Write a Spark DataFrame to a CSV
R/data_interface.R
spark_write_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
| Arguments | 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_insert_table(), 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()