SparkR (version 3.1.2)

first: Return the first row of a SparkDataFrame

Description

Aggregate function: returns the first value in a group.

Usage

first(x, ...)
# S4 method for SparkDataFrame
first(x)
# S4 method for characterOrColumn
first(x, na.rm = FALSE)

Arguments

x

a SparkDataFrame or a column used in aggregation function.

...

further arguments to be passed to or from other methods.

na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds.

Details

The function by default returns the first values it sees. It will return the first non-missing value it sees when na.rm is set to true. If all values are missing, then NA is returned. Note: the function is non-deterministic because its results depends on the order of the rows which may be non-deterministic after a shuffle.

See Also

Other SparkDataFrame functions: SparkDataFrame-class, agg(), alias(), arrange(), 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(), 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(), withColumn(), withWatermark(), with(), write.df(), write.jdbc(), write.json(), write.orc(), write.parquet(), write.stream(), write.text()

Other aggregate functions: avg(), column_aggregate_functions, corr(), count(), cov(), last()

Examples

# NOT RUN {
sparkR.session()
path <- "path/to/file.json"
df <- read.json(path)
first(df)
# }
# NOT RUN {
first(df$c)
first(df$c, TRUE)
# }