Class Room Training Apache Spark crash course on 25th and 26th November

Class Room Training Apache Spark crash course on 25th and 26th November

 

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About The Event

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Course Content:

 SPARK - Basic & Advanced

 SPARK  with SCALA

 * Scala overview

 * Introducing Scala

* Journey – Java to Scala

* What is Scala?

* Why Scala?

 * Scala Installation

* Execution Mechanisms

 * Scala in interactive mode

* Scala Scripts

 * Scala Advanced programming

 * Defining Functions

 SPARK - Python

 * SPARK - Python overview

 * What is Python?

* Why Python?

 * How to use PYSPARK?

* Advantages of Python in SPARK

* Web scraping using Python

* Handling high volume unstructured data using Python

* Generating huge volumes (10 crore + records) using Python

 SPARK

 * Spark overview

 * What is Spark?

* Why Spark?

* Linking with Spark

* Initializing Spark

* Using the Shell

 * Spark Installation

* Resilient Distributed Datasets (RDDs)

 * Parallelized Collections

* External Datasets

* RDD Operations

* Basics, Passing Functions to Spark

* Working with Key-Value Pairs

* Transformations

 * RDD Persistence

 * Which Storage Level to Choose?

* Removing Data

* Shared Variables

* Broadcast Variables

* Accumulators

 * SPARK Streaming

 * What is Spark Streaming

* Why we need Spark Streaming

* Differences between SPARK Streaming Vs Flume Vs Kafka

* Dynamic memory allocation of Streaming

* Configuration and settings for Streaming path and sources

 * Spark SQL

 * Why Spark SQL

* Integrating SPARK SQL with RDBMS

* Performance considerations using SPARK SQL

* Integrating unstructured sources to SPARK SQL

* RDD usage in SPARK SQL

 * SPARK GRAPHX

 * What is Spark GraphX

* How to create connected Data Structures

* Develop your first DATA GRAPGH

* Using RDD's and SPARK SQL as input

* Handling complex DATA GRAPHS

 * SPARK R

 * What is R?

* How to work on scientific calculations using SPARK R

* How to execute Statistical operations using SPARK R

 

Expert Faculty with 20years experience 

 

 

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