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SparkR (version 2.1.2)

rbind: Union two or more SparkDataFrames

Description

Union two or more SparkDataFrames. This is equivalent to UNION ALL in SQL.

Usage

rbind(..., deparse.level = 1)

# S4 method for SparkDataFrame rbind(x, ..., deparse.level = 1)

Arguments

...

additional SparkDataFrame(s).

deparse.level

currently not used (put here to match the signature of the base implementation).

x

a SparkDataFrame.

Value

A SparkDataFrame containing the result of the union.

Details

Note: This does not remove duplicate rows across the two SparkDataFrames.

See Also

union

Other SparkDataFrame functions: SparkDataFrame-class, agg, arrange, as.data.frame, attach, cache, coalesce, collect, colnames, coltypes, createOrReplaceTempView, crossJoin, dapplyCollect, dapply, describe, dim, distinct, dropDuplicates, dropna, drop, dtypes, except, explain, filter, first, gapplyCollect, gapply, getNumPartitions, group_by, head, histogram, insertInto, intersect, isLocal, join, limit, merge, mutate, ncol, nrow, persist, printSchema, randomSplit, registerTempTable, rename, repartition, sample, saveAsTable, schema, selectExpr, select, showDF, show, storageLevel, str, subset, take, union, unpersist, withColumn, with, write.df, write.jdbc, write.json, write.orc, write.parquet, write.text

Examples

Run this code
# NOT RUN {
sparkR.session()
unions <- rbind(df, df2, df3, df4)
# }

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