Write a ORC Stream

R/stream_data.R

stream_write_orc

Description

Writes a Spark dataframe stream into an ORC stream.

Usage

stream_write_orc( 
  x, 
  path, 
  mode = c("append", "complete", "update"), 
  trigger = stream_trigger_interval(), 
  checkpoint = file.path(path, "checkpoints", random_string("")), 
  options = list(), 
  partition_by = NULL, 
  ... 
) 

Arguments

Arguments Description
x A Spark DataFrame or dplyr operation
path The destination path. Needs to be accessible from the cluster. Supports the "hdfs://", "s3a://" and "file://" protocols.
mode Specifies how data is written to a streaming sink. Valid values are "append", "complete" or "update".
trigger The trigger for the stream query, defaults to micro-batches runnnig every 5 seconds. See stream_trigger_interval and stream_trigger_continuous.
checkpoint The location where the system will write all the checkpoint information to guarantee end-to-end fault-tolerance.
options A list of strings with additional options.
partition_by Partitions the output by the given list of columns.
Optional arguments; currently unused.

Examples

library(sparklyr)
sc <- spark_connect(master = "local") 
sdf_len(sc, 10) %>% spark_write_orc("orc-in") 
stream <- stream_read_orc(sc, "orc-in") %>% stream_write_orc("orc-out") 
stream_stop(stream) 

See Also

Other Spark stream serialization: stream_read_csv(), stream_read_delta(), stream_read_json(), stream_read_kafka(), stream_read_orc(), stream_read_parquet(), 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_parquet(), stream_write_text()