Hi all,

It’s time to send our quarterly report to the ASF board. Here is my draft — 
please feel free to suggest any changes.

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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:

- We made the first preview release for Spark 3.0 on November 6th. This
  release aims to get early feedback on the new APIs and functionality
  targeting Spark 3.0 but does not provide API or stability guarantees. We
  encourage community members to try this release and leave feedback on
  JIRA. More info about what’s new and how to report feedback is found at
  https://spark.apache.org/news/spark-3.0.0-preview.html.

- We published Spark 2.4.4. and 2.3.4 as maintenance releases to fix bugs
  in the 2.4 and 2.3 branches.

- We added one new PMC members and six committers to the project
  in August and September, covering data sources, streaming, SQL, ML
  and other components of the project.

Trademarks:

- Nothing new to report since August.

Latest releases:

- Spark 3.0.0-preview was released on Nov 6th, 2019.
- Spark 2.3.4 was released on Sept 9th, 2019.
- Spark 2.4.4 was released on Sept 1st, 2019.

Committers and PMC:

- The latest committer was added on Sept 4th, 2019 (Dongjoon Hyun).
- The latest committer was added on Sept 9th, 2019 (Weichen Xu). We
  also added Ryan Blue, L.C. Hsieh, Gengliang Wang, Yuming Wang and
  Ruifeng Zhang as committers in the past three months.

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