Spark Training In Chennai

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Apache Spark is created for in-memory computing for lightning speed processing of applications. Apache Spark is basically a processing engine built with the objective of quicker processing, ease of use and better analytics. Spark is a better alternative to Map Reduce where large amount of data can be processed with much lower latency than Map Reduce. Apache Spark supports Java, Python APIs and Scala unlike Map Reduce that supports only Java.

Spark can access diverse data sources like Amazon S3, No SQL databases like Cassandra, HBase and Hadoop Distributed File System.

Course Objective

Students will:
Understand purpose of using Spark
Use Resilient Distributed Datasets operations
Use Java to create and run a Spark applications practically
Create applications using Spark SQL, MLlib, Spark Streaming and GraphX
Configure Spark Applications
Monitor Spark Applications
Tune Spark Applications

Prerequisite

Good understanding of Hadoop Fundamentals is needed. Please talk to our Student counselor to customize Spark Training in Chennai with Hadoop Fundamentals if you are new to Hadoop

Target Audience

Spark training intended for anyone who aspires to get into the field of Big Data and lightning speed processing of Big Data

Big Data and Hadoop Enthusiasts

Software Architects, Engineers and Developers with background in any programming languages like Java, Dot Net, PHP, Python or Scala

Data Scientists and Analytics Professionals

Course Agenda

Module 1: Getting Familiar with Spark

Apache Spark in Big Data Landscape and purpose of Spark
Apache Spark vs. Apache MapReduce
Components of Spark Stack
Downloading and installing Spark
Launch Spark

Module 2: Working with Resilient Distributed Dataset (RDD)

Transformations and Actions in RDD
Loading and Saving Data in RDD
Key-Value Pair RDD
MapReduce and Pair RDD Operations
Playing with Sequence Files
Using Partitioner and its impact on performance improvement

Module 3: Spark Application Programming

Master SparkContext
Initialize Spark with Java
Create and Run Real time Project with Spark
Pass functions to Spark
Submit Spark applications to the cluster

Module 4: Spark Libraries

Module 5: Spark configuration, monitoring, and tuning

Understand various components of Spark cluster
Configure Spark to modify
Spark properties
environmental variables
logging properties
Visualizing Jobs and DAGs
Monitor Spark using the web UIs, metrics, and external instrumentation
Understand performance tuning requirements

Module 6: Spark Streaming

Understanding the Streaming Architecture - DStreams and RDD batches
Receivers
Common transformations and actions on DStreams

Module 7: MLlib and GraphX

Spark Documentation and Resources

FITA is leading Spark Training Institute in Chennai offering training on Spark and Hadoop - trainings are offered by experienced Hadoop data scientists. Call Us @ 98404-11333 to know more about spark training.

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