[SPARK-2410][SQL] Merging Hive Thrift/JDBC server

JIRA issue:

- Main: [SPARK-2410](https://issues.apache.org/jira/browse/SPARK-2410)
- Related: [SPARK-2678](https://issues.apache.org/jira/browse/SPARK-2678)

Cherry picked the Hive Thrift/JDBC server from [branch-1.0-jdbc](https://github.com/apache/spark/tree/branch-1.0-jdbc).

(Thanks chenghao-intel for his initial contribution of the Spark SQL CLI.)

TODO

- [x] Use `spark-submit` to launch the server, the CLI and beeline
- [x] Migration guideline draft for Shark users

----

Hit by a bug in `SparkSubmitArguments` while working on this PR: all application options that are recognized by `SparkSubmitArguments` are stolen as `SparkSubmit` options. For example:

```bash
$ spark-submit --class org.apache.hive.beeline.BeeLine spark-internal --help
```

This actually shows usage information of `SparkSubmit` rather than `BeeLine`.

~~Fixed this bug here since the `spark-internal` related stuff also touches `SparkSubmitArguments` and I'd like to avoid conflict.~~

**UPDATE** The bug mentioned above is now tracked by [SPARK-2678](https://issues.apache.org/jira/browse/SPARK-2678). Decided to revert changes to this bug since it involves more subtle considerations and worth a separate PR.

Author: Cheng Lian <lian.cs.zju@gmail.com>

Closes #1399 from liancheng/thriftserver and squashes the following commits:

090beea [Cheng Lian] Revert changes related to SPARK-2678, decided to move them to another PR
21c6cf4 [Cheng Lian] Updated Spark SQL programming guide docs
fe0af31 [Cheng Lian] Reordered spark-submit options in spark-shell[.cmd]
199e3fb [Cheng Lian] Disabled MIMA for hive-thriftserver
1083e9d [Cheng Lian] Fixed failed test suites
7db82a1 [Cheng Lian] Fixed spark-submit application options handling logic
9cc0f06 [Cheng Lian] Starts beeline with spark-submit
cfcf461 [Cheng Lian] Updated documents and build scripts for the newly added hive-thriftserver profile
061880f [Cheng Lian] Addressed all comments by @pwendell
7755062 [Cheng Lian] Adapts test suites to spark-submit settings
40bafef [Cheng Lian] Fixed more license header issues
e214aab [Cheng Lian] Added missing license headers
b8905ba [Cheng Lian] Fixed minor issues in spark-sql and start-thriftserver.sh
f975d22 [Cheng Lian] Updated docs for Hive compatibility and Shark migration guide draft
3ad4e75 [Cheng Lian] Starts spark-sql shell with spark-submit
a5310d1 [Cheng Lian] Make HiveThriftServer2 play well with spark-submit
61f39f4 [Cheng Lian] Starts Hive Thrift server via spark-submit
2c4c539 [Cheng Lian] Cherry picked the Hive Thrift server

.gitignore

@@ -57,3 +57,4 @@ metastore_db/
 metastore/
 warehouse/
 TempStatsStore/
+sql/hive-thriftserver/test_warehouses

assembly/pom.xml

@@ -165,6 +165,16 @@
         </dependency>
       </dependencies>
     </profile>
+    <profile>
+      <id>hive-thriftserver</id>
+      <dependencies>
+        <dependency>
+          <groupId>org.apache.spark</groupId>
+          <artifactId>spark-hive-thriftserver_${scala.binary.version}</artifactId>
+          <version>${project.version}</version>
+        </dependency>
+      </dependencies>
+    </profile>
     <profile>
       <id>spark-ganglia-lgpl</id>
       <dependencies>

bagel/pom.xml

@@ -28,7 +28,7 @@
   <groupId>org.apache.spark</groupId>
   <artifactId>spark-bagel_2.10</artifactId>
   <properties>
-     <sbt.project.name>bagel</sbt.project.name>
+    <sbt.project.name>bagel</sbt.project.name>
   </properties>
   <packaging>jar</packaging>
   <name>Spark Project Bagel</name>

