The following sections provide information about horizontal scaling.
The Oracle CDC Source connector scales horizontally using the existing Kafka Connect framework. The connector is configured with three tasks in the following graphic.
- Task 1: Reads records from the Oracle Database Redo Log, then writes these records to a redo log topic in Apache Kafka®.
- Task 2: Creates a snapshot for the DEPARTMENTS and EMPLOYEES tables.
- Task 3: Creates a snapshot for the JOBS table.
Once Task 2 and Task 3 are done with snapshotting, they read records from the Redo Log Topic in Kafka rather than from the Oracle database Redo Log Topic. The three tasks populate Kafka with table-specific topics from the snapshot forward.
If you need to create snapshots for many tables, you can add more tasks to get better snapshot performance.
Table Partition Snapshots¶
The Oracle CDC Source connector supports table partition snapshots when used
with Confluent Platform version 6.0 (or later) and connector version 1.1.0 (or later). The
connector performs snapshots, in parallel, of large tables that are partitioned
in Oracle, and distributes these table-partition snapshots across all tasks. To
do this, you use the connector properties
For example, when the connector is configured with
can set the property
snapshot.by.table.partitions=true allowing you to
assign more than one task to one table (if the table is partitioned). This is
scaling the number of tasks linearly, so more snapshots are performed in
parallel across a larger number of tasks. For example, a connector can capture
and snapshot a single large table (N=1) with many table partitions (for example,
P=20) using up to P+1 tasks. This reduces the overall time required to perform
the snapshot by scaling out the number of tasks.
When running a connector with
table-specific topics ahead of time. If table-specific topics are not created
ahead of time, some tasks assigned to partitioned tables will fail. To view the
property description, go to snapshot.by.table.partitions.