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SPARK & SCALA
Apache Spark with Scala Online Training by experts from Industry
Scala Essentials | Traits and OOPs in Scala |Functional Programming in Scala
Introduction to Big Data and Spark | Spark Baby Steps | Playing with RDDs
Shark – When Spark meets Hive ( Spark SQL) | Spark Streaming
Spark Mlib | Spark GraphX | Project and Installation
1043 Satisfied Learners
SPARK & SCALA TRAINING IN PUNE
Spark & Scala Online Training with 15+ years Experienced Faculty
Duration of Spark Scala Training : 32 hrs
Batch type : Weekdays/Weekends
Mode of Training : Classroom/Online/Corporate Training
Spark & Scala Online Training & Certification in Pune
Realtime Projects, Scenarios & Assignments
Why Radical Technologies
100% Placement Guarantee for the Right Candidate
10+ Years Real Time Experienced Trainers
Learn from Industry Experts, Hands-on labs
Flexible Options: online, instructor-led, self-paced
14+ Years of Industry Recognitions
1 Lakh+ Students Trained
50,000+ Students Placed
Guaranteed 5+ Interview Calls
Top MNCs - Associated with 800+ Recruiters
Free Internship Project & Certification
Monthly Job Fair - Virtual as well as Physica
5000+ Reviews & Ratings
COURSE CONTENT :
Module 1 :
Introduction to Scala
Learning Objectives – In this module, you will understand basic concepts of Scala,
motives towards learning a new language and get your set-up ready.
Topics
- Why Scala?
- What is Scala?
- Introducing Scala
- Installing Scala
- Journey – Java to Scala
- First Dive – Interactive Scala
- Writing Scala Scripts – Compiling Scala Programs
- Scala Basics
- Scala Basic Types
- Defining Functions
- IDE for Scala, Scala Community
Module 2 :
Scala Essentials
Learning Objectives – In this module, you will learn essentials of Scala that are
needed to work on it.
Topics
- Immutability in Scala – Semicolons
- Method Declaration, Literals
- Lists
- Tuples
- Options
- Maps
- Reserved Words
- Operators
- Precedence Rules
- If statements
- Scala For Comprehensions
- While Loops
- Do-While Loops
- Conditional Operators
- Pattern Matching
- Enumerations
Module 3 :
Traits and OOPs in Scala
Learning Objectives – In this module, you will understand implementation of OOPs
concepts in Scala and use Traits as Mixins
Topics
- Traits Intro – Traits as Mixins
- Stackable Traits
- Creating Traits Basic OOPS – Class and Object Basics
- Scala Constructors
- Nested Classes
- Visibility Rules
Module 4 :
Functional Programming in Scala
Learning Objectives – In this module, you will understand functional programming
know how for Scala.
Topics
- What is Functional Programming?
- Functional Literals and Closures
- Recursion
- Tail Calls
- Functional Data Structures
- Implicit Function Parameters
- Call by Name
- Call by Value
Module 5 :
Introduction to Big Data and Spark
Learning Objectives – In this module, you will understand what is Big Data, it’s
associated challenges, various frameworks available and will get the first hand introduction
to Spark
Topics
- 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 – Storm
- In Memory Data – Spark
- What is Spark?
- Modes of Spark
- Spark Installation Demo
- Overview of Spark on a cluster
- Spark Standalone Cluster
Module 6 :
Spark Baby Steps
Learning Objectives – In this module, you will learn how to invoke Spark shell and
use it for various common operations.
Topics
- Invoking Spark Shell
- Loading a File in Shell
- Performing Some Basic Operations on Files in Spark Shell
- Building a Spark Project with sbt, Building and Running Spark Project with sbt
- Caching Overview, Distributed Persistence
- Spark Streaming Overview
- Example: Streaming Word Count
Module 7 :
Playing with RDDs
Learning Objectives – In this module, you will learn one of the building blocks of
Spark – RDDs and related manipulations for implementing business logics.
Topics
- RDDs
- Transformations in RDD
- Actions in RDD
- Loading Data in RDD
- Saving Data through RDD
- Scala and Hadoop Integration Hands on
Module 8 :
Shark – When Spark meets Hive ( Spark SQL)
Learning Objectives – In this module, you will see various offspring’s of Spark like
Shark, SparkSQL and Mlib. This session is primarily interactive for discussing industrial use
cases of Spark and latest developments happening in this area.
Topics
- Why Shark?
