server1.INVENTORY.CUSTOMERS.Value Kafka Connect schema used in before.

• source is a mandatory field that contains a structure describing the source metadata for the event, which in the case of Oracle contains these fields: the Debezium version, the connector name, whether the event is part of an ongoing snapshot or not, the transaction id (not while snapshotting), the SCN of the change, and a timestamp representing the point in time when the record was changed in the source database (during snapshotting, this is the point in time of snapshotting)

• ts_ms is optional and if present contains the time (using the system clock in the JVM running the Kafka Connect task) at which the connector processed the event.

And of course, the schema portion of the event message’s value contains a schema that describes this envelope structure and the nested fields within it.

Create events

Let’s look at what a create event value might look like for our customers table:

{
    "schema": {
        "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": "server1.DEBEZIUM.CUSTOMERS.Value",
                "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": "server1.DEBEZIUM.CUSTOMERS.Value",
                "field": "after"
            },
            {
                "type": "struct",
                "fields": [
                    {
                        "type": "string",
                        "optional": true,
                        "field": "version"
                    },
                    {
                        "type": "string",
                        "optional": false,
                        "field": "name"
                    },
                    {
                        "type": "int64",
                        "optional": true,
                        "field": "ts_ms"
                    },
                    {
                        "type": "string",
                        "optional": true,
                        "field": "txId"
                    },
                    {
                        "type": "int64",
                        "optional": true,
                        "field": "scn"
                    },
                    {
                        "type": "boolean",
                        "optional": true,
                        "field": "snapshot"
                    }
                ],
                "optional": false,
                "name": "io.debezium.connector.oracle.Source",
                "field": "source"
            },
            {
                "type": "string",
                "optional": false,
                "field": "op"
            },
            {
                "type": "int64",
                "optional": true,
                "field": "ts_ms"
            }
        ],
        "optional": false,
        "name": "server1.DEBEZIUM.CUSTOMERS.Envelope"
    },
    "payload": {
        "before": null,
        "after": {
            "ID": 1004,
            "FIRST_NAME": "Anne",
            "LAST_NAME": "Kretchmar",
            "EMAIL": "annek@noanswer.org"
        },
        "source": {
            "version": "0.9.0.Alpha1",
            "name": "server1",
            "ts_ms": 1520085154000,
            "txId": "6.28.807",
            "scn": 2122185,
            "snapshot": false
        },
        "op": "c",
        "ts_ms": 1532592105975
    }
}

If we look at the schema portion of this event’s value, we can see the schema for the envelope, the schema for the source structure (which is specific to the Oracle connector and reused across all events), and the table-specific schemas for the before and after fields.

If we look at the payload portion of this event’s value, we can see the information in the event, namely that it is describing that the row was created (since op=c), and that the after field value contains the values of the new inserted row’s’ ID, FIRST_NAME, LAST_NAME, and EMAIL columns.

Update events

The value of an update change event on this table will actually have the exact same schema, and its payload will be structured the same but will hold different values. Here’s an example:

{
    "schema": { ... },
    "payload": {
        "before": {
            "ID": 1004,
            "FIRST_NAME": "Anne",
            "LAST_NAME": "Kretchmar",
            "EMAIL": "annek@noanswer.org"
        },
        "after": {
            "ID": 1004,
            "FIRST_NAME": "Anne",
            "LAST_NAME": "Kretchmar",
            "EMAIL": "anne@example.com"
        },
        "source": {
            "version": "0.9.0.Alpha1",
            "name": "server1",
            "ts_ms": 1520085811000,
            "txId": "6.9.809",
            "scn": 2125544,
            "snapshot": false
        },
        "op": "u",
        "ts_ms": 1532592713485
    }
}

When we compare this to the value in the insert event, we see a couple of differences in the payload section:

• The op field value is now u, signifying that this row changed because of an update

• The before field now has the state of the row with the values before the database commit

• The after field now has the updated state of the row, and here was can see that the EMAIL value is now anne@example.com.

• The source field structure has the same fields as before, but the values are different since this event is from a different position in the redo log.

• The ts_ms shows the timestamp that Debezium processed this event.

There are several things we can learn by just looking at this payload section. We can compare the before and after structures to determine what actually changed in this row because of the commit. The source structure tells us information about Oracle’s record of this change (providing traceability), but more importantly this has information we can compare to other events in this and other topics to know whether this event occurred before, after, or as part of the same Oracle commit as other events.

Delete events

So far we’ve seen samples of create and update events. Now, let’s look at the value of a delete event for the same table. Once again, the schema portion of the value will be exactly the same as with the create and update events:

{
    "schema": { ... },
    "payload": {
        "before": {
            "ID": 1004,
            "FIRST_NAME": "Anne",
            "LAST_NAME": "Kretchmar",
            "EMAIL": "anne@example.com"
        },
        "after": null,
        "source": {
            "version": "0.9.0.Alpha1",
            "name": "server1",
            "ts_ms": 1520085153000,
            "txId": "6.28.807",
            "scn": 2122184,
            "snapshot": false
        },
        "op": "d",
        "ts_ms": 1532592105960
    }
}

If we look at the payload portion, we see a number of differences compared with the create or update event payloads:

• The op field value is now d, signifying that this row was deleted

• The before field now has the state of the row that was deleted with the database commit.

• The after field is null, signifying that the row no longer exists

• The source field structure has many of the same values as before, except the ts_ms, scn and txId fields have changed

• The ts_ms shows the timestamp that Debezium processed this event.

