HdfsTutorial’s Hadoop Developer Online training helps you gain expertise in Big Data Hadoop. You will learn how Hadoop is successfully solving the Big Data problem. In this Hadoop online training we will learn the components like MapReduce, HDFS, Pig, Hive, Sqoop, Flume, Oozie, YARN, Hbase and several other Hadoop ecosystems.
The course has been designed considering the industry needs and we focus a lot on the practical approach. We also provide 100% placement assistance with this Hadoop Developer Training.
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Why Learn Hadoop Development From HDFSTutorial?
HDFSTutorial is a leading online training provider worldwide on the leading and latest technologies and business processes. Here are some of the unique features of HDFSTutorial’s Hadoop Developer online training course.
Hadoop Developer Online Training Course Description
The HdfsTutorial’s Hadoop Developer online training course is job oriented. It has been developed by considering the industry needs and candidates’ expectations.
About the Hadoop Developer Online Training Course
HdfsTutorial’s Hadoop Developer online Training course has been designed by industry experts from Hadoop Architects. All the trainers have rich IT experience and are working since long in the industry on Hadoop and related technologies. They also possess wide teaching experience and will help you with industry projects and requirements.
HdfsTutorial’s Hadoop Developer online training course will make you an expert in Big Data Hadoop. You will be working on different projects to understand end-to-end development and analytics related work in Big Data and Hadoop.
The course will begin by explaining the architecture and components of Hadoop along with clusters, security, access levels and multiple other things.
You’ll see how companies are using Hadoop to manage their huge amount of data in an effective way. Also, you’ll learn how to define the insight from the huge amount of data and make business decisions.
At the end of the HdfsTutorial’s Hadoop Development training course, you will be presented with a certificate which will show you as a Hadoop Development expert. Our certificate is trusted by many companies.
Training Objective
- HdfsTutorial’s Hadoop Developer online training course’s main objective is to make you a Hadoop expert. After completing this course, you will be able to-
- • Master the concepts of Hadoop and related ecosystems• Understand Hadoop 1.x, Hadoop 2.x, and what new is coming in Hadoop 3.x• Setup Hadoop Cluster and write Complex MapReduce programs• Learn data loading techniques using Sqoop and Flume• Perform data analytics using Pig, and Hive• Implement HBase and MapReduce integration• Implement Advanced Analytics on top of the data• Schedule jobs using Oozie• Query optimization and resource planning• Understand Spark and its Ecosystem• Learn how to work in RDD in Spark• Work on a real-life Project on Big Data Analytics
Why Learn Hadoop?
- Big Data & Hadoop Market is expected to reach $99.31 Bn by 2022 growing at a CAGR of 42.1% from 2015 – ForbesMcKinsey predicts that by 2018 there will be a shortage of 1.5 Mn data experts – Mckinsey ReportAverage Salary of Big Data Hadoop Developers is $110k (Payscale salary data)
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Over 50k+ MNCs spread across 185+ countries are using Hadoop to manage their huge amount of data. These companies include TCS, Deloitte, EY, PWC, CTS, Accenture, etc. among 50,000+ companies.
Who should take this Training?
HdfsTutorial’s Hadoop Adminstration online training course has been developed for anyone who wants to enter the data field. They can be from Big data, Data Analytics, and Data Science fields. Roles can include but are not limited to-
- I. Developers and ArchitectsII. BI /ETL/DW professionals. Senior IT Professionals. Testing professionals. Mainframe Professional VI. Freshers
What are the prerequisites for taking this Training Course?
Although you don’t need anything special, if you have some SQL/Java knowledge then it will be an additional advantage for you.
