So many great new features, thanks everyone for contributing, and thanks Sung for running the release!
Kind regards, Fokko Op wo 31 jul 2024 om 05:00 schreef Jack Ye <yezhao...@gmail.com>: > Thank you Sung for managing the release! And many thanks to everyone that > participated! > > Best, > Jack Ye > > > On Tue, Jul 30, 2024 at 12:24 PM Kevin Liu <kevin.jq....@gmail.com> wrote: > >> Woot! Thank you, Sung, for managing the release! I'm very excited about >> this new version. >> >> I want to highlight the many contributors who have improved PyIceberg >> since the last release. There have been 34 unique contributors (source >> <https://github.com/apache/iceberg-python/compare/pyiceberg-0.6.1...pyiceberg-0.7.0rc2>). >> Also, as seen in issue #511 >> <https://github.com/apache/iceberg-python/issues/511>, the community has >> come together to contribute various metadata table implementations to >> PyIceberg. >> >> Onwards and upwards, >> >> Kevin >> >> On Tue, Jul 30, 2024 at 12:08 PM Sung Yun <sungwy...@gmail.com> wrote: >> >>> I'm pleased to announce the release of Apache PyIceberg 0.7.0! >>> >>> Once again, this large release includes the following features on a high >>> level: >>> >>> * Write support to partitioned tables with IdentityTransform and >>> TimeTransform partitions >>> * Support for deletes using predicates. It will drop whole files when it >>> is able to based on the Iceberg statistics, otherwise it will perform a >>> copy-on-write. >>> * Parallelizing writes for a given partition based on a target file size >>> * A new API for rendering PyArrow tables that show metadata about the >>> tables’ manifests, partitions, etc >>> * Support for evolving table partitions >>> * Updated schema compatibility check to be more permissive, by >>> supporting promotable types and subset of schemas on write >>> * Option to merge manifests on write when number of manifests exceeds a >>> threshold >>> * Support staging a table for creation and building a transaction >>> * A new table scan API to return an Arrow RecordBatchReader as opposed >>> to a fully materialized Arrow table >>> * Support for categorical and large PyArrow types on write >>> * A new API to add existing parquet files to a table without rewriting >>> them >>> * Support for loading custom catalog >>> >>> This Python release can be downloaded from: >>> https://pypi.org/project/pyiceberg/0.7.0/ >>> >>> Thank you everyone again for the amazing contributions and engagement >>> since the last release. >>> >>> Sincerely, >>> Sung >>> >>
