stream_write_memory

Write Memory Stream

Description

Writes a Spark dataframe stream into a memory stream.

Usage

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

Arguments

Argument	Description
x	A Spark DataFrame or dplyr operation
name	The name to assign to the newly generated stream.
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

sc <- spark_connect(master = "local")

dir.create("csv-in")
write.csv(iris, "csv-in/data.csv", row.names = FALSE)

csv_path <- file.path("file://", getwd(), "csv-in")

stream <- stream_read_csv(sc, csv_path) %>% stream_write_memory("csv-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_orc(), stream_write_parquet(), stream_write_text()