This event gives a consumer all kinds of information that it can use to process the removal of this row.

The Oracle connector’s events are designed to work with Kafka log compaction, which allows for the removal of some older messages as long as at least the most recent message for every key is kept. This allows Kafka to reclaim storage space while ensuring the topic contains a complete dataset and can be used for reloading key-based state.

When a row is deleted, the delete event value listed above still works with log compaction, since Kafka can still remove all earlier messages with that same key. But only if the message value is null will Kafka know that it can remove all messages with that same key. To make this possible, Debezium’s Oracle connector always follows the delete event with a special tombstone event that has the same key but null value.

Transaction Metadata

Debezium can generate events that represents tranaction metadata boundaries and enrich data messages.

Transaction boundaries

Debezium generates events for every transaction BEGIN and END. Every event contains

• status - BEGIN or END

• id - string representation of unique transaction identifier

• event_count (for END events) - total number of events emmitted by the transaction

• data_collections (for END events) - an array of pairs of data_collection and event_count that provides number of events emitted by changes originating from given data collection

Following is an example of what a message looks like:

{
  "status": "BEGIN",
  "id": "5.6.641",
  "event_count": null,
  "data_collections": null
}
{
  "status": "END",
  "id": "5.6.641",
  "event_count": 2,
  "data_collections": [
    {
      "data_collection": "ORCLPDB1.DEBEZIUM.CUSTOMER",
      "event_count": 1
    },
    {
      "data_collection": "ORCLPDB1.DEBEZIUM.ORDER",
      "event_count": 1
    }
  ]
}

The transaction events are written to the topic named <database.server.name>.transaction.

Data events 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 - the 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 that were emitted by the transaction

Following is an example of what a message looks like:

{
  "before": null,
  "after": {
    "pk": "2",
    "aa": "1"
  },
  "source": {
...
  },
  "op": "c",
  "ts_ms": "1580390884335",
  "transaction": {
    "id": "5.6.641",
    "total_order": "1",
    "data_collection_order": "1"
  }
}

Data Types

As described above, the Debezium Oracle connector represents the changes to rows with events that are structured like the table in which the row exist. The event contains a field for each column value, and how that value is represented in the event depends on the Oracle data type of the column. This section describes this mapping from Oracle’s data types to a literal type and semantic type within the events’ fields.

Here, the literal type describes how the value is literally represented using Kafka Connect schema types, namely INT8, INT16, INT32, INT64, FLOAT32, FLOAT64, BOOLEAN, STRING, BYTES, ARRAY, MAP, and STRUCT.

The 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.

Support for further data types will be added in subsequent releases. Please file a JIRA issue for any specific types you are missing.

Character Values

Numeric Values

Decimal Values

When decimal.handling.mode configuration property is set to precise, then the connector will use the predefined Kafka Connect org.apache.kafka.connect.data.Decimal or io.debezium.data.VariableScaleDecimal logical types for numeric columns as described above. This is the default mode.

However, when decimal.handling.mode configuration property is set to double, then the connector will represent the values as Java double values with schema type FLOAT64. The last option for decimal.handling.mode configuration property is string. In this case the connector will represent the values as their formatted string representation with schema type STRING.

Temporal Values

Deploying a Connector

Due to licensing requirements, the Debezium Oracle Connector does not ship with the Oracle JDBC driver and the XStream API JAR. You can obtain them for free by downloading the Oracle Instant Client.

Extract the archive into a directory, e.g. /path/to/instant_client/. Copy the files _ojdbc8.jar and xstreams.jar from the Instant Client into Kafka’s libs directory. Create the environment variable LD_LIBRARY_PATH, pointing to the Instant Client directory:

LD_LIBRARY_PATH=/path/to/instant_client/

Example Configuration

The following shows an example JSON request for registering an instance of the Debezium Oracle connector:

{
    "name": "inventory-connector",
    "config": {
        "connector.class" : "io.debezium.connector.oracle.OracleConnector",
        "tasks.max" : "1",
        "database.server.name" : "server1",
        "database.hostname" : "<oracle ip>",
        "database.port" : "1521",
        "database.user" : "c##xstrm",
        "database.password" : "xs",
        "database.dbname" : "ORCLCDB",
        "database.pdb.name" : "ORCLPDB1",
        "database.out.server.name" : "dbzxout",
        "database.history.kafka.bootstrap.servers" : "kafka:9092",
        "database.history.kafka.topic": "schema-changes.inventory"
    }
}

Monitoring

The Debezium Oracle connector has three metric types in addition to the built-in support for JMX metrics that Zookeeper, Kafka, and Kafka Connect have.

• snapshot metrics; for monitoring the connector when performing snapshots

• streaming metrics; for monitoring the connector when processing change events

• schema history metrics; for monitoring the status of the connector’s schema history

Please refer to the monitoring documentation for details of how to expose these metrics via JMX.

Snapshot Metrics

The MBean is debezium.oracle:type=connector-metrics,context=snapshot,server=*<database.server.name>*.

Streaming Metrics

The MBean is debezium.oracle:type=connector-metrics,context=streaming,server=*<database.server.name>*.

Schema History Metrics

The MBean is debezium.mysql:type=connector-metrics,context=schema-history,server=*<database.server.name>*.

Connector Properties

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

column.mask.hash.SHA-256.with.salt.CzQMA0cB5K = inventory.orders.customerName, inventory.shipment.customerName