Table of Contents
ToggleApache Spark Training in Hyderabad
Batch Details
Trainer Name | Mr. Venkatesh (Certified Trainer) |
Trainer Experience | 15+ Years |
Next Batch Date | 19-03-2025 (8:00 AM IST) |
Training Modes: | Online Training (Instructor Led) |
Course Duration: | 30 Days |
Call us at: | +91 81868 44555 |
Email Us at: | brollyacademy@gmail.com |
Demo Class Details: | ENROLL FOR A FREE DEMO CLASS |
Apache Spark Course Curriculum
Course Contents
- Introduction To Spark and Hadoop Platform
- Overview of Apache Hadoop
- Overview of Apache Spark
- Data, Locality, Ingestion and Storage
- Analysis and Exploration
- Other Ecosystem Tools
- Functional Programing Vs Object Orient Programing
- Scalable Language
- Overview of Scala
- Getting Started With Scala
- Scala Background, Scala Vs Java and Basics
- Running the Program with Scala Compiler
- Explore the Type Lattice and Use Type Inference
- Define Methods and Pattern Matching
- Ubuntu 14.04 LTS Installation VMware Player
- Installing Hadoop
- Apache Spark, JDK-8, Scala and SBT Installation
- Why we need HDFS
- Apache Hadoop Cluster Components
- HDFS Architecture
- Failures of HDFS 1.0
- Reading and Writing Data in HDFS
Fault Tolerance
- Configuring Apache Spark
- Scala Setup on Windows and UNIX
- Java Setup
- SCALA Editor
- Interprepter
- Compiler
- Benefits of Scala
- Language Offerings
- Type Inferencing
- Variables, Functions and Loops
- Control Structures
- Vals, Arrays, Lists, Tuples, Sets, Maps
- Traits and Mixins
- Classes and Objects
- First class Functions
- Clousers, Inheritance, Sub classes, Case Classes
- Modules, Pattern Matching, Exception Handling, FILE Operations
- Batch Versus Real-time Data Processing
- Introduction to Spark, Spark Versus Hadoop
- The Architecture of Spark
- Coding Spark Jobs in Scala
- Exploring the Spark Shell to Creating Spark Context
- RDD Programming
- Operations on RDD
- Transformations and Actions
- Loading Data and Saving Data
- Key Value Pair RDD
- Spark Streaming
- MLlib
- GraphX
- Spark SQL
- What is Apache Spark?
- Starting the Spark Shell
- Getting Started with Datasets and Data Frames
- Data Frame Operations
- Apache Spark Overview and Architecture
- RDD Overview
- RDD Data Sources
- Creating and Saving RDDs
- RDD Operations
- Transformations and Actions
- Converting Between RDDs and Data Frames
- Key-Value Pair RDDs
- Map-Reduce Operations
- Overview About Spark Documentation
- Initializing Spark Job
- Create Resilient Distributed Data Sets
- Previewing Data from RDD
- Transformations Overview
- Level Transformations Using Map and Flat Map
- Filtering the Data
- Inner Join and Outer Join
- Writing a Spark Application
- Building and Running an Application
- Application Deployment Mode
- The Spark Application Web UI
- Configuring Application Properties
- RDD Partitions
- Stages and Tasks
- Job Execution Planning
- Data Frame and Dataset Persistence
- Persistence Storage Levels
- Viewing Persisted RDDs
- Difference Between RDD, Data Frame and Dataset
- Common Apache Spark
- Different Interfaces to Run Hive Queries
- Create Hive Tables and Load Data in Text File Format & ORC File Format
- Using Spark-Shell to Run Hive Queries or Commands
Apache Spark Training in Hyderabad
Key Points
- Get advanced Apache Spark training from experienced trainer with 9+ Years of experience in the field of Apache Spark
- Brolly Academy trained more than 300 students and placed more than 150 of them In the last 4 months
- Master the concepts of Machine Learning libraries (Mllib), Spark Core, Spark SQL, Spark RDD, Spark GraphX, etc. to analyze real-time data
- Learn how to design and manage Spark cluster
- Understand the core concepts of Scala programming with hands-on projects and clear the Cloudera Certification Exam
- Understand the concepts of Apache Spark Databricks and Databricks Visualisation with our expert guidance
- Learn how to complete a project using basic Spark DataFrame tasks using Python or Scala.
