spark_write_csv
Write a Spark DataFrame to a CSV
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
characterelement. 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
charactervector. 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_avro(),
spark_read_csv(),
spark_read_delta(),
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()