stream_write_csv {sparklyr}

Write files to the stream

Description

Write files to the stream

Usage

stream_write_csv(
  x,
  path,
  mode = c("append", "complete", "update"),
  trigger = stream_trigger_interval(),
  checkpoint = file.path(path, "checkpoint"),
  header = TRUE,
  delimiter = ",",
  quote = "\"",
  escape = "\\",
  charset = "UTF-8",
  null_value = NULL,
  options = list(),
  partition_by = NULL,
  ...
)

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

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

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

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,
  ...
)

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

stream_write_console(
  x,
  mode = c("append", "complete", "update"),
  options = list(),
  trigger = stream_trigger_interval(),
  partition_by = NULL,
  ...
)

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

Arguments

x

A Spark DataFrame or dplyr operation

path

The path to the file. 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 running 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.

header

Should the first row of data be used as a header? Defaults to TRUE.

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 default values, defaults to NULL.

options

A list of strings with additional options.

partition_by

Partitions the output by the given list of columns.

...

Optional arguments; currently unused.

See Also

Other Spark stream serialization: stream_write_memory(), stream_write_table()

Examples

## Not run: 

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_csv("csv-out")

stream_stop(stream)

## End(Not run)