spark_save_table
Saves a Spark DataFrame as a Spark table
Description
Saves a Spark DataFrame and as a Spark table.
Usage
spark_save_table(x, path, mode = NULL, options = list())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. 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. options | A list of strings with additional options.
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_write_avro(), spark_write_csv(), spark_write_delta(), spark_write_jdbc(), spark_write_json(), spark_write_orc(), spark_write_parquet(), spark_write_source(), spark_write_table(), spark_write_text()