Spark for big data analytics

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Transcript of Spark for big data analytics

PowerPoint Presentation

Big Data Analytics with Spark

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What will you learn today ?

What is Apache Spark ? How Spark fits into Hadoop Ecosystem ? Why Spark for Big Data Analytics ? Sparks popularity Hands-On : Analyzing data with Spark

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Apache Spark

Apache Spark is a general purpose data processing engine with in-memory computing Spark provides API for Scala, Java, Python and R which makes Spark widely adopted for data processing

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How Spark fits into Hadoop Ecosystem ? Spark is intended to enhance, not replace, the Hadoop stack

Spark is designed to read and write data to HDFS as well as other storage systems such as CSV files, Amazon S3 and NoSQL databases

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Why Spark for Big Data Analytics ?

What makes Spark suitable for Big Data Analytics ?

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Why Spark for Big Data Analytics ?Following features make Spark, the best fit for Big Data Analytics :Spark simplifies data analysisSpark provides built-in libraries to do advanced analyticsSpark speaks more than one languageSpark provides faster resultsSpark allows you to use different Hadoop vendors

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Word Count Problem - MapReduce

MapReduce Code for a Simple Word Count Problem

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Word Count Problem - SparkSpark Scala Code for Word Count Problem Spark Python Code for Word Count Problem

Clearly processing data with Spark is much easier than MapReduce and Spark gives you the flexibility to choose your favorite language Scala, Java, Python etc.

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Spark is blazingly Fast

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Spark LibrariesSpark SQL : Sparks module for working with structured data

MLlib : Sparks machine learning library

GraphX : Sparks API for graph computation

Spark Streaming : Sparks API to process streaming data

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Spark Multiple Language Support

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Spark in one Snapshot

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Spark Use Cases

Different companies are using Spark for solving various problems e.g. recommendation systems, business intelligence, fraud detection etc.

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Who is using Spark?

A complete list of companies using Spark can be found here : https://cwiki.apache.org/confluence/display/SPARK/Powered+By+Spark

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Spark is here to staySpark is not one of those "here today, gone tomorrow". Spark is here to stay for the foreseeable future, and it is well worth to get your teeth into it in order to get some value out of your data

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Hands-onAnalyzing data with Spark

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ReferencesIBM backs Apache Spark for Big Data Analytics : http://www.forbes.com/sites/paulmiller/2015/06/15/ibm-backs-apache-spark-for-big-data-analytics/

How eBay uses Spark to ignite Data Analytics : http://www.ebaytechblog.com/2014/05/28/using-spark-to-ignite-data-analytics/

Why Cloudera is saying 'Goodbye, MapReduce' and 'Hello, Spark' :http://fortune.com/2015/09/09/cloudera-spark-mapreduce/

5 reasons to turn to Spark for Big Data Analytics : http://www.infoworld.com/article/2897287/big-data/5-reasons-to-turn-to-spark-for-big-data-analytics.html

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