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.
By the end of this book, you’ll be well-versed in building reliable and scalable data pipelines using modern data engineering technologies.

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Spis treści

Data Engineering with Databricks Cookbook. Build effective data and AI solutions using Apache Spark, Databricks, and Delta Lake eBook -- spis treści

• 1. Data Ingestion and Data Extraction with Apache Spark
• 2. Data Transformation and Data Manipulation with Apache Spark
• 3. Data Management with Delta Lake
• 4. Ingesting Streaming Data
• 5. Processing Streaming Data
• 6. Performance Tuning with Apache Spark
• 7. Performance Tuning in Delta Lake
• 8. Orchestration and Scheduling Data Pipeline with Databricks Workflows
• 9. Building Data Pipelines with Delta Live Tables
• 10. Data Governance with Unity Catalog
• 11. Implementing DataOps and DevOps on Databricks