spark_load_table

Reads from a Spark Table into a Spark DataFrame.

Description

Reads from a Spark Table into a Spark DataFrame.

Usage

spark_load_table(
  sc,
  name,
  path,
  options = list(),
  repartition = 0,
  memory = TRUE,
  overwrite = TRUE
)

Arguments

Argument Description
sc A spark_connection.
name The name to assign to the newly generated table.
path The path to the file. Needs to be accessible from the cluster. Supports the “hdfs://”, “s3a://” and “file://” protocols.
options A list of strings with additional options. See https://spark.apache.org/docs/latest/sql-programming-guide.html#configuration.
repartition The number of partitions used to distribute the generated table. Use 0 (the default) to avoid partitioning.
memory Boolean; should the data be loaded eagerly into memory? (That is, should the table be cached?)
overwrite Boolean; overwrite the table with the given name if it already exists?

See Also

Other Spark serialization routines: collect_from_rds(), 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_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()