MySQL to Spark
real-time replication
TwinCommit replicates MySQL to Apache Spark in real time by reading the MySQL transaction log and applying every committed change exactly once and in commit order. Use it to process every committed MySQL change in real time with Spark, with no triggers or capture tables on the source.
MySQL
log reader
commit-ordered · exactly-once
Spark
native writer
How capture works on MySQL
TwinCommit connects as a replica, reads the row-based binary log and tracks position by GTID, so failovers and replica promotions are seamless.
Prerequisites
- ✓binlog_format = ROW and binlog_row_image = FULL
- ✓GTID mode recommended
- ✓REPLICATION SLAVE and REPLICATION CLIENT grants
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 MySQL → Spark in four steps
- 1
Prepare MySQL
Run twincommit check. It verifies binlog_format = row and binlog_row_image = full 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: mysql
dsn: ${SOURCE_DSN}
server_id: 4201
target:
type: spark
listen: 0.0.0.0:7443
tls: true
tables:
- source: SALES.ORDERS
- source: SALES.ORDER_LINES
exclude_columns: [INTERNAL_NOTES]MySQL to Spark replication FAQ
How does TwinCommit replicate MySQL to Spark?
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TwinCommit reads changes from the MySQL 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 MySQL to Spark replication need triggers or capture tables?
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No. TwinCommit reads the MySQL log directly and creates no objects in the source database.
Is MySQL 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 MySQL versions are supported?
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MySQL 5.7, 8.0, 8.4, 9.x · Amazon RDS & Aurora MySQL · Azure Database for MySQL · Cloud SQL.
Stream MySQL to Spark today.
Download the free Developer edition, or have one of our replication engineers walk you through a migration plan.