This document summarizes updates from the August 2015 Berlin Apache Flink Meetup. It discusses that Apache Flink now has a new committer, discussions have started for the 0.9.1 release, and Flink is gaining popularity with over 1000 Twitter followers and 500 GitHub stars. It also provides information on improvements now in the master version including the Gelly Scala API and a streaming connector for Elastic Search. Upcoming events are noted including Flink meetups in Washington DC, Belgium, and the Flink Talks schedule being announced for ApacheCon in Budapest.

1. Berlin Apache Flink Meetup #10
Community Update
August 2015
Robert Metzger
Committer and PMC Member
rmetzger@apache.org
@rmetzger_

2. Apache Flink is an open source platform for
scalable batch and stream data processing.
Apache Flink is …
flink.apache.org 1
• The core of Flink is a distributed
streaming dataflow engine.
• Executing dataflows in
parallel on clusters
• Providing a reliable
foundation for various
workloads
• DataSet and DataStream
programming abstractions are
the foundation for user programs
and higher layers

3. One engine for many use cases
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Real time streaming
topologies
Machine Learning at scale
Graph Analysis
Long batch
pipelines

4. What happened?
• New Committer: Chesnay Schepler
• Discussions for a 0.9.1 release started
• Flink is becoming more popular:
– 1000+ Twitter followers
– 500+ GitHub stars
– Named as “open source Big Data project” to
watch by ZDNet.
– Flink Forward schedule with great speakers
announced
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5. Now in master (0.10-SNAPSHOT)
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• Gelly Scala API
• Flink dropped Java 6 support
• Streaming connector for Elastic Search
• Sampling operation on DataSet API
• A lot of bug fixes:
– Streaming: APIs, general stability, kafka
connector

6. Articles and Meetups
• High-throughput, low-latency, and exactly-once stream
processing with Apache Flink [1]
• Introducing Gelly: Graph Processing with Apache Flink [2]
• Apache Flink and the case for stream processing [3]
• Crunching Parquet Files with Apache Flink [4]
• The morning paper: Asynchronous Distributed Snapshots for
Distributed Dataflows [5]
• Five open source Big Data projects to watch [6]
• Big Data Performance Engineering: Examples from Hadoop,
Pig, HBase, Flink and Spark [7]
5
[1] http://data-artisans.com/high-throughput-low-latency-and-exactly-once-stream-processing-with-apache-flink/
[2] http://flink.apache.org/news/2015/08/24/introducing-flink-gelly.html
[3] http://www.kdnuggets.com/2015/08/apache-flink-stream-processing.html
[4] https://medium.com/@istanbul_techie/crunching-parquet-files-with-apache-flink-200bec90d8a7
[5] http://blog.acolyer.org/2015/08/19/asynchronous-distributed-snapshots-for-distributed-dataflows/
[6] http://www.zdnet.com/article/five-open-source-big-data-projects-to-watch/
[7] http://www.bigsynapse.com/addressing-big-data-performance

7. GitHub stats
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8. Upcoming
• Sept 15: Washington DC Area Apache
Flink Meetup
• Sept 17: StreamProcessing.be meetup
• Sept 28-30: Flink Talks at ApacheCon Big
Data Budapest
New Meetup groups:
• New York
• Boston
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9. Flink Forward schedule published
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• http://flink-forward.org/?post_type=day
• Talks by Huawei, CapitalOne, Bouyges,
Ericsson, Amadeus, ResearchGate, RedHat,
and many more.