Apache Spark Training in Chandigarh

Apache Spark Training in Chandigarh – webtechlearning provide the best training in Hadoop Spark in Chandigarh, Mohali and Panchkula. 100% practical training with live projects.

Apache Spark developer training

Course Syllabus of Apache Spark:

Hadoop Overview

• Lecture
  • How HDFS read/write the data
  • YARN internal architecture
  • HDFS Internal Architecture .
• Hands-On
  • HDFS Shell Commands
  • Install Hadoop & Spark in Ubuntu
  • Configure hadoop/spark environment in Eclipse

Hive Overview

• Lecture
  • How Hive functioning properly
  • Optimize Hive queries
  • Using Sqoop
• Hands-On
  • Process csv, json data
  • Bucketing, Partitioning tables.
  • Import MySQL/Oracle data using Sqoop

Scala Basics

• Lecture
  • Functional language
  • Scala Vs Java
• Hands-On
  • Strings, Numbers
  • List, Array, Map, Set
  • Control Statements, collections
  • Functions, methods
  • Patren matching

Spark Overview

• Lecture
  • The power of Spark?
  • Spark Ecosystem
  • Spark Components vs Hadoop
• Hands-On
  • Installation & Eclipse configuration
  • Programs in Command line Interface & Eclipse
  • Process Local, HDFS files

RDD Fundamentals

• Lecture
  • Purpose and Structure of RDDs
  • Transformations, Actions, and DAG
  • Key-Value Pair RDDs
• Hands-On
  • Creating RDDs from Data Files
  • Reshaping Data to Add Structure
  • Interactive Queries Using RDDs

SparkSQL and DataFrames

• Lecture
  • Spark SQL and DataFrame Uses
  • DataFrame / SQL APIs
  • Catalyst Query Optimization
• Hands-on
  • Creating (CSV, JSON) DataFrames
  • Querying with DataFrame API and SQL
  • Caching and Re-using DataFrames
  • Process Hive data in Spark

Spark DataSet API

• Lecture
  • Power of Dataset API in Spark 2.0
  • Serialization concept in DataSet
• Hands-on
  • Creating DataSet API
  • Process CSV, JSON, XML, Text data
  • DataSet Operation

Spark Job Execution

• Lecture
  • Jobs, Stages, and Tasks
  • Partitions and Shuffles
  • Broadcast Variables and accumulators
  • Job Performance
• Hands-On
  • Visualizing DAG Execution
  • Observing Task Scheduling
  • Understanding Performance
  • Measuring Memory Usage
  • shared variables usage

Clustering Architecture

• Lecture
  • Cluster Managers for Spark: Spark Standalone, YARN, and Mesos
  • Understanding Spark on YARN
  • What happened in cluster when you submit a job
• Hands-On
  • Tracking Jobs through the Cluster UI
  • Understanding Deploy Modes
  • Submit a sample job and monitor job

Spark Streaming

• Lecture
  • Streaming Sources and Tasks
  • DStream APIs and Stateful Streams
  • Flink Introduction
  • Kafka architecture
• Hands-On
  • Creating DStreams from Sources
  • Operating on DStream Data
  • Viewing Streaming Jobs in the Web UI
  • Sample Flink Streaming program.
  • Kafka sample program

AWS with Spark

• Lecture
  • AWS architecture
  • Redshift, EMR and EC2 functionalities
  • How to minimize AWS cost
• Hands-On
  • Submit a sample jar in AWS Cluster
  • Create a cluster using EMR
  • Read/Write data from Redshift

Advanced concepts in Spark

• Lecture
  • Memory management in Spark
  • How to optimize Spark Applications
  • Spark how to integrate with other Applications
• Hands-On
  • Spark with Cassandra Integration
  • Alluxio/Tachyon hands on experience

Sample Spark Project

• Lecture
  • End to end a project overview
  • Complicated problems in a project
  • Common steps in any project
• Hands-On
  • Implement Spark SQL Mini project
  • Kafka, Cassandra, Spark Streaming project
  • Pull Twitter data and analyse the data

Important notes:

• Daily after training assign a task
• After training provide solution to that problem.
• Minimum 3 months online support & Job Assistance
• Training in Spark 2.x and spark 1.6.2 in Scala language
• Excellent Materials all major spark and Scala books
• Guide to get Cloudera/MapR/Databricks spark certification

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