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https://issues.apache.org/jira/browse/FLINK-5756?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15925592#comment-15925592
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Wenlong Lyu commented on FLINK-5756:
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In RocksDB , the merge operation is processed in both compaction and get but
not in merge. When merging two Slices by a StringAppendOperator, you will need
to create a new string, which can be time costly when there are thousands of
slice to merge.
I think that is why it is slow to get the value after you added five thousand
of items to List. If you call {{rocksdb.compactRange()}} before get, it will be
quite quickly.
In really application scenario, the compaction happens more often than what is
in the test, and the performance will be much better in real environment except
for in the extreme test scenario.
> 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 to execute get()
> operation.
> ///////////////////////////////////////////////////////////////////////////////
> The flink's code is as follows:
> {code}
> 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()
> {code}
> ////////////////////////////////////
> The RocksDB Test code:
> {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))
> }
> }
> {code}
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