Hadoop Training

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Best Big Data Hadoop Training in Chennai at Credo Systemz will help you learn and upgrade your knowledge in the Core components, Database concepts and Linux Operating system. Also, Our Hadoop Course Content  has been designed by industry experts which helps you to become a Professional Hadoop Developer through live projects on all frameworks of Big Data Hadoop with hands-on session.

We are the best  provider of Hadoop Big Data Training in Chennai, Velachery and OMR with affordable fees according to the positive reviews across the internet. Likewise, Our Hadoop training is well designed to gain knowledge with economical Training Cost for Hadoop Training in Chennai. We are provides you the complete Hadoop training program from absolute scratch and reach up to expert level. Also,you can download the Hadoop course content PDF below which has been designed by the experts in the industry.

In this Big Data Hadoop Training, the candidates obtains the live practical sessions on Data Engineering using SQL, NoSQL, Hadoop ecosystem, including most extensively used elements like HDFS, Spark, Hive, Sqoop, Impala & Cloud Computing. Also, we offer both Classroom Training and Online Training will access the Hadoop training requirements and also provide Hadoop Certification Guidance.

About Hadoop Course

First of all, Big Data is a large set of data as the name mentions “Big Data”. It is complex to collected using traditional data processed systems since the most of the data generation is unstructured form so it’s hard to handle the critical environment, So Hadoop come up the solution to this problem. Hadoop is open source tool which is developed by Apache that is used for handle the large set of unstructured data in distributed computing environment. It can measure from single to thousands servers and it also saves the time. Joining the Big Data Hadoop course in Chennai with placement will help you to learn from scratch.
Hadoop is used to store and process a large amount of data easily and most of the big IT companies uses hadoop for storage purpose. So hadoop job opportunities increasingly for many hadoop positions. Also, Hadoop used big companies are Google, Yahoo, IBM and Ebay etc.. If you are learn Hadoop Training surely you get Job in one of the best MNC's.
Nowadays Data is Everything in the World. Here is the short story of how the data is rapidly increasing. Due to the vast variety of Technologies, Mobile Apps and Huge Amount of Social Networks, the amount of generating data is rapidly increasing in every minute. Here is a small statistics.
  • Up to the year 2003, all over the production of data was 6 billion gigabytes.
  • In 2011, the same amount of data was generated in every two days
  • Very surprisingly, in 2013, the same amount of data generated in every 2 minutes.
  • Just think about now and upcoming years!!
The graphical representation of Big Data application given below,Big Data Application

Key Features

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Training from
Industrial Experts

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24 x 7
Expert Support

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Hands on
Practicals/ Projects

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Certification
of Completion

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100% Placement
Assistance

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Free
Live Demo

HADOOP TRAINING COURSE CONTENT

Learning Outcomes of our Hadoop Course:

On successfully completing our 60 hours of Hadoop Training Program, You will be an expert with the below skills to match the industrial expectations,

  • Firstly, Strong knowledge in Hadoop Fundamental concepts.
  • Secondly, Deep Understanding of Hadoop Distributed File System(HDFS) and MapReduce concepts.
  • Morever, Installation and deployment of Apache Hadoop.
  • Most Importantly, Become an Expert in Map Reduce Programs and Implementation of HBase.
  • On the other words, Hands-on knowledge in Data loading techniques using sqoop and flume.
  • Likewise, Gain an depth knowledge of Big Data Framework using Hadoop and Apache Spark.
  • Further, Best practices in buliding, optimizing and debugging the Hadoop solutions.
  • In the conclusion, Over all understanding of Big Data Hadoop and be equipped to clear Big Data Hadoop Certification.

Hadoop Training Highlights

  • Learn Hadoop training from our Expert by working on hands-on real time projects.
  • Most importantly our Hadoop training in Chennai will start from complete scratch which includes spark with scala.
  • Further, Hands-on Practical assignments for each and every topic which makes you strong in technically.
  • On Successfully completion of this Hadoop training via online, classroom and corporate an individual. Also it will acquire the complete skillset required to be a professional Hadoop Developer.
  • In addition,Guidance for Hadoop Developer Certification.
  • Similarly, Special Combo Course (Hadoop and Spark) is available with Combo offer for interested candidates.
  • In addition, Latest Hadoop Job Openings will be shared with our trained Candidates.

