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HADOOP DEV + SPARK & SCALA
- Solution for BigData Problem
- Open Source Technology
- Based on open source platforms
- Contains several tool for entire ETL data processing Framework
- It can process Distributed data and no need to store entire data in centralized storage as it is required for SQL based tools.
5600 Satisfied Learners
HADOOP DEV + SPARK & SCALA TRAINING IN PUNE
BigData Hadoop Online Training in India
Hadoop Developer + Spark & Scala/Hadoop (Java + Non- Java)
Duration of Training : 50 hrs
Batch type : Weekdays/Weekends
Mode of Training : Classroom/Online/Corporate Training
Hadoop Dev + Spark & Scala Training & Certification in Pune
Highly Experienced Certified Trainer with 10+ yrs Exp. in Industry
Realtime Projects, Scenarios & Assignments
Hadoop Certification : Cloudera Certified Professional (CCP)
We Provide all guidance & support for making you a Hadoop Certified Professional
Best BigData Hadoop Training with 2 Real-time Projects with 1 TB Data set
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
For whom Hadoop is?
IT folks who want to change their profile in a most demanding technology which is in demand by almost all clients in all domains because of below mentioned reasons-
Hadoop is open source (Cost saving / Cheaper)
Hadoop solves Big Data problem which is very difficult or impossible to solve using highly paid tools in market
It can process Distributed data and no need to store entire data in centralized storage as it is there with other tools.
Now a days there is job cut in market in so many existing tools and technologies because clients are moving towards a cheaper and efficient solution in market named HADOOP
There will be almost 4.4 million jobs in market on Hadoop by next year.
Please refer below given links :
Can I learn Hadoop if I don’t know Java?
Yes.
It is a big myth that if a guy don’t know Java then he can’t learn Hadoop. The truth is that Only Map Reduce framework needs Java except Map Reduce all other components are based on different terms like Hive is similar to SQL, HBase is similar to RDBMS and Pig is script based.
Only MR requires Java but there are so many organizations who started hiring on specific skill set also like HBASE developer or Pig and Hive specific requirements. Knowing MapReuce also is just like become all-rounder in Hadoop for any requirement.
Why Hadoop?
- Solution for BigData Problem
- Open Source Technology
- Based on open source platforms
- Contains several tool for entire ETL data processing Framework
- It can process Distributed data and no need to store entire data in centralized storage as it is required for SQL based tools. ,
COURSE CONTENT :
HADOOP DEV + SPARK & SCALA + NoSQL + Splunk + HDFS (Storage) + YARN (Hadoop Processing Framework) + MapReduce using Java (Processing Data) + Apache Hive + Apache Pig + HBASE (Real NoSQL ) + Sqoop + Flume + Oozie + Kafka With ZooKeeper + Cassandra + MongoDB + Apache Splunk
Big Data :
Distributed computing
Data management – Industry Challenges
Overview of Big Data
Characteristics of Big Data
Types of data
Sources of Big Data
Big Data examples
What is streaming data?
Batch vs Streaming data processing
Overview of Analytics
Big data Hadoop opportunities
Hadoop :
Why we need Hadoop
Data centers and Hadoop Cluster overview
Overview of Hadoop Daemons
Hadoop Cluster and Racks
Learning Linux required for Hadoop
Hadoop ecosystem tools overview
Understanding the Hadoop configurations and Installation
HDFS (Storage) :
HDFS
HDFS Daemons – Namenode, Datanode, Secondary Namenode
Hadoop FS and Processing Environment’s UIs
Fault Tolerant
High Availability
Block Replication
How to read and write files
Hadoop FS shell commands
YARN (Hadoop Processing Framework) :
YARN
YARN Daemons – Resource Manager, Node Manager etc.
Job assignment & Execution flow
MapReduce using Java (Processing Data) :
The introduction of MapReduce.
MapReduce Architecture
Data flow in MapReduce
Understand Difference Between Block and InputSplit
Role of RecordReader
Basic Configuration of MapReduce
MapReduce life cycle
How MapReduce Works
Writing and Executing the Basic MapReduce Program using Java
Submission & Initialization of MapReduce Job.
