diff --git a/core/src/main/scala/org/apache/spark/SparkContext.scala b/core/src/main/scala/org/apache/spark/SparkContext.scala index c4541aa3766a823c1e2e41928d29859f2b38aff5..67230f4207b832b644f3350a6c8c66b7adac1658 100644 --- a/core/src/main/scala/org/apache/spark/SparkContext.scala +++ b/core/src/main/scala/org/apache/spark/SparkContext.scala @@ -2095,7 +2095,7 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli /** Default min number of partitions for Hadoop RDDs when not given by user */ @deprecated("use defaultMinPartitions", "1.0.0") - def defaultMinSplits: Int = math.min(defaultParallelism, 2) + def defaultMinSplits: Int = defaultMinPartitions /** * Default min number of partitions for Hadoop RDDs when not given by user diff --git a/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala b/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala index c2ebf30596215f270ca9634729a33a26d781e873..77c88baa9be2070f419a283f44174b6e99596040 100644 --- a/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala +++ b/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala @@ -257,7 +257,7 @@ private[spark] object CoarseGrainedExecutorBackend extends Logging { // scalastyle:off println System.err.println( """ - |"Usage: CoarseGrainedExecutorBackend [options] + |Usage: CoarseGrainedExecutorBackend [options] | | Options are: | --driver-url <driverUrl> diff --git a/core/src/main/scala/org/apache/spark/rpc/netty/RpcEndpointAddress.scala b/core/src/main/scala/org/apache/spark/rpc/netty/RpcEndpointAddress.scala index d2e94f943aba5f13104a56e99b019dd2ae2cec20..cd6f00cc08e6c765f9132951e6e5ed4bb09fea02 100644 --- a/core/src/main/scala/org/apache/spark/rpc/netty/RpcEndpointAddress.scala +++ b/core/src/main/scala/org/apache/spark/rpc/netty/RpcEndpointAddress.scala @@ -26,7 +26,7 @@ import org.apache.spark.rpc.RpcAddress * The `rpcAddress` may be null, in which case the endpoint is registered via a client-only * connection and can only be reached via the client that sent the endpoint reference. * - * @param rpcAddress The socket address of the endpint. + * @param rpcAddress The socket address of the endpoint. * @param name Name of the endpoint. */ private[netty] case class RpcEndpointAddress(val rpcAddress: RpcAddress, val name: String) { diff --git a/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala index a02f3017cb6e9482425c35eccd953d4c6473eefc..380301f1c9aecfe18b35fa87e3aaba5289514256 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala @@ -608,7 +608,7 @@ private[spark] class TaskSetManager( } /** - * Marks the task as successful and notifies the DAGScheduler that a task has ended. + * Marks a task as successful and notifies the DAGScheduler that the task has ended. */ def handleSuccessfulTask(tid: Long, result: DirectTaskResult[_]): Unit = { val info = taskInfos(tid) @@ -705,7 +705,7 @@ private[spark] class TaskSetManager( ef.exception case e: ExecutorLostFailure if !e.exitCausedByApp => - logInfo(s"Task $tid failed because while it was being computed, its executor" + + logInfo(s"Task $tid failed because while it was being computed, its executor " + "exited for a reason unrelated to the task. Not counting this failure towards the " + "maximum number of failures for the task.") None diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala index 2279e8cad7bcf4362918c5b6e12c0cc308e715c2..f222007a38c9b899b2633236ce9b3a0ab19e9f6a 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala @@ -30,7 +30,7 @@ import org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend.ENDPOINT import org.apache.spark.util.{ThreadUtils, SerializableBuffer, AkkaUtils, Utils} /** - * A scheduler backend that waits for coarse grained executors to connect to it through Akka. + * A scheduler backend that waits for coarse-grained executors to connect. * This backend holds onto each executor for the duration of the Spark job rather than relinquishing * executors whenever a task is done and asking the scheduler to launch a new executor for * each new task. Executors may be launched in a variety of ways, such as Mesos tasks for the