Course Features

  • Duration60 hours
  • Skill levelAll level
  • Batch Strength15
  • AssessmentsYes
  • Mock InterviewsYes
  • Resume BuildingYes
  • PlacementsYes
  • Flexible TimingYes
  • Fee InstallmentsYes
  • LanguageTamil/English
Section 1: INTRODUCTION TO BIG DATA-HADOOP
  • Overview of Hadoop Ecosystem
  • Role of Hadoop in Big data– Overview of other Big Data Systems
  • Who is using Hadoop
  • Hadoop integrations into Exiting Software Products
  • Current Scenario in Hadoop Ecosystem
  • Installation
  • Configuration
  • Use Cases ofHadoop (HealthCare, Retail, Telecom)
Section 2: HDFS
  • Concepts
  • Architecture
  • Data Flow (File Read , File Write)
  • Fault Tolerance
  • Shell Commands
  • Data Flow Archives
  • Coherency -Data Integrity
  • Role of Secondary NameNode
Section 3: MAPREDUCE
  • Theory
  • Data Flow (Map – Shuffle - Reduce)
  • MapRed vs MapReduce APIs
  • Programming [Mapper, Reducer, Combiner, Partitioner]
  • Writables
  • InputFormat
  • Outputformat
  • Streaming API using python
  • Inherent Failure Handling using Speculative Execution
  • Magic of Shuffle Phase
  • FileFormats
  • Sequence Files
Section 4: HBASE
  • Introduction to NoSQL
  • CAP Theorem
  • Classification of NoSQL
  • Hbase and RDBMS
  • HBASE and HDFS
  • Architecture (Read Path, Write Path, Compactions, Splits)
  • Installation
  • Configuration
  • Role of Zookeeper
  • HBase Shell  Introduction to Filters
  • RowKeyDesign -What's New in HBase  Hands On
Section 5: HIVE
  • Architecture
  • Installation
  • Configuration
  • Hive vs RDBMS
  • Tables
  • DDL
  • DML
  • UDF
  • Partitioning
  • Bucketing
  • Hive functions
  • Date functions
  • String functions
  • Cast function Meta Store
  • Joins
  • Real-time HQL will be shared along with database migration project

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Section 6: PIG
  • Architecture
  • Installation
  • Hive vs Pig
  • Pig Latin Syntax
  • Data Types
  • Functions (Eval, Load/Store, String, DateTime)
  • Joins
  • UDFs- Performance
  • Troubleshooting
  • Commonly Used Functions
Section 7: SQOOP
  • Architecture , Installation, Commands(Import , Hive-Import, EVal, Hbase Import, Import All tables, Export)
  • Connectors to Existing DBs and DW
Real-time Practicals
  • SQOOP to import Real Time Weblogs from application to DB and try to export the same to MySQL
Section 8: KAFKA
  • Kafka introduction
  • Data streaming Introduction
  • Producer-consumer-topics
  • Brokers
  • Partitions
  • Unix Streaming via kafka
Real-time Practicals
    Kafka
  • Producer and Subscribers setup and publish a topic from Producer to subscriber
Section 9: OOZIE
  • Architecture
  • Installation
  • Workflow
  • Coordinator
  • Action (Mapreduce, Hive, Pig, Sqoop)
  • Introduction to Bundle
  • Mail Notifications
Section 10: HADOOP 2.0 and Spark
  • Limitations in Hadoop
  • 1.0 - HDFS Federation
  • High Availability in HDFS
  • HDFS Snapshots
  • Other Improvements in HDFS2
  • Introduction to YARN aka MR2
  • Limitations in MR1
  • Architecture of YARN
  • MapReduce Job Flow in YARN
  • Introduction to Stinger Initiative and Tez
  • BackWard Compatibility for Hadoop 1.X
  • Spark Fundamentals
  • RDD- Sample Scala Program- Spark Streaming
Real-time Practicals
  • Difference between SPARK1.x and SPARK2.x
  • PySpark program to create word count program in pyspark
Section 11: Big Data Use cases
  • Hadoop
  • HDFS architecture and usage
  • MapReduce Architecture and real time exercises
  • Hadoop Eco systems
  • Sqoop - mysql Db Migration
  • Hive. -- Deep drive
  • Pig - weblog parsing and ETL
  • Oozie - Workflow scheduling
  • Flume - weblogs ingestion
  • No SQL
  • HBase
  • Apache Kafka
  • Pentaho ETL tool integration & working with Hadoop eco system
  • Apache SPARK
  • Introduction and working with RDD.
  • Multinode Setup Guidance
  • Hadoop latest version Pros & cons discussion
  • Ends with Introduction of Data science.
Section 12: Real Time Project
  • Getting applications web logs
  • Getting user information from my sql via sqoop
  • Getting extracted data from Pig script
  • Creating Hive SQL Table for querying
  • Creating Reports from Hive QL

