sparklyr (version 1.1.0)

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(), ...)

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.

...

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

# NOT RUN {
library(sparklyr)
sc <- spark_connect(master = "local", version = "2.4", 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)

# }
# NOT RUN {
# }