spark-instrumented-optimizer/R/pkg/NAMESPACE
Felix Cheung 17579bda3c [SPARK-18958][SPARKR] R API toJSON on DataFrame
## What changes were proposed in this pull request?

It would make it easier to integrate with other component expecting row-based JSON format.
This replaces the non-public toJSON RDD API.

## How was this patch tested?

manual, unit tests

Author: Felix Cheung <felixcheung_m@hotmail.com>

Closes #16368 from felixcheung/rJSON.
2016-12-22 20:54:38 -08:00

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# Imports from base R
# Do not include stats:: "rpois", "runif" - causes error at runtime
importFrom("methods", "setGeneric", "setMethod", "setOldClass")
importFrom("methods", "is", "new", "signature", "show")
importFrom("stats", "gaussian", "setNames")
importFrom("utils", "download.file", "object.size", "packageVersion", "tail", "untar")
# Disable native libraries till we figure out how to package it
# See SPARKR-7839
#useDynLib(SparkR, stringHashCode)
# S3 methods exported
export("sparkR.session")
export("sparkR.init")
export("sparkR.stop")
export("sparkR.session.stop")
export("sparkR.conf")
export("sparkR.version")
export("sparkR.uiWebUrl")
export("print.jobj")
export("sparkR.newJObject")
export("sparkR.callJMethod")
export("sparkR.callJStatic")
export("install.spark")
export("sparkRSQL.init",
"sparkRHive.init")
# MLlib integration
exportMethods("glm",
"spark.glm",
"predict",
"summary",
"spark.kmeans",
"fitted",
"spark.mlp",
"spark.naiveBayes",
"spark.survreg",
"spark.lda",
"spark.posterior",
"spark.perplexity",
"spark.isoreg",
"spark.gaussianMixture",
"spark.als",
"spark.kstest",
"spark.logit",
"spark.randomForest",
"spark.gbt")
# Job group lifecycle management methods
export("setJobGroup",
"clearJobGroup",
"cancelJobGroup")
# Export Utility methods
export("setLogLevel")
exportClasses("SparkDataFrame")
exportMethods("arrange",
"as.data.frame",
"attach",
"cache",
"collect",
"colnames",
"colnames<-",
"coltypes",
"coltypes<-",
"columns",
"count",
"cov",
"corr",
"covar_samp",
"covar_pop",
"createOrReplaceTempView",
"crossJoin",
"crosstab",
"dapply",
"dapplyCollect",
"describe",
"dim",
"distinct",
"drop",
"dropDuplicates",
"dropna",
"dtypes",
"except",
"explain",
"fillna",
"filter",
"first",
"freqItems",
"gapply",
"gapplyCollect",
"group_by",
"groupBy",
"head",
"insertInto",
"intersect",
"isLocal",
"join",
"limit",
"merge",
"mutate",
"na.omit",
"names",
"names<-",
"ncol",
"nrow",
"orderBy",
"persist",
"printSchema",
"randomSplit",
"rbind",
"registerTempTable",
"rename",
"repartition",
"sample",
"sample_frac",
"sampleBy",
"saveAsParquetFile",
"saveAsTable",
"saveDF",
"schema",
"select",
"selectExpr",
"show",
"showDF",
"storageLevel",
"subset",
"summarize",
"summary",
"take",
"toJSON",
"transform",
"union",
"unionAll",
"unique",
"unpersist",
"where",
"with",
"withColumn",
"withColumnRenamed",
"write.df",
"write.jdbc",
"write.json",
"write.orc",
"write.parquet",
"write.text",
"write.ml")
exportClasses("Column")
exportMethods("%in%",
"abs",
"acos",
"add_months",
"alias",
"approxCountDistinct",
"approxQuantile",
"array_contains",
"asc",
"ascii",
"asin",
"atan",
"atan2",
"avg",
"base64",
"between",
