Next Big Thing for Data Engineers - Open Table Formats 🚀 (Apache Iceberg, Hudi, Delta Tables)

Introduction

In this tutorial, we will explore the next big trends in data engineering, focusing on open table formats like Apache Iceberg, Hudi, and Delta Tables. These technologies are essential for managing large datasets efficiently and are becoming increasingly popular in data engineering workflows. By the end of this guide, you'll understand the advantages of these formats and how they can enhance your data engineering projects.

Step 1: Understanding Open Table Formats

Open table formats provide a structured way to store and manage large datasets. Here's what you need to know:

Apache Iceberg

• Designed for large analytic datasets.
• Supports features like schema evolution and partitioning.

Apache Hudi

• Focuses on incremental data processing.
• Allows for efficient upserts and deletes.

Delta Tables

• Built on top of Apache Parquet.
• Provides ACID transactions for reliable data operations.

Practical Tip

Familiarize yourself with the documentation and use cases for each format to determine which one aligns best with your project needs.

Step 2: Setting Up Your Environment

To work with these open table formats, you need the right environment. Here’s how to set it up:

1. Install Apache Spark:

   • Download Spark from the official website or use a package manager like Homebrew (for Mac).
   • Ensure that you have Java installed, as it is a prerequisite.

2. Install Necessary Libraries:

   • For Iceberg:

     pip install iceberg
     

   • For Hudi:

     pip install hudi
     

   • For Delta Tables:

     pip install delta-spark
     

Common Pitfall

Ensure that you are using compatible versions of Spark and the libraries mentioned, as version mismatches can lead to errors.

Step 3: Creating and Managing Tables

Once your environment is set up, you can start creating and managing your datasets. Follow these steps:

For Apache Iceberg

• Create a new table:

  CREATE TABLE iceberg_table (
      id INT,
      name STRING,
      created_at TIMESTAMP
  ) USING iceberg;
  

For Apache Hudi

• Create a new Hudi table:

  CREATE TABLE hudi_table (
      id INT,
      name STRING
  ) USING hudi;
  

For Delta Tables

• Create a new Delta table:

  CREATE TABLE delta_table (
      id INT,
      name STRING
  ) USING delta;
  

Step 4: Inserting and Querying Data

Now that your tables are set up, you can insert and query data to see how these formats work in action.

1. Inserting Data:

   • Use standard SQL INSERT commands to add data to your tables.
   • Ensure you handle the schema correctly, especially when using Iceberg and Hudi.

2. Querying Data:

   • Use SELECT statements to retrieve data:

   SELECT * FROM iceberg_table;
   SELECT * FROM hudi_table;
   SELECT * FROM delta_table;
   

Practical Tip

Consider using data validation checks after inserting data to ensure integrity.

Step 5: Leveraging Advanced Features

Explore some advanced functionalities of each format:

• Versioning:

  • Iceberg and Delta support time travel queries, allowing you to query historical versions of your data.

• Schema Evolution:

  • Hudi and Iceberg support changes in your schema without requiring a complete rewrite of your data.

• Data Compaction:

  • Regularly compact your data in Hudi to optimize performance.

Conclusion

By understanding and implementing open table formats like Apache Iceberg, Hudi, and Delta Tables, you can significantly enhance your data engineering capabilities. These technologies offer powerful features for managing large datasets efficiently. Start experimenting with these formats in your projects to unlock their full potential. For further learning, consider exploring additional resources and projects related to data engineering.