From 2ff72f60ac6e42e9511fcf4effd1df89da8dc410 Mon Sep 17 00:00:00 2001
From: haoyuan <haoyuan@eecs.berkeley.edu>
Date: Tue, 4 Sep 2012 17:55:55 -0700
Subject: add TopKWordCountRaw.scala

---
 .../streaming/examples/TopKWordCountRaw.scala      | 86 ++++++++++++++++++++++
 1 file changed, 86 insertions(+)
 create mode 100644 streaming/src/main/scala/spark/streaming/examples/TopKWordCountRaw.scala

(limited to 'streaming')

diff --git a/streaming/src/main/scala/spark/streaming/examples/TopKWordCountRaw.scala b/streaming/src/main/scala/spark/streaming/examples/TopKWordCountRaw.scala
new file mode 100644
index 0000000000..7c01435f85
--- /dev/null
+++ b/streaming/src/main/scala/spark/streaming/examples/TopKWordCountRaw.scala
@@ -0,0 +1,86 @@
+package spark.streaming.examples
+
+import spark.util.IntParam
+import spark.storage.StorageLevel
+import spark.streaming._
+import spark.streaming.StreamingContext._
+
+object WordCountRaw {
+  def main(args: Array[String]) {
+    if (args.length != 7) {
+      System.err.println("Usage: WordCountRaw <master> <streams> <host> <port> <batchMs> <chkptMs> <reduces>")
+      System.exit(1)
+    }
+
+    val Array(master, IntParam(streams), host, IntParam(port), IntParam(batchMs),
+              IntParam(chkptMs), IntParam(reduces)) = args
+
+    // Create the context and set the batch size
+    val ssc = new StreamingContext(master, "TopKWordCountRaw")
+    ssc.setBatchDuration(Milliseconds(batchMs))
+
+    // Make sure some tasks have started on each node
+    ssc.sc.parallelize(1 to 1000, 1000).count()
+    ssc.sc.parallelize(1 to 1000, 1000).count()
+    ssc.sc.parallelize(1 to 1000, 1000).count()
+
+    val rawStreams = (1 to streams).map(_ =>
+      ssc.createRawNetworkStream[String](host, port, StorageLevel.MEMORY_ONLY_2)).toArray
+    val union = new UnifiedDStream(rawStreams)
+
+    import WordCount2_ExtraFunctions._
+
+    val windowedCounts = union.mapPartitions(splitAndCountPartitions)
+      .reduceByKeyAndWindow(add _, subtract _, Seconds(30), Milliseconds(batchMs), reduces)
+    windowedCounts.persist(StorageLevel.MEMORY_ONLY_DESER, StorageLevel.MEMORY_ONLY_DESER_2,
+      Milliseconds(chkptMs))
+    //windowedCounts.print()    // TODO: something else?
+
+    def topK(data: Iterator[(String, JLong)], k: Int): Iterator[(String, JLong)] = {
+      val taken = new Array[(String, JLong)](k)
+      
+      var i = 0
+      var len = 0
+      var done = false
+      var value: (String, JLong) = null
+      var swap: (String, JLong) = null
+      var count = 0
+
+      while(data.hasNext) {
+        value = data.next
+        count += 1
+        println("count = " + count)
+        if (len == 0) {
+          taken(0) = value
+          len = 1
+        } else if (len < k || value._2 > taken(len - 1)._2) {
+          if (len < k) {
+            len += 1
+          }
+          taken(len - 1) = value
+          i = len - 1
+          while(i > 0 && taken(i - 1)._2 < taken(i)._2) {
+            swap = taken(i)
+            taken(i) = taken(i-1)
+            taken(i - 1) = swap
+            i -= 1
+          }
+        }
+      }
+      println("Took " + len + " out of " + count + " items")
+      return taken.toIterator  
+    }
+    
+    val k = 50
+    val partialTopKWindowedCounts = windowedCounts.mapPartitions(topK(_, k))
+    partialTopKWindowedCounts.foreachRDD(rdd => {
+      val collectedCounts = rdd.collect
+      println("Collected " + collectedCounts.size + " items")
+      topK(collectedCounts.toIterator, k).foreach(println)
+    })
+
+//    windowedCounts.foreachRDD(r => println("Element count: " + r.count()))
+
+    ssc.start()
+  }
+}
-- 
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