Explore dynamic Change Data Capture (CDC) techniques using Flink CDC and consistent hashing in this informative conference talk. Learn how Goldsky tackled the challenge of configuring CDC for a large Postgres database dynamically, addressing issues with static deployments and the limitations of replication slots. Discover the implementation of incremental snapshotting and the innovative use of consistent hashing algorithms to distribute tables across multiple Flink jobs. Gain valuable insights into Debezium, Flink CDC, and Postgres replication as the speaker shares their experiences and learnings from this complex data extraction project.
Dynamic Change Data Capture with Flink CDC and Consistent Hashing
Overview
Syllabus
Dynamic Change Data Capture with Flink CDC and Consistent Hashing
Taught by
Confluent
Related Courses
-
Real-Time Data Integration Practice Based on Flink CDC at Alibaba Cloud
-
Change Data Streaming Patterns with Debezium and Apache Flink
-
Realtime Change Data Capture Streaming - End-to-End Data Engineering Project
-
Data Streaming for Microservices Using Debezium
-
Streaming Database Changes with Debezium
-
Change Data Capture for Non-Relational Databases
