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Showing content from https://spark.apache.org/docs/latest/api/R/reference/arrange.html below:

Arrange Rows by Variables — arrange • SparkR

Sort a SparkDataFrame by the specified column(s).

arrange(x, col, ...)

# S4 method for class 'SparkDataFrame,Column'
arrange(x, col, ..., withinPartitions = FALSE)

# S4 method for class 'SparkDataFrame,character'
arrange(x, col, ..., decreasing = FALSE, withinPartitions = FALSE)

# S4 method for class 'SparkDataFrame,characterOrColumn'
orderBy(x, col, ...)

x

a SparkDataFrame to be sorted.

col

a character or Column object indicating the fields to sort on

...

additional sorting fields

withinPartitions

a logical argument indicating whether to sort only within each partition

decreasing

a logical argument indicating sorting order for columns when a character vector is specified for col

A SparkDataFrame where all elements are sorted.

arrange(SparkDataFrame, Column) since 1.4.0

arrange(SparkDataFrame, character) since 1.4.0

orderBy(SparkDataFrame, characterOrColumn) since 1.4.0

Other SparkDataFrame functions: SparkDataFrame-class, agg(), alias(), as.data.frame(), attach,SparkDataFrame-method, broadcast(), cache(), checkpoint(), coalesce(), collect(), colnames(), coltypes(), createOrReplaceTempView(), crossJoin(), cube(), dapplyCollect(), dapply(), describe(), dim(), distinct(), dropDuplicates(), dropna(), drop(), dtypes(), exceptAll(), except(), explain(), filter(), first(), gapplyCollect(), gapply(), getNumPartitions(), group_by(), head(), hint(), histogram(), insertInto(), intersectAll(), intersect(), isLocal(), isStreaming(), join(), limit(), localCheckpoint(), merge(), mutate(), ncol(), nrow(), persist(), printSchema(), randomSplit(), rbind(), rename(), repartitionByRange(), repartition(), rollup(), sample(), saveAsTable(), schema(), selectExpr(), select(), showDF(), show(), storageLevel(), str(), subset(), summary(), take(), toJSON(), unionAll(), unionByName(), union(), unpersist(), unpivot(), withColumn(), withWatermark(), with(), write.df(), write.jdbc(), write.json(), write.orc(), write.parquet(), write.stream(), write.text()

if (FALSE) { # \dontrun{
sparkR.session()
path <- "path/to/file.json"
df <- read.json(path)
arrange(df, df$col1)
arrange(df, asc(df$col1), desc(abs(df$col2)))
arrange(df, "col1", decreasing = TRUE)
arrange(df, "col1", "col2", decreasing = c(TRUE, FALSE))
arrange(df, "col1", "col2", withinPartitions = TRUE)
} # }

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