sparklyr (version 1.7.1)

stream_read_parquet: Read Parquet Stream

Description

Reads a parquet stream as a Spark dataframe stream.

Usage

stream_read_parquet(
  sc,
  path,
  name = NULL,
  columns = NULL,
  options = list(),
  ...
)

Arguments

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 stream.

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.

options

A list of strings with additional options.

...

Optional arguments; currently unused.

See Also

Other Spark stream serialization: stream_read_csv(), stream_read_delta(), stream_read_json(), stream_read_kafka(), stream_read_orc(), stream_read_socket(), stream_read_text(), stream_write_console(), stream_write_csv(), stream_write_delta(), stream_write_json(), stream_write_kafka(), stream_write_memory(), stream_write_orc(), stream_write_parquet(), stream_write_text()

Examples

# NOT RUN {
sc <- spark_connect(master = "local")

sdf_len(sc, 10) %>% spark_write_parquet("parquet-in")

stream <- stream_read_parquet(sc, "parquet-in") %>% stream_write_parquet("parquet-out")

stream_stop(stream)
# }
# NOT RUN {
# }