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) Write Delta Stream
R/stream_data.R
stream_write_delta
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
| Arguments | Description |
|---|---|
| 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()
Examples
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()