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()