You will be going through detailed 2 to 3 months of Hadoop Hands-on training

  • Detailed instructor led sessions to help you become a proficient Expert in Hadoop.
  • Build a Hadoop professional portfolio by working on hands on assignments and projects.
  • Personalised mentorship from professionals working in leading companies.
  • Lifetime access to downloadable Hadoop course materials, interview questions and project resources.
Credo-Systemz-Velachery

Credo Systemz - Velachery, Chennai
Call Us +91 9884412301

Credo-Systemz-OMR

Credo Systemz - OMR, Chennai
Call Us +91 9600112302

Best institute for big data in chennai  
Murugan   
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I Completed my big data certification in chennai @ Credo Systemz. The Big Data sessions were very good. Tutor explanations given by us was nice and easy to learn. He will move to the next topic only after we completely understood the current session. He will clear the doubts whenever we call him, He is very friendly, The whole training session are very interactive and useful. Now I'm a certified Hadoop developer.

I learnt a lot on this course  
Felicia   
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Hello Everyone Myself Felicia, I Completed my B.E Graduate in 2017. I am really interested to learn big data technology.So I searched Big Data Training Institutes in Chennai then I found Credo Systemz. After attending the demo Session I joined here for Big Data training. Big Data Training was started from Java Basics which helpful to learn Big Data completely. My Trainer explained Every concept with Real-Time examples which useful to understand all concepts easily. After Completing Java concepts, we started Hadoop from basics concepts & Components. In training period we Prepared many use cases in different field like Retail, Healthcare, Telecom. After completion of my training, I learned whole concepts of Big data with practical Knowledge. I like to thank my trainer & Credo Systemz Placement team. Now I got my dream job in Bigdata Technology.

Highly Recommended  
Nithin Prasath   
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Hai, This is Nithin Prasath. I am worked as Java Developer and Having two years experience in Java Platform. I would like to enhance my career growth in Hadoop. So, I approached Credo Systemz for my Hadoop Developer Training. First I attended Free Demo Session with Hadoop Tutor. After the Demo class I am really satisfied with the demo and also affordable big data course fees in chennai, so I Joined Hadoop training in Credo Systemz. The Hadoop tutor was very well knowledged person in all Hadoop Components. Training program covered from basics level to advanced level with Spark Concept. In this training, I am worked on a real-time project using MapReduce. I am very much satisfied with the Practical Oriented Hadoop Training. I am really Happy to say this is the Best Hadoop Training Institute in Chennai. Thanks to Credo Systemz

Best Hadoop Training Chennai Review  
Reshmi Sharma   
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Hi, I am Reshmi Sharma having 2 yrs experience in a Mainframe. I wish to take my career to next level, so I just searching the best Hadoop institute, I found credo systemz and I saw their reviews and rating was so good. I am really satisfied so I joined here. I have taken Hadoop training for 2 months from basics of java, My trainer taught java initially and he gave a lot of practical work in java. After we start Hadoop, in this session also I done more practice and credo provided course material and interview question which was very helpful for us. Overall experienced with credo was very nice. I strongly recommended credo systemz for Hadoop training.

