Big data , hadoop and spark

Big data is an important technology as it allows analyzing large amounts of information – both structured and unstructured – quickly. Map Reduce is a paradigm that allows computation to be done in distributed and parallel manner. It is cheaper to run 1000 machine with 1 GB RAM than buying a single 1000 GB machine.

Hadoop is a MapReduce framework that enables processing large datasets in parallel, on clusters of commodity hardware. It’s faster on massive data volumes as data processing is done in parallel. Read more about Hadoop here

Apache Spark can be said as a better version of Hadoop using in-memory operations whenever possible. Spark provides a unified and comprehensive solution to manage numerous big data workloads. It improves the performance and makes speed several times faster as compared to other big data technologies.

Read more about Spark here

Spark has originally been written in Scala programming language and runs on Java Virtual Machine environment (JVM Environment). It supports multiple programming languages for developing applications, these are – Scala, Java, Python, SQL, and R.

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Webinar on Big Data with Scala and Spark
CloudxLab has a free Live Session on Big Data with Scala & Spark. The live session is on Sunday, March 18 @ 8:00pm – 11:00pm IST

Register here:

Topics to be covered:

• What is Big Data & why is it important

• Big Data – examples and applications

• Understanding the Spark architecture

• Overview of Scala Programming Language

• Hands-on demo on cloud-based real-time cluster

For more info