Big Data Processing with Apache Spark & Scala

IST: 7:00 AM – 08:00 AM, 17th October’14

PDT: 6:30 PM – 7:30 PM, 16th October ’14

Limited seats!! Fill in the form on the right and book your slot today.

Hi all, we are conducting a Free Webinar on Apache Spark and Scala on 18th October’14. The title of the webinar is ‘Big Data Processing with Apache Spark and Scala’. In this webinar, the essential topics regarding Apache Spark and Scala will be discussed. Any queries or doubts can be clarified during the session.

Topics to be Covered:

• What is Big Data?
• What is Spark?
• Why Spark?
• Spark Ecosystem
• A Note about Scala
• Why Scala?
• Hello Spark – Hands on

Why Spark?

Apache Spark is an open-source cluster computing framework for Hadoop community clusters. It qualifies to be one of the best data analytics and processing engines for large-scale data with its unmatchable speed, ease of use, and sophisticated analytics. Following are the advantages and features that make Apache Spark a crossover hit for operational as well as investigative analytics:

• The programs developed over Spark run 100 times faster than those developed in Hadoop MapReduce.
• Spark compiles 80 high-level operators.
• Spark Streaming enables real-time data processing.
• GraphX is a library for graphical computations.
• MLib is the machine learning library for Spark.
• Primarily written in Scala, Spark can be embedded in any JVM-based operational system, at the same time can also be used in REPL (Read, Evaluate, Process and Load) way.
• It has powerful caching and disk persistence capabilities.
• Spark SQL allows it to proficiently handle SQL queries
• Apache Spark can be deployed through Apache Mesos, Yarn in HDFS, HBase, Cassandra, or Spark Cluster Manager (Spark’s own cluster manager).
• Spark simulates Scala’s functional style and collections API, which is a great advantage to Scala and Java developers.

Need for Apache Spark:

Spark is rendering immense benefits to the industry in terms of speed, variety of tasks it can perform, flexibility, quality data analysis, cost-effectiveness, etc., which are the needs of the day. It delivers high-end, real-time big data analytics solutions to the IT industry, meeting the rising customer demand. Real-time analytics leverages business capabilities to heaps. Its compatibility with Hadoop makes it very easy for the companies to quickly adopt it. There is a steep need for Spark-learned experts and developers, as this is a relatively new technology, which is being increasingly adopted. Join our Spark Training and learn more about Apache Spark.