bin/beeline

+#!/usr/bin/env bash
+
+#
+# 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.
+#
+
+# Figure out where Spark is installed
+FWDIR="$(cd `dirname $0`/..; pwd)"
+
+# Find the java binary
+if [ -n "${JAVA_HOME}" ]; then
+  RUNNER="${JAVA_HOME}/bin/java"
+else
+  if [ `command -v java` ]; then
+    RUNNER="java"
+  else
+    echo "JAVA_HOME is not set" >&2
+    exit 1
+  fi
+fi
+
+# Compute classpath using external script
+classpath_output=$($FWDIR/bin/compute-classpath.sh)
+if [[ "$?" != "0" ]]; then
+  echo "$classpath_output"
+  exit 1
+else
+  CLASSPATH=$classpath_output
+fi
+
+CLASS="org.apache.hive.beeline.BeeLine"
+exec "$RUNNER" -cp "$CLASSPATH" $CLASS "$@"

bin/compute-classpath.sh

@@ -52,6 +52,7 @@ if [ -n "$SPARK_PREPEND_CLASSES" ]; then
   CLASSPATH="$CLASSPATH:$FWDIR/sql/catalyst/target/scala-$SCALA_VERSION/classes"
   CLASSPATH="$CLASSPATH:$FWDIR/sql/core/target/scala-$SCALA_VERSION/classes"
   CLASSPATH="$CLASSPATH:$FWDIR/sql/hive/target/scala-$SCALA_VERSION/classes"
+  CLASSPATH="$CLASSPATH:$FWDIR/sql/hive-thriftserver/target/scala-$SCALA_VERSION/classes"
   CLASSPATH="$CLASSPATH:$FWDIR/yarn/stable/target/scala-$SCALA_VERSION/classes"
 fi
 

bin/spark-shell

@@ -46,11 +46,11 @@ function main(){
         # (see https://github.com/sbt/sbt/issues/562).
         stty -icanon min 1 -echo > /dev/null 2>&1
         export SPARK_SUBMIT_OPTS="$SPARK_SUBMIT_OPTS -Djline.terminal=unix"
-        $FWDIR/bin/spark-submit spark-shell "$@" --class org.apache.spark.repl.Main
+        $FWDIR/bin/spark-submit --class org.apache.spark.repl.Main spark-shell "$@"
         stty icanon echo > /dev/null 2>&1
     else
         export SPARK_SUBMIT_OPTS
-        $FWDIR/bin/spark-submit spark-shell "$@" --class org.apache.spark.repl.Main
+        $FWDIR/bin/spark-submit --class org.apache.spark.repl.Main spark-shell "$@"
     fi
 }
 

bin/spark-shell.cmd

@@ -19,4 +19,4 @@ rem
 
 set SPARK_HOME=%~dp0..
 
-cmd /V /E /C %SPARK_HOME%\bin\spark-submit.cmd spark-shell %* --class org.apache.spark.repl.Main
+cmd /V /E /C %SPARK_HOME%\bin\spark-submit.cmd spark-shell --class org.apache.spark.repl.Main %*

bin/spark-sql

+#!/usr/bin/env bash
+
+#
+# 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.
+#
+
+#
+# Shell script for starting the Spark SQL CLI
+
+# Enter posix mode for bash
+set -o posix
+
+# Figure out where Spark is installed
+FWDIR="$(cd `dirname $0`/..; pwd)"
+
+if [[ "$@" = *--help ]] || [[ "$@" = *-h ]]; then
+  echo "Usage: ./sbin/spark-sql [options]"
+  $FWDIR/bin/spark-submit --help 2>&1 | grep -v Usage 1>&2
+  exit 0
+fi
+
+CLASS="org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver"
+exec "$FWDIR"/bin/spark-submit --class $CLASS spark-internal $@

core/pom.xml

@@ -28,7 +28,7 @@
   <groupId>org.apache.spark</groupId>
   <artifactId>spark-core_2.10</artifactId>
   <properties>
-     <sbt.project.name>core</sbt.project.name>
+    <sbt.project.name>core</sbt.project.name>
   </properties>
   <packaging>jar</packaging>
   <name>Spark Project Core</name>

core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala

@@ -46,6 +46,10 @@ object SparkSubmit {
   private val CLUSTER = 2
   private val ALL_DEPLOY_MODES = CLIENT | CLUSTER
 
