[jira] [Updated] (SPARK-21443) Very long planning duration for queries with lots of operations

["Eyal Zituny (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-21443?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Eyal Zituny updated SPARK-21443:
--------------------------------
    Priority: Minor  (was: Major)

> Very long planning duration for queries with lots of operations
> ---------------------------------------------------------------
>
>                 Key: SPARK-21443
>                 URL: https://issues.apache.org/jira/browse/SPARK-21443
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL, Structured Streaming
>    Affects Versions: 2.2.0
>            Reporter: Eyal Zituny
>            Priority: Minor
>
> Creating a streaming query with large amount of operations and fields (100+) results in a very long query planning phase. in the example bellow, the plan phase has taken 35 seconds while the actual batch execution took only 1.3 second.
> after some investigation, i have found out that the root causes of this are 2 optimizer rules which seems to take most of the planning time: InferFiltersFromConstraints and PruneFilters
> I would suggest the following:
> # fix the inefficient optimizer rules
> # add warn level logging if a rule has taken more then xx ms
> # allow custom removing of optimizer rules (opposite to spark.experimental.extraOptimizations)
> # reuse query plans (optional) where possible
> reproducing this issue can be done with the bellow script which simulates the scenario:
> {code:java}
> import org.apache.spark.sql.SparkSession
> import org.apache.spark.sql.execution.streaming.MemoryStream
> import org.apache.spark.sql.streaming.StreamingQueryListener.{QueryProgressEvent, QueryStartedEvent, QueryTerminatedEvent}
> import org.apache.spark.sql.streaming.{ProcessingTime, StreamingQueryListener}
> case class Product(pid: Long, name: String, price: Long, ts: Long = System.currentTimeMillis())
> case class Events (eventId: Long, eventName: String, productId: Long) {
> 	def this(id: Long) = this(id, s"event$id", id%100)
> }
> object SparkTestFlow {
> 	def main(args: Array[String]): Unit = {
> 		val spark = SparkSession
> 		  .builder
> 		  .appName("TestFlow")
> 		  .master("local[8]")
> 		  .getOrCreate()
> 		spark.sqlContext.streams.addListener(new StreamingQueryListener {
> 			override def onQueryTerminated(event: QueryTerminatedEvent): Unit = {}
> 			override def onQueryProgress(event: QueryProgressEvent): Unit = {
> 				if (event.progress.numInputRows>0) {
> 					println(event.progress.toString())
> 				}
> 			}
> 			override def onQueryStarted(event: QueryStartedEvent): Unit = {}
> 		})
> 		
> 		import spark.implicits._
> 		implicit val  sclContext = spark.sqlContext
> 		import org.apache.spark.sql.functions.expr
> 		val seq = (1L to 100L).map(i => Product(i, s"name$i", 10L*i))
> 		val lookupTable = spark.createDataFrame(seq)
> 		val inputData = MemoryStream[Events]
> 		inputData.addData((1L to 100L).map(i => new Events(i)))
> 		val events = inputData.toDF()
> 		  .withColumn("w1", expr("0"))
> 		  .withColumn("x1", expr("0"))
> 		  .withColumn("y1", expr("0"))
> 		  .withColumn("z1", expr("0"))
> 		val numberOfSelects = 40 // set to 100+ and the planning takes forever
> 		val dfWithSelectsExpr = (2 to numberOfSelects).foldLeft(events)((df,i) =>{
> 			val arr = df.columns.++(Array(s"w${i-1} + rand() as w$i", s"x${i-1} + rand() as x$i", s"y${i-1} + 2 as y$i", s"z${i-1} +1 as z$i"))
> 			df.selectExpr(arr:_*)
> 		})
> 		val withJoinAndFilter = dfWithSelectsExpr
> 		  .join(lookupTable, expr("productId = pid"))
> 		  .filter("productId < 50")
> 		val query = withJoinAndFilter.writeStream
> 		  .outputMode("append")
> 		  .format("console")
> 		  .trigger(ProcessingTime(2000))
> 		  .start()
> 		query.processAllAvailable()
> 		spark.stop()
> 	}
> }
> {code}
> the query progress output will show: 
> {code:java}
> "durationMs" : {
>     "addBatch" : 1310,
>     "getBatch" : 6,
>     "getOffset" : 0,
>     "*queryPlanning*" : 36924,
>     "triggerExecution" : 38297,
>     "walCommit" : 33
>   }
> {code}



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