Skip to content

Latest commit

 

History

History
41 lines (28 loc) · 1.49 KB

File metadata and controls

41 lines (28 loc) · 1.49 KB

SparkStreming

Streaming App to analyse live top twitter hashtags via Graph

Requirements

  • JDK 7 or higher version
  • Scala 2.10.3
  • Apache Spark Core & Streaming 1.0.2 ( sbt :"org.apache.spark" %% "spark-core" % "1.0.2", "org.apache.spark" %% "spark-streaming" % "1.0.2" ) => http://www.apache.org/dyn/closer.cgi/spark/spark-1.0.2/spark-1.0.2-bin-hadoop1.tgz
  • Twitter4j Stream Library 3.0.3 ( sbt : "org.twitter4j" % "twitter4j-stream" % "3.0.3" )
  • Twitter4j Core Library 3.0.3 ( sbt : "org.twitter4j" % "twitter4j-core" % "3.0.3" )
  • Apache Spark Streaming Twitter 1.0.2 ( sbt : "org.apache.spark" %% "spark-streaming-twitter" % "1.0.2")
  • Akka 2.2-M1 ( sbt : "com.typesafe.akka" % "akka-actor_2.10" % "2.2-M1" )
  • Socko Web Server 0.4.2 ( sbt : "org.mashupbots.socko" % "socko-webserver_2.10" % "0.4.2" )
  • Chart.js ( http://www.chartjs.org/ )

Configuration

  • Configure run.sh script as per your directory structure.
  • Configure build.sbt as per your project configuration.
  • Set Apache Spark directory as SPARK_HOME.

Usage

The project focus on exploring Apache Spark Streaming API to analyse twitter steaming information. We are plotting a live graph based on n second sliding window streaming. We analysed which topic or hashtag is mostly discussed by the user on the twitter.

License

MobGopher is released under the MIT license. Checkout MIT license for more information.

Contact me

Maninder Pal Singh