sparklyr (version 0.8.0)

spark_read_source: Read from a generic source into a Spark DataFrame.

Description

Read from a generic source into a Spark DataFrame.

Usage

spark_read_source(sc, name, source, options = list(), repartition = 0,
  memory = TRUE, overwrite = TRUE, columns = NULL, ...)

Arguments

sc

A spark_connection.

name

The name to assign to the newly generated table.

source

A data source capable of reading data.

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?

columns

A vector of column names or a named vector of column types.

...

Optional arguments; currently unused.

See Also

Other Spark serialization routines: spark_load_table, spark_read_csv, spark_read_jdbc, spark_read_json, spark_read_libsvm, spark_read_parquet, spark_read_table, spark_read_text, spark_save_table, spark_write_csv, spark_write_jdbc, spark_write_json, spark_write_parquet, spark_write_source, spark_write_table, spark_write_text