Real time Project Hadoop Training  
Ramya   
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My Friend Suggested me CREDO SYSTEMZ. That he recently trained in Credo Systemz and placed in a MNC. All the trainers are very professional. The way they handle the classes are extra ordinary. Fees is also affordable. Credo is the best institute for Hadoop in Velachery

Hadoop Developer Training in Chennai  
Sanjay   
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I am Sanjay and completed my hadoop admin training in chennai at Credo Systemz. My trainer is very professional and his way of approach toward the class was very interactive and interesting. He always used to ensure that everyone in the class is clear about the days hadoop training topics. I like to thank Credo Systemz and my trainer for providing this big data training and placement in chennai.

Hadoop training institute in chennai  
Mutheen Hussain   
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I attended Big data hadoop course, training went on very well and I was able to explore in and out concepts in working with big data eco system. Trainer who taught me had a vast knowledge about the big data solutions and the exercise which the institute provided really helped me to understand the in depth idea of Big data. Trainer was very friendly and ready to provide help and support all the time. Never hesitated to clarify our questions. I would strong recommend this institute, if someone is looking for Big data hadoop training centre in Chennai.

Check here for candidates feedback on Hadoop Training through

Top MNC Hadoop Interview Questions

  1. What is Fact Table and Dimension Table (When I said that I am aware of Dataware house concept)
  2. What type of data we should store in Fact table and dimension table?
  3. There is a string in a Hive column, how you will find the count of a character. For example, the string is “hdfstutorial”, then how to count number of ‘t’.
  4. There is a table in Hive, and the columns are student id, score and year. Find the top 3 students based on the score in each year.
  5. There is a table having 500 Million records. Now you want to copy the data of that table in some other table, what best approach you will choose.
  6. You have 10 tables, and there are certain join conditions you have to put and then the result needs to be updated in another table. How you will do it and what best practice you will follow
  7. Which all analytical functions you have used in Hive
  8. Why we use bucketing
  9. what is actually hapeening in bucketing and when we apply
  10. How bucketing is different from Partition and why we use it
  11. If you have a bucketed table then can you take those records to Sqoop directly
  1. What are the differences between Hadoop and Spark?
  2. What are the daemons required to run a Hadoop cluster?
  3. How will you restart a NameNode?
  4. Explain about the different schedulers available in Hadoop.
  5. List few Hadoop shell commands that are used to perform a copy operation.
  6. What is jps command used for?
  7. What are the important hardware considerations when deploying Hadoop in production environment?
  8. How many NameNodes can you run on a single Hadoop cluster?
  9. What happens when the NameNode on the Hadoop cluster goes down?
  10. What is the conf/hadoop-env.sh file and which variable in the file should be set for Hadoop to work?
  11. Apart from using the jps command is there any other way that you can check whether the NameNode is working or not.
  12. Which command is used to verify if the HDFS is corrupt or not?
  13. List some use cases of the Hadoop Ecosystem
  14. Which is the best operating system to run Hadoop?
  15. What are the network requirements to run Hadoop?
  16. What is the best practice to deploy a secondary NameNode?
  17. How often should the NameNode be reformatted?
  18. How can you add and remove nodes from the Hadoop cluster?
  19. Explain about the different configuration files and where are they located.
  20. What is the role of the namenode?
  1. What is serialization?
  2. How to remove the duplicate records from a hive table?
  3. How to find the number of delimiter from a file?
  4. Replace a certain word from a file using Unix?
  5. How to import a table without a primary key?
  6. What is cogroup in pig?
  7. How to write a UDF in Hive?
  8. How you can join two big tables in Hive?
  9. The difference between order by and sort by?
  1. What is rack awareness? And why is it necessary?
  2. What is the default block size and how is it defined?
  3. How do you get the report of hdfs file system? About disk availability and no.of active nodes?
  4. What is Hadoop balancer and why is it necessary?
  5. Difference between Cloudera and Ambari?
  6. What are the main actions performed by the Hadoop admin?
  7. What is Kerberos?
  8. What is the important list of hdfs commands?
  9. How to check the logs of a Hadoop job submitted in the cluster and how to terminate already running process?
