Syncer: MySQL/MongoDB => Elasticsearch/MySQL/Kafka/HBase

中文文档

Features

• Sync data consistently: make sure data consistency
• Sync data async: little effect on origin server
• Sync data and manipulate: write Java code to customize sync
• Sync data from MySQL/MongoDB to Kafka/ES/MySQL/HBase
• ETL and real-time data sync combined: missing no data, sample config

Use Syncer

Preparation

• MySQL config
  • binlog_format: row
  • binlog_row_image: full
• MongoDB config:
  • (optional) update bind_ip to allow listens for connections from applications on configured addresses.
  • enable replication set:
    • mongod --replSet myapp
    • Or use docker: docker run -d --name mongodb -p 27017:27017 -v /root/mongodb-container/db:/data/db mongo:3.2 mongod --replSet chat
  • init replication set in shell: rs.initiate()

    Run

    git clone https://github.com/zzt93/syncer
    cd syncer/ && mvn package
    # /path/to/config/: producer.yml, consumer.yml, password-file
    # use `-XX:+UseParallelOldGC` if you have less memory and lower input pressure
    # use `-XX:+UseG1GC` if you have at least 4g memory and event input rate larger than 2*10^4/s
    java -server -XX:+UseG1GC -jar ./syncer-core/target/syncer-core-1.0-SNAPSHOT.jar [--debug] [--port=40000] [--config=/absolute/path/to/syncerConfig.yml] --producerConfig=/absolute/path/to/producer.yml --consumerConfig=/absolute/path/to/consumer1.yml,/absolute/path/to/consumer2.yml

    Full and usable sample config can be found under test/config/, like test/config/simplest

How to ?

If you have any problems with how to use Syncer or bugs of it, write an issue.
I will handle it as soon as I can.

FAQ

• Q: “Got error produce response in correlation id xxx on topic-partition xxx.xxPartition-0, splitting and retrying (5 attempts left). Error: MESSAGE_TOO_LARGE”?
  • A: Adjust message batch.size to smaller number or config kafka to receive large message

Used In Production

• Search system: search data sync
• Micro-service: auth/recommend/chat data sync
  • Sync Requirement: low latency, high availability
• Join table: avoid join in production env, use space for speed by joining table
  • Sync Requirement: low latency, high availability
• Kafka: sync data to kafka, for other heterogeneous system to use
• For data recovery: In case of drop entity mistakenly, or you know where to start & end
• For alter table sync:
  • MySQL very slow for alter table
  • MySQL 8.0: InnoDB now supports Instant ADD COLUMN
• For data warehouse sync

TODO

See Issue 1

Implementation

Implementation detail can be found in doc