+  // A special jar name that indicates the class being run is inside of Spark itself, and therefore
+  // no user jar is needed.
+  private val SPARK_INTERNAL = "spark-internal"
+
   // Special primary resource names that represent shells rather than application jars.
   private val SPARK_SHELL = "spark-shell"
   private val PYSPARK_SHELL = "pyspark-shell"
@@ -257,7 +261,9 @@ object SparkSubmit {
     // In yarn-cluster mode, use yarn.Client as a wrapper around the user class
     if (clusterManager == YARN && deployMode == CLUSTER) {
       childMainClass = "org.apache.spark.deploy.yarn.Client"
-      childArgs += ("--jar", args.primaryResource)
+      if (args.primaryResource != SPARK_INTERNAL) {
+        childArgs += ("--jar", args.primaryResource)
+      }
       childArgs += ("--class", args.mainClass)
       if (args.childArgs != null) {
         args.childArgs.foreach { arg => childArgs += ("--arg", arg) }
@@ -332,7 +338,7 @@ object SparkSubmit {
    * Return whether the given primary resource represents a user jar.
    */
   private def isUserJar(primaryResource: String): Boolean = {
-    !isShell(primaryResource) && !isPython(primaryResource)
+    !isShell(primaryResource) && !isPython(primaryResource) && !isInternal(primaryResource)
   }
 
   /**
@@ -349,6 +355,10 @@ object SparkSubmit {
     primaryResource.endsWith(".py") || primaryResource == PYSPARK_SHELL
   }
 
+  private[spark] def isInternal(primaryResource: String): Boolean = {
+    primaryResource == SPARK_INTERNAL
+  }
+
   /**
    * Merge a sequence of comma-separated file lists, some of which may be null to indicate
    * no files, into a single comma-separated string.

core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala

@@ -204,8 +204,9 @@ private[spark] class SparkSubmitArguments(args: Seq[String]) {
 
   /** Fill in values by parsing user options. */
   private def parseOpts(opts: Seq[String]): Unit = {
-    // Delineates parsing of Spark options from parsing of user options.
     var inSparkOpts = true
+
+    // Delineates parsing of Spark options from parsing of user options.
     parse(opts)
 
     def parse(opts: Seq[String]): Unit = opts match {
@@ -318,7 +319,7 @@ private[spark] class SparkSubmitArguments(args: Seq[String]) {
               SparkSubmit.printErrorAndExit(errMessage)
             case v =>
               primaryResource =
-                if (!SparkSubmit.isShell(v)) {
+                if (!SparkSubmit.isShell(v) && !SparkSubmit.isInternal(v)) {
                   Utils.resolveURI(v).toString
                 } else {
                   v

dev/create-release/create-release.sh

@@ -53,7 +53,7 @@ if [[ ! "$@" =~ --package-only ]]; then
     -Dusername=$GIT_USERNAME -Dpassword=$GIT_PASSWORD \
     -Dmaven.javadoc.skip=true \
     -Dhadoop.version=2.2.0 -Dyarn.version=2.2.0 \
-    -Pyarn -Phive -Phadoop-2.2 -Pspark-ganglia-lgpl\
+    -Pyarn -Phive -Phive-thriftserver -Phadoop-2.2 -Pspark-ganglia-lgpl\
     -Dtag=$GIT_TAG -DautoVersionSubmodules=true \
     --batch-mode release:prepare
 
@@ -61,7 +61,7 @@ if [[ ! "$@" =~ --package-only ]]; then
     -Darguments="-DskipTests=true -Dmaven.javadoc.skip=true -Dhadoop.version=2.2.0 -Dyarn.version=2.2.0 -Dgpg.passphrase=${GPG_PASSPHRASE}" \
     -Dhadoop.version=2.2.0 -Dyarn.version=2.2.0 \
     -Dmaven.javadoc.skip=true \
-    -Pyarn -Phive -Phadoop-2.2 -Pspark-ganglia-lgpl\
+    -Pyarn -Phive -Phive-thriftserver -Phadoop-2.2 -Pspark-ganglia-lgpl\
     release:perform
 
   cd ..
@@ -111,10 +111,10 @@ make_binary_release() {
     spark-$RELEASE_VERSION-bin-$NAME.tgz.sha
 }
 