- Get Placement assistance and career guidance in Apache Spark both for freshers and working professionals
- Get Practical/Job oriented training and practice on real-time project scenarios
- Get an industry recognized course completion certificate on Apache Spark from Brolly Academy
- Get advantage of our free 3 day demo sessions before enrolling the course
What is Apache Spark ?
- Apache Spark is an open source cluster computing framework started in 2009 as a project at the University of California, Berkeley's AMPLabs by Matei Zaharia.
- In 2010 Apache Spark was open-sourced under a BSD license.
- In 2013 Spark become an Apache top level project.
- Apache Spark used by databricks to short large-scale datasets and set a new world record in 2014.
- Apache Spark is one of the most in-demand open-soursed processing framework/in-memory computing framework used by across the big data industry.
- It provides an interface for programming entire clusters with implicit data parallelism and fault-tolerance.
- It support programming languages like - Scala, Python, R, Java etc. and also called as Polygot.
- Spark helps to process data 100 times faster then MapReduce as it is done in-memory computing framework.
- It has less lines of code as it is implemented in Scala.
What is it used for?
- Apache Spark is an open source data processing engine used to store & process data in batch and also in real-time across different clusters of computers using simple computer constructs.
- It helps to create reports faster, perform aggregations of a large amount of both static data and streams.
- Developers and data scientists incorporate spark into their applications or build spark based applications to process, analyse, query and transform data at a very large scale.
- It solves the problem of machine learning and distributed data integration. It is easy enough to do.
- data scientists may use Spark features through R- and Python-connectors.
- Spark is often used with distributed data stores such as HPE Ezmeral Data Fabric, Hadoop's HDFS, and Amazon's S3, and with popular NoSQL databases such as HPE Ezmeral Data Fabric,MongoDB, Apache HBase, and Apache Cassandra with distributed messaging stores such as HPE Ezmeral Data Fabric and Apache Kafka.
Who should learn this?
- Developers
- Architects
- IT Professionals
- Software Engineers
- Data scientists
- Analysts Professionals
- Big Data Enthusiasts
- ETL Developers and Data Engineers
- Graduates wanting to make career in this domain
Apache Spark Training in Hyderabad
About
Apache Spark developed by Apache Software Foundation has turned out to be the fast and scalable open-source analytics tool for Big Data Analytics that can be used to solve data analysis problems in big data.
It is a unique cluster computing framework for big data analytics which gives one unique integrated API by developers for the purpose of data scientists and data analysts to perform different tasks.
Spark is a unified analytics engine for big data processing, with built-in modules for Streaming, SQL, Machine Learning and Graph Processing.
Apache Spark is also compatible with several other programming languages such as – Java, Python, R and Scala and that makes it easy for data engineers and developers to deploy.
Brolly Academy offers Apache Spark training in Hyderabad with certification and have a team of highly skilled professionals who are very much familiar with the technology and it’s implementation.
Our Apache Spark Training course is designed to equip you with the best skills and includes topics like –
- Introduction to Apache Spark
- Implementing Spark on a cluster
- Scala programming language and its concepts
- Writing Spark applications in Python, Java, and Scala
- Spark streaming
- Scala and Java interoperability
- Difference between Spark and Hadoop
- DStreams, Streaming
- Spark GraphX
- Spark SQL, Machine Learning libraries (Mllib) and more.
After completing the Apache Spark certification training program, you will receive a certificate certifying your expertise in Apache Spark and this certificate will be sent to you once you complete all the training modules.
Our trainers provide students with a technical and theoretical understanding of their craft so that learning becomes easier.
We offer both online and in-person training courses, as well as a placement program that includes an intensive interview preparation workshop.
Enroll with us to get the most comprehensive Apache Spark training in Hyderabad.
