{"id":71705,"date":"2023-08-30T14:36:21","date_gmt":"2023-08-30T06:36:21","guid":{"rendered":"https:\/\/version-2.com\/?p=71705"},"modified":"2023-08-25T14:42:05","modified_gmt":"2023-08-25T06:42:05","slug":"how-to-sync-data-from-mysql-to-google-bigquery-using-debezium-and-kafka-connect","status":"publish","type":"post","link":"https:\/\/version-2.com\/en\/2023\/08\/how-to-sync-data-from-mysql-to-google-bigquery-using-debezium-and-kafka-connect\/","title":{"rendered":"How to sync data from MySQL to Google BigQuery using Debezium and Kafka Connect"},"content":{"rendered":"
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Syncing data from a MySQL database to Google BigQuery can be a great way to keep your data up to date and easily accessible for analysis. In this article, we will explore the process of setting up Debezium and Kafka Connect to sync data from MySQL to BigQuery, providing you with all the information you need to get started.\u00a0<\/p>

<\/p>

Why use Debezium and Kafka Connect?\u00a0<\/b><\/h2>

Debezium and Kafka Connect are open-source platforms that provide a powerful solution for streaming data changes in real-time between systems. That real-time interaction allows you to keep your data in sync and easily accessible for various use cases such as real-time analytics, data warehousing, and data pipeline integrations.<\/p>

High level solution diagram<\/b><\/h2>

\"\"<\/span>\"solution<\/span><\/p>

solution architecture<\/p><\/div>

Technology used<\/b><\/h2>

Before we go into the details of setting up Debezium and Kafka Connect to sync data from MySQL to BigQuery, it is important to understand the technologies that you will be using and how they are connected.<\/p>

Change data capture<\/b><\/h3>

Change Data Capture (CDC) is a technique for capturing and recording all the changes made to a database over time. This allows for real-time data replication, making it easy to keep multiple systems in sync.<\/p>

CDC does this by detecting row-level changes in database source tables, which are characterized as \u201cInsert,\u201d \u201cUpdate,\u201d and \u201cDelete\u201d events. CDC then notifies other systems or services that rely on the same data.\u200b<\/p>

Apache Kafka<\/b><\/h3>

Apache Kafka is a distributed streaming platform that is used for building real-time data pipelines and streaming applications. It allows for the storage and processing of streams of records in a fault-tolerant way.<\/p>

Kafka Connect<\/b><\/h3>

Kafka Connect is a framework for connecting Kafka with external systems such as databases, key-value stores, search indexes, and file systems, using so-called connectors.\u200b<\/p>

Kafka connectors are ready-to-use components that can help you to import data from external systems into Kafka topics and export data from Kafka topics into external systems. You can use existing connector implementations for common data sources and syncs or implement our own connectors.\u200b<\/p>

Debezium<\/b><\/h3>

Debezium is an open-source platform that allows you to easily stream changes from your MySQL database to other systems using CDC. It works by reading MySQL binlog to capture data changes in a transactional manner, so you can be sure that you’re always working with the most up-to-date data.<\/p>

By using Debezium, you can capture the changes made to the MySQL database and stream them to Kafka. Data on the changes can then be consumed by Kafka Connect to load the data into BigQuery.<\/p>

BigQuery setup<\/h2>

1. Creating a BigQuery project and dataset:<\/p>

a. In the Google Cloud Console, navigate to the BigQuery page and create a new project (Creating and managing projects | Resource Manager Documentation | Google Cloud<\/a>). We will name it \u201cmysql-bigquery\u201d for this tutorial.<\/p>

b. Within the project, create a new dataset (Creating datasets | BigQuery | Google Cloud<\/a>). We will name it \u201cdebezium\u201d for this tutorial.<\/p>

c. Note that Debezium will automatically create tables in the dataset that match the structure of the MySQL tables being monitored.<\/p>

2. Creating a GCP service account with BigQuery editor role:<\/p>

a. In the Google Cloud Console, navigate to the IAM & Admin page and create a new service account (Creating and managing service accounts | IAM Documentation | Google Cloud<\/a>).<\/p>

b. Give the service account a name and description, then select the \u201cBigQuery Data Editor\u201d role<\/p>

3. Generating and downloading a key for the service account:<\/p>

a. In the Google Cloud Console, navigate to the IAM & Admin page, find the service account, and click on the three dots on the right, then select “create key” (Create and manage service account keys | IAM Documentation | Google Cloud<\/a>).<\/p>

b. Select JSON as the key type and download the key file.<\/p>

c. Store the key file securely and use it to authenticate the connector in Kafka Connect when accessing the BigQuery dataset.<\/p>

Tutorial<\/b><\/h2>

To start syncing data from MySQL to BigQuery we will need following components:<\/p>