-make_binary_release "hadoop1" "-Phive -Dhadoop.version=1.0.4"
-make_binary_release "cdh4" "-Phive -Dhadoop.version=2.0.0-mr1-cdh4.2.0"
+make_binary_release "hadoop1" "-Phive -Phive-thriftserver -Dhadoop.version=1.0.4"
+make_binary_release "cdh4" "-Phive -Phive-thriftserver -Dhadoop.version=2.0.0-mr1-cdh4.2.0"
 make_binary_release "hadoop2" \
-  "-Phive -Pyarn -Phadoop-2.2 -Dhadoop.version=2.2.0 -Pyarn.version=2.2.0"
+  "-Phive -Phive-thriftserver -Pyarn -Phadoop-2.2 -Dhadoop.version=2.2.0 -Pyarn.version=2.2.0"
 
 # Copy data
 echo "Copying release tarballs"

dev/run-tests

@@ -65,7 +65,7 @@ echo "========================================================================="
 # (either resolution or compilation) prompts the user for input either q, r, 
 # etc to quit or retry. This echo is there to make it not block.
 if [ -n "$_RUN_SQL_TESTS" ]; then
-  echo -e "q\n" | SBT_MAVEN_PROFILES="$SBT_MAVEN_PROFILES -Phive" sbt/sbt clean package \
+  echo -e "q\n" | SBT_MAVEN_PROFILES="$SBT_MAVEN_PROFILES -Phive -Phive-thriftserver" sbt/sbt clean package \
     assembly/assembly test | grep -v -e "info.*Resolving" -e "warn.*Merging" -e "info.*Including"
 else
   echo -e "q\n" | sbt/sbt clean package assembly/assembly test | \

dev/scalastyle

@@ -17,7 +17,7 @@
 # limitations under the License.
 #
 
-echo -e "q\n" | sbt/sbt -Phive scalastyle > scalastyle.txt
+echo -e "q\n" | sbt/sbt -Phive -Phive-thriftserver scalastyle > scalastyle.txt
 # Check style with YARN alpha built too
 echo -e "q\n" | sbt/sbt -Pyarn -Phadoop-0.23 -Dhadoop.version=0.23.9 yarn-alpha/scalastyle \
   >> scalastyle.txt

docs/sql-programming-guide.md

@@ -136,7 +136,7 @@ val sqlContext = new org.apache.spark.sql.SQLContext(sc)
 import sqlContext.createSchemaRDD
 
 // Define the schema using a case class.
-// Note: Case classes in Scala 2.10 can support only up to 22 fields. To work around this limit, 
+// Note: Case classes in Scala 2.10 can support only up to 22 fields. To work around this limit,
 // you can use custom classes that implement the Product interface.
 case class Person(name: String, age: Int)
 
@@ -548,7 +548,6 @@ results = hiveContext.hql("FROM src SELECT key, value").collect()
 </div>
 </div>
 
-
 # Writing Language-Integrated Relational Queries
 
 **Language-Integrated queries are currently only supported in Scala.**
@@ -573,4 +572,199 @@ prefixed with a tick (`'`).  Implicit conversions turn these symbols into expres
 evaluated by the SQL execution engine.  A full list of the functions supported can be found in the
 [ScalaDoc](api/scala/index.html#org.apache.spark.sql.SchemaRDD).
 
