Master the MapReduce programming model. Enroll today to get training from a MapReduce expert.
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Corporate Served- MapReduce is a licit programming model and an associated implementation for processing and initiating big data sets with a parallel, distributed algorithm on a cluster. In fact, you will find these specific applications scripting applications that can process huge amounts of data across the clusters of in-expensive nodes. Hadoop MapReduce is the processing part of Apache Hadoop. It is also referred as the heart of Hadoop.
- It is the most preferred data distilling application. Huge establishments like Amazon, Yahoo, Zuventus, etc. are utilizing the MapReduce platform for high volume data processing. In the present scenario, it is one of the most demanding courses in Big Data Hadoop field, and acquiring its accreditation will help you to uplift your career in various ways. And regarding it’s training Croma Campus would be the appropriate place for you.
- Things you will learn:
- Here, you will receive a detailed sort of training concerning several instances. Along with theoretical training, you will also be given practical training respectively.
Here, you will find a wide range of courses belonging from different industries.
Along with training, here, you will be able to acquire its prerequisites as well.
Our trainers will also give you the flexibility to acquire training via online/offline medium both.
We will also assure you 100% placement.
MapReduce Certification Training
- Croma Campus is immensely popular because of its exceptional offerings like high-quality training, placement offers. Moreover, it also makes you aware of its latest trends.
By enrolling in our certification program, you will get the opportunity to have a strong base knowledge concerning this subject.
In fact, our trainers will thoroughly guide you to the main concepts of MapReduce and Big Data, and their implementations.
Further, you will be explained the detailed information regarding the MapReduce framework.
You will also receive sessions regarding executing non-Java programs.
Moreover, utilization of HDFS will also get cleared.
- By acquiring this valuable accreditation, you will get a decent salary structure right from the beginning.
Post acquiring its minute details, you will always stand out differently from your peers.
You will receive immense respect from your colleagues, and senior officials.
Well, at the beginning your salary package will be around- 2,71,000-3,71,000 respectively, which is eventually good for starters.
With time and experience, your salary bracket will eventually get increased.
Moreover, you will also end up acquiring a higher place in your direction.
- Big Data Hadoop is one of the leading fields and has a bright scope ahead as well. Choosing this direction will only give you ample opportunities to acquire the latest facts and features concerning this technology.
By acquiring this important accreditation, you will be able to work as a Hadoop Administrator, Hadoop Developer, Machine Learning Engineer, Big Data Architect, and Big Data Consultant respectively.
There are different sorts of certifications as well. And our trainers will briefly tell you about that accreditation in detail.
By obtaining this accreditation along with higher-level certifications, you will be able to secure a much higher place in an organization.
You will also get the chance to lead the team and make business-driven decisions for your company.
Moreover, you will also get the opportunity to learn new things.
- There are several valid reasons to acquire this accreditation, and one of the significant ones is its high demand, and scope in the coming years.
It's quite a cost-effective way.
By learning its details, and features, you will be able to secure your applications with a different aspect.
Furthermore, you will be able to implement parallel processing respectively.
This specific technology is quite easy to handle, and with its simple structure, you will be able to execute your tasks smoothly.
By obtaining this accreditation in hand, you will be able to sustain yourself in this field in the long run.
- A MapReduce Programmer has to execute a lot of things. If you also aspire to turn into a good MapReduce Programmer, then you should know its duties beforehand.
You will have to execute the dataset across Mapper, and Reducer.
Your job role will also comprise of executing tasks on the slave node.
In fact, you will also have to handle Hadoop Distributed File System effectively.
Furthermore, you will also have to solve job requests from the clients.
In a way, you will have to understand the functioning of its numerous elements to come up with effective results respectively.
- Today many firms are always looking for MapReduce experts that can help them utilize the power of this magnificent programming model/ framework. This is why firms that use this framework for data processing don’t hesitate to give a decent amount of money to MapReduce experts who can help them use this framework without any difficulty.
- Top hiring companies for MapReduce professionals:
Impetus, Capgemini, TCS, Accenture, etc., are the top-most companies hiring skilled candidates.
Moreover, by graduating from our institution, you will be able to get settled in this direction easily.
