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Various spark scripts load spark-env.sh. This can cause growth of any variables that may be appended to (SPARK_CLASSPATH, SPARK_REPL_OPTS) and it makes the precedence order for options specified in spark-env.sh less clear.
One use-case for the latter is that we want to set options from the command-line of spark-shell, but these options will be overridden by subsequent loading of spark-env.sh. If we were to load the spark-env.sh first and then set our command-line options, we could guarantee correct precedence order.
Note that we use SPARK_CONF_DIR if available to support the sbin/ scripts, which always set this variable from sbin/spark-config.sh. Otherwise, we default to the ../conf/ as usual.
Author: Aaron Davidson <aaron@databricks.com>
Closes #184 from aarondav/idem and squashes the following commits:
e291f91 [Aaron Davidson] Use "private" variables in load-spark-env.sh
8da8360 [Aaron Davidson] Add .sh extension to load-spark-env.sh
93a2471 [Aaron Davidson] SPARK-1286: Make usage of spark-env.sh idempotent
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Refactored the streaming project to separate external libraries like Twitter, Kafka, Flume, etc.
At a high level, these are the following changes.
1. All the external code was put in `SPARK_HOME/external/` as separate SBT projects and Maven modules. Their artifact names are `spark-streaming-twitter`, `spark-streaming-kafka`, etc. Both SparkBuild.scala and pom.xml files have been updated. References to external libraries and repositories have been removed from the settings of root and streaming projects/modules.
2. To avail the external functionality (say, creating a Twitter stream), the developer has to `import org.apache.spark.streaming.twitter._` . For Scala API, the developer has to call `TwitterUtils.createStream(streamingContext, ...)`. For the Java API, the developer has to call `TwitterUtils.createStream(javaStreamingContext, ...)`.
3. Each external project has its own scala and java unit tests. Note the unit tests of each external library use classes of the streaming unit tests (`TestSuiteBase`, `LocalJavaStreamingContext`, etc.). To enable this code sharing among test classes, `dependsOn(streaming % "compile->compile,test->test")` was used in the SparkBuild.scala . In the streaming/pom.xml, an additional `maven-jar-plugin` was necessary to capture this dependency (see comment inside the pom.xml for more information).
4. Jars of the external projects have been added to examples project but not to the assembly project.
5. In some files, imports have been rearrange to conform to the Spark coding guidelines.
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Conflicts:
core/src/test/scala/org/apache/spark/DriverSuite.scala
docs/python-programming-guide.md
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spark-915-segregate-scripts
Conflicts:
bin/spark-shell
core/pom.xml
core/src/main/scala/org/apache/spark/SparkContext.scala
core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/CoarseMesosSchedulerBackend.scala
core/src/main/scala/org/apache/spark/ui/UIWorkloadGenerator.scala
core/src/test/scala/org/apache/spark/DriverSuite.scala
python/run-tests
sbin/compute-classpath.sh
sbin/spark-class
sbin/stop-slaves.sh
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Signed-off-by: shane-huang <shengsheng.huang@intel.com>
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Signed-off-by: shane-huang <shengsheng.huang@intel.com>
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