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(Updated Nov. 8, 2016, 12:47 a.m.) Review request for samza, Chris Pettitt, Jake Maes, and Navina Ramesh. Changes ------- Updates based on the previous feedback. Thanks a lot for the comments! Repository: samza Description ------- In the recent experiments of samza batch job (consuming hdfs data on hadoop), the results are subpar to map/reduce and spark. By looking at the metrics closely, we found two basic problems: 1) Not enough data to process. This is spotted as the unprocessed message queue length was zero for quite a lot of times. 2) Not process fast enough. We found samza performed closely in both median size records (100B) and small record (10B), while spark can scale very well in the small record (over 1M/s). The first problem is solved by increasing the buffer size. This ticket is to address the second problem, which contains three major improvements: - Option to turn off timer metrics calculation: one of the main time spent in samza processing turns out to be just keeping the timer metrics. While it is useful in debugging, it becomes a bottleneck when running a stable job with high performance. In my testing job which consumes 8M mock data, it took 30 secs with timer metrics on. After turning it off, it only took 14 secs. - Java coding improvements: The AsyncRunLoop code can be further optimized for efficiency. Some of the thread-safe data structure I am using is not for optimal performance (Collections.synchronizedSet). I switched to use CopyOnWriteArraySet, which has far better performance due to more reads and small set size. - Specific handling for in-order processing improvements: AsyncRunLoop handles the callbacks regardless of whether it's in-order or out-of-order (max concurrency > 1), which incurs quite some cost. By simplying the logic for in-order handling, the performance gains. After all three improvements, my test job with mock input (8M messages) can be processed within 8 sec (down from org 30 secs), so it's 1M/s for one cpu core. For the performance benchmark jobs running in Hadoop, we also see a 4 times improvement with all the fixes above. Please take a look at the attached spreedsheet (see the numbers with fix(turn off the timing metrics) and fix2(all three together). Diffs (updated) ----- samza-core/src/main/java/org/apache/samza/container/RunLoopFactory.java 609a956a1f2fa97419c2f66fe2fb6876aaaeecd0 samza-core/src/main/java/org/apache/samza/task/AsyncRunLoop.java 8fac8155c7f64e67d4a39ec6943f98da1e1d63d9 samza-core/src/main/java/org/apache/samza/task/CoordinatorRequests.java 052b3b91ec609ca6288662cfa2d3e71b0273d020 samza-core/src/main/java/org/apache/samza/task/TaskCallbackImpl.java 9b700998d2af040c6734289f7f28bbd78c36bd2c samza-core/src/main/java/org/apache/samza/task/TaskCallbackManager.java 132cf59eb593524a4cac134aeceeeb37a4c74b1f samza-core/src/main/java/org/apache/samza/util/TimerClock.java PRE-CREATION samza-core/src/main/java/org/apache/samza/util/Utils.java 472e0a59d5aa992b136292c8a3347c311e2cd606 samza-core/src/main/scala/org/apache/samza/config/MetricsConfig.scala c3fd8bfb2e16a4c5146d34682d04cb1d4e9bbe72 samza-core/src/main/scala/org/apache/samza/container/SamzaContainer.scala e0468ee89c89fd720834461771ebb36475475bcb samza-core/src/main/scala/org/apache/samza/system/SystemConsumers.scala e2aed5b1c2e77a914268963b21809380972037b6 samza-core/src/main/scala/org/apache/samza/util/Util.scala c4836f202f7eda1d4e71eac94fd48e46207b0316 samza-core/src/test/java/org/apache/samza/task/TestAsyncRunLoop.java 6000ffaf2b8723d48a72e58b571f242a42dc8128 samza-core/src/test/java/org/apache/samza/task/TestAsyncStreamAdapter.java 99e1e18bcfa6bca1e275d8ae030a77ff8d70a4eb samza-core/src/test/java/org/apache/samza/task/TestTaskCallbackImpl.java f1dbf35165e6ddfc02e3522887c25d78a4bbfcd7 samza-core/src/test/java/org/apache/samza/task/TestTaskCallbackManager.java d7110f34a9eae6e9ffc15b4982bfbb180da88b2d samza-kv/src/main/scala/org/apache/samza/storage/kv/BaseKeyValueStorageEngineFactory.scala c975893a42689732c39c39600fecacee843bf9d6 Diff: https://reviews.apache.org/r/53282/diff/ Testing ------- ./gradlew build Tested in the yarn hadoop cluster with different kinds of jobs. File Attachments ---------------- hdfs performance https://reviews.apache.org/media/uploaded/files/2016/11/02/c05007fe-2fdd-4c8c-b5ef-b7862dea13b2__hdfs_perf.png Thanks, Xinyu Liu