In fact, you will end up grabbing a good decent salary package as well.
Here, you will also get the chance to obtain hidden facts concerning this subject.
Your every query will also get solved.
You will imbibe some latest trends, and features as well.
- Once you complete the MapReduce certification training program, you will become proficient in working with this phenomenal software framework/programming model. Furthermore, you will get a MapReduce training completion certificate. This will help you stand out from the rest of the candidates in front of recruiters and help you quickly get a job as a MapReduce expert/programmer in a good company.
- Advantages of getting certification:
You will find our every accreditation being extensively acknowledged in the industry.
Apart from technical courses, here at Croma Campus, you will get 140+ courses belonging to different sections.
Here, our trainers will not only impart information but will enhance your communication skills as well.
Our trainers will also make you aware of its relevant higher-level accreditation also.
By obtaining this certification, you will see positive growth in your career graph.
Why you should choose MapReduce Programmer certification?
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Course Duration
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CURRICULUM & PROJECTS
MapReduce Certification Training
- Master various popular Hadoop Frameworks and make yourself stand out in the IT and the Big Data space.
- List of Popular Hadoop Frameworks covered in the course:
Apache PIG Framework
Apache Spark with Scala Framework
Apache HIVE Framework
Apache SQOOP Framework
Apache Hbase Framework
Apache Flume Framework
Apache Drill Framework
Apache Kafka Framework
Apache Storm Framework
- Pig is a high-level platform for creating MapReduce programs used with Hadoop. The language for this platform is called Pig Latin. In this course we will go through the PIG data flow platform and the language used by PIG tool.
- Things you will learn:
Introduction
PIG Architecture
Data Models, Operators, and Streaming in PIG
Functions in PIG
Advanced Concepts in PIG
- Introduction
Big Data Overview
Apache Hadoop Overview
Hadoop Distribution File System
Hadoop MapReduce Overview
Introduction to PIG
Prerequisites for Apache PIG
Exploring use cases for PIG
History of Apache PIG
Why you need PIG
Significance of PIG
PIG over MapReduce
When PIG suits the most
When to avoid PIG
- PIG Architecture
PIG Latin Language
Running PIG in Different Modes
PIG Architecture
GRUNT Shell
PIG Latin Statements
Running Pig Scripts
Utility Commands
- Data Models, Operators, and Streaming in PIG
PIG Data Model- Scalar Data type
PIG Data Model - Complex Data Type
Arithmetic Operators
Comparison Operators
Cast Operators
Type Construction Operator
Relational Operators
Loading and Storing Operators
Filtering Operators
Filtering Operators-Pig Streaming with Python
Grouping and Joining Operators-
Sorting Operator
Combining and Splitting Operators
Diagnostic Operators
- Functions in PIG
Eval Functions
Load and Store Functions
Tuple and Bag Functions
String Functions
Math Function
- Advanced Concepts in PIG
File compression in PIG
Intermediate Compression
Pig Unit Testing
Embedded PIG in JAVA
Pig Macros
Import Macros
Parameter Substitutions
- Things you will learn:
Introduction
Scala
Using Resilient Distributed Datasets
Spark SQL, Data Frames, and Data Sets
Running Spark on a cluster
Machine Learning with Spark ML
Spark Streaming
Graph X
- Introduction
Big Data Overview
Apache Hadoop Overview
Hadoop Distribution File System
Hadoop MapReduce Overview
Introduction to IntelliJ and Scala
Installing IntelliJ and Scala
Apache Spark Overview
What’s new in Apache Spark 3
- Using Resilient Distributed Datasets
Scala Basics
Flow control in Scala
Functions in Scala
Data Structures in Scala
- Using Resilient Distributed Datasets
The Resilient Distributed Dataset
Ratings Histogram Example
Key / Value RDD's, and the Average Friends by Age example
Filtering RDD's, and the Minimum Temperature by Location Example
Check Your Results and Implementation Against Mine
