sbin/spark-class* -> bin/spark-class*

bin/run-example

@@ -36,7 +36,7 @@ if [ -e "$FWDIR/conf/spark-env.sh" ] ; then
 fi
 
 if [ -z "$1" ]; then
-  echo "Usage: bin/run-example <example-class> [<args>]" >&2
+  echo "Usage: run-example <example-class> [<args>]" >&2
   exit 1
 fi
 

bin/run-example2.cmd

@@ -30,7 +30,7 @@ if exist "%FWDIR%conf\spark-env.cmd" call "%FWDIR%conf\spark-env.cmd"
 
 rem Test that an argument was given
 if not "x%1"=="x" goto arg_given
-  echo Usage: bin/run-example ^<example-class^> [^<args^>]
+  echo Usage: run-example ^<example-class^> [^<args^>]
   goto exit
 :arg_given
 

bin/spark-shell

@@ -90,10 +90,10 @@ if $cygwin; then
     # "Backspace sends ^H" setting in "Keys" section of the Mintty options
     # (see https://github.com/sbt/sbt/issues/562).
     stty -icanon min 1 -echo > /dev/null 2>&1
-    $FWDIR/sbin/spark-class -Djline.terminal=unix $OPTIONS org.apache.spark.repl.Main "$@"
+    $FWDIR/bin/spark-class -Djline.terminal=unix $OPTIONS org.apache.spark.repl.Main "$@"
     stty icanon echo > /dev/null 2>&1
 else
-    $FWDIR/sbin/spark-class $OPTIONS org.apache.spark.repl.Main "$@"
+    $FWDIR/bin/spark-class $OPTIONS org.apache.spark.repl.Main "$@"
 fi
 
 # record the exit status lest it be overwritten:

core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/CoarseMesosSchedulerBackend.scala

@@ -127,7 +127,7 @@ private[spark] class CoarseMesosSchedulerBackend(
       CoarseGrainedSchedulerBackend.ACTOR_NAME)
     val uri = conf.get("spark.executor.uri", null)
     if (uri == null) {
-      val runScript = new File(sparkHome, "./sbin/spark-class").getCanonicalPath
+      val runScript = new File(sparkHome, "./bin/spark-class").getCanonicalPath
       command.setValue(
         "\"%s\" org.apache.spark.executor.CoarseGrainedExecutorBackend %s %s %s %d".format(
           runScript, driverUrl, offer.getSlaveId.getValue, offer.getHostname, numCores))
@@ -136,7 +136,7 @@ private[spark] class CoarseMesosSchedulerBackend(
       // glob the directory "correctly".
       val basename = uri.split('/').last.split('.').head
       command.setValue(
-        "cd %s*; ./sbin/spark-class org.apache.spark.executor.CoarseGrainedExecutorBackend %s %s %s %d"
+        "cd %s*; ./bin/spark-class org.apache.spark.executor.CoarseGrainedExecutorBackend %s %s %s %d"
           .format(basename, driverUrl, offer.getSlaveId.getValue, offer.getHostname, numCores))
       command.addUris(CommandInfo.URI.newBuilder().setValue(uri))
     }

core/src/main/scala/org/apache/spark/ui/UIWorkloadGenerator.scala

@@ -27,7 +27,7 @@ import org.apache.spark.scheduler.SchedulingMode
 /**
  * Continuously generates jobs that expose various features of the WebUI (internal testing tool).
  *
- * Usage: ./run spark.ui.UIWorkloadGenerator [master]
+ * Usage: ./bin/spark-class org.apache.spark.ui.UIWorkloadGenerator [master] [FIFO|FAIR]
  */
 private[spark] object UIWorkloadGenerator {
 
