- Hadoop Cluster Architecture
- Production cluster setup
- High Availability and Federation
- Hadoop shell commands
- Installation of a single-node cluster
- Configuring files in Hadoop
- Scala, Spark, Sqoop, Flume, and Pig
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Big Data Hadoop Course
Join Intellipaat’s Big Data Hadoop Certification Training to ace Cloudera Big Data Certification (CCA175). Learn Hadoop, Big Data Analytics, and Apache Spark.
Online
₹ 22,743 25,593
Quick facts
particular | details | |||
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Collaborators
IBM
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Medium of instructions
English
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Mode of learning
Self study, Virtual Classroom
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Mode of Delivery
Video and Text Based
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Frequency of Classes
Weekdays, Weekends
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Course overview
The Big Data Hadoop Course by Intellipaat, in collaboration with IBM, is tailored to make you an expert in Hadoop, the various components of its ecosystem, Big Data, and Spark. Industry experts with relevant field experience curate a diverse course curriculum for you. The curriculum strategically encompasses fundamentals as well as advanced tools such as Pig, Hive, and Oozie.
Further, the Big Data Hadoop Course will enable you to master Amazon EC2, Resilient Distributed Datasets, Spark framework, Spark SQL and Scala, and ML using Spark, and more. Built to provide you with both theoretical and practical training, the programme houses a total of 14 industry-based projects that will let you implement your newly acquired skills.
Besides, the Big Data Hadoop Course also features engaging content, instructor-led sessions, and self-paced training. Intellipaat also assists you through their job assistance feature with resume and interview preparation. Upon satisfactorily completing the course, you will receive a course completion certificate from Intellipaat.
The highlights
- Instructor-led sessions
- Self-paced training option
- 80 hours of self-paced videos
- 60 hours of instructor-led training
- Graduation certificate
- Online classroom training
- 120 hours of course project
- Complimentary Java and Linux courses
- Doubt clearance sessions
- Schedule flexibility
- Job assistance
- 24 x 7 technical assistance
Program offerings
- Instructor-led training
- Industry based practical project
- Hands on training
- Online learning
- Self paced training module
- Graduation certificate
- Job assistance
- Flexible training
- Interview preparations
- Complimentary java and linux courses
Course and certificate fees
Fees information
The fee for the Big Data Hadoop Training and Certification can be paid as a whole or in installments. The net payable fee for the course also includes tax- GST. Routinely, Intellipaat also offers variable discounts on the course fee from time to time. Further, if any, you can apply the coupon code for an additional discount.
Big Data Hadoop Certification Training Course Fee Details:
Payment Method | Amount in INR |
Online Classroom Training | Rs. 22,743* (plus GST) |
Self-paced Training | Rs. 15,048 (plus GST) |
*Mentioned fees are discounted which is limited for a time period the original fee will be Rs. 25,593
certificate availability
certificate providing authority
Eligibility criteria
There is no specific eligibility criterion to enroll in the Intellipaat Big Data Hadoop Certification Training Course. However, it is advantageous to know UNIX, Java, and SQL fundamentals and the basics of programming. Besides, to help you fine-tune these necessary skills, Intellipaat offers you complimentary Linus and Java courses.
Certificate Qualifying Details
To earn the Intellipaat course completion certification, you have to complete all assigned projects and assignments satisfactorily. The trainers will duly review your projects. Further, you must score at least 60 percent in the exam.
What you will learn
Upon completion of the Big Data Hadoop course, you will be adept in skills like: -
- Write applications using Hadoop and Yarn.
- Perform cluster set up- multi-node and pseudo-node on Amazon EC2.
- Work with MapReduce, Oozie, Hadoop Distributed File System, Hive, Sqoop, Pig, ZooKeeper, Flume, and HBase.
- Configure ETL tools such as Pentaho to work with Hive and MapReduce, among others.
- Develop the ability to work with different data formats of Apache Avro.
- Perform various Hadoop administration techniques such as troubleshooting, managing, and monitoring of clusters.
- Test Hadoop applications with the help of automation tools such as MRUnit.
- Acquire knowledge of various tools such as Spark, Streaming, RDD, MLib, DataFrame, and Spark SQL.