  1. What Hadoop components will you use to design a Craiglist based architecture?
  2. Why cannot you use Java primitive data types in Hadoop MapReduce?
  3. Can HDFS blocks be broken?
  4. Does Hadoop replace data warehousing systems?
  5. How will you protect the data at rest?
  6. Propose a design to develop a system that can handle ingestion of both periodic data and real-time data.
  7. A folder contains 10000 files with each file having size greater than 3GB.The files contain users, their names and date. How will you get the count of all the unique users from 10000 files using Hadoop?
  8. File could be replicated to 0 Nodes, instead of 1. Have you ever come across this message? What does it mean?
  9. How do reducers communicate with each other?
  10. How can you backup file system metadata in Hadoop?
  11. What do you understand by a straggler in the context of MapReduce
  1. Why Hadoop? (Compare to RDBMS)
  2. What would happen if NameNode failed? How do you bring it up?
  3. What details are in the “fsimage” file?
  4. What is SecondaryNameNode?
  5. Explain the MapReduce processing framework? (start to end)
  6. What is Combiner? Where does it fit and give an example? Preferably from your project.
  7. What is Partitioner? Why do you need it and give an example? Preferably from your project.
  8. Oozie – What are the nodes?
  9. What are the actions in Action Node?
  10. Explain your Pig project?
  11. What log file loaders did you use in Pig?
  12. Hive Joining? What did you join?
  13. Explain Partitioning & Bucketing (based on your project)?
  14. Why do we need bucketing?
  15. Did you write any Hive UDFs?
  16. Filter – What did you filter out?
  17. HBase?
  18. Flume?
  19. Sqoop?
  20. Zookeeper?
  1. What is Hive variable
  2. What is Object inspector
  3. Please explain Consolidation in hive
  4. What are the differences between MapReduce and YARN
  5. Can you differentiate between Spark and MapReduce
  6. Explain RDD and data frames in spark
  7. Can you write the syntax for Sqoop import
  8. WHat do you know about Hive views
  9. Difference between Hive external table and Hive managed Table
  10. What are the differences between HBase and Hive
  11. What are Orderby, sortby, and clustered by
  12. What is Speculative execution
  13. Which all Alter column command in hive you have worked
  14. What is lazy evaluation in pig?
  15. What is dynamic partition and static partition in hive?
  16. What is the use of partitions and bucketing in hive?
  17. Explain the flow of MapReduce program?
  18. What is default partition in MapReduce and how can we override it?
  19. What is difference between key class and value class in MapReduce?
  20. What is the level of sub queries in hive?
  21. What is transformation and action in spark?
  1. What is heap error and how can you fix it?
  2. How many joins does MapReduce have and when will you use each type of join?
  3. What are sinks and sources in Apache Flume when working with Twitter data?
  4. How many JVMs run on a DataNode and what is their use?
  5. If you have configured Java version 8 for Hadoop and Java version 7 for Apache Spark, how will you set the environment variables in the basic configuration file?
  6. Differentiate between bash and basic profile.
  1. Garbage Collection in Java – How it works?
  2. Different Types of Comprassions in Hive?
  3. Job Properties in Oozie
  4. How do you ensure 3rparty Jar files are available in Data Nodes.
  5. How do you define and use UDF’s in Hive
  6. If we have 10GB and 10MB file, How do you load and process the 10 MB file in map-reduce
  7. What are Joins in Hive in Map-Reduce Paradigm
  8. Apart from Map-side and reduce side joins any other joins in map-reduce?
  9. What is Sort-merge-Bucketing?
  10. How do we test Hive in production?
  11. What is the difference between Hashmap and HashTable
  12. What is bucketing
  1. What are the differences between Hadoop and Spark?
  2.  What are the real-time industry applications of Hadoop?
  3. How is Hadoop different from other parallel computing systems?
  4. In what all modes Hadoop can be run?
  5. Explain the major difference between HDFS block and InputSplit.
  6. What is distributed cache? What are its benefits?
  7. Explain the difference between NameNode, Checkpoint NameNode, and Backup Node.
  8. What are the most common input formats in Hadoop?
  9. Define DataNode. How does NameNode tackle DataNode failures?
  10. What are the core methods of a Reducer?
  11. What is a SequenceFile in Hadoop?
  12. What is the role of a JobTracker in Hadoop?
  13. What is the use of RecordReader in Hadoop?
  14. What is Speculative Execution in Hadoop?
  15. How can you debug Hadoop code?
  1. How will you decide whether you need to use the Capacity Scheduler or the Fair Scheduler?
  2. What are the daemons required to run a Hadoop cluster?
  3. How will you restart a NameNode?
