Apache Hadoop Training
Apache™ Hadoop® is an open source software project that enables the distributed processing of large data sets across clusters of commodity servers. It is designed to scale up from a single server to thousands of machines, with a very high degree of fault tolerance. Rather than relying on high-end hardware, the resiliency of these clusters comes from the software’s ability to detect and handle failures at the application layer.
Hadoop enables a computing solution that is:
- Scalable– New nodes can be added as needed, and added without needing to change data formats, how data is loaded, how jobs are written, or the applications on top.
- Cost effective– Hadoop brings massively parallel computing to commodity servers. The result is a sizeable decrease in the cost per terabyte of storage, which in turn makes it affordable to model all your data.
- Flexible– Hadoop is schema-less, and can absorb any type of data, structured or not, from any number of sources. Data from multiple sources can be joined and aggregated in arbitrary ways enabling deeper analyses than any one system can provide.
- Fault tolerant– When you lose a node, the system redirects work to another location of the data and continues processing without missing a beat.
- Hadoop – Architecture
- Understand HDFS and Mapreduce – Deep Dive
- Building Applications using mapreduce
- Verify, Evaluate and test your Mapreduce applications
- Exploring mapreduce combiners, Partitioners, distributed cache
- Tips & Tricks for debugging and building mapreduce applications
- Learn joining data sets, How hadoop integration to data center
- Exploring Various algorithms involved in hadoop
- Build super fast applications using Hive and Pig.