Hadoop Developer Training Curriculum
- Module-1
- Module-2
- Module-3
- Module-4
- Module-5
- Module-6
- Module-7
- Module-8
- Projects/Real-Time Case Studies
- Module-9
- Module-10
- Module-11
- Module-12&13
- Module- 14&15
Module-1: Introduction to BigData, Hadoop (HDFS and MapReduce)
- 1. BigData Inroduction2. Hadoop Introduction3. Hadoop components4. HDFS Introduction5. MapReduce Introduction
Module 2: Deep Dive in HDFS
- 1. HDFS Design and Architecture 2. Fundamentals of HDFS (Blocks, NameNode, DataNode, Secondary Name Node) 3. Rack Awareness 4. Read/Write from HDFS 5. HDFS Federation and High Availability (Hadoop 2.x.x) 6. Parallel Copying using DistCp 7. HDFS Command Line Interface
Module 3: HDFS File Operation Lifecycle
- 1. File Read Cycle from HDFS- DistributedFileSystem- FSDataInputStream2. Failure or Error Handling When File Reading Fails3. File Write Cycle from HDFS- FSDataOutputStream4. Failure or Error Handling while File write fails
Module 4: Understanding MapReduce
1. JobTracker and TaskTracker2. Topology Hadoop cluster3. Example of MapReduce- Map Function- Reduce Function4. Java Implementation of MapReduce5. DataFlow of MapReduce6. Use of Combiner
Module 5: Deep Dive to MapReduce
- 1. How MapReduce Works2. Anatomy of MapReduce Job (MR-1)3. Submission & Initialization of MapReduce Job (What Happen ?)4. Assigning & Execution of Tasks5. Monitoring & Progress of MapReduce Job6. Completion of Job7. Handling of MapReduce Job- Task Failure- TaskTracker Failure- JobTracker Failure
Module 6: MapReduce-2 (YARN : Yet Another Resource Negotiator Hadoop 2.x.x )
1. Limitation of Current Architecture (Classic)2. What are the Requirement ?3. YARN Architecture4. JobSubmission and Job Initialization5. Task Assignment and Task Execution6. Progress and Monitoring of the Job
Module 7: Failure Handling in YARN
- 1. Task Failure2. Application Master Failure3. Node Manager Failure4. Resource Manager Failure
Module 8: Apache Pig
- 1. What is Pig ?2. Introduction to Pig Data Flow Engine3. Pig and MapReduce in Detail4. When should Pig Used ?5. Pig and Hadoop Cluster6. Pig Interpreter and MapReduce7. Pig Relations and Data Types8. PigLatin Example in Detail9. Debugging and Generating Example in Apache Pig
Projects & Real-Time Case Studies
You will be working on industry projects which will help you become an expert in Hadoop Administration. Here are the few projects you will work.
- 1. Setup a minimum 2 Node Hadoop Cluster with AWS/Cloudera/HortonWorks
- Node 1 – Namenode, JobTracker, datanode, tasktrackerNode 2 – Secondary namenode, datanode, tasktracker2. Create a simple text file and copy to HDFS- Name it as firstfile.txt
- Locate the node where the file has been copied in HDFSAfter operation find on which datanode, output data is written3. Create a large text file and copy to HDFS with a block size of 256 MB. Keep all the other files in default block size and find how block size has an impact on the performance.4. Set a spaceQuota of 200MB for projects and copy a file of 70MB with replication=2Identify the reason the system is not letting you copy the file?How will you solve this problem without increasing the spaceQuota?5. Configure Rack Awareness and copy the file to HDFS
- Find its rack distribution and identify the command used for it.Find out how to change the replication factor of the existing file. The final certification project is based on real world use cases as follows:Problem Statement 1:1. Setup a Hadoop cluster with a single node or a 2-node cluster with all daemons like namenode, datanode, JobTracker, tasktracker, a secondary namenode that must run in the cluster with block size = 128MB.2. Write a Namespace ID for the cluster and create a directory with name space quota as 10 and a space quota of 100MB in the directory.3. Use the distcp command to copy the data to the same cluster or a different cluster, and create the list of data nodes participating in the cluster. Problem statement 2:1. Save the namespace of the Namenode, without using the secondary namenode, and ensure that the edit file merge, without stopping the namenode daemon.2. Set include file, so that no other nodes can talk to the namenode.3. Set the cluster re-balancer threshold to 40%. 4. Set the map and reduce slots to s4 and 2 respectively for each node.
