HADOOP DEV + SPARK & SCALA
- Solution for BigData Problem
- Open Source Technology
- Based on open source platforms
- Contains several tool for entire ETL data processing Framework
- It can process Distributed data and no need to store entire data in centralized storage as it is required for SQL based tools.
HADOOP DEV + SPARK & SCALA TRAINING IN PUNE
BigData Hadoop Online Training in India
Hadoop Developer + Spark & Scala/Hadoop (Java + Non- Java)
Duration of Training : 50 hrs
Batch type : Weekdays/Weekends
Mode of Training : Classroom/Online/Corporate Training
Hadoop Dev + Spark & Scala Training & Certification in Pune
Highly Experienced Certified Trainer with 10+ yrs Exp. in Industry
Realtime Projects, Scenarios & Assignments
Hadoop Certification : Cloudera Certified Professional (CCP)
We Provide all guidance & support for making you a Hadoop Certified Professional
Best BigData Hadoop Training with 2 Real-time Projects with 1 TB Data set
For whom Hadoop is?
IT folks who want to change their profile in a most demanding technology which is in demand by almost all clients in all domains because of below mentioned reasons-
Hadoop is open source (Cost saving / Cheaper)
Hadoop solves Big Data problem which is very difficult or impossible to solve using highly paid tools in market
It can process Distributed data and no need to store entire data in centralized storage as it is there with other tools.
Now a days there is job cut in market in so many existing tools and technologies because clients are moving towards a cheaper and efficient solution in market named HADOOP
There will be almost 4.4 million jobs in market on Hadoop by next year.
Please refer below given links :
Can I learn Hadoop if I don’t know Java?
Yes.
It is a big myth that if a guy don’t know Java then he can’t learn Hadoop. The truth is that Only Map Reduce framework needs Java except Map Reduce all other components are based on different terms like Hive is similar to SQL, HBase is similar to RDBMS and Pig is script based.
Only MR requires Java but there are so many organizations who started hiring on specific skill set also like HBASE developer or Pig and Hive specific requirements. Knowing MapReuce also is just like become all-rounder in Hadoop for any requirement.
Why Hadoop?
- Solution for BigData Problem
- Open Source Technology
- Based on open source platforms
- Contains several tool for entire ETL data processing Framework
- It can process Distributed data and no need to store entire data in centralized storage as it is required for SQL based tools. ,
COURSE CONTENT :
HADOOP DEV + SPARK & SCALA + NoSQL + Splunk + HDFS (Storage) + YARN (Hadoop Processing Framework) + MapReduce using Java (Processing Data) + Apache Hive + Apache Pig + HBASE (Real NoSQL ) + Sqoop + Flume + Oozie + Kafka With ZooKeeper + Cassandra + MongoDB + Apache Splunk
Big Data :
Distributed computing
Data management – Industry Challenges
Overview of Big Data
Characteristics of Big Data
Types of data
Sources of Big Data
Big Data examples
What is streaming data?
Batch vs Streaming data processing
Overview of Analytics
Big data Hadoop opportunities
Hadoop :
Why we need Hadoop
Data centers and Hadoop Cluster overview
Overview of Hadoop Daemons
Hadoop Cluster and Racks
Learning Linux required for Hadoop
Hadoop ecosystem tools overview
Understanding the Hadoop configurations and Installation
HDFS (Storage) :
HDFS
HDFS Daemons – Namenode, Datanode, Secondary Namenode
Hadoop FS and Processing Environment’s UIs
Fault Tolerant
High Availability
Block Replication
How to read and write files
Hadoop FS shell commands
YARN (Hadoop Processing Framework) :
YARN
YARN Daemons – Resource Manager, Node Manager etc.
Job assignment & Execution flow
MapReduce using Java (Processing Data) :
The introduction of MapReduce.
MapReduce Architecture
Data flow in MapReduce
Understand Difference Between Block and InputSplit
Role of RecordReader
Basic Configuration of MapReduce
MapReduce life cycle
How MapReduce Works
Writing and Executing the Basic MapReduce Program using Java
Submission & Initialization of MapReduce Job.
