| Commit message (Collapse) | Author | Age | Files | Lines |
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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:
examples/src/main/java/org/apache/spark/streaming/examples/JavaFlumeEventCount.java
streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala
streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaStreamingContext.scala
streaming/src/test/java/org/apache/spark/streaming/JavaAPISuite.java
streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala
streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala
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repositoris from other poms and sbt.
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their own self-contained scala API, java API, scala unit tests and java unit tests. Updated examples to use the external projects.
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Add a script to download sbt if not present on the system
As per the discussion on the dev mailing list this script will use the system sbt if present or otherwise attempt to install the sbt launcher. The fall back error message in the event it fails instructs the user to install sbt. While the URLs it fetches from aren't controlled by the spark project directly, they are stable and the current authoritative sources.
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Made java options to be applied during tests so that they become self explanatory.
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explanatory.
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Conflicts:
core/src/test/scala/org/apache/spark/DriverSuite.scala
docs/python-programming-guide.md
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Closes #316
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Conflicts:
project/SparkBuild.scala
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Conflicts:
core/src/main/scala/org/apache/spark/rdd/CheckpointRDD.scala
streaming/src/main/scala/org/apache/spark/streaming/Checkpoint.scala
streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobGenerator.scala
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Conflicts:
core/src/main/scala/org/apache/spark/SparkContext.scala
core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala
core/src/main/scala/org/apache/spark/scheduler/cluster/ClusterTaskSetManager.scala
core/src/main/scala/org/apache/spark/scheduler/local/LocalScheduler.scala
core/src/main/scala/org/apache/spark/util/MetadataCleaner.scala
core/src/test/scala/org/apache/spark/scheduler/TaskResultGetterSuite.scala
core/src/test/scala/org/apache/spark/scheduler/TaskSetManagerSuite.scala
new-yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
streaming/src/main/scala/org/apache/spark/streaming/Checkpoint.scala
streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaStreamingContext.scala
streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobGenerator.scala
streaming/src/test/scala/org/apache/spark/streaming/BasicOperationsSuite.scala
streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala
streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala
streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala
streaming/src/test/scala/org/apache/spark/streaming/WindowOperationsSuite.scala
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Approximate distinct count
Added countApproxDistinct() to RDD and countApproxDistinctByKey() to PairRDDFunctions to approximately count distinct number of elements and distinct number of values per key, respectively. Both functions use HyperLogLog from stream-lib for counting. Both functions take a parameter that controls the trade-off between accuracy and memory consumption. Also added Scala docs and test suites for both methods.
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Without this, in some cases, Ivy attempts to download the wrong file
and fails, stopping the whole build. See bug for more details.
(This is probably also the beginning of the slow death of our
recently prettified dependencies. Form follow function.)
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akka-bug-fix
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Conflicts:
core/pom.xml
core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
pom.xml
project/SparkBuild.scala
streaming/pom.xml
yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocationHandler.scala
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dependencies.
This also includes:
-Change `isNewYarn` to `isNewHadoop`, since the protobuf-2.5 dependency is from Hadoop-2.2 itself.
-Regexp bugix
Credits to @alig for this patch.
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Conflicts:
yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
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If the Hadoop used is version 2.2 or derived from it, then Spark
will be compiled against protobuf-2.5 and a protobuf-2.5 version of
Akka 2.0.5.
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Conflicts:
core/src/main/scala/org/apache/spark/rdd/RDD.scala
project/SparkBuild.scala
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Add graphite sink for metrics
This adds a metrics sink for graphite. The sink must
be configured with the host and port of a graphite node
and optionally may be configured with a prefix that will
be prepended to all metrics that are sent to graphite.
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This adds a metrics sink for graphite. The sink must
be configured with the host and port of a graphite node
and optionally may be configured with a prefix that will
be prepended to all metrics that are sent to graphite.
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I've diff'd this patch against my own -- since they were both created
independently, this means that two sets of eyes have gone over all the
merge conflicts that were created, so I'm feeling significantly more
confident in the resulting PR.
@rxin has looked at the changes to the repl and is resoundingly
confident that they are correct.
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spark-assembly.jar fails to authenticate with YARN ResourceManager
The META-INF/services/ sbt MergeStrategy was discarding support for Kerberos, among others. This pull request changes to a merge strategy similar to sbt-assembly's default. I've also included an update to sbt-assembly 0.9.2, a minor fix to it's zip file handling.
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sbt-assembly is setup to pick the first META-INF/services/org.apache.hadoop.security.SecurityInfo file instead of merging them. This causes Kerberos authentication to fail, this manifests itself in the "info:null" debug log statement:
DEBUG SaslRpcClient: Get token info proto:interface org.apache.hadoop.yarn.api.ApplicationClientProtocolPB info:null
DEBUG SaslRpcClient: Get kerberos info proto:interface org.apache.hadoop.yarn.api.ApplicationClientProtocolPB info:null
ERROR UserGroupInformation: PriviledgedActionException as:foo@BAR (auth:KERBEROS) cause:org.apache.hadoop.security.AccessControlException: Client cannot authenticate via:[TOKEN, KERBEROS]
DEBUG UserGroupInformation: PrivilegedAction as:foo@BAR (auth:KERBEROS) from:org.apache.hadoop.ipc.Client$Connection.handleSaslConnectionFailure(Client.java:583)
WARN Client: Exception encountered while connecting to the server : org.apache.hadoop.security.AccessControlException: Client cannot authenticate via:[TOKEN, KERBEROS]
ERROR UserGroupInformation: PriviledgedActionException as:foo@BAR (auth:KERBEROS) cause:java.io.IOException: org.apache.hadoop.security.AccessControlException: Client cannot authenticate via:[TOKEN, KERBEROS]
This previously would just contain a single class:
$ unzip -c assembly/target/scala-2.10/spark-assembly-0.9.0-incubating-SNAPSHOT-hadoop2.2.0.jar META-INF/services/org.apache.hadoop.security.SecurityInfo
Archive: assembly/target/scala-2.10/spark-assembly-0.9.0-incubating-SNAPSHOT-hadoop2.2.0.jar
inflating: META-INF/services/org.apache.hadoop.security.SecurityInfo
org.apache.hadoop.security.AnnotatedSecurityInfo
And now has the full list of classes:
$ unzip -c assembly/target/scala-2.10/spark-assembly-0.9.0-incubating-SNAPSHOT-hadoop2.2.0.jar META-INF/services/org.apache.hadoop.security.SecurityInfoArchive: assembly/target/scala-2.10/spark-assembly-0.9.0-incubating-SNAPSHOT-hadoop2.2.0.jar
inflating: META-INF/services/org.apache.hadoop.security.SecurityInfo
org.apache.hadoop.security.AnnotatedSecurityInfo
org.apache.hadoop.mapreduce.v2.app.MRClientSecurityInfo
org.apache.hadoop.mapreduce.v2.security.client.ClientHSSecurityInfo
org.apache.hadoop.yarn.security.client.ClientRMSecurityInfo
org.apache.hadoop.yarn.security.ContainerManagerSecurityInfo
org.apache.hadoop.yarn.security.SchedulerSecurityInfo
org.apache.hadoop.yarn.security.admin.AdminSecurityInfo
org.apache.hadoop.yarn.server.RMNMSecurityInfoClass
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Allow spark on yarn to be run from HDFS.
Allows the spark.jar, app.jar, and log4j.properties to be put into hdfs. Allows you to specify the files on a different hdfs cluster and it will copy them over. It makes sure permissions are correct and makes sure to put things into public distributed cache so they can be reused amongst users if their permissions are appropriate. Also add a bit of error handling for missing arguments.
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