Module-9A: Apache Hive
- 1. What is Hive ?2. Architecture of Hive3. Hive Services4. Hive Clients5. how Hive Differs from Traditional RDBMS6. Introduction to HiveQL7. Data Types and File Formats in Hive8. File Encoding9. Common problems while working with Hive
Module-9B: Advanced Deep Dive To Apache Hive
- 1. HiveQL2. Managed and External Tables3. Understand Storage Formats4. Querying Data- Sorting and Aggregation- MapReduce In Query- Joins, SubQueries and Views5. Writing User Defined Functions (UDFs)3. Data types and schemas4. Querying Data5. HiveODBC6. User-Defined Functions
Module-10: HBase Basics & Advanced
- 1. Fundamentals of HBase2. Usage Scenario of HBase3. Use of HBase in Search Engine4. HBase DataModel- Table and Row- Column Family and Column Qualifier- Cell and its Versioning- Regions and Region Server5. HBase Designing Tables6. HBase Data Coordinates7. Versions and HBase Operation- Get/Scan- Put- Delete8. Hive Hbase Integration9. HBase Analytics Tools Integration
Module-11: Apache Oozie
- 1. Sqoop Tutorial2. How does Sqoop Work3. Sqoop JDBCDriver and Connectors4. Sqoop Importing Data5. Various Options to Import Data- Table Import- Binary Data Import- SpeedUp the Import- Filtering Import- Full DataBase Import Introduction to Sqoop
Module-12: Apache Flume
- 1. Data Acquisition : Apache Flume Introduction2. Apache Flume Components3. POSIX and HDFS File Write4. Flume Events5. Interceptors, Channel Selectors, Sink Processor
Module-13: Apache Oozie
- 1. Introduction to Oozie2. Creating different jobs– Workflow- Co-ordinator- Bundle3. Creating and scheduling jobs for different components
Module-14: Advanced Big Data & Analytics
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Module-15: 100% Job Placement Assistance
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FAQs
How can I get certification from HdfsTutorial?
After the completion of the course, your performance and projects will be evaluated by the experts of the HdfsTutorial team. After that, you will get the HdfsTutorial Hadoop Administration certificate which you can show in your resume.
What If I Missed a Live Class?
We provide the free access to our LMS which consists of the recording of the live class. You can check that video to catch the class. Also, we have other batches going on where you can attend and cover the missed part.
Can I Get Placement Assistance?
HdfsTutorial is committed to getting your dream job and our dedicated team will help you get the one. We provide 100% placement assistance. Once your course is 70% complete, our team will start working on your resume and interviews.
Who are all the Instructors?
All our instructors are highly qualified, highly experienced, and have great teaching experience. Most of our instructors are an architect and they share the real-time and actual problem faced by the employees.
What About Support & Quires?
HdfsTutorial provides 24×7 support through email and forum. You can email us your questions/doubts on Info@hdfstutorial.com and our team will resolve your query in 24 hours. And this support is completely free.
Do you Provide Business/Corporate Training?
Yes, we also provide corporate training. If you are looking for the same, please email us at Info@hdfstutorial.com.
Reviews From Our Earlier Students
Philip Westing
Worked as Linux Admin
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I was working as a Linux Admin and wanted to learn Hadoop Administration to enhance my skills and switch the job. I can say, the HdfsTutorial team provided an amazing training on Hadoop Administration. I worked on multiple project and happy to say, I was able to change my job in Hadoop Admin field.
Kanak Yadav
Windows Administrator
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I was working as a Windows admin in HCL and thought to learn Hadoop Admin for better career prospective. I joined HdfsTutorial’s Online session and now I am serving the notice in my company.I received a good offer from another MNC in Noida.