Db2 to Spark
real-time replication
TwinCommit replicates IBM Db2 to Apache Spark in real time by reading the Db2 transaction log and applying every committed change exactly once and in commit order. Use it to process every committed Db2 change in real time with Spark, with no triggers or capture tables on the source.
Db2
log reader
commit-ordered · exactly-once
Spark
native writer
How capture works on Db2
TwinCommit reads the Db2 recovery log through the native log read API and decodes row images itself. No SQL Replication, no Q Replication, no CD tables, no triggers and no capture agents are installed on the source.
Prerequisites
- ✓Archive logging enabled (LOGARCHMETH1)
- ✓DATA CAPTURE CHANGES on each replicated table
- ✓A primary key or unique index on each replicated table
- ✓DBADM (or SYSADM) for the capture user
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 Db2 → Spark in four steps
- 1
Prepare Db2
Run twincommit check. It verifies archive logging enabled (logarchmeth1) 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: db2
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]Db2 to Spark replication FAQ
How does TwinCommit replicate Db2 to Spark?
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TwinCommit reads changes from the Db2 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 Db2 to Spark replication need triggers or capture tables?
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No. TwinCommit reads the Db2 log directly and creates no objects in the source database.
Is Db2 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 Db2 versions are supported?
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Db2 LUW 11.1, 11.5, 12.1 · Db2 for z/OS 12 and 13 · Db2 on Cloud (target).
Stream Db2 to Spark today.
Download the free Developer edition, or have one of our replication engineers walk you through a migration plan.