  4. Explain about the different schedulers available in Hadoop.
  5. List few Hadoop shell commands that are used to perform a copy operation.
  6. What is jps command used for?
  7. What are the important hardware considerations when deploying Hadoop in production environment?
  8. How many NameNodes can you run on a single Hadoop cluster?
  9. What happens when the NameNode on the Hadoop cluster goes down?
  10. What is the conf/hadoop-env.sh file and which variable in the file should be set for Hadoop to work
  11. Apart from using the jps command is there any other way that you can check whether the NameNode is working or not.
  12. Which command is used to verify if the HDFS is corrupt or not?
  13. List some use cases of the Hadoop Ecosystem
  14. I want to see all the jobs running in a Hadoop cluster. How can you do this?
  15. Is it possible to copy files across multiple clusters? If yes, how can you accomplish this?
  16. Which is the best operating system to run Hadoop?
  1. Explain Hadoop streaming?
  2. What is HDFS- Hadoop Distributed File System?
  3. What does hadoop-metrics.properties file do?
  4. How Hadoop’s CLASSPATH plays a vital role in starting or stopping in Hadoop daemons?
  5. What are the different commands used to startup and shutdown Hadoop daemons?
  6. What is configured in /etc/hosts and what is its role in setting Hadoop cluster?
  7. How is the splitting of file invoked in Hadoop framework?
  8. Is it possible to provide multiple input to Hadoop? If yes then how?
  9. Is it possible to have hadoop job output in multiple directories? If yes, how?
  10. Explain NameNode and DataNode in HDFS?
  11. Why is block size set to 128 MB in Hadoop HDFS?
  12. How data or file is written into HDFS?
  13. How data or file is read in HDFS?
  14. How is indexing done in HDFS?
  15. What is a Heartbeat in HDFS?
  16. Explain Hadoop Archives?
  1. Configure slots in Hadoop 2.0 and Hadoop 1.0.
  2. In case of high availability, if the connectivity between Standby and Active NameNode is lost. How will this impact the Hadoop cluster?
  3. What is the minimum number of ZooKeeper services required in Hadoop 2.0 and Hadoop 1.0?
  4. If the hardware quality of few machines in a Hadoop Cluster is very low. How will it affect the performance of the job and the overall performance of the cluster?
  5. How does a NameNode confirm that a particular node is dead?
  6. Explain the difference between blacklist node and dead node.
  7. How can you increase the NameNode heap memory?
  8. Configure capacity scheduler in Hadoop.
  9. After restarting the cluster, if the MapReduce jobs that were working earlier are failing now, what could have gone wrong while restarting?
  10. Explain the steps to add and remove a DataNode from the Hadoop cluster.
  11. In a large busy Hadoop cluster-how can you identify a long running job?
  12. When NameNode is down, what does the JobTracker do?
  13. When configuring Hadoop manually, which property file should be modified to configure slots?
  14. How will you add a new user to the cluster?
  15. What is the advantage of speculative execution? Under what situations, Speculative Execution might not be beneficial?
  1. What is Apache Hadoop?
  2. Why do we need Hadoop?
  3. What are the core components of Hadoop?
  4. What are the Features of Hadoop?
  5. Compare Hadoop and RDBMS?
  6. What are the modes in which Hadoop run?
  7. What are the features of Standalone (local) mode?
  8. What are the features of Pseudo mode?
  9. What are the features of Fully-Distributed mode?
  10. What are configuration files in Hadoop?
  11. What are the limitations of Hadoop?
  12. Compare Hadoop 2 and Hadoop 3?
  13. Explain Data Locality in Hadoop?
  14. What is Safemode in Hadoop?
  15. What is Safemode in Hadoop?
  16. What is a “Distributed Cache” in Apache Hadoop?
  17. How is security achieved in Hadoop?
  18. Why does one remove or add nodes in a Hadoop cluster frequently?
  19. What is throughput in Hadoop?
  20. How to restart NameNode or all the daemons in Hadoop?
  1. How will you initiate the installation process if you have to setup a Hadoop Cluster for the first time?
  2. How will you install a new component or add a service to an existing Hadoop cluster?
  3. If Hive Metastore service is down, then what will be its impact on the Hadoop cluster?
  4. How will you decide the cluster size when setting up a Hadoop cluster?
  5. How can you run Hadoop and real-time processes on the same cluster?
  6. If you get a connection refused exception - when logging onto a machine of the cluster, what could be the reason? How will you solve this issue?
  7. How can you identify and troubleshoot a long running job?
  8. How can you decide the heap memory limit for a NameNode and Hadoop Service?
  9. If the Hadoop services are running slow in a Hadoop cluster, what would be the root cause for it and how will you identify it?
  10. How many DataNodes can be run on a single Hadoop cluster?

