Delta Lake is a storage layer that brings scalable, ACID transactions to Apache Spark and other big-data engines.
See the Delta Lake Documentation for details.
See the Quick Start Guide to get started with Scala, Java and Python.
See the online documentation for the latest release.
Compatibility with Apache Spark Versions
See the online documentation for the releases and their compatibility with Apache Spark versions.
There are two types of APIs provided by the Delta Lake project.
- Spark-based APIs - You can read Delta tables through the
df.writeStream). Options to these APIs will remain stable within a major release of Delta Lake (e.g., 1.x.x).
- Direct Java/Scala/Python APIs - The classes and methods documented in the API docs are considered as stable public APIs. All other classes, interfaces, methods that may be directly accessible in code are considered internal, and they are subject to change across releases.
Data Storage Compatibility
Delta Lake guarantees backward compatibility for all Delta Lake tables (i.e., newer versions of Delta Lake will always be able to read tables written by older versions of Delta Lake). However, we reserve the right to break forward compatibility as new features are introduced to the transaction protocol (i.e., an older version of Delta Lake may not be able to read a table produced by a newer version).
Breaking changes in the protocol are indicated by incrementing the minimum reader/writer version in the
For detailed detailed timeline, see the project roadmap.
Delta Lake is compiled using SBT.
To compile, run
To generate artifacts, run
To execute tests, run
Refer to SBT docs for more commands.
Delta Transaction Log Protocol document provides a specification of the transaction protocol.
Requirements for Underlying Storage Systems
Delta Lake ACID guarantees are predicated on the atomicity and durability guarantees of the storage system. Specifically, we require the storage system to provide the following.
- Atomic visibility: There must be a way for a file to be visible in its entirety or not visible at all.
- Mutual exclusion: Only one writer must be able to create (or rename) a file at the final destination.
- Consistent listing: Once a file has been written in a directory, all future listings for that directory must return that file.
See the online documentation on Storage Configuration for details.
Delta Lake ensures serializability for concurrent reads and writes. Please see Delta Lake Concurrency Control for more details.
We welcome contributions to Delta Lake. See our CONTRIBUTING.md for more details.
We also adhere to the Delta Lake Code of Conduct.
Apache License 2.0, see LICENSE.
There are two mediums of communication within the Delta Lake community.