iMerge remote-tracking branch 'upstream/master' into ldaonline

Author: hhbyyh

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

@@ -188,10 +188,10 @@ private[spark] class ContextCleaner(sc: SparkContext) extends Logging {
   /** Perform broadcast cleanup. */
   def doCleanupBroadcast(broadcastId: Long, blocking: Boolean) {
     try {
-      logDebug("Cleaning broadcast " + broadcastId)
+      logDebug(s"Cleaning broadcast $broadcastId")
       broadcastManager.unbroadcast(broadcastId, true, blocking)
       listeners.foreach(_.broadcastCleaned(broadcastId))
-      logInfo("Cleaned broadcast " + broadcastId)
+      logDebug(s"Cleaned broadcast $broadcastId")
     } catch {
       case e: Exception => logError("Error cleaning broadcast " + broadcastId, e)
     }

core/src/main/scala/org/apache/spark/storage/BlockManager.scala

@@ -1074,7 +1074,7 @@ private[spark] class BlockManager(
    * Remove all blocks belonging to the given broadcast.
    */
   def removeBroadcast(broadcastId: Long, tellMaster: Boolean): Int = {
-    logInfo(s"Removing broadcast $broadcastId")
+    logDebug(s"Removing broadcast $broadcastId")
     val blocksToRemove = blockInfo.keys.collect {
       case bid @ BroadcastBlockId(`broadcastId`, _) => bid
     }
@@ -1086,7 +1086,7 @@ private[spark] class BlockManager(
    * Remove a block from both memory and disk.
    */
   def removeBlock(blockId: BlockId, tellMaster: Boolean = true): Unit = {
-    logInfo(s"Removing block $blockId")
+    logDebug(s"Removing block $blockId")
     val info = blockInfo.get(blockId).orNull
     if (info != null) {
       info.synchronized {

core/src/main/scala/org/apache/spark/storage/BlockManagerMaster.scala

@@ -61,7 +61,7 @@ class BlockManagerMaster(
       tachyonSize: Long): Boolean = {
     val res = askDriverWithReply[Boolean](
       UpdateBlockInfo(blockManagerId, blockId, storageLevel, memSize, diskSize, tachyonSize))
-    logInfo("Updated info of block " + blockId)
+    logDebug(s"Updated info of block $blockId")
     res
   }
 

core/src/main/scala/org/apache/spark/storage/MemoryStore.scala

@@ -184,7 +184,7 @@ private[spark] class MemoryStore(blockManager: BlockManager, maxMemory: Long)
       val entry = entries.remove(blockId)
       if (entry != null) {
         currentMemory -= entry.size
-        logInfo(s"Block $blockId of size ${entry.size} dropped from memory (free $freeMemory)")
+        logDebug(s"Block $blockId of size ${entry.size} dropped from memory (free $freeMemory)")
         true
       } else {
         false

examples/scala-2.10/src/main/scala/org/apache/spark/examples/streaming/DirectKafkaWordCount.scala

@@ -30,7 +30,8 @@ import org.apache.spark.SparkConf
  *   <topics> is a list of one or more kafka topics to consume from
  *
  * Example:
- *    $ bin/run-example streaming.KafkaWordCount broker1-host:port,broker2-host:port topic1,topic2
+ *    $ bin/run-example streaming.DirectKafkaWordCount broker1-host:port,broker2-host:port \
+ *    topic1,topic2
  */
 object DirectKafkaWordCount {
   def main(args: Array[String]) {

examples/src/main/python/streaming/kafka_wordcount.py

@@ -23,7 +23,7 @@
  http://kafka.apache.org/documentation.html#quickstart
 
  and then run the example
-    `$ bin/spark-submit --driver-class-path external/kafka-assembly/target/scala-*/\
+    `$ bin/spark-submit --jars external/kafka-assembly/target/scala-*/\
       spark-streaming-kafka-assembly-*.jar examples/src/main/python/streaming/kafka_wordcount.py \
       localhost:2181 test`
 """

graphx/src/main/scala/org/apache/spark/graphx/impl/EdgeRDDImpl.scala

@@ -19,7 +19,7 @@ package org.apache.spark.graphx.impl
 
 import scala.reflect.{classTag, ClassTag}
 
-import org.apache.spark.{OneToOneDependency, HashPartitioner, TaskContext}
+import org.apache.spark.{OneToOneDependency, HashPartitioner}
 import org.apache.spark.rdd.RDD
 import org.apache.spark.storage.StorageLevel
 

python/pyspark/streaming/kafka.py

@@ -82,7 +82,7 @@ def createStream(ssc, zkQuorum, groupId, topics, kafkaParams={},
 
   2. Download the JAR of the artifact from Maven Central http://search.maven.org/,
      Group Id = org.apache.spark, Artifact Id = spark-streaming-kafka-assembly, Version = %s.
-     Then, innclude the jar in the spark-submit command as
+     Then, include the jar in the spark-submit command as
 
      $ bin/spark-submit --jars <spark-streaming-kafka-assembly.jar> ...