File Input/Output Formats in MapReduce Jobs
Text Input Format
Key Value Input Format
Sequence File Input Format
NLine Input Format
Joins
Map-side Joins
Reducer-side Joins
Word Count Example(or) Election Vote Count
Will cover five to Ten Map Reduce Examples with real time data
Apache Hive :
Data warehouse basics
OLTP vs OLAP Concepts
Hive
Hive Architecture
Metastore DB and Metastore Service
Hive Query Language (HQL)
Managed and External Tables
Partitioning & Bucketing
Query Optimization
Hiveserver2 (Thrift server)
JDBC, ODBC connection to Hive
Hive Transactions
Hive UDFs
Working with Avro Schema and AVRO file format
Hands on Multiple Real Time datasets
Apache Pig :
Apache Pig
Advantage of Pig over MapReduce
Pig Latin (Scripting language for Pig)
Schema and Schema-less data in Pig
Structured , Semi-Structure data processing in Pig
Pig UDFs
HCatalog
Pig vs Hive Use case
Hands On Two more examples daily use case data analysis in google. And Analysis on Date time dataset
HBASE (Real NoSQL) :
Introduction to HBASE
Basic Configurations of HBASE
Fundamentals of HBase
What is NoSQL?
HBase Data Model
Table and Row.
Column Family and Column Qualifier.
Cell and its Versioning
Categories of NoSQL Data Bases
Key-Value Database
Document Database
Column Family Database
HBASE Architecture
HMaster
Region Servers
Regions
MemStore
Store
SQL vs. NOSQL
How HBASE is differed from RDBMS
HDFS vs. HBase
Client-side buffering or bulk uploads
HBase Designing Tables
HBase Operations
Get
Scan
Put
Delete
Live Dataset
Sqoop :
Sqoop commands
Sqoop practical implementation
Importing data to HDFS
Importing data to Hive
Exporting data to RDBMS
Sqoop connectors
Flume :
Flume commands
Configuration of Source, Channel and Sink
Fan-out flume agents
How to load data in Hadoop that is coming from web server or other storage
How to load streaming data from Twitter data in HDFS using Hadoop
Oozie :
Oozie
Action Node and Control Flow node
Designing workflow jobs
How to schedule jobs using Oozie
How to schedule jobs which are time based
Oozie Conf file
Scala :
Scala
Syntax formation, Datatypes , Variables
Classes and Objects
Basic Types and Operations
Functional Objects
Built-in Control Structures
Functions and Closures
Composition and Inheritance
Scala’s Hierarchy
Traits
Packages and Imports
Working with Lists, Collections
Abstract Members
Implicit Conversions and Parameters
For Expressions Revisited
The Scala Collections API
Extractors
Modular Programming Using Objects
Spark :
Spark
Architecture and Spark APIs
Spark components
Spark master
Driver
Executor
Worker
Significance of Spark context
Concept of Resilient distributed datasets (RDDs)
Properties of RDD
Creating RDDs
Transformations in RDD
Actions in RDD
Saving data through RDD
Key-value pair RDD
Invoking Spark shell
Loading a file in shell
Performing some basic operations on files in Spark shell
Spark application overview
Job scheduling process
DAG scheduler
RDD graph and lineage
Life cycle of spark application
How to choose between the different persistence levels for caching RDDs
Submit in cluster mode
Web UI – application monitoring
Important spark configuration properties
Spark SQL overview
Spark SQL demo
SchemaRDD and data frames
Joining, Filtering and Sorting Dataset
Spark SQL example program demo and code walk through
Kafka With ZooKeeper :
What is Kafka
Cluster architecture With Hands On
Basic operation
Integration with spark
Integration with Camel
Additional Configuration
Security and Authentication
Apache Kafka With Spring Boot Integration
Running
Usecase
Apache Splunk :
Introduction & Installing Splunk
Play with Data and Feed the Data
Searching & Reporting
Visualizing Your Data
Advanced Splunk Concepts
Cassandra + MongoDB :
Introduction of NoSQL
What is NOSQL & N0-SQL Data Types
System Setup Process
MongoDB Introduction
MongoDB Installation
DataBase Creation in MongoDB
ACID and CAP Theorum
What is JSON and what all are JSON Features?
JSON and XML Difference
CRUD Operations – Create , Read, Update, Delete
Cassandra Introduction
Cassandra – Different Data Supports
Cassandra – Architecture in Detail
Cassandra’s SPOF & Replication Factor
Cassandra – Installation & Different Data Types
Database Creation in Cassandra
Tables Creation in Cassandra
Cassandra Database and Table Schema and Data
Update, Delete, Insert Data in Cassandra Table
Insert Data From File in Cassandra Table
Add & Delete Columns in Cassandra Table
Cassandra Collections
RELATED COMBO PROGRAMS :
Oracle SQL+ core Java + Bigdata Hadoop
Student Stories and Reviews :
FAQs :
Big Data Hadoop is a framework for processing and analyzing large datasets. Training in this field is crucial for individuals aiming to harness the power of big data and advance their careers in analytics.
