Syinchwun Leo created FLINK-5756: ------------------------------------ Summary: When there are many values under the same key in ListState, RocksDBStateBackend performances poor Key: FLINK-5756 URL: https://issues.apache.org/jira/browse/FLINK-5756 Project: Flink Issue Type: Improvement Components: State Backends, Checkpointing Affects Versions: 1.2.0 Environment: CentOS 7.2 Reporter: Syinchwun Leo
When using RocksDB as the StateBackend, if there are many values under the same key in ListState, the windowState.get() operator performances very poor. I also the the RocksDB using version 4.11.2, the performance is also very poor. The problem is likely to related to RocksDB itself's get() operator after using merge(). The problem may influences the window operation's performance when the size is very large using ListState. I try to merge 50000 values under the same key in RocksDB, It costs 120 seconds /////////////////////////////////////////////////////////////////////////////// The flink's code is as follows: class SEventSource extends RichSourceFunction [SEvent] { private var count = 0L private val alphabet = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWZYX0987654321" override def run(sourceContext: SourceContext[SEvent]): Unit = { while (true) { for (i <- 0 until 5000) { sourceContext.collect(SEvent(1, "hello-"+count, alphabet,1)) count += 1L } Thread.sleep(1000) } } } env.addSource(new SEventSource) .assignTimestampsAndWatermarks(new AssignerWithPeriodicWatermarks[SEvent] { override def getCurrentWatermark: Watermark = { new Watermark(System.currentTimeMillis()) } override def extractTimestamp(t: SEvent, l: Long): Long = { System.currentTimeMillis() } }) .keyBy(0) .window(SlidingEventTimeWindows.of(Time.seconds(20), Time.seconds(2))) .apply(new WindowStatistic) .map(x => (System.currentTimeMillis(), x)) .print() //////////////////////////////////// The RocksDB Test code: val stringAppendOperator = new StringAppendOperator val options = new Options() options.setCompactionStyle(CompactionStyle.LEVEL) .setCompressionType(CompressionType.SNAPPY_COMPRESSION) .setLevelCompactionDynamicLevelBytes(true) .setIncreaseParallelism(4) .setUseFsync(true) .setMaxOpenFiles(-1) .setCreateIfMissing(true) .setMergeOperator(stringAppendOperator) val write_options = new WriteOptions write_options.setSync(false) val rocksDB = RocksDB.open(options, "/******/Data/") val key = "key" val value = "abcdefghijklmnopqrstuvwxyz0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ7890654321" val beginmerge = System.currentTimeMillis() for(i <- 0 to 50000) { rocksDB.merge(key.getBytes(), ("s"+ i + value).getBytes()) //rocksDB.put(key.getBytes, value.getBytes) } println("finish") val begin = System.currentTimeMillis() rocksDB.get(key.getBytes) val end = System.currentTimeMillis() println("merge cost:" + (begin - beginmerge)) println("Time consuming:" + (end - begin)) } } -- This message was sent by Atlassian JIRA (v6.3.15#6346)