[GitHub] [spark] gaborgsomogyi commented on a change in pull request #22138: [SPARK-25151][SS] Apply Apache Commons Pool to KafkaDataConsumer

[GitBox <gi...@apache.org>]

gaborgsomogyi commented on a change in pull request #22138: [SPARK-25151][SS] Apply Apache Commons Pool to KafkaDataConsumer
URL: https://github.com/apache/spark/pull/22138#discussion_r302972803
 
 

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 File path: external/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/FetchedDataPool.scala
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+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.kafka010
+
+import java.{util => ju}
+import java.util.concurrent.{ScheduledFuture, TimeUnit}
+import java.util.concurrent.atomic.LongAdder
+
+import scala.collection.mutable
+import scala.util.control.NonFatal
+
+import org.apache.kafka.clients.consumer.ConsumerRecord
+
+import org.apache.spark.SparkEnv
+import org.apache.spark.internal.Logging
+import org.apache.spark.sql.kafka010.KafkaDataConsumer.{CacheKey, UNKNOWN_OFFSET}
+import org.apache.spark.util.ThreadUtils
+
+/**
+ * Provides object pool for [[FetchedData]] which is grouped by [[CacheKey]].
+ *
+ * Along with CacheKey, it receives desired start offset to find cached FetchedData which
+ * may be stored from previous batch. If it can't find one to match, it will create
+ * a new FetchedData.
+ */
+private[kafka010] class FetchedDataPool extends Logging {
+  import FetchedDataPool._
+
+  private val cache: mutable.Map[CacheKey, CachedFetchedDataList] = mutable.HashMap.empty
+
+  private val (minEvictableIdleTimeMillis, evictorThreadRunIntervalMillis): (Long, Long) = {
+    val conf = SparkEnv.get.conf
+
+    val minEvictIdleTime = conf.getLong(CONFIG_NAME_MIN_EVICTABLE_IDLE_TIME_MILLIS,
+      DEFAULT_VALUE_MIN_EVICTABLE_IDLE_TIME_MILLIS)
+
+    val evictorThreadInterval = conf.getLong(
+      CONFIG_NAME_EVICTOR_THREAD_RUN_INTERVAL_MILLIS,
+      DEFAULT_VALUE_EVICTOR_THREAD_RUN_INTERVAL_MILLIS)
+
+    (minEvictIdleTime, evictorThreadInterval)
+  }
+
+  private val executorService = ThreadUtils.newDaemonSingleThreadScheduledExecutor(
+    "kafka-fetched-data-cache-evictor")
+
+  private def startEvictorThread(): ScheduledFuture[_] = {
+    executorService.scheduleAtFixedRate(new Runnable {
+      override def run(): Unit = {
+        try {
+          removeIdleFetchedData()
+        } catch {
+          case NonFatal(e) =>
+            logWarning("Exception occurred while removing idle fetched data.", e)
+        }
+      }
+    }, 0, evictorThreadRunIntervalMillis, TimeUnit.MILLISECONDS)
+  }
+
+  private var scheduled = startEvictorThread()
+
+  private val numCreatedFetchedData = new LongAdder()
+  private val numTotalElements = new LongAdder()
+
+  def getNumCreated: Long = numCreatedFetchedData.sum()
+  def getNumTotal: Long = numTotalElements.sum()
+
+  def acquire(key: CacheKey, desiredStartOffset: Long): FetchedData = synchronized {
+    val fetchedDataList = cache.getOrElseUpdate(key, new CachedFetchedDataList())
+
+    val cachedFetchedDataOption = fetchedDataList.find { p =>
+      !p.inUse && p.getObject.nextOffsetInFetchedData == desiredStartOffset
+    }
+
+    var cachedFetchedData: CachedFetchedData = null
+    if (cachedFetchedDataOption.isDefined) {
+      cachedFetchedData = cachedFetchedDataOption.get
+    } else {
+      cachedFetchedData = CachedFetchedData.empty()
+      fetchedDataList += cachedFetchedData
+
+      numCreatedFetchedData.increment()
+      numTotalElements.increment()
+    }
+
+    cachedFetchedData.lastAcquiredTimestamp = System.currentTimeMillis()
+    cachedFetchedData.inUse = true
+
+    cachedFetchedData.getObject
+  }
+
+  def invalidate(key: CacheKey): Unit = synchronized {
+    cache.remove(key) match {
+      case Some(lst) => numTotalElements.add(-1 * lst.size)
+      case None =>
+    }
+  }
+
+  def release(key: CacheKey, fetchedData: FetchedData): Unit = synchronized {
+    cache.get(key) match {
+      case Some(fetchedDataList) =>
+        val cachedFetchedDataOption = fetchedDataList.find { p =>
+          p.inUse && p.getObject == fetchedData
+        }
+
+        if (cachedFetchedDataOption.isDefined) {
+          val cachedFetchedData = cachedFetchedDataOption.get
+          cachedFetchedData.inUse = false
+          cachedFetchedData.lastReleasedTimestamp = System.currentTimeMillis()
+        }
+
+      case None => logWarning(s"No matching data in pool for $fetchedData in key $key. " +
+        "It might be released before, or it was not a part of pool.")
+    }
+  }
+
+  def shutdown(): Unit = {
+    executorService.shutdownNow()
+  }
+
+  def reset(): Unit = synchronized {
+    scheduled.cancel(true)
+
+    cache.clear()
+    numTotalElements.reset()
+    numCreatedFetchedData.reset()
+
+    scheduled = startEvictorThread()
+  }
+
+  private def removeIdleFetchedData(): Unit = synchronized {
+    val timestamp = System.currentTimeMillis()
+    val maxAllowedIdleTimestamp = timestamp - minEvictableIdleTimeMillis
+    cache.values.foreach { p: CachedFetchedDataList =>
+      val idles = p.filter(q => !q.inUse && q.lastReleasedTimestamp < maxAllowedIdleTimestamp)
+      val lstSize = p.size
+      idles.foreach(idle => p -= idle)
+      numTotalElements.add(-1 * (lstSize - p.size))
+    }
+  }
+}
+
+private[kafka010] object FetchedDataPool {
+  private[kafka010] case class CachedFetchedData(fetchedData: FetchedData) {
+    var lastReleasedTimestamp: Long = Long.MaxValue
+    var lastAcquiredTimestamp: Long = Long.MinValue
+    var inUse: Boolean = false
+
+    def getObject: FetchedData = fetchedData
+  }
+
+  private object CachedFetchedData {
+    def empty(): CachedFetchedData = {
+      val emptyData = FetchedData(
+        ju.Collections.emptyListIterator[ConsumerRecord[Array[Byte], Array[Byte]]],
+        UNKNOWN_OFFSET,
+        UNKNOWN_OFFSET)
+
+      CachedFetchedData(emptyData)
+    }
+  }
+
+  private[kafka010] type CachedFetchedDataList = mutable.ListBuffer[CachedFetchedData]
+
+  val CONFIG_NAME_PREFIX = "spark.sql.kafkaFetchedDataCache."
 
 Review comment:
   In the meantime such configs are prefixed with `spark.kafka.`, for example `spark.kafka.consumer.cache.capacity`. Please see https://github.com/apache/spark/pull/24590.

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