Apache Iceberg

Clone this repo:
  1. 2ff3043 Python: Fix missing assert in test case (#1828) by Fokko Driesprong · 2 hours ago master
  2. 66b218c ORC: Allow reads of tinyint, smallint, char, varchar types (#1821) by Shardul Mahadik · 6 hours ago
  3. c4f53e3 README: Fix links to java-api-quickstart (#1827) by Adrian Woodhead · 7 hours ago
  4. b1eff51 Spark: Make refresh of Spark cache optional in procedures (#1811) by Anton Okolnychyi · 22 hours ago
  5. b1296bc Core: Add NaN value count to content file (#1803) by yyanyy · 22 hours ago

Slack

Apache Iceberg is a new table format for storing large, slow-moving tabular data. It is designed to improve on the de-facto standard table layout built into Hive, Presto, and Spark.

Background and documentation is available at https://iceberg.apache.org

Status

Iceberg is under active development at the Apache Software Foundation.

The core Java library that tracks table snapshots and metadata is complete, but still evolving. Current work is focused on adding row-level deletes and upserts, and integration work with new engines like Flink and Hive.

The Iceberg format specification is being actively updated and is open for comment. Until the specification is complete and released, it carries no compatibility guarantees. The spec is currently evolving as the Java reference implementation changes.

Java API javadocs are available for the master.

Collaboration

Iceberg tracks issues in GitHub and prefers to receive contributions as pull requests.

Community discussions happen primarily on the dev mailing list or on specific issues.

Building

Iceberg is built using Gradle 5.4.1 with Java 1.8 or Java 11.

  • To invoke a build and run tests: ./gradlew build
  • To skip tests: ./gradlew build -x test

Iceberg table support is organized in library modules:

  • iceberg-common contains utility classes used in other modules
  • iceberg-api contains the public Iceberg API
  • iceberg-core contains implementations of the Iceberg API and support for Avro data files, this is what processing engines should depend on
  • iceberg-parquet is an optional module for working with tables backed by Parquet files
  • iceberg-arrow is an optional module for reading Parquet into Arrow memory
  • iceberg-orc is an optional module for working with tables backed by ORC files
  • iceberg-hive-metastore is an implementation of Iceberg tables backed by the Hive metastore Thrift client
  • iceberg-data is an optional module for working with tables directly from JVM applications

This project Iceberg also has modules for adding Iceberg support to processing engines:

  • iceberg-spark2 is an implementation of Spark's Datasource V2 API in 2.4 for Iceberg (use iceberg-spark-runtime for a shaded version)
  • iceberg-spark3 is an implementation of Spark's Datasource V2 API in 3.0 for Iceberg (use iceberg-spark3-runtime for a shaded version)
  • iceberg-flink contains classes for integrating with Apache Flink (use iceberg-flink-runtime for a shaded version)
  • iceberg-mr contains an InputFormat and other classes for integrating with Apache Hive
  • iceberg-pig is an implementation of Pig's LoadFunc API for Iceberg

Compatibility

Iceberg's Spark integration is compatible with Spark 2.4 and Spark 3.0 using the modules in the following table:

Iceberg versionSpark 2.4.xSpark 3.0.x
master branchspark-runtimespark3-runtime
0.9.0spark-runtimespark3-runtime
0.8.0spark-runtime