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

Argument Description
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 https://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: collect_from_rds(), spark_load_table(), spark_read_avro(), spark_read_binary(), spark_read_csv(), spark_read_delta(), spark_read_image(), spark_read_jdbc(), spark_read_json(), spark_read_libsvm(), spark_read_orc(), spark_read_parquet(), spark_read_source(), spark_read_table(), spark_read_text(), spark_read(), spark_save_table(), spark_write_avro(), spark_write_delta(), spark_write_jdbc(), spark_write_json(), spark_write_orc(), spark_write_parquet(), spark_write_source(), spark_write_table(), spark_write_text()