Apache Flink 1.9.0 Release Announcement • Hacker News Board

Re: Apache Flink 1.9.0 Release Announcement

#11

Post by jdm2212 » Sun, Aug 25, 2019, 6:52 AM UTC

BFLpL0QNek wrote: post #10

jdm2212 wrote: post #5

Earlier quoted context omitted.

The only two of those I know are Kafka and Flink. For those two: Flink is much more full-featured and performant (basically the full Google DataFlow API, and several orders of magnitude faster than Kafka Streaming), but Kafka Streaming has a stupid simple API that is useful if you need streaming because $reason but don't care about scaling up to infinity. If you're doing some really hacky demoware, Kafka Streaming wi…

Do you have any numbers to back up Flink is faster than KStreams, also under what scenario? I am genuinely interested as use KStreams a lot but the engineering discipline in the API leads a lot to be desired and more than happy to switch the API if Flink is that much better.

Here's a benchmark of KStreams and Flink [1]. Note that the Flink vs Spark comparison is disputed [2], but both Flink and Spark are several orders of magnitude faster than KStreams. This is inevitable given KStreams architecture -- it stores all its state in Kafka rather than in a data store and with data structures optimized for the use case and doesn't do much coordination among workers. KStreams is there if you want streaming semantics on top of a small-ish Kafka topic you own, but don't care too much about perf. Deploying and maintaining Flink is a much bigger hassle than KStreams -- you need DevOps support to get Flink running, whereas KStreams runs (albeit quite slowly) inside your application with no new state store needed.

Confluent has a good discussion of the ownership issue (DevOps for Flink, devs for KStreams) here [3] though they seriously downplay the huge gap in perf.

[1] https://databricks.com/blog/2017/10/11/benchmarking-structur...

[2] https://www.ververica.com/blog/curious-case-broken-benchmark...

[3] https://www.confluent.io/blog/apache-flink-apache-kafka-stre...

Re: Apache Flink 1.9.0 Release Announcement

#12

Post by readme3 » Sun, Aug 25, 2019, 8:03 AM UTC

continuations wrote: post #3

Apache has a large number of stream processing frameworks: Flink vs Spark vs Storm vs Kafka vs Samza vs Apex How do they compare? How would you choose which one to use?

Also include storm in the mix too. Storm 2.0 was released recently. We have been using storm for a long time and we really like its a) Simple programming model b) Support for a wide variety of sources (e.g Kinesis , EventHub) c)Easy troubleshooting We did evaluate Spark streaming (we use Spark for batch workloads and it works well) , but fell back to storm because of the above

Re: Apache Flink 1.9.0 Release Announcement

#13

Post by je42 » Sun, Aug 25, 2019, 10:42 AM UTC

jdm2212 wrote: post #11

BFLpL0QNek wrote: post #10

Earlier quoted context omitted.

Do you have any numbers to back up Flink is faster than KStreams, also under what scenario? I am genuinely interested as use KStreams a lot but the engineering discipline in the API leads a lot to be desired and more than happy to switch the API if Flink is that much better.

Here's a benchmark of KStreams and Flink [1]. Note that the Flink vs Spark comparison is disputed [2], but both Flink and Spark are several orders of magnitude faster than KStreams. This is inevitable given KStreams architecture -- it stores all its state in Kafka rather than in a data store and with data structures optimized for the use case and doesn't do much coordination among workers. KStreams is there if you wa…

mmh. i found this more recent benchmark. where flink was still faster but kstreams' perfromance much more closer then in the 2017 benchmarks.

I guess kstreams improved performance over time ? Or is the benchmark design just different ?