Data Engineering with Databricks Cookbook
eBook Details:
- Paperback: 438 pages
- Publisher: WOW! eBook (May 31, 2024)
- Language: English
- ISBN-10: 1837633355
- ISBN-13: 978-1837633357
eBook Description:
Data Engineering with Databricks Cookbook: Build effective data and AI solutions using Apache Spark, Databricks, and Delta Lake. Work through 70 recipes for implementing reliable data pipelines with Apache Spark, optimally store and process structured and unstructured data in Delta Lake, and use Databricks to orchestrate and govern your data.
Data Engineering with Databricks Cookbook will guide you through recipes to effectively use Apache Spark, Delta Lake, and Databricks for data engineering, beginning with an introduction to data ingestion and loading with Apache Spark.
As you progress, you’ll be introduced to various data manipulation and data transformation solutions that can be applied to data. You’ll find out how to manage and optimize Delta tables, as well as how to ingest and process streaming data. The book will also show you how to improve the performance problems of Apache Spark apps and Delta Lake. Later chapters will show you how to use Databricks to implement DataOps and DevOps practices and teach you how to orchestrate and schedule data pipelines using Databricks Workflows. Finally, you’ll understand how to set up and configure Unity Catalog for data governance.
- Perform data loading, ingestion, and processing with Apache Spark
- Discover data transformation techniques and custom user-defined functions (UDFs) in Apache Spark
- Manage and optimize Delta tables with Apache Spark and Delta Lake APIs
- Use Spark Structured Streaming for real-time data processing
- Optimize Apache Spark application and Delta table query performance
- Implement DataOps and DevOps practices on Databricks
- Orchestrate data pipelines with Delta Live Tables and Databricks Workflows
- Implement data governance policies with Unity Catalog
By the end of this Data Engineering with Databricks Cookbook book, you’ll be well-versed in building reliable and scalable data pipelines using modern data engineering technologies.