"bin",
"bitwiseNOT",
"bround",
"cast",
"cbrt",
"ceil",
"ceiling",
"column",
"concat",
"concat_ws",
"contains",
"conv",
"cos",
"cosh",
"count",
"countDistinct",
"crc32",
"hash",
"cume_dist",
"date_add",
"date_format",
"date_sub",
"datediff",
"dayofmonth",
"dayofyear",
"decode",
"dense_rank",
"desc",
"encode",
"endsWith",
"exp",
"explode",
"expm1",
"expr",
"factorial",
"first",
"floor",
"format_number",
"format_string",
"from_unixtime",
"from_utc_timestamp",
"getField",
"getItem",
"greatest",
"hex",
"histogram",
"hour",
"hypot",
"ifelse",
"initcap",
"instr",
"isNaN",
"isNotNull",
"isNull",
"is.nan",
"isnan",
"kurtosis",
"lag",
"last",
"last_day",
"lead",
"least",
"length",
"levenshtein",
"like",
"lit",
"locate",
"log",
"log10",
"log1p",
"log2",
"lower",
"lpad",
"ltrim",
"max",
"md5",
"mean",
"min",
"minute",
"monotonically_increasing_id",
"month",
"months_between",
"n",
"n_distinct",
"nanvl",
"negate",
"next_day",
"ntile",
"otherwise",
"over",
"percent_rank",
"pmod",
"posexplode",
"quarter",
"rand",
"randn",
"rank",
"regexp_extract",
"regexp_replace",
"reverse",
"rint",
"rlike",
"round",
"row_number",
"rpad",
"rtrim",
"second",
"sha1",
"sha2",
"shiftLeft",
"shiftRight",
"shiftRightUnsigned",
"sd",
"sign",
"signum",
"sin",
"sinh",
"size",
"skewness",
"sort_array",
"soundex",
"spark_partition_id",
"stddev",
"stddev_pop",
"stddev_samp",
"struct",
"sqrt",
"startsWith",
"substr",
"substring_index",
"sum",
"sumDistinct",
"tan",
"tanh",
"toDegrees",
"toRadians",
"to_date",
"to_utc_timestamp",
"translate",
"trim",
"unbase64",
"unhex",
"unix_timestamp",
"upper",
"var",
"variance",
"var_pop",
"var_samp",
"weekofyear",
"when",
"window",
"year")
exportClasses("GroupedData")
exportMethods("agg")
exportMethods("pivot")
export("as.DataFrame",
"cacheTable",
"clearCache",
"createDataFrame",
"createExternalTable",
"dropTempTable",
"dropTempView",
"jsonFile",
"loadDF",
"parquetFile",
"read.df",
"read.jdbc",
"read.json",
"read.orc",
"read.parquet",
"read.text",
"spark.lapply",
"spark.addFile",
"spark.getSparkFilesRootDirectory",
"spark.getSparkFiles",
"sql",
"str",
"tableToDF",
"tableNames",
"tables",
"uncacheTable",
"print.summary.GeneralizedLinearRegressionModel",
"read.ml",
"print.summary.KSTest",
"print.summary.RandomForestRegressionModel",
"print.summary.RandomForestClassificationModel",
"print.summary.GBTRegressionModel",
"print.summary.GBTClassificationModel")
export("structField",
"structField.jobj",
"structField.character",
"print.structField",
"structType",
"structType.jobj",
"structType.structField",
"print.structType")
exportClasses("WindowSpec")
export("partitionBy",
"rowsBetween",
"rangeBetween")
export("windowPartitionBy",
"windowOrderBy")
S3method(print, jobj)
S3method(print, structField)
S3method(print, structType)
S3method(print, summary.GeneralizedLinearRegressionModel)
S3method(print, summary.KSTest)
S3method(print, summary.RandomForestRegressionModel)
S3method(print, summary.RandomForestClassificationModel)
S3method(print, summary.GBTRegressionModel)
S3method(print, summary.GBTClassificationModel)
S3method(structField, character)
S3method(structField, jobj)
S3method(structType, jobj)
S3method(structType, structField)