spark_load_table

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Reads from a Spark Table into a Spark DataFrame.

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
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 http://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: 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_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()

Aliases
  • spark_load_table
Documentation reproduced from package sparklyr, version 1.4.0, License: Apache License 2.0 | file LICENSE

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