Upcoming Batch Details

21
Feb
Hadoop Training in OMR
10:00 am - 11:00 am
OMR,Chennai
23
Feb
Hadoop Training in Velachery
11:00 am - 1:00 pm
Velachery,Chennai
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About Hadoop trainer

The flood of data is increased in everywhere, so the big data expert is needed for every organization to align the data with secure. We ensured our tutor having latest knowledge and hand on practical knowledge.
  • Our Big data tutor trained more than 1000+ candidates to become a certified expert.
  • Certified Big data Expert.
  • Our Tutor having more than 8+years working professional.
  • Multiple domain knowledge like Machine learning, Python, Data Science.
  • Experienced in more than 8+ real time projects.

Hadoop Combo Course

First of all, Big Data Hadoop is one of the latest technology which has been listed down in top technologies survey result as well. Also, this open-source distributed processing framework is been developed by Apache Software Foundation which combines different open-source software utilities.According to the latest need and requirements, we have been also providing the Hadoop Combo Course which is listed down as follows,
  • Hadoop + Spark
  • Hadoop + Data Analytics
  • Hadoop + Data Science

Hadoop Certification Details

Credo Systemz Hadoop certification course helps you learn the Hadoop certification syllabus with the help of experts from top IT firms. Likewise, this course will guide you into the professional way to work on each and every component with practical and real-time scenarios based sessions. Similarly, Our expert level certified trainers will help you to gain the required skillset to clear the examination easily.
The Hadoop Developer certification details is given below,
Exam CodeExam Name
CCA175 CCA Spark and Hadoop Developer
CCA159 CCA Data Analyst
CCA131 CCA Administrator
DE575 CCP Data Engineer

Cloudera Certification Exam Information

Here you go with details about the Hadoop Certification Cost and other details.
Exam Details
No of Questions8 to 12 Hands-on tasks to be carried out on a Cloudera Enterprise Cluster
Duration120 minutes for candidates answering in English language.
Pass mark70%

Scope of Hadoop in Future

First of all, Big data Hadoop is the best choice for everyone who is interested to shine in the world of Big data. Thsi is to say,there are multiple Career options are available in Big data Hadoop Such as Hadoop adminstration, Hadoop developer ,Hadoop Architect, Hadoop tester and Analytics. Currently Big data Hadoop people demand is huge shortage since data continuously increased in every seconds and also most of the MNC’s like TCS, Wipro are investing their application in Hadoop technology.
According to the survey Hadoop technology will achieve $99B by 2020. So Hadoop technology has the lot of scope in future. Thus, increasing the job opportunities for hadoop professionals to make an excellent career with better salary packages.