@@ -36,7 +36,7 @@ private[spark] object UIWorkloadGenerator {
 
   def main(args: Array[String]) {
     if (args.length < 2) {
-      println("usage: ./sbin/spark-class org.apache.spark.ui.UIWorkloadGenerator [master] [FIFO|FAIR]")
+      println("usage: ./bin/spark-class org.apache.spark.ui.UIWorkloadGenerator [master] [FIFO|FAIR]")
       System.exit(1)
     }
 

core/src/test/scala/org/apache/spark/DriverSuite.scala

@@ -35,7 +35,7 @@ class DriverSuite extends FunSuite with Timeouts {
     val masters = Table(("master"), ("local"), ("local-cluster[2,1,512]"))
     forAll(masters) { (master: String) =>
       failAfter(60 seconds) {
-        Utils.execute(Seq("./sbin/spark-class", "org.apache.spark.DriverWithoutCleanup", master),
+        Utils.execute(Seq("./bin/spark-class", "org.apache.spark.DriverWithoutCleanup", master),
           new File(System.getenv("SPARK_HOME")))
       }
     }

docs/running-on-yarn.md

@@ -54,7 +54,7 @@ There are two scheduler mode that can be used to launch spark application on YAR
 
 The command to launch the YARN Client is as follows:
 
-    SPARK_JAR=<SPARK_ASSEMBLY_JAR_FILE> ./sbin/spark-class org.apache.spark.deploy.yarn.Client \
+    SPARK_JAR=<SPARK_ASSEMBLY_JAR_FILE> ./bin/spark-class org.apache.spark.deploy.yarn.Client \
       --jar <YOUR_APP_JAR_FILE> \
       --class <APP_MAIN_CLASS> \
       --args <APP_MAIN_ARGUMENTS> \
@@ -79,7 +79,7 @@ For example:
 
     # Submit Spark's ApplicationMaster to YARN's ResourceManager, and instruct Spark to run the SparkPi example
     $ SPARK_JAR=./assembly/target/scala-{{site.SCALA_VERSION}}/spark-assembly-{{site.SPARK_VERSION}}-hadoop2.0.5-alpha.jar \
-        ./sbin/spark-class org.apache.spark.deploy.yarn.Client \
+        ./bin/spark-class org.apache.spark.deploy.yarn.Client \
           --jar examples/target/scala-{{site.SCALA_VERSION}}/spark-examples-assembly-{{site.SPARK_VERSION}}.jar \
           --class org.apache.spark.examples.SparkPi \
           --args yarn-standalone \

docs/spark-standalone.md

@@ -28,7 +28,7 @@ the master's web UI, which is [http://localhost:8080](http://localhost:8080) by
 
 Similarly, you can start one or more workers and connect them to the master via:
 
-    ./sbin/spark-class org.apache.spark.deploy.worker.Worker spark://IP:PORT
+    ./bin/spark-class org.apache.spark.deploy.worker.Worker spark://IP:PORT
 
 Once you have started a worker, look at the master's web UI ([http://localhost:8080](http://localhost:8080) by default).
 You should see the new node listed there, along with its number of CPUs and memory (minus one gigabyte left for the OS).

python/pyspark/java_gateway.py

@@ -31,7 +31,7 @@ def launch_gateway():
     # Launch the Py4j gateway using Spark's run command so that we pick up the
     # proper classpath and SPARK_MEM settings from spark-env.sh
     on_windows = platform.system() == "Windows"
-    script = "./sbin/spark-class.cmd" if on_windows else "./sbin/spark-class"
+    script = "./bin/spark-class.cmd" if on_windows else "./bin/spark-class"
     command = [os.path.join(SPARK_HOME, script), "py4j.GatewayServer",
                "--die-on-broken-pipe", "0"]
     if not on_windows:

sbin/spark-daemon.sh

@@ -147,7 +147,7 @@ case $startStop in
     spark_rotate_log "$log"
     echo starting $command, logging to $log
     cd "$SPARK_PREFIX"
-    nohup nice -n $SPARK_NICENESS "$SPARK_PREFIX"/sbin/spark-class $command "$@" >> "$log" 2>&1 < /dev/null &
+    nohup nice -n $SPARK_NICENESS "$SPARK_PREFIX"/bin/spark-class $command "$@" >> "$log" 2>&1 < /dev/null &
     newpid=$!
     echo $newpid > $pid
     sleep 2

sbin/spark-executor

@@ -20,4 +20,4 @@
 FWDIR="$(cd `dirname $0`/..; pwd)"
 
 echo "Running spark-executor with framework dir = $FWDIR"
-exec $FWDIR/sbin/spark-class org.apache.spark.executor.MesosExecutorBackend
+exec $FWDIR/bin/spark-class org.apache.spark.executor.MesosExecutorBackend