library(sparklyr)
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) Read Parquet Stream
R/stream_data.R
stream_read_parquet
Description
Reads a parquet stream as a Spark dataframe stream.
Usage
stream_read_parquet(
sc,
path,
name = NULL,
columns = NULL,
options = list(),
...
) Arguments
| Arguments | 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 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. |
Examples
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()