Who it is for
The Big Data Hadoop Course by Intellipaat is recommended for the following professionals: -
- Programming Developers
- Experienced working professionals
- System Administrators
- Senior IT Professionals
- Project Managers
- Mainframe Professionals
- Solution Architects
- Big Data Hadoop Developers wanting to learn verticals like administration, analytics, and testing
- Testing Professionals
- Data Warehousing Professionals
- Data Analytics Professionals
- Business Intelligence Professionals
- Big Data Enthusiasts
Admission details
To enrol in the Big Data Hadoop course by Intellipaat, follow these steps:
- Go to the official website
- Now, browse the website for the “Big Data Hadoop Certification Training” course.
- You will be redirected to the programme web page, where you can locate the “Enroll Now” tab.
- You will be taken to the fee section when you click on the tab. You have different options to select from as per your preference.
- You can opt for a batch from the available online classroom batches and click on the tab.
- A prompt to “Checkout” will appear on your screen. Click on it.
- Log in to your Facebook/Google/Intellipaat account to proceed further.
- Choose a convenient payment method. Make the payment and download the transaction receipt.
Filling the form
To enrol in the Intellipaat Big Data Hadoop Certification Course, log in with your Facebook/Google/Intellipaat account on Intellipaat. Select the course of choice and the learning mode. To view the billing details, proceed to the checkout. Choose the form of payment and render the amount successfully to validate enrolment.
The syllabus
Installation and Setup of Hadoop
MapReduce
- Working mechanism
- Sort
- Input Format
- Mapping and reducing stages
- Output Format
- Combiners
- Partitioners
- Shuffle
Big Data Hadoop, MapReduce, and HDFS Intro
- Big Data
- MapReduce
- How Hadoop helps?
- YARN
- HDFS
Hive
- Hadoop Hive
- Create a database, group, and table
- Architecture of Hive
- Buckets
- Hive with Pig and RDBMS
- Work with HQL
- Store Hive Results
- HCatalog
- Hive partitioning
Impala and Advanced Hive
- Hive Indexing
- Work with complex data types
- The ap Side Join in Hive
- Hive UDFs
- Hive vs Impala
- Impala
- Impala Architecture
Pig
- Hive data types and schema
- Apache Pig
- Functions in Pig, Tuples, Fields, and Hive Bags
Sqoop, HBase, Flume
- Apache Sqoop
- CAP theorem
- Performance improvement
- Import and export data
- Limitations of Sqoop
- Architecture of Flume
- Flume
- HBase
Write Spark Apps Using Scala
- Scala
- Use Scala to write Apache Spark apps
- Need for Scala
- Execute the Scala code
- Concept of OOPs
- Spark and Hadoop ecosystem
- Classes in Scala
- Functional programming
- Interoperability of Java and Scala
- Anonymous functions
- Mutable vs immutable collections
- Bob Rockets package
- Scala REPL
- Control Structures in Scala
- Lazy Values
- Directed Acyclic Graph
- Spark Web UI
- First Spark app using SBT/Eclipse
Spark Framework
- Scala
- Apache Spark
- Spark components
- Spark vs Hadoop
- Combining HDFS with Spark
- Need for Scala and RDD
Spark RDD
- Types of RDD operations
- Key/Value pair
- Spark RDD operations
- Spark transformation
- Spark vs MapReduce
- Loading data in Spark
Spark SQL and DataFrames
- Spark SQL
- JSON support
- Significance of SQL in working with structured data processing
- Work with XML data
- Create a Hive Context
- Spark SQL UDFs
- Work with parquet files
- Write DataFrame to Hive
- Data conversion from DataFrame to JDBC
- Significance of a Spark data frame
- Deployment of Hive on Spark
- Reading a JDBC file
- Creating a data frame
- Working with CSV files
- JDBC table reading
- Schema manual inferring
- Querying and transforming data in DataFrames
MLib
- Spark MLlib
- Graph processing analysis
- Spark iterative algorithm
- K-Means clustering
- Decision tree
- Accumulators
- K-means clustering
- MLib supported ML algorithms
- Linear regression
- Machine Learning
- Random forest
- Spark variables
- Logistic regression
Apache Flume and Apache Kafka Integration
- Kafka
- Apache Flume and Kafka integration
- Workflow of Kafka
- Kafka architecture
- Kafka cluster configuration
- Kafka monitoring tools
- Basic operations
Hadoop Administration
- Work with the Cloudera Manager setup
- Running the MapReduce code
- Run MapReduce Jobs
- Creating a four-node Hadoop cluster setup
Spark Streaming
- Spark streaming
- Spark streaming program working
- Spark streaming architecture
- Stateful operators
- Data processing with Spark streaming
