Hortonworks Technology Training in Chennai , India

Hadoop Big Data Training - Classroom / online / corporate training @ chennai
Hadoop is a batch-oriented system. Data are loaded into HDFS, processed, and then retrieved. This is somewhat of a computing throwback, and often, interactive and random access to data is required.
Enter HBase,a column-oriented database that runs on top of HDFS.Modeled after Google’s BigTable,the project’s goal is to host billions of rows of data for rapid access.MapReduce can use HBase as both a source and a destination for its computations, and Hive and Pig can be used in combination with HBase.
In order to grant random access to the data, HBase does impose a few restrictions: Hive performance with HBase is 4-5 times slower than with plain HDFS, and the maximum amount of data you can store in HBase is approximately a petabyte, versus HDFS’ limit of over 30PB.
HBase is ill-suited to ad-hoc analytics and more appropriate for integrating big data as part of a larger application. Use cases include logging, counting and storing time-series data.Hadoop Training India | BigData Developer / Consultant/ Architect / Admin Training Programs with placements!
The Hadoop Distributed File System is a versatile, resilient, clustered approach to managing files in a big data environment. HDFS is not the final destination for files. Rather, it is a data service that offers a unique set of capabilities needed when data volumes and velocity are high. Because the data is written once and then read many times thereafter, rather than the constant read-writes of other file systems, HDFS is an excellent choice for supporting big data analysis. The service includes a “NameNode” and multiple “data nodes” running on a commodity hardware cluster and provides the highest levels of performance when the entire cluster is in the same physical rack in the data center.Big Data / Hadoop Training Online
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