[SPARK-29081][CORE] Replace calls to SerializationUtils.clone on properties with a faster implementation

core/src/main/scala/org/apache/spark/SparkContext.scala

@@ -31,7 +31,6 @@ import scala.reflect.{classTag, ClassTag}
 import scala.util.control.NonFatal
 
 import com.google.common.collect.MapMaker
-import org.apache.commons.lang3.SerializationUtils
 import org.apache.hadoop.conf.Configuration
 import org.apache.hadoop.fs.{FileSystem, Path}
 import org.apache.hadoop.io.{ArrayWritable, BooleanWritable, BytesWritable, DoubleWritable, FloatWritable, IntWritable, LongWritable, NullWritable, Text, Writable}
@@ -346,7 +345,7 @@ class SparkContext(config: SparkConf) extends Logging {
     override protected def childValue(parent: Properties): Properties = {
       // Note: make a clone such that changes in the parent properties aren't reflected in
       // the those of the children threads, which has confusing semantics (SPARK-10563).
-      SerializationUtils.clone(parent)
+      Utils.cloneProperties(parent)
     }
     override protected def initialValue(): Properties = new Properties()
   }

core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala

@@ -29,8 +29,6 @@ import scala.collection.mutable.{HashMap, HashSet, ListBuffer}
 import scala.concurrent.duration._
 import scala.util.control.NonFatal
 
-import org.apache.commons.lang3.SerializationUtils
-
 import org.apache.spark._
 import org.apache.spark.broadcast.Broadcast
 import org.apache.spark.executor.{ExecutorMetrics, TaskMetrics}
@@ -698,7 +696,7 @@ private[spark] class DAGScheduler(
     if (partitions.isEmpty) {
       val time = clock.getTimeMillis()
       listenerBus.post(
-        SparkListenerJobStart(jobId, time, Seq[StageInfo](), SerializationUtils.clone(properties)))
+        SparkListenerJobStart(jobId, time, Seq[StageInfo](), Utils.cloneProperties(properties)))
       listenerBus.post(
         SparkListenerJobEnd(jobId, time, JobSucceeded))
       // Return immediately if the job is running 0 tasks
@@ -710,7 +708,7 @@ private[spark] class DAGScheduler(
     val waiter = new JobWaiter[U](this, jobId, partitions.size, resultHandler)
     eventProcessLoop.post(JobSubmitted(
       jobId, rdd, func2, partitions.toArray, callSite, waiter,
-      SerializationUtils.clone(properties)))
+      Utils.cloneProperties(properties)))
     waiter
   }
 
@@ -782,7 +780,7 @@ private[spark] class DAGScheduler(
     val func2 = func.asInstanceOf[(TaskContext, Iterator[_]) => _]
     eventProcessLoop.post(JobSubmitted(
       jobId, rdd, func2, rdd.partitions.indices.toArray, callSite, listener,
-      SerializationUtils.clone(properties)))
+      Utils.cloneProperties(properties)))
     listener.awaitResult()    // Will throw an exception if the job fails
   }
 
@@ -819,7 +817,7 @@ private[spark] class DAGScheduler(
       this, jobId, 1,
       (_: Int, r: MapOutputStatistics) => callback(r))
     eventProcessLoop.post(MapStageSubmitted(
-      jobId, dependency, callSite, waiter, SerializationUtils.clone(properties)))
+      jobId, dependency, callSite, waiter, Utils.cloneProperties(properties)))
     waiter
   }
 

core/src/main/scala/org/apache/spark/util/Utils.scala

@@ -2950,6 +2950,13 @@ private[spark] object Utils extends Logging {
     val codec = codecFactory.getCodec(path)
     codec == null || codec.isInstanceOf[SplittableCompressionCodec]
   }
+
+  /** Create a new properties object with the same values as `props` */
+  def cloneProperties(props: Properties): Properties = {
+    val resultProps = new Properties()
+    props.forEach((k, v) => resultProps.put(k, v))
+    resultProps
+  }
 }
 
 private[util] object CallerContext extends Logging {

core/src/test/scala/org/apache/spark/benchmark/Benchmark.scala

@@ -141,8 +141,9 @@ private[spark] class Benchmark(
     val minIters = if (overrideNumIters != 0) overrideNumIters else minNumIters
     val minDuration = if (overrideNumIters != 0) 0 else minTime.toNanos
     val runTimes = ArrayBuffer[Long]()
+    val startTime = System.nanoTime()
     var i = 0
-    while (i < minIters || runTimes.sum < minDuration) {
+    while (i < minIters || (System.nanoTime() - startTime) < minDuration) {
       val timer = new Benchmark.Timer(i)
       f(timer)
       val runTime = timer.totalTime()