- Installing Shark
- Running Shark
- Loading of Data
- Hive Queries through Spark
- Testing Tips in Scala
- Performance Tuning Tips in Spark
- Shared Variables: Broadcast Variables
- Shared Variables: Accumulators
Module 9 :
Spark Streaming
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.
Topics
- Spark Streaming Architecture
- First Spark Streaming Program
- Transformations in Spark Streaming
- Fault tolerance in Spark Streaming
- Check pointing
- Parallelism level
Module 10 :
Spark Mlib
Learning Objectives – In this module, you will learn about the machine learning
concepts in Spark
Topics
- Classification Algorithm
- Clustering Algorithm
- Sequence Mining Algorithm
- Collbrative filtering
Module 11 :
Spark GraphX
Learning Objectives – In this module, you will learn about Graph Analysis concepts in
Spark
Topics
- Graph analysis with Spark
- GraphX for graphs
- Graph-parallel computation
Module 12 :
Project and Installation
Topics
- Installation of Spark and Scala
- Discussion of real time use cases using Spark
- Mini project implementation in Spark
Student Stories and Reviews :
FAQs :
Apache Spark is an open-source, distributed computing system that provides an interface for programming entire clusters with implicit data parallelism and fault tolerance. Learning Apache Spark enhances your ability to handle big data, perform data processing, and implement machine learning algorithms efficiently. This makes it a valuable skill in the data engineering and data science fields.
The Apache Spark with Scala Course at Radical Technologies covers core Spark concepts, Spark SQL, Spark Streaming, and Spark Machine Learning. It also includes hands-on exercises and projects to ensure practical understanding and experience.
Apache Spark Training can significantly benefit your career by providing you with in-demand big data skills, making you a valuable asset for companies that handle large-scale data processing and analytics. It can open doors to roles such as Data Engineer, Data Scientist, and Big Data Developer.
Apache Spark Training focuses on teaching the practical skills needed to use Spark effectively, including theoretical concepts and hands-on practice. Spark Certification, on the other hand, is an official recognition that validates your expertise and knowledge in using Apache Spark.
Yes, basic programming knowledge is required. Familiarity with Scala is beneficial but not mandatory, as the course will cover Scala basics as part of the training.
Obtaining a Spark Certification demonstrates your expertise in Apache Spark, making you more competitive in the job market. It can lead to higher salaries, job promotions, and recognition as a skilled professional in big data analytics.
The Spark Machine Learning component of the course equips you with the skills to build and deploy scalable machine learning models, which are crucial for tasks such as predictive analytics, recommendation systems, and data-driven decision-making in real-world applications.
Yes, Radical Technologies offers Spark Training Online, allowing you to learn at your own pace from anywhere. This includes live instructor-led sessions, recorded lectures, and access to a virtual lab environment.
The Apache Spark Course includes practical projects such as data processing with Spark SQL, real-time data streaming, and implementing machine learning algorithms using Spark MLlib. These projects provide hands-on experience with real-world data scenarios.
The duration of the Apache Spark with Scala Course varies depending on the format (online or in-person) and the intensity of the schedule. Typically, it ranges from 4 to 6 weeks.
Yes, Radical Technologies offers job assistance, including resume building, interview preparation, and connecting you with potential employers, to help you secure a job in the field of big data.
Radical Technologies is considered the best choice due to its comprehensive curriculum, experienced instructors, practical training approach, and strong industry connections that provide excellent job placement opportunities.
Yes, having a basic understanding of programming languages, particularly Scala, and familiarity with big data concepts are recommended prerequisites for the Apache Spark Developer Certification.
The Advanced Spark Training delves deeper into complex topics such as optimization techniques, advanced data processing, and real-time analytics, offering a more comprehensive understanding for experienced professionals.
During the Spark Online Classes, you will have access to live instructor support, discussion forums, and a virtual lab environment to practice and resolve queries in real-time.
Scala is used as the primary programming language for developing Spark applications in this course. The curriculum includes learning Scala syntax, functional programming concepts, and using Scala to interact with Spark’s APIs.
After completing the Apache Spark with Scala Training, you can pursue roles such as Big Data Engineer, Data Scientist, Data Analyst, and Spark Developer, among others in the data engineering and analytics domains.
The Spark Certification Courses enhance your data analytics skills by teaching you how to process large datasets efficiently, perform advanced data analysis, and build scalable machine learning models using Apache Spark.
The Apache Spark Online Course materials include lecture slides, video recordings, hands-on lab exercises, assignments, and access to a virtual lab for practical experience.
