Oracle to Spark
real-time replication
TwinCommit replicates Oracle Database to Apache Spark in real time by reading the Oracle transaction log and applying every committed change exactly once and in commit order. Use it to process every committed Oracle change in real time with Spark, with no triggers or capture tables on the source.
Oracle
log reader
commit-ordered · exactly-once
Spark
native writer
How capture works on Oracle
TwinCommit parses online redo and archived logs directly, including RAC threads, and reassembles transactions in SCN order before they leave the host.
Prerequisites
- ✓ARCHIVELOG mode
- ✓Minimal plus primary-key supplemental logging
- ✓Read access to V$ views and the archive destination
How apply works on Spark
The TwinCommit Spark connector exposes each pipeline as a Structured Streaming source with offsets mapped to log positions, so your jobs get exactly-once semantics with Spark checkpoints.
Requirements
- ✓The twincommit-spark connector JAR on the driver class path
- ✓Network access from the driver to the TwinCommit change feed endpoint
Setup
Set up Oracle → Spark in four steps
- 1
Prepare Oracle
Run twincommit check. It verifies archivelog mode and the other prerequisites, and prints the exact fix for anything missing.
- 2
Point at Spark
Add a target block for Spark. TwinCommit can generate target DDL with twincommit ddl -apply.
- 3
Snapshot
twincommit snapshot copies each table under a brief share lock and records the exact log position.
- 4
Stream
twincommit run streams every committed change from that position, exactly once and in commit order.
source:
type: oracle
database: PRODDB
user: ${SRC_USER}
password: ${SRC_PASSWORD}
target:
type: spark
listen: 0.0.0.0:7443
tls: true
tables:
- source: SALES.ORDERS
- source: SALES.ORDER_LINES
exclude_columns: [INTERNAL_NOTES]Oracle to Spark replication FAQ
How does TwinCommit replicate Oracle to Spark?
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TwinCommit reads changes from the Oracle transaction log, buffers them per transaction, and applies each committed transaction to Spark in commit order. The TwinCommit Spark connector exposes each pipeline as a Structured Streaming source with offsets mapped to log positions, so your jobs get exactly-once semantics with Spark checkpoints.
Does Oracle to Spark replication need triggers or capture tables?
+
No. TwinCommit reads the Oracle log directly and creates no objects in the source database.
Is Oracle to Spark replication exactly-once?
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Yes. TwinCommit commits its checkpoint in the same Spark transaction as the data, so a crash or restart never loses or duplicates a transaction.
What Oracle versions are supported?
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Oracle 19c, 21c, 23ai · RAC, Data Guard standby, CDB/PDB · Autonomous Database (target).
Stream Oracle to Spark today.
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