We offer industry-recognized Big Data Hadoop certifications to validate your skills. These certifications enhance your resume, making you stand out to employers seeking qualified professionals.
Radical Technologies is recognized for its state-of-the-art facilities, experienced faculty, and industry-aligned curriculum, making it the preferred choice for Big Data Hadoop training in Pune.
Yes, we offer Big Data Hadoop classes online, providing the same curriculum as in-person classes. Online courses offer flexibility for learners who prefer remote access.
We provide a variety of tutorials and learning resources, including guides, videos, and materials to support your understanding of Big Data Hadoop concepts and techniques.
Our training programs cover a range of topics, including Hadoop architecture, MapReduce, Hive, Pig, HBase, and other essential components of the Hadoop ecosystem.
The duration of our Big Data Hadoop training programs varies, with flexible scheduling options to accommodate different learning preferences and timeframes.
While some courses may have specific prerequisites, many are suitable for beginners. Our admissions team can guide you on the right course based on your skill level.
Yes, we offer job placement assistance, guaranteeing support for qualified candidates. Our industry connections and partnerships facilitate job placements for our graduates.
Our Big Data Hadoop training opens doors to various career opportunities, including roles such as Big Data Analyst, Hadoop Developer, and Data Engineers.
Yes, we understand the importance of flexibility. We offer part-time Big Data Hadoop training options to accommodate individuals with work or other commitments.
Absolutely. Our training includes practical hands-on sessions to ensure that students gain real-world experience working with Big Data Hadoop tools.
Our curriculum is dynamic and evolves with industry trends. Faculty members actively engage with industry experts and stay informed about the latest advancements.
Yes, we offer various financial aid options and scholarships. Contact our admissions team to discuss your eligibility and available opportunities.
Yes, graduates have continued access to course materials and resources to support ongoing learning and professional development.
Our certification programs are designed with industry relevance, focusing on practical skills and preparing graduates for real-world challenges in Big Data analytics.
Our guarantee ensures that qualified graduates receive support in securing relevant job opportunities, leveraging our strong industry connections and placement partnerships.
Yes, we offer tailored training options to meet individual needs. Speak with our advisors to discuss customization based on your interests and career goals.
Yes, we provide ongoing support and mentorship to our alumni, connecting them with industry professionals and opportunities for continued growth in the Big Data field.
We are dedicated to the holistic development of Big Data professionals by offering comprehensive training, industry-relevant certifications, and ongoing support throughout their careers.
Most Probable Interview Questions for HADOOP DEV + SPARK & SCALA
Interview Question No. 1 for HADOOP DEV + SPARK & SCALA : Can you provide an overview of your experience working with Hadoop ecosystem technologies, including HDFS, MapReduce, YARN, and Hive?
Interview Question No. 2 for HADOOP DEV + SPARK & SCALA : Describe a project where you utilized Spark and Scala within a Hadoop environment What was your role, and what challenges did you encounter?
Interview Question No. 3 for HADOOP DEV + SPARK & SCALA : How do you optimize Spark jobs for performance and efficiency in large-scale data processing tasks?
Interview Question No. 4 for HADOOP DEV + SPARK & SCALA : Have you worked with Apache Kafka in conjunction with Hadoop? If so, can you explain how you integrated them and the benefits it provided?
Interview Question No. 5 for HADOOP DEV + SPARK & SCALA : Discuss your experience with Spark Streaming or Structured Streaming for real-time data processing What use cases did you address, and what were the outcomes?
Interview Question No. 6 for HADOOP DEV + SPARK & SCALA : Explain your understanding of RDDs (Resilient Distributed Datasets) and DataFrames in Apache Spark, and when you would choose one over the other in your development
Interview Question No. 7 for HADOOP DEV + SPARK & SCALA : Have you implemented machine learning algorithms using Spark’s MLlib library? If yes, can you provide examples and discuss the results?
Interview Question No. 8 for HADOOP DEV + SPARK & SCALA : How do you handle data skewness and imbalance in Spark jobs, especially when dealing with large datasets?
Interview Question No. 9 for HADOOP DEV + SPARK & SCALA : Describe your approach to fault tolerance and resilience in Spark applications, considering factors like node failures and data consistency
Interview Question No. 10 for HADOOP DEV + SPARK & SCALA : Have you worked with Spark SQL for querying and analyzing data? If so, discuss your experience with optimizing SQL queries for performance
Interview Question No. 11 for HADOOP DEV + SPARK & SCALA : Explain your experience with deploying and managing Spark applications in production environments, including considerations for scalability and resource management
Interview Question No. 12 for HADOOP DEV + SPARK & SCALA : Can you discuss your familiarity with Hadoop security mechanisms and how you ensure data privacy and access control in your projects?