File Input/Output Formats in MapReduce Jobs
Text Input Format
Key Value Input Format
Sequence File Input Format
NLine Input Format
Joins
Map-side Joins
Reducer-side Joins
Word Count Example(or) Election Vote Count
Will cover five to Ten Map Reduce Examples with real time data
Apache Hive :
Data warehouse basics
OLTP vs OLAP Concepts
Hive
Hive Architecture
Metastore DB and Metastore Service
Hive Query Language (HQL)
Managed and External Tables
Partitioning & Bucketing
Query Optimization
Hiveserver2 (Thrift server)
JDBC, ODBC connection to Hive
Hive Transactions
Hive UDFs
Working with Avro Schema and AVRO file format
Hands on Multiple Real Time datasets
Apache Pig :
Apache Pig
Advantage of Pig over MapReduce
Pig Latin (Scripting language for Pig)
Schema and Schema-less data in Pig
Structured , Semi-Structure data processing in Pig
Pig UDFs
HCatalog
Pig vs Hive Use case
Hands On Two more examples daily use case data analysis in google. And Analysis on Date time dataset
HBASE (Real NoSQL) :
Introduction to HBASE
Basic Configurations of HBASE
Fundamentals of HBase
What is NoSQL?
HBase Data Model
Table and Row.
Column Family and Column Qualifier.
Cell and its Versioning
Categories of NoSQL Data Bases
Key-Value Database
Document Database
Column Family Database
HBASE Architecture
HMaster
Region Servers
Regions
MemStore
Store
SQL vs. NOSQL
How HBASE is differed from RDBMS
HDFS vs. HBase
Client-side buffering or bulk uploads
HBase Designing Tables
HBase Operations
Get
Scan
Put
Delete
Live Dataset
Sqoop :
Sqoop commands
Sqoop practical implementation
Importing data to HDFS
Importing data to Hive
Exporting data to RDBMS
Sqoop connectors
Flume :
Flume commands
Configuration of Source, Channel and Sink
Fan-out flume agents
How to load data in Hadoop that is coming from web server or other storage
How to load streaming data from Twitter data in HDFS using Hadoop
Oozie :
Oozie
Action Node and Control Flow node
Designing workflow jobs
How to schedule jobs using Oozie
How to schedule jobs which are time based
Oozie Conf file
Scala :
Scala
Syntax formation, Datatypes , Variables
Classes and Objects
Basic Types and Operations
Functional Objects
Built-in Control Structures
Functions and Closures
Composition and Inheritance
Scala’s Hierarchy
Traits
Packages and Imports
Working with Lists, Collections
Abstract Members
Implicit Conversions and Parameters
For Expressions Revisited
The Scala Collections API
Extractors
Modular Programming Using Objects
Spark :
Spark
Architecture and Spark APIs
Spark components
Spark master
Driver
Executor
Worker
Significance of Spark context
Concept of Resilient distributed datasets (RDDs)
Properties of RDD
Creating RDDs
Transformations in RDD
Actions in RDD
Saving data through RDD
Key-value pair RDD
Invoking Spark shell
Loading a file in shell
Performing some basic operations on files in Spark shell
Spark application overview
Job scheduling process
DAG scheduler
RDD graph and lineage
Life cycle of spark application
How to choose between the different persistence levels for caching RDDs
Submit in cluster mode
Web UI – application monitoring
Important spark configuration properties
Spark SQL overview
Spark SQL demo
SchemaRDD and data frames
Joining, Filtering and Sorting Dataset
Spark SQL example program demo and code walk through
Kafka With ZooKeeper :
What is Kafka
Cluster architecture With Hands On
Basic operation
Integration with spark
Integration with Camel
Additional Configuration
Security and Authentication
Apache Kafka With Spring Boot Integration
Running
Usecase
Apache Splunk :
Introduction & Installing Splunk
Play with Data and Feed the Data
Searching & Reporting
Visualizing Your Data
Advanced Splunk Concepts
Cassandra + MongoDB :
Introduction of NoSQL
What is NOSQL & N0-SQL Data Types
System Setup Process
MongoDB Introduction
MongoDB Installation
DataBase Creation in MongoDB
ACID and CAP Theorum
What is JSON and what all are JSON Features?
JSON and XML Difference
CRUD Operations – Create , Read, Update, Delete
Cassandra Introduction
Cassandra – Different Data Supports
Cassandra – Architecture in Detail
Cassandra’s SPOF & Replication Factor
Cassandra – Installation & Different Data Types
Database Creation in Cassandra
Tables Creation in Cassandra
Cassandra Database and Table Schema and Data
Update, Delete, Insert Data in Cassandra Table
Insert Data From File in Cassandra Table
Add & Delete Columns in Cassandra Table
Cassandra Collections
RELATED COMBO PROGRAMS :
Oracle SQL+ core Java + Bigdata Hadoop
We Provide Cloudera Hadoop Certifications
Cloudera Certified Professional (CCP)
The industry’s most demanding performance-based certifications, CCP evaluates and recognizes a candidate’s mastery of the technical skills most sought after by employers.