Apache Spark Training in Hyderabad
Modes
Classroom Training
- One-One Mentors
- Live project included
- One year batch access Validity
- Certifications
- 100% Placement assistance
- Interview Guidance
Online Training
- Doubt Clearing Sessions
- Daily recorded videos
- 100% Placement assistance
- Course Materials
- Whatsapp Group Access
- Interview Guidance
Video Course
- Doubt Clearing Session
- Basic to advance level
- Lifetime Video Access
- Course Materials
- Interview Preparation Materials
- Interview Guidance
Why choose
Apache Spark Training in Hyderabad
Apache Spark Training In Hyderabad
Testimonials
Apache Spark Certification
Certification
For Big Data Analytics Apache Spark has turned out to be the fastest-growing tool and it has been adopted by many companies worldwide.
There are many organizations provides Apache Spark certifications online and this certification programs are available for professionals who want to demonstrate their skills and career in the Apache Spark framework.
Learning about some of the most popular Apache Spark certifications can help you choose one that matches your career goals and also a proper certification would help you increase your earning potential.
Here are five Apache Spark certifications that you can explore –
What are they?
- Databricks Certified Developer for Apache Spark
- HDP Certified Apache Spark Developer
- Cloudera Spark and Hadoop Developer
- MapR Certified Spark Developer
- O’Reilly Developer Apache Spark Certification
Exam Details –
Key details about the certification exam –
Exam Name – Databricks Certified Developer for Apache Spark
- Exam Fee – $200 (Testers might be subjected to tax payments depending on their location)
- Eligibility/Pre-Requisite – Candidate must have a working knowledge of either Python or Scala
- Exam Duration – 2 hours
- Exam Language – English
- Programming Language – Python and Scala
- Certification Validity – 2 years
- Number of Questions – 60 multiple-choice questions
- Exam Format – The questions will be distributed by high-level topic in the following way –
- Apache Spark Architecture Concepts – 17% (10/60)
- Apache Spark Architecture Applications – 11% (7/60)
- Apache Spark DataFrame API Applications – 72% (43/60)
Exam Name – HDP Certified Apache Spark Developer
- Exam Code – HDPCSD
- Exam Fee – $250 USD
- Eligibility/Pre-Requisite – No
- Exam Duration – 2 hours
- Exam Language – English
- Exam Format – Multiple Choice and Multi-Response Questions
- Exam Form – Computer Based Exam
- Exam Paper – Computer Based
- Exam Type – Developer
Type of Questions – There will be 7-8 tasks (performance based test) given from which candidate have to do at least 6 tasks in 2 hours.
Exam Name – Cloudera Spark and Hadoop Developer
- Exam Code – CCA-175
- Exam Fee – US$295
- Eligibility/Pre-Requisite – No
- Exam Duration – 2 hours
- Exam Language – English
- Exam Format – You need to solve a particular scenario, in some cases a tool (Impala or Hive) may be used and coding is required in most of the cases.
- Passing Score – 70%
- Number of Questions – 8–12 performance-based (hands-on)
Exam Name – MapR Certified Spark Developer
- Exam Code – (MCSD)
- Exam Fee – US$250
- Eligibility/Pre-Requisite – Candidate must have prior programming experience with both Java and Scala.
- Exam Duration – 2 hours
- Exam Language – English
- Number of Questions – 60 to 80 questions based on programming
Exam Name – O’Reilly Developer Apache Spark Certification
- Exam Fee – $300
- Eligibility/Pre-Requisite – No
- Exam Duration – 1 hr 30 mins
- Exam Language – English
- Number of Questions – 40 multiple-choice questions
Advantages of Learning Apache Spark
Brolly Academy’s unique approach, combining theoretical knowledge with practical experience enabled by our trainees applying what they’ve learned directly in real-time projects is unlike any other available today. Here are some of the Advantage of using Apache Spark are mentioned below –
- Excellent Speed & Performance - Apache Spark is wildly popular amoung data scientists and developers because of its excellent speed and performance. It is 100x faster than Hadoop for large scale data processing and uses an in-memory (RAM) computing system where Hadoop uses local memory space to store data. Apache Spark also handles multiple petabytes of clustered data of more than 8000 nodes at same time.