- Spark SQL, Data Frames, and Data Sets
Introduction to Spark SQL
What are Data Frames
What are Data Sets
Item-Based Collaborative Filtering in Spark, cache (), and persist ()
- Running Spark on a cluster
What is a Cluster
Cluster management in Hadoop
Introducing Amazing Elastic MapReduce
Partitioning Concepts
Troubleshooting and managing dependencies
- Machine Learning with Spark ML
Introducing MLLib
Using MLLib
Linear Regression with MLLib
- Spark Streaming
Spark Streaming
The DStream API for Spark Streaming
Structured Streaming
- Graph X
What is Graph X
About Pregel
Breadth-First-Search with Pregel
Using Pregel API with Spark API
- Things you will learn:
Introduction
Installing and Configuring HIVE
Working on HIVE
HIVE Implementation
- Introduction
Big Data Overview
Hadoop Overview
What is a Hadoop Framework
Types of Hadoop Frameworks
What is Hive
Motivation Behind the Tool
Hive use cases
Hive Architecture
Different Modes of HIVE
- Installing and Configuring HIVE
Downloading, installing, and configuring HIVE
Hive Shell Commands
Different configuration properties in HIVE
Beeswax
Installing and configuring MySQL Database
Installing Hive Server
- Working on HIVE
Databases in Hive
Datatypes in Hive
Schema on Read
Schema on Write
Download Datasets
Internal Tables
External Tables
Partition in HIVE
Bucketing in HIVE
- HIVE Implementation
Hive in Real Time Projects
Auditing in Hive
Troubleshooting Infra issues in Hive
Troubleshooting User issues in Hive
- Things you will learn:
Hadoop Overview
Sqoop Overview
Sqoop Import
Sqoop Export
Career Guidance and Roadmap
- Hadoop Overview
Course overview
Big Data Overview
Hadoop Overview
HDFS
YARN Cluster Overview
Cluster Setup on Google Cloud
Environment Update
- Sqoop Overvi
Sqoop Introduction
Why Sqoop
Sqoop Features
Flume vs Sqoop
Sqoop Architecture & Working
Sqoop Commands.
- Sqoop Import
Managing Target Directories
Working with Parquet File Format
Working with Avro File Format
Working with Different Compressions
Conditional Imports
Split-by and Boundary Queries
Field delimiters
Incremental Appends
Sqoop Hive Import
Sqoop List Tables/Database
- Sqoop Export
Export from HDFS to MySQL
Export from Hive to MySQL
Export Avro Compressed to MySQL
Sqoop with Airflow
- Career Guidance and Roadmap
- Things you will learn:
Hadoop Overview
No SQL Databases HBase
Administration in HBASE
Troubleshooting in HBASE
Tuning in HBASE
Apache HBase Operations Continuity
Apache HBASE Ecosystem
Career Guidance and Roadmap
- Hadoop Overview
Course overview
Big Data Overview
Hadoop Overview
HDFS
Hadoop Ecosystem
What is a Hadoop Framework
Types of Hadoop frameworks
- No SQL Databases HBase
NoSQL Databases HBase
NoSQL Introduction
HBase Overview
HBase Architecture
Data Model
Connecting to HBase
HBase Shell
- Administration in HBASE
Introduction
Learn and Understand HBase Fault Tolerance
Hardware Recommendations
Software Recommendations
HBase Deployment at Scale
Installation with Cloudera Manager
Basic Static Configuration
Rolling Restarts and Upgrades
Interacting with HBase
- Troubleshooting in HBASE
Introduction
Troubleshooting Distributed Clusters
Learn How to Use the HBase UI
Learn How to Use the Metrics
Learn How to Use the Logs
- Tuning in HBASE
Introduction
Generating Load & Load Test Tool
Generating With YCSB
Region Tuning
Table Storage Tuning
Memory Tuning
Tuning with Failures
Tuning for Modern Hardware
- Apache HBase Operations Continuity
Introduction
Corruption: hbck
Corruption: Other Tools
Security
Security Demo
Snapshots
Import, Export and Copy Table
Cluster Replication
- Apache HBASE Ecosystem
Introduction
Hue
HBase With Apache Phoenix’
- Career Guidance and Roadmap
- Things you will learn:
Apache Flume Overview
Setting up Agents
Configuring A Multi Agent Flow
Flume Sinks
Flume Channels
Flume Sink Processors
Flume Interceptors
Security
Career Guidance and Roadmap
- Overview
Course overview
Big Data Overview
Hadoop Overview
HDFS
Hadoop Ecosystem
What is a Hadoop Framework
Types of Hadoop frameworks
Flume Overview
Architecture
Data flow mode
Reliability and Recoverability
- Setting up Agents
Setting up an individual agent
Configuring individual components