-<!-- TODO: Include the table of operations here. -->
\ No newline at end of file
+<!-- TODO: Include the table of operations here. -->
+
+## Running the Thrift JDBC server
+
+The Thrift JDBC server implemented here corresponds to the [`HiveServer2`]
+(https://cwiki.apache.org/confluence/display/Hive/Setting+Up+HiveServer2) in Hive 0.12. You can test
+the JDBC server with the beeline script comes with either Spark or Hive 0.12.  In order to use Hive
+you must first run '`sbt/sbt -Phive-thriftserver assembly/assembly`' (or use `-Phive-thriftserver`
+for maven).
+
+To start the JDBC server, run the following in the Spark directory:
+
+    ./sbin/start-thriftserver.sh
+
+The default port the server listens on is 10000.  You may run
+`./sbin/start-thriftserver.sh --help` for a complete list of all available
+options.  Now you can use beeline to test the Thrift JDBC server:
+
+    ./bin/beeline
+
+Connect to the JDBC server in beeline with:
+
+    beeline> !connect jdbc:hive2://localhost:10000
+
+Beeline will ask you for a username and password. In non-secure mode, simply enter the username on
+your machine and a blank password. For secure mode, please follow the instructions given in the
+[beeline documentation](https://cwiki.apache.org/confluence/display/Hive/HiveServer2+Clients)
+
+Configuration of Hive is done by placing your `hive-site.xml` file in `conf/`.
+
+You may also use the beeline script comes with Hive.
+
+### Migration Guide for Shark Users
+
+#### Reducer number
+
+In Shark, default reducer number is 1 and is controlled by the property `mapred.reduce.tasks`. Spark
+SQL deprecates this property by a new property `spark.sql.shuffle.partitions`, whose default value
+is 200. Users may customize this property via `SET`:
+
+```
+SET spark.sql.shuffle.partitions=10;
+SELECT page, count(*) c FROM logs_last_month_cached
+GROUP BY page ORDER BY c DESC LIMIT 10;
+```
+
+You may also put this property in `hive-site.xml` to override the default value.
+
+For now, the `mapred.reduce.tasks` property is still recognized, and is converted to
+`spark.sql.shuffle.partitions` automatically.
+
+#### Caching
+
+The `shark.cache` table property no longer exists, and tables whose name end with `_cached` are no
+longer automcatically cached. Instead, we provide `CACHE TABLE` and `UNCACHE TABLE` statements to
+let user control table caching explicitly:
+
+```
+CACHE TABLE logs_last_month;
+UNCACHE TABLE logs_last_month;
+```
+
+**NOTE** `CACHE TABLE tbl` is lazy, it only marks table `tbl` as "need to by cached if necessary",
+but doesn't actually cache it until a query that touches `tbl` is executed. To force the table to be
+cached, you may simply count the table immediately after executing `CACHE TABLE`:
+
+```
+CACHE TABLE logs_last_month;
+SELECT COUNT(1) FROM logs_last_month;
+```
+
+Several caching related features are not supported yet:
+
+* User defined partition level cache eviction policy
+* RDD reloading
+* In-memory cache write through policy
+
+### Compatibility with Apache Hive
+
+#### Deploying in Exising Hive Warehouses
+
+Spark SQL Thrift JDBC server is designed to be "out of the box" compatible with existing Hive
+installations. You do not need to modify your existing Hive Metastore or change the data placement
+or partitioning of your tables.
+
+#### Supported Hive Features
+
+Spark SQL supports the vast majority of Hive features, such as:
+
+* Hive query statements, including:
+ * `SELECT`
+ * `GROUP BY
+ * `ORDER BY`
+ * `CLUSTER BY`
+ * `SORT BY`
+* All Hive operators, including:
+ * Relational operators (`=`, `⇔`, `==`, `<>`, `<`, `>`, `>=`, `<=`, etc)
+ * Arthimatic operators (`+`, `-`, `*`, `/`, `%`, etc)
+ * Logical operators (`AND`, `&&`, `OR`, `||`, etc)
+ * Complex type constructors
+ * Mathemtatical functions (`sign`, `ln`, `cos`, etc)
+ * String functions (`instr`, `length`, `printf`, etc)
+* User defined functions (UDF)
+* User defined aggregation functions (UDAF)
+* User defined serialization formats (SerDe's)
+* Joins
+ * `JOIN`
+ * `{LEFT|RIGHT|FULL} OUTER JOIN`
+ * `LEFT SEMI JOIN`
+ * `CROSS JOIN`
+* Unions
+* Sub queries
+ * `SELECT col FROM ( SELECT a + b AS col from t1) t2`
+* Sampling
+* Explain
+* Partitioned tables
+* All Hive DDL Functions, including:
+ * `CREATE TABLE`
+ * `CREATE TABLE AS SELECT`
+ * `ALTER TABLE`
+* Most Hive Data types, including:
+ * `TINYINT`
+ * `SMALLINT`
+ * `INT`
+ * `BIGINT`
+ * `BOOLEAN`
+ * `FLOAT`
+ * `DOUBLE`
+ * `STRING`
+ * `BINARY`
+ * `TIMESTAMP`
+ * `ARRAY<>`
+ * `MAP<>`
+ * `STRUCT<>`
+
+#### Unsupported Hive Functionality
+
+Below is a list of Hive features that we don't support yet. Most of these features are rarely used
+in Hive deployments.
+
+**Major Hive Features**
+
+* Tables with buckets: bucket is the hash partitioning within a Hive table partition. Spark SQL
+  doesn't support buckets yet.
+
+**Esoteric Hive Features**
+
+* Tables with partitions using different input formats: In Spark SQL, all table partitions need to
+  have the same input format.
+* Non-equi outer join: For the uncommon use case of using outer joins with non-equi join conditions
+  (e.g. condition "`key < 10`"), Spark SQL will output wrong result for the `NULL` tuple.
+* `UNIONTYPE`
+* Unique join
+* Single query multi insert
+* Column statistics collecting: Spark SQL does not piggyback scans to collect column statistics at
+  the moment.
+
+**Hive Input/Output Formats**
+
+* File format for CLI: For results showing back to the CLI, Spark SQL only supports TextOutputFormat.
+* Hadoop archive
+
+**Hive Optimizations**
+
+A handful of Hive optimizations are not yet included in Spark. Some of these (such as indexes) are
+not necessary due to Spark SQL's in-memory computational model. Others are slotted for future
+releases of Spark SQL.
+
+* Block level bitmap indexes and virtual columns (used to build indexes)
+* Automatically convert a join to map join: For joining a large table with multiple small tables,
+  Hive automatically converts the join into a map join. We are adding this auto conversion in the
+  next release.
+* Automatically determine the number of reducers for joins and groupbys: Currently in Spark SQL, you
+  need to control the degree of parallelism post-shuffle using "SET
+  spark.sql.shuffle.partitions=[num_tasks];". We are going to add auto-setting of parallelism in the
+  next release.
+* Meta-data only query: For queries that can be answered by using only meta data, Spark SQL still
+  launches tasks to compute the result.
+* Skew data flag: Spark SQL does not follow the skew data flags in Hive.
+* `STREAMTABLE` hint in join: Spark SQL does not follow the `STREAMTABLE` hint.
+* Merge multiple small files for query results: if the result output contains multiple small files,
+  Hive can optionally merge the small files into fewer large files to avoid overflowing the HDFS
+  metadata. Spark SQL does not support that.
+
+## Running the Spark SQL CLI
+
+The Spark SQL CLI is a convenient tool to run the Hive metastore service in local mode and execute
+queries input from command line. Note: the Spark SQL CLI cannot talk to the Thrift JDBC server.
+
+To start the Spark SQL CLI, run the following in the Spark directory:
+
+    ./bin/spark-sql
+
+Configuration of Hive is done by placing your `hive-site.xml` file in `conf/`.
+You may run `./bin/spark-sql --help` for a complete list of all available
+options.

