I am following the book Spark the Definitive Guide The following code is executed locally using spark-shell
Procedure: Started the spark-shell without any other options
val static = spark.read.json("/part-00079-tid-730451297822678341-1dda7027-2071-4d73-a0e2-7fb6a91e1d1f-0-c000.json")
val dataSchema = static.schema
val streaming = spark.readStream.schema(dataSchema) .option(“maxFilesPerTrigger”,1).json("/part-00079-tid-730451297822678341-1dda7027-2071-4d73-a0e2-7fb6a91e1d1f-0-c000.json")
val activityCounts = streaming.groupBy(“gt”).count()
val activityQuery = activityCounts.writeStream.queryName(“activity_counts”).format(“memory”).outputMode(“complete”).start()
activityQuery.awaitTermination()
The Books says that "After this code is executed the streaming computation will have started in the background" … "Now that this stream is running , we can experiment with the result by querying"
MY OBSERVATION:
When this code is executed it does not frees the shell for me to type in the commands such asspark.streams.active
Hence I cannot query this stream
My research
I tried to open a new spark-shell but querying in that shell does not returns any results. Are the streams obtained from this shell accessible from other another instance of the shell.
I want the table in memory so that I can use the to query using command
for( i <- 1 to 5)
{
spark.sql(“SELECT * FROM activity_counts”).show()
Thread.sleep(1000)
}