Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Spark for big data analytics


Published on

Big Data Analytics with Spark

Published in: Technology
  • Be the first to comment

Spark for big data analytics

  1. 1. Data Analytics with Spark
  2. 2. What will you learn today ?  What is Apache Spark ?  How Spark fits into Hadoop Ecosystem ?  Why Spark for Big Data Analytics ?  Spark’s popularity  Hands-On : Analyzing data with Spark
  3. 3. 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
  4. 4. 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
  5. 5. Why Spark for Big Data Analytics ? What makes Spark suitable for Big Data Analytics ?
  6. 6. Why Spark for Big Data Analytics ? Following features make Spark, the best fit for Big Data Analytics :  Spark simplifies data analysis  Spark provides built-in libraries to do advanced analytics  Spark speaks more than one language  Spark provides faster results  Spark allows you to use different Hadoop vendors
  7. 7. Word Count Problem - MapReduce MapReduce Code for a Simple Word Count Problem
  8. 8. Word Count Problem - Spark Spark 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.
  9. 9. Spark is blazingly Fast
  10. 10. Spark Libraries  Spark SQL : Spark’s module for working with structured data  MLlib : Spark’s machine learning library  GraphX : Spark’s API for graph computation  Spark Streaming : Spark’s API to process streaming data
  11. 11. Spark Multiple Language Support
  12. 12. Spark in one Snapshot
  13. 13. Spark Use Cases Different companies are using Spark for solving various problems e.g. recommendation systems, business intelligence, fraud detection etc.
  14. 14. Who is using Spark? A complete list of companies using Spark can be found here :
  15. 15. Spark is here to stay Spark 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
  16. 16. Hands-on Analyzing data with Spark
  17. 17. References IBM backs Apache Spark for Big Data Analytics : How eBay uses Spark to ignite Data Analytics : Why Cloudera is saying 'Goodbye, MapReduce' and 'Hello, Spark' : 5 reasons to turn to Spark for Big Data Analytics :
  18. 18. Survey Your feedback is vital for us, be it a compliment, a suggestion or a complaint. It helps us to make your experience better! Please spare few minutes to take the survey after the webinar.
  19. 19. Thank You … Questions/Queries/Feedback Recording and presentation will be made available to you within 24 hours