Apache Iceberg (incubating) 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.incubator.apache.org
Iceberg is under active development in the Apache Incubator.
The core Java library that tracks table snapshots and metadata is complete, but still evolving. Current work is focused on integrating Iceberg into Spark and Presto.
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 0.6.0 tag.
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.
Iceberg is built using Gradle 4.4.
Iceberg table support is organized in library modules:
iceberg-commoncontains utility classes used in other modules
iceberg-apicontains the public Iceberg API
iceberg-corecontains implementations of the Iceberg API and support for Avro data files, this is what processing engines should depend on
iceberg-parquetis an optional module for working with tables backed by Parquet files
iceberg-orcis an optional module for working with tables backed by ORC files (experimental)
iceberg-hiveis an implementation of iceberg tables backed by hive metastore thrift client
This project Iceberg also has modules for adding Iceberg support to processing engines:
iceberg-sparkis an implementation of Spark's Datasource V2 API for Iceberg (use iceberg-runtime for a shaded version)
iceberg-datais a client library used to read Iceberg tables from JVM applications
iceberg-pigis an implementation of Pig's LoadFunc API for Iceberg
iceberg-presto-runtimegenerates a shaded runtime jar that is used by presto to integrate with iceberg tables
Iceberg's Spark integration is compatible with the following Spark versions:
|Iceberg version||Spark version|
An asterisk (*) refers to releases under the now deprecated Netflix/iceberg repo.