From 9ac4cb1c5fd7637ff9936f1ef54fa27f6f6aa214 Mon Sep 17 00:00:00 2001
From: Patrick Wendell <pwendell@gmail.com>
Date: Fri, 21 Dec 2012 17:11:39 -0800
Subject: Adding a Twitter InputDStream with an example

---
 .../spark/streaming/TwitterInputDStream.scala      | 59 ++++++++++++++++++++++
 .../spark/streaming/examples/TwitterBasic.scala    | 37 ++++++++++++++
 2 files changed, 96 insertions(+)
 create mode 100644 streaming/src/main/scala/spark/streaming/TwitterInputDStream.scala
 create mode 100644 streaming/src/main/scala/spark/streaming/examples/TwitterBasic.scala

(limited to 'streaming/src')

diff --git a/streaming/src/main/scala/spark/streaming/TwitterInputDStream.scala b/streaming/src/main/scala/spark/streaming/TwitterInputDStream.scala
new file mode 100644
index 0000000000..5d177e96de
--- /dev/null
+++ b/streaming/src/main/scala/spark/streaming/TwitterInputDStream.scala
@@ -0,0 +1,59 @@
+package spark.streaming
+
+import spark.RDD
+import spark.streaming.{Time, InputDStream}
+import twitter4j._
+import twitter4j.auth.BasicAuthorization
+import collection.mutable.ArrayBuffer
+import collection.JavaConversions._
+
+/* A stream of Twitter statuses, potentially filtered by one or more keywords.
+*
+* @constructor create a new Twitter stream using the supplied username and password to authenticate.
+* An optional set of string filters can be used to restrict the set of tweets. The Twitter API is
+* such that this may return a sampled subset of all tweets during each interval.
+*/
+class TwitterInputDStream(
+    @transient ssc_ : StreamingContext,
+    username: String,
+    password: String,
+    filters: Seq[String]
+    ) extends InputDStream[Status](ssc_)  {
+  val statuses: ArrayBuffer[Status] = ArrayBuffer()
+  var twitterStream: TwitterStream = _
+
+  override def start() = {
+    twitterStream = new TwitterStreamFactory()
+      .getInstance(new BasicAuthorization(username, password))
+    twitterStream.addListener(new StatusListener {
+      def onStatus(status: Status) = {
+        statuses += status
+      }
+      // Unimplemented
+      def onDeletionNotice(statusDeletionNotice: StatusDeletionNotice) {}
+      def onTrackLimitationNotice(i: Int) {}
+      def onScrubGeo(l: Long, l1: Long) {}
+      def onStallWarning(stallWarning: StallWarning) {}
+      def onException(e: Exception) {}
+    })
+
+    val query: FilterQuery = new FilterQuery
+    if (filters.size > 0) {
+      query.track(filters.toArray)
+      twitterStream.filter(query)
+    } else {
+      twitterStream.sample()
+    }
+  }
+
+  override def stop() = {
+    twitterStream.shutdown()
+  }
+
+  override def compute(validTime: Time): Option[RDD[Status]] = {
+    // Flush the current tweet buffer
+    val rdd = Some(ssc.sc.parallelize(statuses))
+    statuses.foreach(x => statuses -= x)
+    rdd
+  }
+}
diff --git a/streaming/src/main/scala/spark/streaming/examples/TwitterBasic.scala b/streaming/src/main/scala/spark/streaming/examples/TwitterBasic.scala
new file mode 100644
index 0000000000..c7e380fbe1
--- /dev/null
+++ b/streaming/src/main/scala/spark/streaming/examples/TwitterBasic.scala
@@ -0,0 +1,37 @@
+package spark.streaming.examples
+
+import spark.streaming.StreamingContext._
+import spark.streaming.{TwitterInputDStream, Seconds, StreamingContext}
+
+object TwitterBasic {
+  def main(args: Array[String]) {
+    if (args.length != 3) {
+      System.err.println("Usage: TwitterBasic <master> <twitter_username> <twitter_password>")
+      System.exit(1)
+    }
+
+    val Array(master, username, password) = args
+
+    val ssc = new StreamingContext(master, "TwitterBasic", Seconds(2))
+    val stream = new TwitterInputDStream(ssc, username, password, Seq())
+    ssc.graph.addInputStream(stream)
+
+    val hashTags = stream.flatMap(
+      status => status.getText.split(" ").filter(_.startsWith("#")))
+
+    // Word count over hashtags
+    val counts = hashTags.map((_, 1)).reduceByKeyAndWindow(_ + _, Seconds(60))
+
+    // TODO: Sorts on one node - should do with global sorting once streaming supports it
+    val topCounts = counts.collect().map(_.sortBy(-_._2).take(5))
+
+    topCounts.foreachRDD(rdd => {
+      val topList = rdd.take(1)(0)
+      println("\nPopular topics in last 60 seconds:")
+      topList.foreach(t => println("%s (%s tweets)".format(t._1, t._2)))
+    }
+    )
+
+    ssc.start()
+  }
+}
-- 
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