Read from a generic source into a Spark DataFrame.
R/data_interface.R
spark_read_source
Description
Read from a generic source into a Spark DataFrame.
Usage
spark_read_source(
sc, name = NULL,
path = name,
source, options = list(),
repartition = 0,
memory = TRUE,
overwrite = TRUE,
columns = NULL,
... )
Arguments
Arguments | 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. |
source | A data source capable of reading data. |
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? |
columns | A vector of column names or a named vector of column types. If specified, the elements can be "binary" for BinaryType , "boolean" for BooleanType , "byte" for ByteType , "integer" for IntegerType , "integer64" for LongType , "double" for DoubleType , "character" for StringType , "timestamp" for TimestampType and "date" for DateType . |
… | Optional arguments; currently unused. |
See Also
Other Spark serialization routines: collect_from_rds()
, spark_insert_table()
, spark_load_table()
, 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_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()