vanzin 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_r318752130
########## File path: external/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/InternalKafkaConsumerPool.scala ########## @@ -0,0 +1,217 @@ +/* + * 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.ConcurrentHashMap + +import org.apache.commons.pool2.{BaseKeyedPooledObjectFactory, PooledObject, SwallowedExceptionListener} +import org.apache.commons.pool2.impl.{DefaultEvictionPolicy, DefaultPooledObject, GenericKeyedObjectPool, GenericKeyedObjectPoolConfig} + +import org.apache.spark.SparkConf +import org.apache.spark.internal.Logging +import org.apache.spark.sql.kafka010.InternalKafkaConsumerPool._ +import org.apache.spark.sql.kafka010.KafkaDataConsumer.CacheKey + +/** + * Provides object pool for [[InternalKafkaConsumer]] which is grouped by [[CacheKey]]. + * + * This class leverages [[GenericKeyedObjectPool]] internally, hence providing methods based on + * the class, and same contract applies: after using the borrowed object, you must either call + * returnObject() if the object is healthy to return to pool, or invalidateObject() if the object + * should be destroyed. + * + * The soft capacity of pool is determined by "spark.kafka.consumer.cache.capacity" config value, + * and the pool will have reasonable default value if the value is not provided. + * (The instance will do its best effort to respect soft capacity but it can exceed when there's + * a borrowing request and there's neither free space nor idle object to clear.) + * + * This class guarantees that no caller will get pooled object once the object is borrowed and + * not yet returned, hence provide thread-safety usage of non-thread-safe [[InternalKafkaConsumer]] + * unless caller shares the object to multiple threads. + */ +private[kafka010] class InternalKafkaConsumerPool( + objectFactory: ObjectFactory, + poolConfig: PoolConfig) { + + def this(conf: SparkConf) = { + this(new ObjectFactory, new PoolConfig(conf)) + } + + // the class is intended to have only soft capacity + assert(poolConfig.getMaxTotal < 0) + + private val pool = { + val internalPool = new GenericKeyedObjectPool[CacheKey, InternalKafkaConsumer]( + objectFactory, poolConfig) + internalPool.setSwallowedExceptionListener(CustomSwallowedExceptionListener) + internalPool + } + + /** + * Borrows [[InternalKafkaConsumer]] object from the pool. If there's no idle object for the key, + * the pool will create the [[InternalKafkaConsumer]] object. + * + * If the pool doesn't have idle object for the key and also exceeds the soft capacity, + * pool will try to clear some of idle objects. + * + * Borrowed object must be returned by either calling returnObject or invalidateObject, otherwise + * the object will be kept in pool as active object. + */ + def borrowObject(key: CacheKey, kafkaParams: ju.Map[String, Object]): InternalKafkaConsumer = { + updateKafkaParamForKey(key, kafkaParams) + + if (size == poolConfig.softMaxSize()) { + pool.clearOldest() + } + + pool.borrowObject(key) + } + + /** Returns borrowed object to the pool. */ + def returnObject(consumer: InternalKafkaConsumer): Unit = { + pool.returnObject(extractCacheKey(consumer), consumer) + } + + /** Invalidates (destroy) borrowed object to the pool. */ + def invalidateObject(consumer: InternalKafkaConsumer): Unit = { + pool.invalidateObject(extractCacheKey(consumer), consumer) + } + + /** Invalidates all idle consumers for the key */ + def invalidateKey(key: CacheKey): Unit = { + pool.clear(key) + } + + /** + * Closes the keyed object pool. Once the pool is closed, + * borrowObject will fail with [[IllegalStateException]], but returnObject and invalidateObject + * will continue to work, with returned objects destroyed on return. + * + * Also destroys idle instances in the pool. + */ + def close(): Unit = { + pool.close() + } + + def reset(): Unit = { + // this is the best-effort of clearing up. otherwise we should close the pool and create again + // but we don't want to make it "var" only because of tests. + pool.clear() + } + + def numIdle: Int = pool.getNumIdle + + def numIdle(key: CacheKey): Int = pool.getNumIdle(key) + + def numActive: Int = pool.getNumActive + + def numActive(key: CacheKey): Int = pool.getNumActive(key) + + def size: Int = numIdle + numActive + + def size(key: CacheKey): Int = numIdle(key) + numActive(key) + + private def updateKafkaParamForKey(key: CacheKey, kafkaParams: ju.Map[String, Object]): Unit = { + // We can assume that kafkaParam should not be different for same cache key, + // otherwise we can't reuse the cached object and cache key should contain kafkaParam. + // So it should be safe to put the key/value pair only when the key doesn't exist. + val oldKafkaParams = objectFactory.keyToKafkaParams.putIfAbsent(key, kafkaParams) + require(oldKafkaParams == null || kafkaParams == oldKafkaParams, "Kafka parameters for same " + + s"cache key should be equal. old parameters: $oldKafkaParams new parameters: $kafkaParams") + } + + private def extractCacheKey(consumer: InternalKafkaConsumer): CacheKey = { + new CacheKey(consumer.topicPartition, consumer.kafkaParams) + } +} + +private[kafka010] object InternalKafkaConsumerPool { + object CustomSwallowedExceptionListener extends SwallowedExceptionListener with Logging { + override def onSwallowException(e: Exception): Unit = { + logError(s"Error closing Kafka consumer", e) + } + } + + class PoolConfig(conf: SparkConf) extends GenericKeyedObjectPoolConfig[InternalKafkaConsumer] { + private var _softMaxSize = Int.MaxValue + + def softMaxSize(): Int = _softMaxSize + + init() + + def init(): Unit = { + _softMaxSize = conf.get(CONSUMER_CACHE_CAPACITY) + + val jmxEnabled = conf.get(CONSUMER_CACHE_JMX_ENABLED) + val minEvictableIdleTimeMillis = conf.get(CONSUMER_CACHE_TIMEOUT) + val evictorThreadRunIntervalMillis = conf.get( + CONSUMER_CACHE_EVICTOR_THREAD_RUN_INTERVAL) + + // NOTE: Below lines define the behavior, so do not modify unless you know what you are + // doing, and update the class doc accordingly if necessary when you modify. + + // 1. Set min idle objects per key to 0 to avoid creating unnecessary object. + // 2. Set max idle objects per key to 3 but set total objects per key to infinite + // which ensures borrowing per key is not restricted. + // 3. Set max total objects to infinite which ensures all objects are managed in this pool. + setMinIdlePerKey(0) + setMaxIdlePerKey(3) + setMaxTotalPerKey(-1) + setMaxTotal(-1) + + // Set minimum evictable idle time which will be referred from evictor thread + setMinEvictableIdleTimeMillis(minEvictableIdleTimeMillis) + setSoftMinEvictableIdleTimeMillis(-1) + + // evictor thread will run test with ten idle objects + setTimeBetweenEvictionRunsMillis(evictorThreadRunIntervalMillis) + setNumTestsPerEvictionRun(10) + setEvictionPolicy(new DefaultEvictionPolicy[InternalKafkaConsumer]()) + + // Immediately fail on exhausted pool while borrowing + setBlockWhenExhausted(false) + + setJmxEnabled(jmxEnabled) + setJmxNamePrefix("kafka010-cached-simple-kafka-consumer-pool") + } + } + + class ObjectFactory extends BaseKeyedPooledObjectFactory[CacheKey, InternalKafkaConsumer] + with Logging { Review comment: This isn't logging anything. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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