Previously posted on link at Nov 3, 2020. Traditionally, MySQL has been used to power most of the backend services at Bolt. We've designed our schemas in a way that they're sharded into different MySQL clusters. Each MySQL cluster contains a subset of data and consists of one primary and multiple replication nodes. Once data is persisted to the database, we use the Debezium MySQL Connector to capture data change events and send them to Kafka.

Introduction In this article, we are going to see how we can implement an audit logging mechanism using MySQL database triggers to store the old and new row states in JSON column types. Database tables Let’s assume we have a library application that has the following two tables: The book table stores all the books that are found in our library, and the book_audit_log table stores the CDC (Change Data Capture) events that happened to a given book record via an INSERT, UPDATE, or DELETE DML statement. The book_audit_log table is created... Read More

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We are living in the DataLake world. Now almost every oraganization wants their reporting in Near Real Time. Kafka is of the best streaming platform for realtime reporting. Based on the Kafka connector, RedHat designed the Debezium which is an OpenSource product and high recommended for real time CDC from transnational databases. I referred many blogs to setup this cluster. But I found just basic installation steps. So I setup this cluster for AWS with Production grade and publishing this blog.

A shot intro:

Debezium is a set of distributed services to capture changes in your databases so that your applications can see those changes and respond to them. Debezium records all row-level changes within each database table in a change event stream, and applications simply read these streams to see the change events in the same order in which they occurred.

Basic Tech Terms:

• Kafka …

We are living in the DataLake world. Now almost every organizations wants their reporting in Near Real Time. Kafka is of the best streaming platform for realtime reporting. Based on the Kafka connector, RedHat designed the Debezium which is an OpenSource product and high recommended for real time CDC from transnational databases. I referred many blogs to setup this cluster. But I found just basic installation steps. So I setup this cluster for AWS with Production grade and publishing this blog.

A shot intro:

Debezium is a set of distributed services to capture changes in your databases so that your applications can see those changes and respond to them. Debezium records all row-level changes within each database table in a change event stream, and applications simply read these streams to see the change events in the same order in which they occurred.

Basic Tech Terms:

• Kafka …

Introduction As previously explained, CDC (Change Data Capture) is one of the best ways to interconnect an OLTP database system with other systems like Data Warehouse, Caches, Spark or Hadoop. Debezium is an open source project developed by Red Hat which aims to simplify this process by allowing you to extract changes from various database … Continue reading How to extract change data events from MySQL to Kafka using Debezium →

In this post, we’ll look at MySQL CDC, streaming binary logs and asynchronous triggers.

What is Change Data Capture and why do we need it?

Change Data Capture (CDC) tracks data changes (usually close to realtime). In MySQL, the easiest and probably most efficient way to track data changes is to use binary logs. However, other approaches exist. For example:

• General log or Audit Log Plugin (which logs all queries, not just the changes)
• MySQL triggers (not recommended, as it can slow down the application — more below)

One of the first implementations of CDC for …

MySQL replication enables data to be replicated from one MySQL database server (the master) to one or more MySQL database servers (the slaves). However, imagine the number of use cases being served if the slave (to which data is replicated) isn't restricted to be a MySQL server; but it can be any other database server or platform with replication events applied in real-time! 
This is what the new Hadoop Applier empowers you to do.
An example of such a slave could be a data warehouse system such as Apache Hive, which uses HDFS as a data store. If you have a Hive metastore associated with HDFS(Hadoop Distributed File System), the Hadoop Applier can populate Hive tables in real time. Data is …

This is a follow up post, describing the implementation details of Hadoop Applier, and steps to configure and install it. Hadoop Applier integrates MySQL with Hadoop providing the real-time replication of INSERTs to HDFS, and hence can be consumed by the data stores working on top of Hadoop. You can know more about the design rationale and per-requisites in the previous post.

Design and Implementation:

Hadoop Applier replicates rows inserted into a table in MySQL to the Hadoop Distributed File System(HDFS). It uses an API provided by libhdfs, a C library to manipulate files in HDFS.

The library comes pre-compiled with Hadoop distributions. It connects to the MySQL master (or read …