- Multi-batch and sliding window operations
- Request count and DStream
- Windowed operators
- Work with advanced data sources
- The workflow of Spark Streaming
- Spark streaming features
- DStreams
- DStreams Transformations
- Input DStreams and Receivers
- DStreams Output Operations
Cluster Configuration
- Hadoop configuration
- Parameters and values of configuration
- Edit log
- Hadoop configuration file importance
- HDFS parameters
- Setup the Hadoop environment
- MapReduce parameters
- Include and Exclude configuration files
- Data node directory structures
- Maintenance and administration of name node
- File system image
Hadoop Ecosystem and ETL Connectivity
- Big Data integration with ETL tool
- Working of ETL tools
- Work with Big Data in the ETL industry
- ETL and data warehousing
- End-to-end ETL PoC
Monitoring, Maintenance, Troubleshooting
- Adding and removing nodes
- Checkpoint procedure
- Safe Mode
- Name node failure
- Metadata and Data backup
Project Discussion and Cloudera Certification Guidance
- Possible solution outcomes
- The solution of the Hadoop project
- Problem statements
- Focus points for scoring the highest marks
- Preparing for Cloudera certifications
- Tips to crack Hadoop interview questions
Hadoop Application Testing
- Importance of testing
- Integration testing
- Unit testing
- Performance testing
- Functional testing
- Benchmark and end-to-end tests
- Release testing
- Release certification testing
- Scalability testing
- Security testing
- Decommissioning and commissioning
- Reliability testing
MRUnit for Testing of MapReduce Programs
- Reporting defects to the development team
- Consolidate defects and creating defect reports
- Creating a testing framework called MRUnit
Hadoop Testing Professional
- The Requirement
- Test Data
- Testing Estimation Preparation
- Defect Reporting
- User Authorisation and Authentication testing
- Test Cases
- Reporting defects to the development team
- Test Execution
- Defect Retest
- Validating issues and features in Core Hadoop
- Test Bed Creation
- Daily Status report delivery
- Consolidating defects and creating defect reports
- ETL testing
- Test completion
- Reconciliation
Unit Testing
- Automation testing with OOZIE
- Data validation with the query surge tool
Writing Test Cases and Test Plan Strategy
- Test
- Install
- Configure
Test Execution
- HDFS upgrade test plan
- Test automation and result
How it helps
Intellipaat's Big Data Hadoop Course lets you gain mastery of Big Data with the Hadoop and Spark ecosystem. The programme is delivered by field professionals with expertise in the Big Data domain. You will achieve fluency in advanced topics such as Spark Streaming, clustering on Amazon EC2, MLib, Pentaho configuration, Hadoop testing, Hadoop analytics, and Spark SQL, among others.
Furthermore, the Online Big Data Hadoop Training Course prepares you for the CCA 175 examination, which is the Cloudera CCA Spark and Hadoop Developer Certification. The credential will provide your career with excellent acceleration and highlight the relevance of your skills. Besides, obtain excellent learning results with one-on-one doubt sessions and a flexible schedule. There are many features in the course, such as job assistance and directed assignments, which will provide you with practical experience in working with Hadoop and Spark.
FAQs
There are several Hadoop Certifications, and one such popular certification is the Cloudera Hadoop Developer Certification. You can prepare for the same by enrolling in the Big Data Hadoop Certification Training by Intellipaat.
No, you do not require advanced-level programming knowledge to learn Hadoop. The basics of programming are, however, necessary.
Big Data is a promising platform for processing vast quantities of data for data mining. Besides, large multinationals are making a switch towards Big Data Hadoop, certified Big Data professionals are in huge demand. Thus, the Big Data Hadoop Training and Certification allows you to be up and running with the most demanding technical skills.
For the Big Data Hadoop Certification Training course, you can opt for either self-paced or online classroom training. However, the online classroom training has additional features over self-paced training such as one-on-one query resolution and doubt clearance that make it more desirable.
While Hadoop is a database framework, Python is a programming language. The Hadoop Ecosystem is unrelated to Python in these terms. Several companies prefer using Python with Hadoop to write its framework.