Apache Flink in 2017: Year in Review
This post originally appeared on the Apache Flink blog. It was reproduced here under the Apache License, Version 2.0.
In this post, we’ll look back on the project’s progress over the course of 2017, and we’ll also preview what 2018 has in store.
GithubFirst, here’s a summary of community statistics from GitHub. At the time of writing:
- Contributors have increased from 258 in December 2016 to 352 in December 2017 (up 36%)
- Stars have increased from 1830 in December 2016 to 3036 in December 2017 (up 65%)
- Forks have increased from 1255 in December 2016 to 2070 in December 2017 (up 65%)
We also welcomed 3 new members to the project management committee (PMC): Greg Hogan, Tzu-Li (Gordon) Tai and Chesnay Schepler.
Next, let’s take a look at a few other project stats, starting with number of commits. If we run:
git log --pretty<span class="o">=</span>oneline --after<span class="o">=</span>12/31/2016 <span class="p">|</span> wc -l
Now, let’s go a bit deeper, here are instructions to take a look at this data yourself.
Download and install gitstats from the project homepage, then clone the Apache Flink git repository:
git clone firstname.lastname@example.org:apache/flink.git
gitstats flink/ flink-stats/
Monday remains the day of the week with the most commits over the project’s history, but Wednesday is catching up:
5 pm remains the preferred commit time, closely followed by 4 pm:
MeetupsApache Flink Meetup membership grew by 20% this year to a total of 19,767 members at 39 meetups listing Flink as a topic. With meetups on five continents, the Flink community is proud to be truly global.
Flink Forward 20172017 was the first year we ran a Flink Forward conference in both Berlin (September 11-13) and San Francisco (April 10-11), and over 350 members of our community attended each event for speaker sessions, training, and discussion about Flink.
Slides and videos are available for all speaker sessions, and if you’re interested in learning more about how organizations use Flink in production, we encourage you to browse and watch a couple.
For 2018, Flink Forward will be back in September in Berlin, and in April in San Francisco.
Features and Ecosystem
Flink Ecosystem GrowthFlink was added to a selection of distributions and integrations during 2017, making it easier for a wider user base to get started with Flink:
- Official Docker image
- Official DC/OS and Mesos support
- A Flink connector for Pravega, Dell/EMC’s streaming storage system.
- Uber announced AthenaX, a streaming SQL platform powered by Apache Flink.
- dataArtisans announced an early access program of a SaaS product based on Apache Flink, dA Platform 2.
Feature Timeline in 2017Just in time for the end of the year, our 1.4 release read the full release announcement landed in mid-December culminating 5 months of work and the resolution of more than 900 issues. This is the fifth major release in the 1.x.y series.
Here’s a selection of major features added to Flink over the course of 2017:
If you take a look at the resolved issues and enhancements for 2017 on Jira you can see that the community resolved over 1,831 issues and feature additions.
Regarding roadmap commitments from 2016, there is mixed news, with some items a part of current releases, others scheduled for upcoming releases and some that remain under discussion.
Looking ahead to 2018A good source of information about the Flink community’s roadmap is the list of Flink Improvement Proposals (FLIPs) in the project wiki. Below, we’ll highlight a selection of FLIPs accepted by the community as well as some that are still under discussion.
Work is already underway on a number of these features, and some will be included in Flink 1.5 at the beginning of 2018.
- Improved BLOB storage architecture, as described in FLIP-19 to consolidate API usage and improve concurrency.
- Integration of SQL and CEP, as described in FLIP-20 to allow developers to create complex event processing (CEP) patterns using SQL statements.
- Unified checkpoints and savepoints, as described in FLIP-10, to allow savepoints to be triggered automatically–important for program updates for the sake of error handling because savepoints allow the user to modify both the job and Flink version whereas checkpoints can only be recovered with the same job.
- An improved Flink deployment and process model, as described in FLIP-6, to allow for better integration with Flink and cluster managers and deployment technologies such as Mesos, Docker, and Kubernetes.
- Fine-grained recovery from task failures, as described in FLIP-1 to improve recovery efficiency and only re-execute failed tasks, reducing the amount of state that Flink needs to transfer on recovery.
- An SQL Client, as described in FLIP-24 to add a service and a client to execute SQL queries against batch and streaming tables.
- Serving of machine learning models, as described in FLIP-23 to add a library that allows users to apply offline-trained machine learning models to data streams.
Lastly, we’d like to extend a sincere thank you to all the Flink community for making 2017 a great year!