Big Data and Hadoop Developer Training
4.3 /5- Offered byCognixia
Big Data and Hadoop Developer Training at Cognixia Overview
Duration | 36 hours |
Total fee | ₹18,000 |
Mode of learning | Online |
Difficulty level | Intermediate |
Credential | Certificate |
Future job roles | CRUD, .Net, CSR, Credit risk, Senior Software Developer |
Big Data and Hadoop Developer Training at Cognixia Highlights
- Lifetime course materials access, 24/7 technical expert support
- 2 Projects, Case studies, Real-life examples, Placement Assistance
Big Data and Hadoop Developer Training at Cognixia Course details
- Best for anyone looking to make a career in Big Data and Hadoop
- Java Developers
- Big Data professionals
- Architects
- 36 hours of live online training including live POC & assignments
- Live & interactive online session with Industry expert Instructor
- 24/7 technical expert support assistance
- Lifetime course materials access
- 2 Projects as per the industry standard
- Case studies and real life examples
- Placement Assistance : resume preparation & assistance for interview preparation
- The most popular course tendering deep knowledge and insight into Big Data with Apaches Open Source Hadoop, Collabera Big Data and Hadoop Developer certification renders depth understanding
- It includes MapReduce Frameworks, technologies like HBase, ZooKeeper, Pig, Flume and Hadoop Architecture
- Become an expert in Hadoop and get familiar with industry based projects and cases
- By engaging in this training certification, learner will get the right experience to become certified Hadoop professional
- Organizations are and continue to be looking for candidates with a right set of expertise for superb opportunities
Big Data and Hadoop Developer Training at Cognixia Curriculum
Introduction to Linux and Big Data Virtual Machine (VM)
Introduction/ Installation of Virtual Box and the Big Data VM
Introduction to Linux
Why Linux?
Windows and the Linux equivalents
Different flavors of Linux
Unity Shell (Ubuntu UI)
Basic Linux Commands (enough to get started with Hadoop)
Understanding Big Data
3V (Volume- Variety- Velocity) characteristics
Structured and unstructured data
Application and use cases of Big Data
Limitations of traditional large scale systems
How a distributed way of computing is superior (cost and scale)
Opportunities and challenges with Big Data
HDFS (The Hadoop Distributed File System)
HDFS Overview and Architecture
Deployment Architecture
Name Node
Data Node and Checkpoint Node (aka Secondary Name Node)
Safe mode
Configuration files
HDFS Data Flows (Read/Write)
How HDFS Addresses Fault Tolerance?
CRC Checksum
Data Replication
Rack awareness and block placement policy
Small file problems
HDFS Interfaces
Command-Line Interface
File Systems
Administrative
Web Interfaces
Advanced HDFS Features
Load Balancer
Dist cp (Distributed Copy)
HDFS Federation
HDFS High Availability
Hadoop Archives
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