sparklyr (version 0.8.0)

spark_write_csv: Write a Spark DataFrame to a CSV

Description

Write a Spark DataFrame to a tabular (typically, comma-separated) file.

Usage

spark_write_csv(x, path, header = TRUE, delimiter = ",", quote = "\"",
  escape = "\\", charset = "UTF-8", null_value = NULL,
  options = list(), mode = NULL, partition_by = NULL, ...)

Arguments

x

A Spark DataFrame or dplyr operation

path

The path to the file. Needs to be accessible from the cluster. Supports the "hdfs://", "s3a://" and "file://" protocols.

header

Should the first row of data be used as a header? Defaults to TRUE.

delimiter

The character used to delimit each column, defaults to ,.

quote

The character used as a quote. Defaults to '"'.

escape

The character used to escape other characters, defaults to \.

charset

The character set, defaults to "UTF-8".

null_value

The character to use for default values, defaults to NULL.

options

A list of strings with additional options.

mode

A character element. Specifies the behavior when data or table already exists. Supported values include: 'error', 'append', 'overwrite' and ignore. Notice that 'overwrite' will also change the column structure.

For more details see also http://spark.apache.org/docs/latest/sql-programming-guide.html#save-modes for your version of Spark.

partition_by

A character vector. Partitions the output by the given columns on the file system.

...

Optional arguments; currently unused.

See Also

Other Spark serialization routines: spark_load_table, spark_read_csv, spark_read_jdbc, spark_read_json, spark_read_libsvm, spark_read_parquet, spark_read_source, spark_read_table, spark_read_text, spark_save_table, spark_write_jdbc, spark_write_json, spark_write_parquet, spark_write_source, spark_write_table, spark_write_text