library(sparklyr)
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) Write Memory Stream
R/stream_data.R
stream_write_memory
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
| Arguments | 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
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()