examples/pom.xml

@@ -28,7 +28,7 @@
   <groupId>org.apache.spark</groupId>
   <artifactId>spark-examples_2.10</artifactId>
   <properties>
-     <sbt.project.name>examples</sbt.project.name>
+    <sbt.project.name>examples</sbt.project.name>
   </properties>
   <packaging>jar</packaging>
   <name>Spark Project Examples</name>

external/flume/pom.xml

@@ -28,7 +28,7 @@
   <groupId>org.apache.spark</groupId>
   <artifactId>spark-streaming-flume_2.10</artifactId>
   <properties>
-     <sbt.project.name>streaming-flume</sbt.project.name>
+    <sbt.project.name>streaming-flume</sbt.project.name>
   </properties>
   <packaging>jar</packaging>
   <name>Spark Project External Flume</name>

external/kafka/pom.xml

@@ -28,7 +28,7 @@
   <groupId>org.apache.spark</groupId>
   <artifactId>spark-streaming-kafka_2.10</artifactId>
   <properties>
-     <sbt.project.name>streaming-kafka</sbt.project.name>
+    <sbt.project.name>streaming-kafka</sbt.project.name>
   </properties>
   <packaging>jar</packaging>
   <name>Spark Project External Kafka</name>

external/mqtt/pom.xml

@@ -28,7 +28,7 @@
   <groupId>org.apache.spark</groupId>
   <artifactId>spark-streaming-mqtt_2.10</artifactId>
   <properties>
-     <sbt.project.name>streaming-mqtt</sbt.project.name>
+    <sbt.project.name>streaming-mqtt</sbt.project.name>
   </properties>
   <packaging>jar</packaging>
   <name>Spark Project External MQTT</name>

external/twitter/pom.xml

@@ -28,7 +28,7 @@
   <groupId>org.apache.spark</groupId>
   <artifactId>spark-streaming-twitter_2.10</artifactId>
   <properties>
-     <sbt.project.name>streaming-twitter</sbt.project.name>
+    <sbt.project.name>streaming-twitter</sbt.project.name>
   </properties>
   <packaging>jar</packaging>
   <name>Spark Project External Twitter</name>