Introduction to Hadoop
Hadoop is an Apache project (i.e. an open source software) to
store & process Big Data. Hadoop Stores Big Data in a distributed
& fault tolerant manner over commodity hardware. Afterwards,
Hadoop tools are used to perform parallel data processing over
HDFS (Hadoop Distributed File System).
- Interactive training for better learning
- Pre-evaluation learn only what you need to learn
- Experienced and certified trainer
- Convenient weekday and weekend Batches available Demo.
- Timings for classes are arranged upon Flexibility of both the trainee and trainer.
- Access to the recorded videos which you have attended.
Understanding Big Data and Hadoop:
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1Introduction toBig Data & Big Data Challenges
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2Limitations & Solutions of Big Data Architecture
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3Hadoop & its Features
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4Hadoop Ecosystem
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5Hadoop 2.x Core Components
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6Hadoop Storage: HDFS (Hadoop Distributed File System)
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7Hadoop Processing: MapReduce Framework
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8Different Hadoop Distributions
Starting Course
Hadoop Architecture and HDFS:
After Intro
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20Realistic Graphic on UE4
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21Volta GPU for optimization.
The Tensor Core GPU Architecture designed to Bring AI to Every Industry. Equipped with 640 Tensor Cores, Volta delivers over 100 teraflops per second (TFLOPS) of deep learning performance, over a 5X increase compared to prior generation NVIDIA Pascal architecture.
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22Deep Learning
Hadoop MapReduce Framework:
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23Traditional way vs MapReduce way
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24Why MapReduce
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25YARN Components
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26YARN Architecture
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27YARN MapReduce Application Execution Flow
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28YARN Workflow
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29Anatomy of Map Reduce Program
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30Input Splits, Relation between Input Splits and HDFS Blocks
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31MapReduce: Combiner &Partitioner
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32Demo of Health Care Dataset
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33Demo of Weather Dataset
Apache Pig:
Apache Hive:
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47Introduction to Apache Hive
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48Hive vs Pig
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49Hive Architecture and Components
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50Hive Metastore
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51Limitations of Hive
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52Comparison with TraditionalDatabase
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53Hive Data Types and Data Models
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54Hive Partition
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55Hive Bucketing
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56Hive Tables (Managed Tables and External Tables)
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57Importing Data
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58Querying Data & Managing Outputs
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59Hive Script & Hive UDF
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60Retail use case in Hive
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61Hive Demo on Healthcare Dataset
Advanced Apache Hive and HBase:
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62Hive QL: Joining Tables, Dynamic Partitioning
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63Custom MapReduce Scripts
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64Custom MapReduce Scripts
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65Hive Query Optimizers
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66Hive Thrift Server
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67Hive UDF
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68Apache HBase: Introduction to NoSQL Databases and HBase
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69HBase v/s RDBMS
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70HBase Components
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71HBase Architecture
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72HBase Run Modes
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73HBase Configuration
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74HBase Cluster Deployment
Processing Distributed Data with Apache Spark:
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View the recorded session of the class available in your LMS.
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View the recorded session of the class available in your LMS.
You can attend the missed session, in any other live batch."
Your access to the Support Team is for lifetime and will be available 24/7. The team will help you in resolving queries, during and after the course.
Post-enrolment, the LMS access will be instantly provided to you and will be available for lifetime. You will be able to access the complete set of previous class recordings, PPTs, PDFs, assignments. Moreover the access to our 24x7 support team will be granted instantly as well. You can start learning right away.
Yes, the access to the course material will be available for lifetime once you have enrolled into the course.
We have limited number of participants in a live session to maintain the Quality Standards. So, unfortunately participation in a live class without enrollment is not possible. However, you can go through the sample class recording and it would give you a clear insight about how are the classes conducted, quality of instructors and the level of interaction in a class.
All the instructors at MITS are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are trained by MITS for providing an awesome learning experience to the participants.
In today’s data driven world, organizations are relying on the data. They are analysing & deriving meaningful insights from voluminous amount of data i.e. Big Data. As Big Data Market is projected to grow from $42B in 2018 to $103B in 2027, companies will look for professionals who can design, implement, test & maintain the complete Big Data infrastructure. Hadoop being the de-facto for storing & processing Big Data it is the first step towards Big Data glorious Journey. So, if you are planning to make a career in Big Data domain, now is the right time to start with Hadoop Administration Certification Training.
MITS Hadoop Administration Certification Training is designed by subject matter experts which covers comprehensive knowledge on planning Hadoop cluster, Hadoop installation, Hadoop cluster configuration, cluster monitoring and performance tuning. You will learn each & every nuance of the technology with the help hands-on & real-world case-studies.
Organizations have realized the importance of Big Data, & the market of Hadoop is growing exponentially. Technology Giants & MNCs such as Amazon.com Services, Expedia, JP Morgan Chase, Splunk, Visa, SAP, Oracle, Apple are hunting for professionals who can design, test & manage Hadoop clusters. Now is the right time to get a certification in Hadoop Administration and stand a chance to grab your dream job.
Organisations are seizing Big Data projects to gain a competitive edge. Enterprises that do not embrace Big Data will lose their competitive edge in a decade. As Big Data sources are growing, the opportunities for professionals are also increasing. Organisations are looking for professionals who can build, manage & perform administrative tasks on Big Data clusters. If you are planning to pursue a career in Big Data domain, now is the right time to get certified in Hadoop Administration.
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