Interview Question No. 13 for HADOOP DEV + SPARK & SCALA : Describe a scenario where you used Spark to process semi-structured or unstructured data (eg, JSON, XML) within a Hadoop cluster What were the key challenges, and how did you overcome them?
Interview Question No. 14 for HADOOP DEV + SPARK & SCALA : Discuss your involvement in designing and implementing data pipelines using Apache Spark, including data ingestion, transformation, and loading processes
Interview Question No. 15 for HADOOP DEV + SPARK & SCALA : How do you monitor and troubleshoot Spark jobs to identify performance bottlenecks and optimize resource utilization?
Interview Question No. 16 for HADOOP DEV + SPARK & SCALA : Have you utilized Spark’s graph processing capabilities for analyzing graph-structured data? If yes, describe your experience and the types of problems you tackled
Interview Question No. 17 for HADOOP DEV + SPARK & SCALA : Explain your understanding of Spark’s broadcast variables and accumulators, and how you leverage them to improve performance and efficiency
Interview Question No. 18 for HADOOP DEV + SPARK & SCALA : Can you discuss your experience with integrating Spark with other big data technologies like Apache HBase or Cassandra? What were the integration challenges you faced?
Interview Question No. 19 for HADOOP DEV + SPARK & SCALA : Describe a situation where you implemented custom functions or UDFs (User-Defined Functions) in Spark using Scala What was the purpose, and how did it enhance your solution?
Interview Question No. 20 for HADOOP DEV + SPARK & SCALA : How do you keep yourself updated with the latest developments and best practices in the Hadoop ecosystem, particularly in Spark and Scala?
Big Data Hadoop – Course in Pune with Training, Certification & Guaranteed Job Placement Assistance!
Welcome to Radical Technologies, the premier institute in Pune offering top-notch Big Data Hadoop training and certification programs. We specialize in providing comprehensive training, industry-recognized certification, and job placement assistance to empower individuals in the field of Big Data.
Big Data Hadoop Training and Certification
Our Big Data Hadoop training programs are designed to equip you with the skills and knowledge required to excel in the dynamic field of big data analytics. Whether you’re a beginner or an experienced professional, our courses cover a wide range of topics, ensuring you receive a well-rounded education in Big Data Hadoop.
Achieving a Big Data Hadoop certification is a significant milestone in your career journey. Our institute is committed to providing you with the best preparation for industry-recognized certifications that will validate your expertise and enhance your employability.
Best Big Data Hadoop Institute in Pune
Radical Technologies takes pride in being recognized as the best Big Data Hadoop institute in Pune. Our state-of-the-art facilities, experienced faculty, and industry-aligned curriculum make us the preferred choice for individuals looking to kickstart or advance their careers in Big Data Hadoop.
Big Data Hadoop Classes and Online Courses
Our Big Data Hadoop classes offer a blend of theoretical knowledge and hands-on experience, ensuring a comprehensive learning experience. For those seeking flexibility, we also provide Big Data Hadoop online courses. These online courses cover the same curriculum as our in-person classes, allowing you to learn at your own pace.
Big Data Hadoop Tutorial and Learning Resources
To enhance your learning journey, we provide a variety of Big Data Hadoop tutorials and learning resources. These resources include guides, videos, and additional materials to reinforce your understanding of key concepts and techniques.
Hadoop Job Placement Assistance Guarantee
One of the standout features of Radical Technologies is our Big Data Hadoop job placement assistance guarantee. We are committed to helping qualified candidates secure promising job opportunities in the Big Data industry. Our strong industry connections and partnerships with leading companies enable us to provide valuable job placement support.
Big Data Hadoop Career Development and Opportunities
By choosing Radical Technologies for your Big Data Hadoop training, you are opening doors to exciting career opportunities. Our courses are designed to align with the latest industry trends, ensuring that you are well-prepared for the ever-evolving landscape of Big Data analytics.
Enroll Today for the Best Big Data Hadoop Training in Pune
If you are passionate about a career in Big Data Hadoop, Radical Technologies is the place to be. Enroll in our Big Data Hadoop training programs, gain valuable skills, and position yourself for a successful and rewarding career in the burgeoning field of big data analytics.
For more information on our Big Data Hadoop courses, certifications, and job placement assistance, contact us today!
