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Delta Lake Cheat Sheet

Download Delta Lake Cheat Sheet

What is Delta Lake?

Delta Lake is an open-source project that enables building a Lakehouse architecture on top of data lakes. Delta Lake provides ACID transactions, scalable metadata handling, and unifies streaming and batch data processing on top of existing data lakes, such as S3, ADLS, GCS, and HDFS.

Specifically, Delta Lake offers:

  • ACID transactions on Spark: Serializable isolation levels ensure that readers never see inconsistent data.
  • Scalable metadata handling: Leverages Spark distributed processing power to handle all the metadata for petabyte-scale tables with billions of files at ease.
  • Streaming and batch unification: A table in Delta Lake is a batch table as well as a streaming source and sink. Streaming data ingest, batch historic backfill, and interactive queries all just work out of the box.
  • Schema enforcement: Automatically handles schema variations to prevent insertion of bad records during ingestion.
  • Time travel: Data versioning enables rollbacks, full historical audit trails, and reproducible machine learning experiments.
  • Upserts and deletes: Supports merge, update and delete operations to enable complex use cases like change-data-capture, slowly-changing-dimension (SCD) operations, streaming upserts, and so on.
Related:  PySpark RDD Basics Cheat Sheet

The Delta Lake cheat sheet provides you with the most commonly used Delta Lake commands for your reference. You can download the Delta Lake cheat sheet using below download link.

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