About the Course
Following are the listed Course Objectives
You will be eligible for the following criteria after completing Apache Spark & Scala course
1) Understand the role of RDDs in Spark.
2) Stream data using Spark Streaming API.
3) Understand Scala and its implementation.
4) Analyze Hive and Spark SQL architecture.
5) Get an insight into the big data challenges.
6) Understand functional programming in Scala.
7) Master the concepts of Traits and OOPS in Scala.
8) Implement Spark applications on YARN (Hadoop).
9) Learn how Spark acts as a solution to these challenges.
10) Apply Control Structures, Loops, Collection, and more.
11) Understand GraphX API and implement graph algorithms.
12) Install Spark and implement Spark operations on Spark Shell.
13) Implement SparkSQL queries to perform several computations.
14) Implement machine learning algorithms in Spark using MLlib API.
15) Implement Broadcast variable and Accumulators for performance tuning.
This course is a foundation to anyone who wants to begin the field of big data and want to be up-to-date with the latest developments around the quick and effective processing of ever-growing data using Spark and related projects. This course is eligible for:
1. Big Data enthusiasts
2. Software architects, engineers and developers
3. Data Scientists and analytics professionals
Analyzing the data for better business insights can be done perfectly through Apache Spark and this is one of the important reasons to learn the Spark. Though there are other alternatives for Big Data processing like Hadoop, Storm, etc, Spark is the evolution in this field as it provides streaming ability and this made every business choose Apache spark for rapid data analysis.
Also, Apache Spark is much simpler than MapReduce and other Big Data frameworks. The Big Data problems which cannot be solved by MapReduce can be easily solved by Spark.
1. Introduction to Scala for Apache Spark
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, Foreach loop, Functions, Procedures, Collections in Scala- Array, ArrayBuffer, Map, Tuples, Lists.
- OOPS and Functional Programming in Scala
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
- Introduction to Big Data and Apache Spark
In this module, you will understand about 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, overview of Spark on a cluster
- Spark Standalone cluster, Spark Web UI
- Spark Common Operations
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
- Playing with RDDs
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
- Spark and Hadoop Integration-Yarn
- Handling Sequence Files, Partitioner.
- Spark Streaming and MLlib
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,
- Check pointing
- Parallelism level, machine learning with Spark, data types,
- Algorithms – statistics, classification and regression, clustering, collaborative filtering.
- GraphX, SparkSQL and Performance Tuning in Spark
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
- A complete project on Apache Spark
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.
Design a system to replay the real time replay of transactions in HDFS using Spark.
- Spark Streaming
- Kafka (for messaging)
- HDFS (for storage)
- Core Spark API (for aggregation)
Benefits of Learning Apache Spark:
Why Root2learn for Apache Spark Certification Training?
Live Online sessions:
Classroom and Online Training:
A course without a certification has no value in the current situation. So, we always offer the courses with certification which is like a standard support from us. The Apache spark training certificate has a great value and there are more chances for you to get a job when compared to other candidates who have no certification.
The candidates who want to advance their career in Big Data can learn the Apache Spark training online and this is the course that will be helpful for Software Engineers, Project Managers, BI, ETL, Data warehousing professionals, Business Analysts, Architects, Mainframe and Testing professionals, DBAs, and any other candidates who want to start their career in Apache Spark.
- Associate Project Managers
- Project Managers
- IT Project Managers
- Project Coordinators
- Project Analysts
- Project Leaders
- Senior Project Managers
- Team Leaders
- Product Managers
- Program Managers
- Project Sponsors
- Project Team Members seeking PMP or CAPM certification.
How do you provide online training ?
The training would be provided over a web platform. It is the most demanded & modernized way of “Instructor Led Training” without the need for expensive travelling that can be attended from anywhere in the world. You can attained from your home.
Which option do I choose for training, Virtual or classroom training?
You can decide which one suitable for you:
|LessÂ Expensive||More Expensive|
|Recorded video of same session to refer in future||No, recorded video|
|Can attain from any place, internet ( 512 KBPS speed) and System required||Need to go at training venue|
|Can attain from home or office or from other country||No, have to stay in same city|
|Interactive session||Interactive session|
|Interaction with global professionals||Mostly local professionals|
|Flexi class pass, can attain as many class want in same fee||One class|
|If miss any class can go through same training video to connect in next session, and ask if have any query or can attain in any batch||If miss the class, will not able to attain same session|
|Gradually learning ( as training will go near about one month, so you can prepare with training) will get enough time to revise covered topics||Some training will finished in 4 days, or within one week. So it will be more load and will not have enough time to revise covered topics|
|Highly expected trainer ( 23 years, 6 years training experience)||May be have experienced trainer|
|Demo session ( past recorded video)||Not available|
What is Virtual classroom training?
Virtual classroom training for Big data and Hadoop is training conducted via online live streaming of a class. The classes are conducted by a Certified trainer with more than 20 years of work and training experience. It is interactive session, you can asked the question to trainer and will also ask the question. it is one to one interaction. It is video conference type of training.
Is this live training, or will I watch pre-recorded videos?
All the classes are live. They are interactive sessions that enable you to ask questions and participate in discussions during the class time. We do, however, provide recordings of each session you attend for your future reference.
What tools do I need to attend the training sessions?
- Windows: any version newer than Windows XP SP3
- Mac: any version newer than OSX 10.6
- Internet speed: Preferably faster than 512 Kbps
- Headset, speakers, microphone: You’ll need headphones or speakers to hear clearly, as well as a microphone to talk to the others. You can use a headset with a built-in microphone, or separate speakers and microphone.
Where is the training held?
There is no training venue for Virtual classroom training. It is online live training you can attained from your home by login at your system, for that we will provide you login id and password.
For classroom training you will get email at your registered email id as per your location.
What is 100% training quality guarentee?
If you are not happy with our training quality, inform us within 1st half of Training on First Day. We will refund your entire training fee with 7 working days.