Find Hadoop Developer + Spark & Scala Course in other cities –
Online Batches Available for the Areas
Ambegaon Budruk | Aundh | Baner | Bavdhan Khurd | Bavdhan Budruk | Balewadi | Shivajinagar | Bibvewadi | Bhugaon | Bhukum | Dhankawadi | Dhanori | Dhayari | Erandwane | Fursungi | Ghorpadi | Hadapsar | Hingne Khurd | Karve Nagar | Kalas | Katraj | Khadki | Kharadi | Kondhwa | Koregaon Park | Kothrud | Lohagaon | Manjri | Markal | Mohammed Wadi | Mundhwa | Nanded | Parvati (Parvati Hill) | Panmala | Pashan | Pirangut | Shivane | Sus | Undri | Vishrantwadi | Vitthalwadi | Vadgaon Khurd | Vadgaon Budruk | Vadgaon Sheri | Wagholi | Wanwadi | Warje | Yerwada | Akurdi | Bhosari | Chakan | Charholi Budruk | Chikhli | Chimbali | Chinchwad | Dapodi | Dehu Road | Dighi | Dudulgaon | Hinjawadi | Kalewadi | Kasarwadi | Maan | Moshi | Phugewadi | Pimple Gurav | Pimple Nilakh | Pimple Saudagar | Pimpri | Ravet | Rahatani | Sangvi | Talawade | Tathawade | Thergaon | Wakad
We Provide Cloudera Hadoop Certifications
Cloudera Certified Professional (CCP)
The industry’s most demanding performance-based certifications, CCP evaluates and recognizes a candidate’s mastery of the technical skills most sought after by employers.
- CCA Spark and Hadoop Developer
A CCA Spark and Hadoop Developer has proven their core skills to ingest, transform, and process data using Apache Spark™ and core Cloudera Enterprise tools.
- CCA HDP Administrator Exam
The HDP Certified Administrator (HDPCA) exam has five main categories of tasks that involve: Installation, Configuration, Troubleshooting, High Availability and Security.
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 toolsets 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.
-
How we are Different from Others : Covers each topics with Real Time Examples . Covers 8 Real time project and more than 72+ Assignments which is divided into Basic , Intermediate and Advanced . Trainer from Real Time Industry with 9 years experience in DWH. Working as BI and Hadoop consultant having 3+ years in Bigdata & Hadoop real time implementation and migrations.This is completely hands own training , which covers 90% Practical And 10% Theory .Here in Radical Technologies , we will take all prerequisite like Java ,SQL, which is required to learn Hadoop Developer and Analytical skills. This way We will accommodate technology illiterate and Technical experts in the same session and at the end of the training , they will gain the confidence that , they got up-skilled to a different level.
- 8 Domain Based Project With Real Time Data ( with one trainer – two project. If you req more projects , you are free to attend any other trainers project orientations sessions )
- 5 POC
- 72 Assignments
- 25 Real Time Scenarios On 16 Node Clusters ( Aws Cloud setup )
- Basic Java
- DWH Concept
- Pig|Hive|Mapreduce|Nosql|Hbase|Zookeeper|Sqoop|Flume|Oozie|Yarn|Hue|Spark |Scala
42 Hours Classroom Section
30 Hours of assignments
25 hours for One Project and 50 Hrs for 2 Project ( Candidates should prepare with mentor support . 50 hours mentioned is total hours spent on project by each trainer )
350+ Interview Questions
Administration and Manual Installation of Hadoop with other Domain based projects will be done on regular basis apart from our normal batch schedule .
We do have projects from Healthcare , Financial , Automotive ,Insurance , Banking , Retail etc , which will be given to our students as per their requirements .
- Training By 14+ Years experienced Real Time Trainer
- A pool of 200+ real time Practical Sessions on Bigdata Hadoop
- 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
[schema type=”review” url=”https://www.radicaltechnologies.co.in/” name=”Hadoop Development Training Review of Radical Technologies Pune” description=”HADOOP DEV + SPARK & SCALA COURSE” rev_name=”HADOOP DEV + SPARK & SCALA” rev_body=”Hadoop Development Learning experience was amazing. Trainers teaching style was really good and the content was well structured to cover all concepts. The classes were full of practical knowledge, most importantly it was never too difficult to understand or monotonous because of teaching style. Would definitely recommend to those who are looking for proper direction and don’t know where to start from. Would like to learn more from Radical Technologies. They helps for getting me Certified with all guidance. ” author=”kalyani Agarwal” pubdate=”2020-04-03″ user_review=”5″ min_review=”0″ max_review=”5″ ]
ML and GraphX ,’R’ Language
Data Analytics / Science
Cloudera Certified Professional (CCP)
CCP Data Engineer