- Apache Spark is powerful - Apache Spark is more powerful and can handle multiple analytics challenges because of its low-latency in-memory data processing capability.
- Libraries - Apache Spark has well-built libraries that support graph analytics algorithms and machine learning. It includes libraries for SQL and structured data, Graph Analytics, and Stream Processing.
- Developer Friendly Tool - Apache Spark allow developers to deal with complex distribution by a simple method.
- Ease of Use - To operate on large sets of data Apache Spark contains easy-to-use APIs and provides 80+ powerful operators that allow us to build parallel applications effortlessly.
- Support Multiple Languages - It supports multiple languages for writing code like - R, Java, Python and Scala.
- Open-source community - Apache Spark has a massive Open-source community.
- Advanced Analytics - Apache Spark not only supports ‘MAP’ and ‘reduce’ it also supports Graph Algorithms, Streaming Data, ML, SQL Queries, and many more.
Skills Developed Post Apache Spark Course
- In-depth understanding of the Apache spark programming
- Gain skills in Scala programming implementation
- Generating spark applications using programming languages like python, Java, scala etc.
- Implementing spark algorithms
- Learn about RDD - its functions and operations
- In-depth knowledge on Spark streaming
- Spark implementation on clusters
- Grasps knowledge in Scala operations
- Executing pattern matching
- Learn the implementation of Machine Learning Algorithms in Spark by using MLlib API
- Get knowledge about how to analyze Hive and Spark SQL architecture
- Get skilled in GraphX API and implementation of Graph Algorithms
- Gain in-depth knowledge about the Implementation of Broadcast Variable and Accumulators for performance tuning and more.
Prerequisites of Apache Spark Training
Pre-requisites
- Basic knowledge of object-oriented programming is enough
- Basic Knowledge of Scala
- Basic understanding of Machine Learning concepts
- Basic knowledge on Database, SQL Query will be an added advantage for Learning this Course.
Career opportunities in Apache Spark
- Big Data- Lead Software Engineer
- Backend Developer Apache Spark
- Big Data Developer
- Apache Spark Application Lead
- Principal Software Engineer
- Big Data- Spark- Software Specialist
- Spark Developer
- Spark Scala Developer
- Apache Spark Application Support Engineer
- Apache Spark Data Platform Engineer
- Apache Spark Application Developer
- Management Analyst
- Project Architect Apache Spark
- Information Security Analysis
Approximate Payscale
- Spark Developer salary in India ranges between ₹ 4.0 Lakhs to ₹ 15.5 Lakhs with an average annual salary of ₹ 6.6 Lakhs.
- An entry-level Spark developer, earn between Rs 6,00,000 to Rs 10,00,000 per annum while an experienced developer, earn between Rs 25,00,000 to Rs 40,00,000 per annum.
- An entry-level Big Data Engineer's salary in India is around ₹466,265 annually.
- A mid-career Big Data Engineer or Lead Big Data Engineer salary (5–9 years of experience) is ₹1,264,555 per year.
Market Trend in Apache Spark
- Apache Spark has a market share of about 3.2%.
- According to marketanalysis.com report, Apache Spark market will grow at a CAGR of 67% between 2019 and 2022 worldwide.
- The Apache Spark market revenue is growing fast and may grow up to $4.2 billion by 2022, with an increasing market valued at $9.2 billion (2019 - 2022).
- According to a survey, The demand for Spark engineers is very high.
- In today’s market, there are over 1,000 contributors to the Apache Spark project across 250+ companies worldwide
- According to the 2015 Data Science Salary Survey by O’Reilly, people with certified Apache Spark skills added $11,000 extra to the median salary, while Scala programming language had an impact of $4000 to the bottom line.
- Using the most prominent Hadoop development tools Apache Spark developers earn the highest average salary among other programmers.
- It is one of the fastest growing big data communities with more than 750 contributors from 200+ companies worldwide.