Apache Spark runs on Hadoop, it is designed for fast computation. It is based on MapReduce and extends and improved the MapReduce model to efficiently use for complex processing

We are providing excellent Apache Spark and Scala training in Chennai by working professionals. This course syllabus is designed to learn Apache Spark from beginner level to in-depth level

Using this course you learn fundamental of Spark and Scala programming language, install and configuration on Spark environment, SparkSQL, Stream Processing, Machine Learning with MLlib and Graph processing using Graphx

Audience

This course is designed for Analytics professional, Data scientists, BI and report professional and Graduates who wants to learn and do their project on Big Data Analytics area

Apache Spark and Scala Training Syllabus

Introduction to Spark

• Understanding Apache Spark
• Limitation of Hadoop
• Stream processing on Spark
• Spark vs Hadoop
• Installing Spark using binaries
• Python installation
• Development environment tool install

Programming model with Spark

• Understanding programming with Spark
• Overview of Spark RDD
• MapReduce and Join programming with Spark
• Creating RDDs
• Operation and methods on RDD
• Spark library stack

Introduction to Scala

• Understanding to Scala
• Feature and Benefit of Scala
• Classes and Objects
• Basic Types and Operations
• Packages and Imports
• Working with Lists
• Stateful Objects

Working with Spark SQL

• Why Spark SQL?
• Concept on SparkSQL
• DataFrame API
• Aggregation in Spark SQL
• Multi-Datasource joining
• Data Catalogs

Spark Data with Python

• Introduction to Python
• Setting up dataset
• Use cases on Data analysis
• Bar chart
• Pie chart
• Scatter plot

Spark Data with Scala

• User cases with Scala
• Write program with Scala

Working with Spark Stream Processing

• Overview of Spark Stream Processing
• Micro batch data processing
• Windowed data processing
• Spark stream processing
• Pie chart
• Scatter plot

Spark Machine Learning

• Overview of Machine Learning
• Concept on Spark Machine Learning
• Wine classification and prediction
• Spam filtering
• ML algorithm
• Model persistence

Spark Machine Learning using MLlib

• Introduction to MLlib
• Create Vector
• Create matrices
• MLlib with regression
• MLlib Classification

Working Spark Graph Processing

• Understanding graphs
• Concept on Spark GraphX programming
• Spark GraphX library
• Understanding GraphFrames
• Graph optimizations

Optimizations and Performance Tuning

• Overview of Optimization
• Memory Optimizing
• Garbage Collection
• Optimizing level of parallelism
• Serialization to improve performance