core/src/test/scala/org/apache/spark/util/PropertiesCloneBenchmark.scala

@@ -0,0 +1,62 @@
+/*
+ * 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.util
+
+import java.util.Properties
+
+import scala.util.Random
+
+import org.apache.commons.lang.SerializationUtils
+
+import org.apache.spark.benchmark.{Benchmark, BenchmarkBase}
+
+
+object PropertiesCloneBenchmark extends BenchmarkBase {
+  /**
+   * Benchmark various cases of cloning properties objects
+   */
+  override def runBenchmarkSuite(mainArgs: Array[String]): Unit = {
+    runBenchmark("Properties Cloning") {
+      def compareSerialization(name: String, props: Properties): Unit = {
+        val benchmark = new Benchmark(name, 1, output = output)
+        benchmark.addCase("SerializationUtils.clone") { _ =>
+          SerializationUtils.clone(props)
+        }
+        benchmark.addCase("Utils.cloneProperties") { _ =>
+          Utils.cloneProperties(props)
+        }
+        benchmark.run()
+      }
+      compareSerialization("Empty Properties", new Properties)
+      compareSerialization("System Properties", System.getProperties)
+      compareSerialization("Small Properties", makeRandomProps(10, 40, 100))
+      compareSerialization("Medium Properties", makeRandomProps(50, 40, 100))
+      compareSerialization("Large Properties", makeRandomProps(100, 40, 100))
+    }
+  }
+
+  def makeRandomProps(numProperties: Int, keySize: Int, valueSize: Int): Properties = {
+    val props = new Properties
+    for (_ <- 1 to numProperties) {
+      props.put(
+        Random.alphanumeric.take(keySize),
+        Random.alphanumeric.take(valueSize)
+      )
+    }
+    props
+  }
+}

core/src/test/scala/org/apache/spark/util/ResetSystemProperties.scala

@@ -19,7 +19,6 @@ package org.apache.spark.util
 
 import java.util.Properties
 
-import org.apache.commons.lang3.SerializationUtils
 import org.scalatest.{BeforeAndAfterEach, Suite}
 
 /**
@@ -43,11 +42,11 @@ private[spark] trait ResetSystemProperties extends BeforeAndAfterEach { this: Su
   var oldProperties: Properties = null
 
   override def beforeEach(): Unit = {
-    // we need SerializationUtils.clone instead of `new Properties(System.getProperties())` because
+    // we need Utils.cloneProperties instead of `new Properties(System.getProperties())` because
     // the later way of creating a copy does not copy the properties but it initializes a new
     // Properties object with the given properties as defaults. They are not recognized at all
     // by standard Scala wrapper over Java Properties then.
-    oldProperties = SerializationUtils.clone(System.getProperties)
+    oldProperties = Utils.cloneProperties(System.getProperties)
     super.beforeEach()
   }
 

streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala

@@ -26,7 +26,6 @@ import scala.collection.mutable.Queue
 import scala.reflect.ClassTag
 import scala.util.control.NonFatal
 
-import org.apache.commons.lang3.SerializationUtils
 import org.apache.hadoop.conf.Configuration
 import org.apache.hadoop.fs.Path
 import org.apache.hadoop.io.{BytesWritable, LongWritable, Text}
@@ -586,7 +585,7 @@ class StreamingContext private[streaming] (
               sparkContext.setCallSite(startSite.get)
               sparkContext.clearJobGroup()
               sparkContext.setLocalProperty(SparkContext.SPARK_JOB_INTERRUPT_ON_CANCEL, "false")
-              savedProperties.set(SerializationUtils.clone(sparkContext.localProperties.get()))
+              savedProperties.set(Utils.cloneProperties(sparkContext.localProperties.get()))
               scheduler.start()
             }
             state = StreamingContextState.ACTIVE

streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala

@@ -22,16 +22,14 @@ import java.util.concurrent.{ConcurrentHashMap, TimeUnit}
 import scala.collection.JavaConverters._
 import scala.util.Failure
 
-import org.apache.commons.lang3.SerializationUtils
-
 import org.apache.spark.ExecutorAllocationClient
 import org.apache.spark.internal.Logging
 import org.apache.spark.internal.io.SparkHadoopWriterUtils
 import org.apache.spark.rdd.RDD
 import org.apache.spark.streaming._
 import org.apache.spark.streaming.api.python.PythonDStream
 import org.apache.spark.streaming.ui.UIUtils
-import org.apache.spark.util.{EventLoop, ThreadUtils}
+import org.apache.spark.util.{EventLoop, ThreadUtils, Utils}
 
 
 private[scheduler] sealed trait JobSchedulerEvent
@@ -231,7 +229,7 @@ class JobScheduler(val ssc: StreamingContext) extends Logging {
     def run() {
       val oldProps = ssc.sparkContext.getLocalProperties
       try {
-        ssc.sparkContext.setLocalProperties(SerializationUtils.clone(ssc.savedProperties.get()))
+        ssc.sparkContext.setLocalProperties(Utils.cloneProperties(ssc.savedProperties.get()))
         val formattedTime = UIUtils.formatBatchTime(
           job.time.milliseconds, ssc.graph.batchDuration.milliseconds, showYYYYMMSS = false)
         val batchUrl = s"/streaming/batch/?id=${job.time.milliseconds}"