Wiring the pieces together
Data ingestion
Executing Commands
Network streams
Setting Multi-Agent Flow
Consolidation
Multiplexing the flow
Configuration
Defining the flow
Configuring individual components
Adding multiple flows in an agent
- Configuring A Multi Agent Flow
Fan out flow
Flume Sources
Avro Source, Exec Source
NetCat Source
Sequence Generator Source
Syslog Sources
Syslog TCP Source
Syslog UDP Source
Legacy Sources
Avro Legacy Source
Thrift Legacy Source
Custom Source
- Flume Sinks
HDFS Sink
Logger Sink
Avro Sink
IRC Sink
File Roll Sink
Null Sink
HbaseSinks
HbaseSink
AsyncHBaseSink
Custom Sink
- Flume Channels
Memory Channel
JDBC Channel
Recoverable Memory Channel
File Channel, Pseudo Transaction Channel
Custom Channel
Flume Channel Selectors
Replicating Channel Selector
Multiplexing Channel Selector
Custom Channel Selector
- Flume Sink Processors
Default Sink Processor
Failover Sink Processor
Load balancing Sink Processor
Custom Sink Processor
- Flume Interceptors
Timestamp Interceptor
Host Interceptor
Flume Properties
Property
- Security
Monitoring
Troubleshooting
Handling agent failures
Compatibility
HDFS
AVRO
- Career Guidance and Roadmap
- Things you will learn:
Apache Drill Overview
Installing & Configuring Drill
Querying Simple Delimited Data
Configuration Options
Understanding Data Types and Functions in Drill
Working with Dates and Times in Drill
Analyzing Nested Data with Drill
Other Data Types
Connecting Multiple Data Sources and programming languages
Career Guidance and Roadmap
- Overview
Course overview
Big Data Overview
Hadoop Overview
HDFS
Hadoop Ecosystem
What is a Hadoop Framework
Types of Hadoop frameworks
Drill Overview
What does Drill do
How does Drill work
Kinds of data which can be queried with Drill
- Installing & Configuring Drill
Comparison of embedded and distributed modes
Introducing and configuring workspaces
Demonstrate Drill’s various interfaces
- Querying Simple Delimited Data
SQL fundamentals
Querying a simple CSV file
Arrays in Drill
Accessing columns in Arrays
- Configuration Options
Extracting headers from csv files
Changing delimiter characters
Specifying options in a query
- Understanding Data Types and Functions in Drill
Overview of Drill Data Types
Converting Strings to Numeric Data Types
Complex Conversions
Windowing functions
- Working with Dates and Times in Drill
Understanding dates and times in Drill
Converting strings to dates
Reformatting dates
Intervals and date/time arithmetic in Drill
- Analyzing Nested Data with Drill
Issues querying nested data with Drill
Maps and Arrays in Drill
Querying deeply nested data in Drill
- Other Data Types
Log files
HTTPD
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Mock Interviews
Projects
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FAQ's
It basically counts the words in each document (map phase), while in the reduce phase it accumulates the data as per the document spanning the entire gathering. Eventually, during the map phase, the input data is divided into splits for analysis by map tasks executing in parallel across the Hadoop framework.
NameNode in Hadoop refers to the node where Hadoop stores all the file location information in HDFS (Hadoop Distributed File System) securely. If you want to acquire its detailed analysis, then you should get started with its professional course.
Yes, it's pretty much in demand, and in the coming years as well, it will remain consistently in use. So, if you possess your interest in this line, then you should acquire its accreditation, and make a career out of it.
Yes, we will provide you with the study material. In fact, you can also use our LMS portal and get extra notes, and class recordings as well.
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Big Data Hadoop
Thanks for making this wonderful platform available. I would love to encourage more people to join Croma Learning Campus to fill the gap for their career needs. I took Big Data Hadoop Training from Croma and I must say that course content is just the great and well-structured as per the certificatio Read more...
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