- What is Big Data
- Dimensions of Big Data
- Big Data in Advertising
- Big Data in Banking
- Big Data in Telecom
- Big Data in eCommerce
- Big Data in Healthcare
- Big Data in Defense
- Processing options of Big Data
- Hadoop as an option
- What is Hadoop
- How Hadoop 1.0 Works
- How Hadoop 2.0 Works
- What is YARN
- How YARN Works
- Advantages of YARN
- How Hadoop has an edge
- Running HDFS commands
- Running your MapReduce program on Hadoop 1.0
- Running your MapReduce Program on Hadoop 2.0
- Running Sqoop Import and Sqoop Export
- Creating Hive tables directly from Sqoop
- Creating Hive tables
- Querying Hive tables
- MapReduce Code Walkthrough
- MR Unit
- Distributed Cache
- Setup and Cleanup methods
- Using Java API to access HDFS
- Map Side joins
- Reduce side joins
- Input Types in MapReduce
- Output Types in MapReduce
- Custom Input Data types
- Custom Input Data types
- Custom Output Data types
- Multiple Reducer MR program
- Zero Reducer Mapper Program
- MR Unit hands on
- Distributed Cache hands on
- Partitioner hands on
- Combiner hands on
- Accessing files using HDFS API hands on
- Map Side joins hands on
- Reduce side joins hands on
- Inverted Index
- Word Co-occurrence
- Distributed Grep
- Bloom Filters
- Average Calculation
- Standard Deviation
- MapSide joins
- Reduce Side joins
- What is Pig
- How Pig Works
- Simple processing using Pig
- Advanced Processing Using Pig
- Pig Hands On
- What is Hive
- How Hive Works
- Simple processing using Hive
- Advanced processing using Hive
- Hive hands-on
- What is Oozie
- How Oozie Works
- Oozie hands-on
- What is Impala
- How Impala Works
- Where Impala is better than Hive
- Impala’s shortcomings
- Impala hands-on
- Understand Big Data and the various types of data stored in Hadoop
- Understand the fundamentals of MapReduce, Hadoop Distributed File System (HDFS), YARN, and how to write MapReduce code
- Learn best practices and considerations for Hadoop development, debugging techniques and implementation of workflows and common algorithms
- Learn how to leverage Hadoop frameworks like ApachePig™, ApacheHive™, Sqoop, Flume, Oozie and other projects from the Apache Hadoop Ecosystem
- Understand optimal hardware configurations and network considerations for building out, maintaining and monitoring your Hadoop cluster
- Learn advanced Hadoop API topics required for real-world data analysis
- Understand the path to ROI with Hadoop
There is no Certification offered for this course. On successful completion of the course, you will receive a Course Completion Certificate from Bacancy Trainings.
Architects and developers who design, develop and maintain Hadoop-based solutions
Data Analysts, BI Analysts, BI Developers, SAS Developers and related profiles who analyze Big Data in Hadoop environment
Consultants who are actively involved in a Hadoop Project
Experienced Java software engineers who need to understand and develop Java MapReduce applications for Hadoop 2.0.
Q. Can you tell me regarding the Training?
Hadoop is considered as the most effective data platform for companies working with big data, and is an integral part of storing, handling and retrieving enormous amounts of data in a variety applications. Hadoop enables you to run deep analytics which cannot be effectively handled by a database engine. Big enterprises around the world have learnt Hadoop to be a game changer in their Big Data management, and as more companies embrace this powerful technology the demand for Hadoop Developers is also increasing. By learning how to harness the power of Hadoop 2.0 to manipulate, analyse and perform computations on Big Data, you will be paving the way for an enriching and financially rewarding career as an expert Hadoop developer.
Q. Who can benefit from this course?
Architects and developers who design, develop and maintain Hadoop-based solutions, Data Analysts, BI Analysts, BI Developers, SAS Developers, and Consultants involved in Hadoop-based projects will greatly benefit from this course.
Q.How we can register for the training?
You can register through online, we will provide online registration link you can use that link and do registration for the same.
Q.There is any group discount?
Yes, if you will be coming with 5 people we will give you 10% discount.
Q. What is training Timing & venue?
Training time will be 9:30 AM to 5:30 PM and venue will be communicated according to locations.