Learning Scala is important for working with Apache Spark because Spark is written in Scala, and using Scala provides seamless integration with Spark’s APIs. It also offers concise syntax and powerful functional programming features that are advantageous for big data processing.
Most Probable Interview Questions for Hadoop Admin
Interview Question No. 1 for Apache Spark with Scala : What are the core components of Apache Spark and their functions?
Interview Question No. 2 for Apache Spark with Scala : How does Apache Spark’s RDD (Resilient Distributed Dataset) work?
Interview Question No. 3 for Apache Spark with Scala : Explain the difference between Spark SQL and Spark DataFrames
Interview Question No. 4 for Apache Spark with Scala : What are the key benefits of using Scala with Apache Spark?
Interview Question No. 5 for Apache Spark with Scala : How does Spark Streaming handle real-time data processing?
Interview Question No. 6 for Apache Spark with Scala : Can you describe the architecture of Apache Spark?
Interview Question No. 7 for Apache Spark with Scala : What is a Spark Executor, and what role does it play in a Spark application?
Interview Question No. 8 for Apache Spark with Scala : How do you optimize Spark jobs for better performance?
Interview Question No. 9 for Apache Spark with Scala : Explain the concept of lazy evaluation in Apache Spark
Interview Question No. 10 for Apache Spark with Scala : What are the differences between Spark’s transformations and actions?
Interview Question No. 11 for Apache Spark with Scala : How do you handle memory management in Spark?
Interview Question No. 12 for Apache Spark with Scala : What is the role of the Catalyst optimizer in Spark SQL?
Interview Question No. 13 for Apache Spark with Scala : Describe how Spark integrates with Hadoop and HDFS
Interview Question No. 14 for Apache Spark with Scala : How does Apache Spark handle fault tolerance?
Interview Question No. 15 for Apache Spark with Scala : What are the different cluster managers supported by Spark, and how do they differ?
Interview Question No. 16 for Apache Spark with Scala : Explain the process of setting up a Spark environment on a local machine
Interview Question No. 17 for Apache Spark with Scala : How do you implement machine learning algorithms using Spark MLlib?
Interview Question No. 18 for Apache Spark with Scala : Describe the process of debugging and monitoring Spark applications
Interview Question No. 19 for Apache Spark with Scala : What are broadcast variables and accumulators in Spark, and how are they used?
Interview Question No. 20 for Apache Spark with Scala : How would you handle skewed data in a Spark application to ensure balanced processing?
Learn Apache Spark with Scala – Course in Pune with Training, Certification & Guaranteed Job Placement Assistance!
Welcome to Radical Technologies, the premier institute in Pune for mastering Apache Spark with Scala. We are dedicated to providing top-notch training, certification, and job assistance in this cutting-edge technology.
Most Probable Interview Questions for Apache Spark with Scala
- Comprehensive Curriculum : Our courses cover everything from the basics to advanced topics in Apache Spark and Scala. Whether you are a beginner or looking to deepen your knowledge, our curriculum is designed to meet your needs.
- Expert Instructors : Learn from industry veterans with extensive experience in Apache Spark and Scala. Our instructors are dedicated to helping you understand complex concepts and apply them in real-world scenarios.
- Certification and Job Assistance : Gain industry-recognized certifications that enhance your resume and open up new career opportunities. We also offer robust job assistance to help you land your dream job in the tech industry.
- Flexible Learning Options : Choose from online classes, in-person training in Pune, or a combination of both. Our flexible schedules and learning modes ensure that you can balance your education with your other commitments.
- Hands-on Training : Engage in practical, hands-on projects that give you real-world experience. Our training programs emphasize practical application, ensuring that you are job-ready upon completion.
Why Apache Spark with Scala?
Apache Spark with Scala is one of the most sought-after skills in the big data industry. This combination allows for rapid data processing and analysis, making it essential for data engineers, data scientists, and developers. By mastering Apache Spark with Scala, you position yourself at the forefront of big data technology, ready to tackle the most challenging data problems.
Join Us
Join Radical Technologies and embark on a journey to become an expert in Apache Spark with Scala. Whether you aim to advance your career, shift into a new role, or simply expand your skill set, our courses are designed to help you achieve your goals. Enroll today and take the first step towards a brighter future in the world of big data and analytics.
For more information, visit our website or contact us directly. Let Radical Technologies be your partner in professional growth and success.
