Using two WriteStreams in same spark structured streaming job - apache-spark

Question

I have a scenario where I would like to save the same streaming dataframe to two different streaming sinks.
I have created a streaming dataframe which I need to send to both Kafka topic and delta lake.
I thought of using forEachBatch, but looks like it doesn't support multiple STREAMING SINKS.
Also, I tried using spark session.awaitAnyTermination() with multiple write streams. But the second stream is not getting processed !
Is there a way through which we can achieve this ?!
This is my code:
I am reading from Kafka stream and creating a single streaming dataframe.
val df = spark.readStream
.format("kafka")
.option("kafka.bootstrap.servers", "localhost:9092")
.option("subscribe", "ingestionTopic1")
.load()
df.selectExpr("CAST(key AS STRING)", "CAST(value AS STRING)").as[(String, String)]
writing the above dataframe to a Kafka topic
val ds1 = df.selectExpr("CAST(key AS STRING)", "CAST(value AS STRING)")
.writeStream
.format("kafka")
.option("kafka.bootstrap.servers", "localhost:9082")
.option("topic", "outputTopic1")
.start()
writing the same streaming dataframe to delta lake
val ds2 = df.format("delta")
.outputMode("append")
.option("checkpointLocation", "/test/delta/events/_checkpoints/etlflow")
.start("/test/delta/events")
ds1.awaitTermination
ds2.awaitTermination

Answer 1

There are a few things you need to follow to use one input stream for multiple output streams:
You need to make sure to have two different checkpointLocations in the two output streams.
Furthermore, you need to ensure to have the writeStream call also on your second output query.
Overall, it is important to start both of the queries before waiting for the termination of both queries. (You are already doing this)