Big data refers to the large and complex set of data that are difficult to process using traditional processing systems. Stock exchanges like NYSE and BSE generate Terabytes of data. Social media sites like Facebook generates data that are approximately 500 times bigger than stock exchanges.
Hadoop is an open source project by Apache used for storage and processing of large every day volume of unstructured data in a distributed environment. Hadoop can scale up from a single server to thousands of servers.
Hadoop framework is used by large giants like Amazon, IBM, New York Times, Google, Facebook, Yahoo and the list is growing every day. Due to the larger investments companies make for Big Data the need for Hadoop Developers and Data Scientists who can analyze the data increases day by day.
The Big Data industry has gained significant growth in recent years and recent research has estimated that the Big Data market is more than a $ 50 billion industry. The Gartner survey confirmed that 64% of companies invested in Big Data in 2013 and that number continues to increase each year. Bigdata, the opportunities are limitless for all those who want to enter the Big Data Hadoop ecosystem.
Software professionals working on obsolete technologies, JAVA professionals, analytics professionals, ETL professionals, data warehouse professionals, test professionals, project managers can undergo Hadoop training in Chennai (vadapalani) and make a career change. Our great data training in Chennai ( vadapalani ) will provide you hands-on experience to meet the demands of the industry needs.
COURSE TOPICS :
Big Data Hadoop
- Introduction to BIGDATA and HADOOP
- HDFS (Hadoop Distributed File System)
- HDFS Architecture – 5 Daemons of Hadoop
- Replication in Hadoop – Fail Over Mechanism
Map Reduce
- Input Split
- Map Reduce Life Cycle
- Map Reduce Programming Model
- How to write a basic Map Reduce Program
- Driver Code
- Mapper Code
- Reducer Code
IDENTITY MAPPER & IDENTITY REDUCER
- Input Format’s in Map Reduce
- Output Format’s in Map Reduce
- Map Reduce API(Application Programming Interface)
- Combiner in Map Reduce
- Partitioner in Map Reduce
- Compression Techniques in Map Reduce
- Map Reduce Job Chaining
- Joins – in Map Reduce
- How to debug Map Reduce Jobs in Local and Pseudo cluster Mode
- Apache PIG
- HIVE
- SQOOP
- Hbase
- Flume
- Oozie
- YARN
- Impala
- MongoDB
- Apache Cassandra
- Apache Kafka
- Mahout
- Apache Spark – with Scala
- SPARK
- Spark SQL
Introduction to Hadoop ‘R’
Hadoop Administration
- Hadoop Single Node Cluster Set Up (Hands on Installation on Laptops)
- Multi Node Hadoop Cluster Set Up (Hands on Installation on Laptops)
- Multi Node Hadoop Cluster Set Up (Hands on Installation on Laptops)
- PIG Installation (Hands on Installation on Laptops)
- SQOOP Installation (Hands on Installation on Laptops)
- HIVE Installation(Hands on Installation on Laptops)
- Hbase Installation (Hands on Installation on Laptops)
- OOZIE Installation (Hands on Installation on Laptops)
- Mongo DB Installation (Hands on Installation on Laptops)
- Commissioning Of Nodes In Hadoop Cluster
- Decommissioning Of Nodes from Hadoop Cluster
CONTACT NUMBER – 8939111234.