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DataQubez University creates meaningful big data & Data Science certifications that are recognized in the industry as a confident measure of qualified, capable big data experts. How do we accomplish that mission? DataQubez certifications are exclusively hands on, performance-based exams that require you to complete a set of tasks. Demonstrate your expertise with the most sought-after technical skills. Big data success requires professionals who can prove their mastery with the tools and techniques of the Hadoop stack. However, experts predict a major shortage of advanced analytics skills over the next few years. At DataQubez, we’re drawing on our industry leadership and early corpus of real-world experience to address the big data & Data Science talent gap.
How To Become Certified Apache – Spark Developer
Certification Code – DQCP – 504
Certification Description – DataQubez Certified Professional Apache – Spark Developer
Exam Objectives
Configuration :-
Define and deploy a rack topology script, Change the configuration of a service using Apache Hadoop, Configure the Capacity Scheduler, Create a home directory for a user and configure permissions, Configure the include and exclude DataNode files
Troubleshooting :-
Demonstrate ability to find the root cause of a problem, optimize inefficient execution, and resolve resource contention scenarios, Resolve errors/warnings in Hadoop Cluster, Resolve performance problems/errors in cluster operation, Determine reason for application failure, Configure the Fair Scheduler to resolve application delays, Restart an Cluster service, View an application’s log file, Configure and manage alerts, Troubleshoot a failed job
High Availability :-
Configure NameNode, Configure ResourceManager, Copy data between two clusters, Create a snapshot of an HDFS directory, Recover a snapshot, Configure HiveServer2
Data Ingestion – with Sqoop & Flume :-
Import data from a table in a relational database into HDFS, Import the results of a query from a relational database into HDFS, Import a table from a relational database into a new or existing Hive table, Insert or update data from HDFS into a table in a relational database, Given a Flume configuration file, start a Flume agent, Given a configured sink and source, configure a Flume memory channel with a specified capacity
Data Processing through Spark & Spark SQL& Python :-
Frame big data analysis problems as Apache Spark scripts, Optimize Spark jobs through partitioning, caching, and other techniques, Develop distributed code using the Scala programming language, Build, deploy, and run Spark scripts on Hadoop clusters, Transform structured data using SparkSQL and DataFrames
Recomandtion Engine using Spark MLLIB & Python :-
Using MLLib to Produce Recomandation Engine, Run Page rank algorithem, using dataframes with mllib, Machine Learning with Spark
Stream Data Processing using Spark Streaming& Python :-
Process Stream Data using spark streaming.
Regression with Spark& Python:-
Introduction to Linear Regression, Introduction to Regression Section, Linear Regression Documentation Alternate Linear Regression Data CSV File, Linear Regression Walkthrough , Linear Regression Project
For Exam Registration of Apache – Spark Developer, Click here:
Spark&Scala trainer is having 17 year experience in IT with 10 years in data warehousing &ETL experience. It has been six years now that he has been working extensively in BigData ecosystem tool sets for few of the banking-retail-manufacturing clients. He is a certified HDP-Spark Developer and Cloudera certified Hbase specialist. He also have done corporate sessions and seminars both in India and abroad. Recently he was engaged by Pune University for 40 hour sessions on BigData analytics to the senior professors of Pune.
All faculties at our organization are currently working on the technologies in reputed organization. The curriculum that is imparted is not just some theory or talk with some PPTs. We absolutely frame the forum in such a way so that at the end the lessons are imparted in easy language and the contents are well absorbed by the candidates. The sessions are backed by hands-on assignment. Also that the faculties are industry experience so during the course he does showcase his practical stories.
- Spark & Scala Training By 17+ Years experienced Real Time Trainer
- A pool of 200+ real time Practical Sessions on Spark & Scala
- Scenarios and Assignments to make sure you compete with current Industry standards
- World class training methods
- Training until the candidate get placed
- Certification and Placement Support until you get certified and placed
- All training in reasonable cost
- 10000+ Satisfied candidates
- 5000+ Placement Records
- Corporate and Online Training in reasonable Cost
- Complete End-to-End Project with Each Course
- World Class Lab Facility which facilitates I3 /I5 /I7 Servers and Cisco UCS Servers
- Covers Topics other than from Books which is required for the IT Industry
- Resume And Interview preparation with 100% Hands-on Practical sessions
- Doubt clearing sessions any time after the course
- Happy to help you any time after the course
ML and GraphX ,’R’ Language
Data Analytics / Science
Cloudera Certified Professional (CCP)
CCP Data Engineer
