| Commit message (Collapse) | Author | Age | Files | Lines |
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To make this work I had to rename the defaults file. Otherwise
maven's pattern matching rules included it when trying to match
other log4j.properties files.
I also fixed a bug in the existing maven build where two
<transformers> tags were present in assembly/pom.xml
such that one overwrote the other.
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Conflicts:
core/src/test/scala/org/apache/spark/DriverSuite.scala
docs/python-programming-guide.md
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build/dep-resolution atleast a bit faster.
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Conflicts:
bagel/pom.xml
core/pom.xml
core/src/test/scala/org/apache/spark/ui/UISuite.scala
examples/pom.xml
mllib/pom.xml
pom.xml
project/SparkBuild.scala
repl/pom.xml
streaming/pom.xml
tools/pom.xml
In scala 2.10, a shorter representation is used for naming artifacts
so changed to shorter scala version for artifacts and made it a property in pom.
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Conflicts:
core/src/main/scala/org/apache/spark/ui/jobs/JobProgressUI.scala
docs/_config.yml
project/SparkBuild.scala
repl/src/main/scala/org/apache/spark/repl/SparkILoop.scala
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Due to this change in HDFS:
https://issues.apache.org/jira/browse/HADOOP-7549
there is a bug when using the new assembly builds. The symptom is that any HDFS access
results in an exception saying "No filesystem for scheme 'hdfs'". This adds a merge
strategy in the assembly build which fixes the problem.
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This includes the following changes:
- The "assembly" package now builds in Maven by default, and creates an
assembly containing both hadoop-client and Spark, unlike the old
BigTop distribution assembly that skipped hadoop-client
- There is now a bigtop-dist package to build the old BigTop assembly
- The repl-bin package is no longer built by default since the scripts
don't reply on it; instead it can be enabled with -Prepl-bin
- Py4J is now included in the assembly/lib folder as a local Maven repo,
so that the Maven package can link to it
- run-example now adds the original Spark classpath as well because the
Maven examples assembly lists spark-core and such as provided
- The various Maven projects add a spark-yarn dependency correctly
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deployed cluster
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