spark_read_delta

Read from Delta Lake into a Spark DataFrame.

Description

Read from Delta Lake into a Spark DataFrame.

Usage

spark_read_delta(
  sc,
  path,
  name = NULL,
  version = NULL,
  timestamp = NULL,
  options = list(),
  repartition = 0,
  memory = TRUE,
  overwrite = TRUE,
  ...
)

Arguments

Argument Description
sc A spark_connection.
path The path to the file. Needs to be accessible from the cluster. Supports the “hdfs://”, “s3a://” and “file://” protocols.
name The name to assign to the newly generated table.
version The version of the delta table to read.
timestamp The timestamp of the delta table to read. For example, "2019-01-01" or "2019-01-01'T'00:00:00.000Z".
options A list of strings with additional options.
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?
Optional arguments; currently unused.

See Also

Other Spark serialization routines: collect_from_rds(), spark_load_table(), spark_read_avro(), spark_read_binary(), spark_read_csv(), 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()