Hadoop Training with Placement in Chennai

Credo Systemz's Hadoop training course is designed by experienced experts who are also worked in the recruitment team of top MNC companies, hence our Hadoop certification topics consists of more number of practical sessions which guide you towards placements. Our Hadoop training Chennai Velachery is named for providing the best hands-on practical session training with real time case studies.
Check Out - Hadoop Assessment Part 1,Hadoop Assessment Part 2

Top Factors which makes us the Best Big Data Training Center in Chennai

  • Firstly, We are ranked as No.1 Best Hadoop Training institute in Chennai according to the reviews across the internet.
  • In addition, Offering Best Hadoop Certification Training in Chennai on both weekday and weekends at flexible timings.
  • Most Importantly our Hadoop Course in chennai provides you the latest updated topics.
  • Moreover, You can attend the Free Demo Session with our Hadoop Experts - Book Now.
  • Our Hadoop training in chennai, velachery and OMR course provides you the latest updated Hadoop topics from scratch.
  • Most importantly our Hadoop training and certification at Credo Systemz is handled by certified Experts.
  • In other words, Our Hadoop certification Training will guide you clear your certification exmas
  • On the other hand, job based Practical Oriented Hadoop training in chennai which makes you to strong in your technical skills.
  • Above all, referred as the Best Hadoop Certification Training in Chennai by our alumini.
  • To emphasize, you can get real time practical oriented Hadoop training with 100% placement assistance

Hadoop Interview Questions and Answers

FAQ

Have a look below the necessary technical skills for learning Hadoop for beginners
  • Must know about the basics concept of Java and Linux
  • Good Understanding of Database and SQL
  • Should have the good knowledge in mathematics and statics.
Also our Hadoop training program will starts from scratch which will be helpful to learn from basics easily.
In our Hadoop training program, our trainers will cover all the important tools required for a Hadoop to handle the data’s as a professional.
It includes the following,
  • Hadoop Distributed File System
  • MapReduce
  • Hbase
  • HIVE
  • PIG
  • Sqoop
  • Spark
  • OOZIE
If you are looking for some specific tools just reach us via +91- 9884412301.
Our Hadoop Course Duration is 45 to 50 hours which covers all the modules of Hadoop training. In this duration, we will give you more case studies to practices and You will get various levels of Hadoop assessments. You have to work on a real time Hadoop application Project.
Hadoop Development will be the best choice for both beginners and experienced professionals for a better career growth.
To know more check here the Hadoop Developer Career Path explained clearly with certification details.
Our Big Data Course is specially designed by Certified Experts.Most importantly, our big data course in chennai to enrich the career of an individual into a professional in handling the real time project. You will develop and maintains the Hadoop application Projects by individually and will able to clear your Hadoop Certification after completing our Hadoop certification in chennai.
YES!
After the course completion, We will conduct Three Mock Interviews. In the Three Mock Interviews, We will figure outs your Technical competence and where you need to Improve. So after the Mock Interviews, it will Increase your Confident Level for Cracking the Interview.
Sample Resume formats for All different Technologies.

Related Trainings

Nearby Access Areas
Our Velachery and OMR branches are very nearby access to the below locations.
Medavakkam, Adyar, Tambaram, Adambakkam, OMR, Anna Salai, Velachery, Ambattur, Ekkattuthangal, Ashok Nagar, Poonamallee, Aminjikarai, Perambur, Anna Nagar, Kodambakkam, Besant Nagar, Purasaiwakkam, Chromepet, Teynampet, Choolaimedu, Madipakkam, Guindy, Navalur, Egmore, Triplicane, K.K. Nagar, Nandanam, Koyambedu, Valasaravakkam, Kilpauk, T.Nagar, Meenambakkam, Thiruvanmiyur, Nungambakkam, Thoraipakkam, Nanganallur, St.Thomas Mount, Mylapore, Pallikaranai, Pallavaram, Porur, Saidapet, Virugambakkam, Siruseri, Perungudi, Vadapalani, Villivakkam, West Mambalam, Sholinganallur.
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