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
"hdfs://".- 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_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