sparklyr (version 1.8.4)

stream_write_delta: Write Delta Stream

Description

Writes a Spark dataframe stream into a Delta Lake table.

Usage

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".

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.

Details

Please note that Delta Lake requires installing the appropriate package by setting the packages parameter to "delta" in spark_connect()

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_json(), stream_write_kafka(), stream_write_memory(), stream_write_orc(), stream_write_parquet(), stream_write_text()

Examples

if (FALSE) {

library(sparklyr)
sc <- spark_connect(master = "local", version = "2.4.0", packages = "delta")

dir.create("text-in")
writeLines("A text entry", "text-in/text.txt")

text_path <- file.path("file://", getwd(), "text-in")

stream <- stream_read_text(sc, text_path) %>% stream_write_delta(path = "delta-test")

stream_stop(stream)
}