- CCA Spark and Hadoop Developer
A CCA Spark and Hadoop Developer has proven their core skills to ingest, transform, and process data using Apache Spark™ and core Cloudera Enterprise tools.
- CCA HDP Administrator Exam
The HDP Certified Administrator (HDPCA) exam has five main categories of tasks that involve: Installation, Configuration, Troubleshooting, High Availability and Security.
Trainer is having 17 year experience in IT with 10 years in data warehousing &ETL experience. It has been six years now that he has been working extensively in BigData ecosystem toolsets for few of the banking-retail-manufacturing clients. He is a certified HDP-Spark Developer and Cloudera certified Hbase specialist. He also have done corporate sessions and seminars both in India and abroad. Recently he was engaged by Pune University for 40 hour sessions on BigData analytics to the senior professors of Pune.
All faculties at our organization are currently working on the technologies in reputed organization. The curriculum that is imparted is not just some theory or talk with some PPTs. We absolutely frame the forum in such a way so that at the end the lessons are imparted in easy language and the contents are well absorbed by the candidates. The sessions are backed by hands-on assignment. Also that the faculties are industry experience so during the course he does showcase his practical stories.
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How we are Different from Others : Covers each topics with Real Time Examples . Covers 8 Real time project and more than 72+ Assignments which is divided into Basic , Intermediate and Advanced . Trainer from Real Time Industry with 9 years experience in DWH. Working as BI and Hadoop consultant having 3+ years in Bigdata & Hadoop real time implementation and migrations.This is completely hands own training , which covers 90% Practical And 10% Theory .Here in Radical Technologies , we will take all prerequisite like Java ,SQL, which is required to learn Hadoop Developer and Analytical skills. This way We will accommodate technology illiterate and Technical experts in the same session and at the end of the training , they will gain the confidence that , they got up-skilled to a different level.
- 8 Domain Based Project With Real Time Data ( with one trainer – two project. If you req more projects , you are free to attend any other trainers project orientations sessions )
- 5 POC
- 72 Assignments
- 25 Real Time Scenarios On 16 Node Clusters ( Aws Cloud setup )
- Basic Java
- DWH Concept
- Pig|Hive|Mapreduce|Nosql|Hbase|Zookeeper|Sqoop|Flume|Oozie|Yarn|Hue|Spark |Scala
42 Hours Classroom Section
30 Hours of assignments
25 hours for One Project and 50 Hrs for 2 Project ( Candidates should prepare with mentor support . 50 hours mentioned is total hours spent on project by each trainer )
350+ Interview Questions
Administration and Manual Installation of Hadoop with other Domain based projects will be done on regular basis apart from our normal batch schedule .
We do have projects from Healthcare , Financial , Automotive ,Insurance , Banking , Retail etc , which will be given to our students as per their requirements .
- Training By 14+ Years experienced Real Time Trainer
- A pool of 200+ real time Practical Sessions on Bigdata Hadoop
- Scenarios and Assignments to make sure you compete with current Industry standards
- World class training methods
- Training until the candidate get placed
- Certification and Placement Support until you get certified and placed
- All training in reasonable cost
- 10000+ Satisfied candidates
- 5000+ Placement Records
- Corporate and Online Training in reasonable Cost
- Complete End-to-End Project with Each Course
- World Class Lab Facility which facilitates I3 /I5 /I7 Servers and Cisco UCS Servers
- Covers Topics other than from Books which is required for the IT Industry
- Resume And Interview preparation with 100% Hands-on Practical sessions
- Doubt clearing sessions any time after the course
- Happy to help you any time after the course
[schema type=”review” url=”https://www.radicaltechnologies.co.in/” name=”Hadoop Development Training Review of Radical Technologies Pune” description=”HADOOP DEV + SPARK & SCALA COURSE” rev_name=”HADOOP DEV + SPARK & SCALA” rev_body=”Hadoop Development Learning experience was amazing. Trainers teaching style was really good and the content was well structured to cover all concepts. The classes were full of practical knowledge, most importantly it was never too difficult to understand or monotonous because of teaching style. Would definitely recommend to those who are looking for proper direction and don’t know where to start from. Would like to learn more from Radical Technologies. They helps for getting me Certified with all guidance. ” author=”kalyani Agarwal” pubdate=”2020-04-03″ user_review=”5″ min_review=”0″ max_review=”5″ ]
ML and GraphX ,’R’ Language
Data Analytics / Science
Cloudera Certified Professional (CCP)
CCP Data Engineer
