26.4. Creating and Using DStreams

import org.infinispan.spark.stream._
import org.apache.spark.streaming.{Seconds, StreamingContext}
import org.apache.spark.storage.StorageLevel
import java.util.Properties

// Spark context
val sc = ... 
// java.util.Properties with Infinispan RDD configuration
val props = ... 
val ssc = new StreamingContext(sc, Seconds(1))

val stream = new InfinispanInputDStream[String, Book](ssc, StorageLevel.MEMORY_ONLY, props)

import org.infinispan.spark.stream._
import org.apache.spark.streaming.{Seconds, StreamingContext}
import org.apache.spark.storage.StorageLevel
import java.util.Properties

// Spark context
val sc = ... 
// java.util.Properties with Infinispan RDD configuration
val props = ... 
val ssc = new StreamingContext(sc, Seconds(1))

val stream = new InfinispanInputDStream[String, Book](ssc, StorageLevel.MEMORY_ONLY, props)

import org.infinispan.spark.stream._

val stream = ... // From previous sample

// Filter only created entries
val createdBooksRDD = stream.filter { case (_, _, t) => t == Type.CLIENT_CACHE_ENTRY_CREATED }

// Reduce last 30 seconds of data, every 10 seconds
val windowedRDD: DStream[Long] = createdBooksRDD.count().reduceByWindow(_ + _, Seconds(30), Seconds(10))

// Prints the results, couting the number of occurences in each individual RDD
windowedRDD.foreachRDD { rdd => println(rdd.reduce(_ + _)) }

// Start the processing
ssc.start()
ssc.awaitTermination()

import org.infinispan.spark.stream._

val stream = ... // From previous sample

// Filter only created entries
val createdBooksRDD = stream.filter { case (_, _, t) => t == Type.CLIENT_CACHE_ENTRY_CREATED }

// Reduce last 30 seconds of data, every 10 seconds
val windowedRDD: DStream[Long] = createdBooksRDD.count().reduceByWindow(_ + _, Seconds(30), Seconds(10))

// Prints the results, couting the number of occurences in each individual RDD
windowedRDD.foreachRDD { rdd => println(rdd.reduce(_ + _)) }

// Start the processing
ssc.start()
ssc.awaitTermination()