stream_write_kafka {sparklyr} | R Documentation |
Writes a Spark dataframe stream into an kafka stream.
stream_write_kafka(x, mode = c("append", "complete", "update"), trigger = stream_trigger_interval(), checkpoint = file.path("checkpoints", random_string("")), options = list(), ...)
x |
A Spark DataFrame or dplyr operation |
mode |
Specifies how data is written to a streaming sink. Valid values are
|
trigger |
The trigger for the stream query, defaults to micro-batches runnnig
every 5 seconds. See |
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. |
Please note that Kafka requires installing the appropriate
package by conneting with a config setting where sparklyr.shell.packages
is set to, for Spark 2.3.2, "org.apache.spark:spark-sql-kafka-0-10_2.11:2.3.2"
.
Other Spark stream serialization: stream_read_csv
,
stream_read_json
,
stream_read_kafka
,
stream_read_orc
,
stream_read_parquet
,
stream_read_scoket
,
stream_read_text
,
stream_write_console
,
stream_write_csv
,
stream_write_json
,
stream_write_memory
,
stream_write_orc
,
stream_write_parquet
,
stream_write_text
## Not run: config <- spark_config() # The following package is dependent to Spark version, for Spark 2.3.2: config$sparklyr.shell.packages <- "org.apache.spark:spark-sql-kafka-0-10_2.11:2.3.2" sc <- spark_connect(master = "local", config = config) read_options <- list(kafka.bootstrap.servers = "localhost:9092", subscribe = "topic1") write_options <- list(kafka.bootstrap.servers = "localhost:9092", topic = "topic2") stream <- stream_read_kafka(sc, options = read_options) %>% stream_write_kafka(options = write_options) stream_stop(stream) ## End(Not run)