Hi all, It’s time to submit our quarterly report to the ASF board again this Wednesday. Here is my draft about what’s new — feel free to suggest changes.
------------ Apache Spark is a fast and general engine for large-scale data processing. It offers high-level APIs in Java, Scala, Python and R as well as a rich set of libraries including stream processing, machine learning, and graph analytics. Project status: - Discussions are continuing about our next feature release, which will likely be Spark 3.0, on the dev and user mailing lists. Some key questions include whether to remove various deprecated APIs, and which minimum versions of Java, Python, Scala, etc to support. There are also a number of new features targeting this release. We encourage everyone in the community to give feedback on these discussions through our mailing lists or issue tracker. - We announced a plan to stop supporting Python 2 in our next major release, as many other projects in the Python ecosystem are now dropping support (https://spark.apache.org/news/plan-for-dropping-python-2-support.html <https://spark.apache.org/news/plan-for-dropping-python-2-support.html>). - We added three new PMC members to the project in May: Takuya Ueshin, Jerry Shao and Hyukjin Kwon. - There is an ongoing discussion on our dev list about whether to consider adding project committers who do not contribute to the code or docs in the project, and what the criteria might be for those. (Note that the project does solicit committers who only work on docs, and has also added committers who work on other tasks, like maintaining our build infrastructure). Trademarks: - We are continuing engagement with various organizations. Latest releases: - May 8th, 2018: Spark 2.4.3 - April 23rd, 2019: Spark 2.4.2 - March 31st, 2019: Spark 2.4.1 - Feb 15th, 2019: Spark 2.3.3 Committers and PMC: - The latest committer was added on Jan 29th, 2019 (Jose Torres). - The latest PMC members were added on May 21st, 2019 (Jerry Shao, Takuya Ueshin and Hyukjin Kwon). ------------
