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Merge remote-tracking branch 'upstream/master' into stopwords
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.gitignore

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@@ -66,6 +66,7 @@ scalastyle-output.xml
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R-unit-tests.log
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R/unit-tests.out
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python/lib/pyspark.zip
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lint-r-report.log
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# For Hive
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metastore_db/

.rat-excludes

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spark-env.cmd
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spark-env.sh.template
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log4j-defaults.properties
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log4j-defaults-repl.properties
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bootstrap-tooltip.js
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jquery-1.11.1.min.js
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d3.min.js
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DESCRIPTION
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NAMESPACE
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test_support/*
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.*Rd
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help/*
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html/*
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INDEX
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.lintr
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gen-java.*
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.*avpr

LICENSE

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@@ -948,5 +948,6 @@ The following components are provided under the MIT License. See project link fo
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(MIT License) SLF4J LOG4J-12 Binding (org.slf4j:slf4j-log4j12:1.7.5 - http://www.slf4j.org)
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(MIT License) pyrolite (org.spark-project:pyrolite:2.0.1 - http://pythonhosted.org/Pyro4/)
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(MIT License) scopt (com.github.scopt:scopt_2.10:3.2.0 - https://github.com/scopt/scopt)
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(The MIT License) Mockito (org.mockito:mockito-all:1.8.5 - http://www.mockito.org)
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(The MIT License) Mockito (org.mockito:mockito-core:1.9.5 - http://www.mockito.org)
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(MIT License) jquery (https://jquery.org/license/)
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(MIT License) AnchorJS (https://github.com/bryanbraun/anchorjs)

R/README.md

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@@ -6,7 +6,7 @@ SparkR is an R package that provides a light-weight frontend to use Spark from R
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#### Build Spark
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Build Spark with [Maven](http://spark.apache.org/docs/latest/building-spark.html#building-with-buildmvn) and include the `-PsparkR` profile to build the R package. For example to use the default Hadoop versions you can run
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Build Spark with [Maven](http://spark.apache.org/docs/latest/building-spark.html#building-with-buildmvn) and include the `-Psparkr` profile to build the R package. For example to use the default Hadoop versions you can run
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```
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build/mvn -DskipTests -Psparkr package
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```

R/install-dev.bat

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MKDIR %SPARK_HOME%\R\lib
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R.exe CMD INSTALL --library="%SPARK_HOME%\R\lib" %SPARK_HOME%\R\pkg\
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rem Zip the SparkR package so that it can be distributed to worker nodes on YARN
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pushd %SPARK_HOME%\R\lib
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%JAVA_HOME%\bin\jar.exe cfM "%SPARK_HOME%\R\lib\sparkr.zip" SparkR
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popd

R/install-dev.sh

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mkdir -p $LIB_DIR
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pushd $FWDIR
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pushd $FWDIR > /dev/null
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# Generate Rd files if devtools is installed
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Rscript -e ' if("devtools" %in% rownames(installed.packages())) { library(devtools); devtools::document(pkg="./pkg", roclets=c("rd")) }'
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# Install SparkR to $LIB_DIR
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R CMD INSTALL --library=$LIB_DIR $FWDIR/pkg/
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popd
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# Zip the SparkR package so that it can be distributed to worker nodes on YARN
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cd $LIB_DIR
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jar cfM "$LIB_DIR/sparkr.zip" SparkR
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popd > /dev/null

R/log4j.properties

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log4j.rootCategory=INFO, file
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log4j.appender.file=org.apache.log4j.FileAppender
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log4j.appender.file.append=true
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log4j.appender.file.file=R-unit-tests.log
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log4j.appender.file.file=R/target/unit-tests.log
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log4j.appender.file.layout=org.apache.log4j.PatternLayout
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log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
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R/pkg/.lintr

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linters: with_defaults(line_length_linter(100), camel_case_linter = NULL, open_curly_linter(allow_single_line = TRUE), closed_curly_linter(allow_single_line = TRUE))
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exclusions: list("inst/profile/general.R" = 1, "inst/profile/shell.R")

R/pkg/DESCRIPTION

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'client.R'
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'context.R'
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'deserialize.R'
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'mllib.R'
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'serialize.R'
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'sparkR.R'
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'utils.R'
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'zzz.R'

R/pkg/NAMESPACE

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export("sparkR.stop")
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export("print.jobj")
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# MLlib integration
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exportMethods("glm",
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"predict",
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"summary")
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# Job group lifecycle management methods
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export("setJobGroup",
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"clearJobGroup",
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"cancelJobGroup")
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exportClasses("DataFrame")
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exportMethods("arrange",
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"cache",
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"collect",
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"columns",
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"count",
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"crosstab",
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"describe",
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"distinct",
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"dropna",
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"atan",
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"atan2",
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"avg",
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"between",
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"cast",
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"cbrt",
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"ceiling",

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