Spark Training

Spark TrainingLycasoft Technologies provides the Best Apache Spark Training in Coimbatore. If you are worried about how to learn Apache Spark then Lycasoft Technologies is the best option for you. Our Apache Spark course starts from the basics of Scala which is required for Apache Spark and at the end of our Apache Spark training program in Coimbatore you will be working on a live Spark project.

Our Apache Spark Certification training program in Coimbatore is designed as 8 sections which are completely hands-on with live project training which will be helpful to enhance your career as a Certified Apache Spark Developer.

Spark provides programmers with an application programming interface centered on a data structure called the resilient distributed dataset (RDD), a read-only multiset of data items distributed over a cluster of machines, that is maintained in a fault-tolerant way. It was developed in response to limitations in the MapReduce cluster computing paradigm, which forces a particular linear dataflow structure on distributed programs.

Spark supports standalone (native Spark cluster), Hadoop YARN, or Apache Mesos. For distributed storage, Spark can interface with a wide variety, including Hadoop Distributed File System (HDFS), MapR File System (MapR-FS), Cassandra, OpenStack Swift, Amazon S3, Kudu, or a custom solution can be implemented.

SECTION 1: INTRODUCTION TO SCALA FOR APACHE SPARK

Learning Objectives – In this module, you will understand the basics of Scala that are required for programming Spark applications. You can learn about the basic constructs of Scala such as variable types, control structures, collections, and more.

  • What is Scala?
  • Why Scala for Spark?
  • Scala in other frameworks
  • Introduction to Scala REPL
  • Basic Scala operations
  • Variable types in Scala
  • Control Structures in Scala
  • For each loop
  • Functions, Procedures, Collections in Scala-Array
  • ArrayBuffer
  • Map, Tuples, Lists, and more.

SECTION 2: OOPS AND FUNCTIONAL PROGRAMMING IN SCALA

Learning Objectives – In this module, you will learn about object-oriented programming and functional programming techniques in Scala.

  • Class in Scala
  • Getters and Setters
  • Custom Getters and Setters
  • Properties with only Getters
  • Auxiliary Constructor
  • Primary Constructor
  • Singletons
  • Companion Objects
  • Extending a Class
  • Overriding Methods
  • Traits as Interfaces
  • Layered Traits
  • Functional Programming
  • Higher Order Functions
  • Anonymous Functions and more.

SECTION3: INTRODUCTION TO BIG DATA AND APACHE SPARK

Learning Objectives – In this module, you will understand what is big data, challenges associated with it and the different frameworks available. The module also includes a first-hand introduction to Spark.

  • Introduction to big data
  • Challenges with big data
  • Batch Vs. Real-Time big data analytics
  • Batch Analytics – Hadoop Ecosystem Overview
  • Real-time Analytics Options
  • Streaming Data- Spark
  • In-memory data- Spark
  • What is Spark?
  • Spark Ecosystem
  • Modes of Spark
  • Spark installation demo
  •  Spark Web UI.ü Spark Standalone cluster üOverview of Spark on a cluster

SECTION 4: SPARK COMMON OPERATIONS

Learning Objectives – In this module, you will learn how to invoke Spark Shell and use it for various common operations.

  • Invoking Spark Shell
  • Creating the Spark Context
  • Loading a file in Shell
  • Performing basic Operations on files in Spark Shell
  • Overview of SBT
  • Building a Spark project with SBT
  • Running Spark project with SBT
  • Local mode
  • Spark mode
  • Caching Overview
  • Distributed Persistence

SECTION 5: PLAYING WITH RDDS

Learning Objectives – In this module, you will learn one of the fundamental building blocks of Spark – RDDs and related manipulations for implementing business logic.

  • RDDs
  • Transformations in RDD
  • Actions in RDD
  • Loading data in RDD
  • Saving data through RDD
  • Key-Value Pair RDD
  • MapReduce and Pair RDD Operations
  • Spark and Hadoop Integration-HDFS
  •  Handling Sequence Files and Partitioner.üSpark and Hadoop Integration-Yarn

SECTION 6: SPARK STREAMING AND MLB

Learning Objectives – In this module, you will learn about the major APIs that Spark offers. You will get an opportunity to work on Spark streaming which makes it easy to build scalable fault-tolerant streaming applications, MLlib which is Spark’s machine learning library.

  • Spark Streaming Architecture
  • First Spark Streaming Program
  • Transformations in Spark Streaming
  • Fault tolerance in Spark Streaming
  • Checkpointing
  • Parallelism level
  • Machine learning with Spark
  • Data types
  • Algorithms– statistics
  • Classification and regression
  • Clustering
  • Collaborative filtering

SECTION 7: GRAPHX, SPARQL AND PERFORMANCE TUNING IN SPARK

Learning Objectives – In this module, you will learn about Spark SQL that is used to process structured data with SQL queries, graph analysis with Spark, GraphX for graphs and graph-parallel computation. You will also0 get a chance to learn the various ways to optimize performance in Spark.

  • Analyze Hive and Spark SQL architecture
  • SQLContext in Spark SQL
  • Working with DataFrames
  • Implementing an example for Spark SQL
  • Integrating hive and Spark SQL
  • Support for JSON and Parquet File Formats
  • Implement data visualization in Spark
  • Loading of data
  • Hive queries through Spark
  • Testing tips in Scala
  • Performance tuning tips in Spark
  • Shared variables: Broadcast Variables
  • Shared Variables: Accumulators.

SECTION 8: A COMPLETE PROJECT ON APACHE SPARK

Learning Objectives – In this module, you will get an opportunity to work on a live Spark project where you can implement the learnings from previous modules hands-on, and solve a real-time use case. Problem Statement: Design a system to replay the real-time replay of transactions in HDFS using Spark.
Technologies used:

  • Spark Streaming
  • Kafka (for messaging)
  • HDFS (for storage)
  • Core Spark API (for aggregation)

Spark Course Features

Apache Spark is lightning fast, in-memory data processing engine. Spark is mainly designed for data science and the abstractions of Spark make it easier. Apache Spark provides high-level APIs in Java, Scala, Python and R. It also has an optimized engine for general execution graph. In data processing, Apache Spark is the largest open source project.

Since Apache Spark was maintained by a non-profit corporation called Apache Software Foundation, there is no official certification for Apache Spark. However, there are other industry-standard certifications available. Our training covers all the relevant information needed to clear any certification related to Apache Spark. Some of the certifications are

  •   Databricks Certified Spark Developer
  •   CCA Spark and Hadoop Developer
  •   Hortonworks Certified Spark Developer

And Scala was maintained by Scala center (not-for-profit center at EPFL) and Lightbend Inc. (a company created to provide commercial support, training, and services for Apache Spark and Scala). So, there are no official certifications available for Scala till now.

However, when you are studying at the best Apache Spark and Scala training institute in Coimbatore, you don’t have to worry about certification to get a job or propel your career. Our training will help you develop your own projects in both Apache Spark and Scala which will validate your skills and make a strong case for your selection at the recruitment process. And our placement training will ensure that all our students have got a great job as soon as they complete our training. This is one of the benefits of studying at the best Apache Spark and Scala training institute in Coimbatore.

View our student’s reviews here

Quick Enquiry

ExperiencedFresher