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.rat-excludes

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@@ -15,20 +15,8 @@ TAGS
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RELEASE
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control
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docs
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docker.properties.template
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fairscheduler.xml.template
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spark-defaults.conf.template
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log4j.properties
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log4j.properties.template
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metrics.properties
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metrics.properties.template
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slaves
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slaves.template
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spark-env.sh
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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
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org.apache.spark.sql.sources.DataSourceRegister
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.*parquet

LICENSE

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NOTICE

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@@ -572,3 +572,38 @@ Copyright 2009-2013 The Apache Software Foundation
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Apache Avro IPC
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Copyright 2009-2013 The Apache Software Foundation
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Vis.js
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Copyright 2010-2015 Almende B.V.
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Vis.js is dual licensed under both
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* The Apache 2.0 License
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http://www.apache.org/licenses/LICENSE-2.0
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and
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* The MIT License
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http://opensource.org/licenses/MIT
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Vis.js may be distributed under either license.
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Vis.js uses and redistributes the following third-party libraries:
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- component-emitter
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https://github.com/component/emitter
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The MIT License
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- hammer.js
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http://hammerjs.github.io/
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The MIT License
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- moment.js
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http://momentjs.com/
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The MIT License
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- keycharm
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https://github.com/AlexDM0/keycharm
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The MIT License

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/create-docs.sh

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@@ -39,7 +39,7 @@ pushd $FWDIR
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mkdir -p pkg/html
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pushd pkg/html
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Rscript -e 'library(SparkR, lib.loc="../../lib"); library(knitr); knit_rd("SparkR")'
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Rscript -e 'libDir <- "../../lib"; library(SparkR, lib.loc=libDir); library(knitr); knit_rd("SparkR", links = tools::findHTMLlinks(paste(libDir, "SparkR", sep="/")))'
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popd
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R/install-dev.sh

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@@ -34,12 +34,12 @@ LIB_DIR="$FWDIR/lib"
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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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popd > /dev/null

R/pkg/DESCRIPTION

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Package: SparkR
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Type: Package
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Title: R frontend for Spark
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Version: 1.4.0
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Version: 1.6.0
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Date: 2013-09-09
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Author: The Apache Software Foundation
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Maintainer: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
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'client.R'
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'context.R'
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'deserialize.R'
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'functions.R'
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'mllib.R'
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'serialize.R'
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'sparkR.R'
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'stats.R'
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'types.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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exportClasses("DataFrame")
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exportMethods("arrange",
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"as.data.frame",
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"attach",
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"cache",
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"collect",
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"coltypes",
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"columns",
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"count",
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"cov",
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"corr",
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"crosstab",
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"describe",
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"dim",
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"distinct",
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"dropna",
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"dtypes",
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"fillna",
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"filter",
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"first",
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"freqItems",
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"group_by",
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"groupBy",
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"head",
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"isLocal",
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"join",
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"limit",
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"orderBy",
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"merge",
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"mutate",
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"na.omit",
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"names",
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"ncol",
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"nrow",
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"orderBy",
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"persist",
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"printSchema",
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"rbind",
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"registerTempTable",
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"rename",
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"repartition",
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"sample",
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"sample_frac",
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"sampleBy",
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"saveAsParquetFile",
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"saveAsTable",
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"saveDF",
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"selectExpr",
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"show",
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"showDF",
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"subset",
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"summarize",
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"summary",
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"take",
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"transform",
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"unionAll",
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"unique",
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"unpersist",
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"where",
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"with",
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"withColumn",
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"withColumnRenamed",
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"write.df")
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exportClasses("Column")
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exportMethods("abs",
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exportMethods("%in%",
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"abs",
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"acos",
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"add_months",
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"alias",
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"approxCountDistinct",
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"asc",
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"ascii",
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"asin",
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"atan",
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"atan2",
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"avg",
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"base64",
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"between",
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"bin",
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"bitwiseNOT",
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"cast",
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"cbrt",
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"ceil",
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"ceiling",
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"column",
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"concat",
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"concat_ws",
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"contains",
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"conv",
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"cos",
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"cosh",
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"count",
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"countDistinct",
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"crc32",
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"cumeDist",
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"date_add",
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"date_format",
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"date_sub",
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"datediff",
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"dayofmonth",
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"dayofyear",
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"denseRank",
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"desc",
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"endsWith",
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"exp",
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"explode",
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"expm1",
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"expr",
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"factorial",
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"first",
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"floor",
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"format_number",
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"format_string",
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"from_unixtime",
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"from_utc_timestamp",
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"getField",
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"getItem",
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"greatest",
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"hex",
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"hour",
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"hypot",
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"ifelse",
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"initcap",
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"instr",
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"isNaN",
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"isNotNull",
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"isNull",
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"lag",
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"last",
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"last_day",
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"lead",
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"least",
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"length",
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"levenshtein",
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"like",
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"lit",
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"locate",
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"log",
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"log10",
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"log1p",
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"log2",
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"lower",
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"lpad",
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"ltrim",
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"max",
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"md5",
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"mean",
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"min",
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"minute",
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"month",
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"months_between",
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"n",
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"n_distinct",
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"nanvl",
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"negate",
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"next_day",
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"ntile",
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"otherwise",
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"percentRank",
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"pmod",
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"quarter",
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"rand",
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"randn",
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"rank",
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"regexp_extract",
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"regexp_replace",
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"reverse",
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"rint",
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"rlike",
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"round",
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"rowNumber",
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"rpad",
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"rtrim",
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"second",
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"sha1",
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"sha2",
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"shiftLeft",
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"shiftRight",
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"shiftRightUnsigned",
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"sign",
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"signum",
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"sin",
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"sinh",
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"size",
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"soundex",
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"sqrt",
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"startsWith",
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"substr",
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"substring_index",
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"sum",
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"sumDistinct",
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"tan",
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"tanh",
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"toDegrees",
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"toRadians",
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"upper")
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"to_date",
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"to_utc_timestamp",
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"translate",
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"trim",
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"unbase64",
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"unhex",
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"unix_timestamp",
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"upper",
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"weekofyear",
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"when",
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"year")
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export("sparkRSQL.init",
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export("cacheTable",
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"cacheTable",
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"print.structType")
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"print.structType")

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