spark_read_csv: Read a CSV file into a Spark DataFrame

In sparklyr: R Interface to Apache Spark

Read a CSV file into a Spark DataFrame

Description

Read a tabular data file into a Spark DataFrame.

Usage

spark_read_csv(
  sc,
  name = NULL,
  path = name,
  header = TRUE,
  columns = NULL,
  infer_schema = is.null(columns),
  delimiter = ",",
  quote = "\"",
  escape = "\\",
  charset = "UTF-8",
  null_value = NULL,
  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.
header	Boolean; should the first row of data be used as a header? Defaults to TRUE.
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.
infer_schema	Boolean; should column types be automatically inferred? Requires one extra pass over the data. Defaults to is.null(columns).
delimiter	The character used to delimit each column. Defaults to ‘⁠','⁠’.
quote	The character used as a quote. Defaults to ‘⁠'"'⁠’.
escape	The character used to escape other characters. Defaults to ‘⁠'\'⁠’.
charset	The character set. Defaults to ‘⁠"UTF-8"⁠’.
null_value	The character to use for null, or missing, values. Defaults to NULL.
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.

Details

You can read data from HDFS (hdfs://), S3 (s3a://), as well as the local file system (file://).

When header is FALSE, the column names are generated with a V prefix; e.g. V1, V2, ....

See Also

Other Spark serialization routines: collect_from_rds(), spark_insert_table(), spark_load_table(), spark_read(), spark_read_avro(), spark_read_binary(), spark_read_delta(), 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_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()

sparklyr documentation built on May 29, 2024, 2:58 a.m.