Apache Spark is a general purpose large scale clustering solution which claims to be faster than Hadoop & other HDFS implementations. More theory on Spark can be accessed on the internet.
Here I will focus only on the Installation steps of Apache Spark on Windows
You need JDK1.6+ to proceed with the steps below or in PDF
Step 1: Download & Untar SPARK
Download the version 1.0.2 of Spark from the official website.
Untar the downloaded file to any location (say C:\spark-1.0.2)
Step 2: Download SBT msi (needed for Windows)
Download sbt.MSI & execute it.
You may need to restart the machine so that command line can identify the sbt command
Step 3: Package Spark using SBT
Note: This step takes enormous amount of time. Please be patient
Step 4: Download SCALA
Spark 1.0.2 needs Scala 2.10. This is extremely important to note. And you can read the README.MD file in the SPARK folder to find the correct scala version needed for your spark.
Download and unzip the scala to any location (say C:\ scala-2.10.1)
Set SCALA_HOME environment variable & set the PATH variable to the bin directory of scala
Verify the scala version (and thus the download)
Step 5: Start the spark shell
Sample program in SPARK
- Create a data set of 1…10000 integers
scala> val data = 1 to 10000
- Use Spark Context to create an RDD [Resilient Distributed Dateset] from that data
scala> val distData = sc.parallelize(data)
- Perform a filter mechanism on that data
scala> distData.filter(_ < 10).collect()