MapReduce is a programming model used to perform distributed processing in parallel in a Hadoop cluster, which Makes Hadoop working so fast. When you are dealing with Big Data, serial processing is no more of any use. MapReduce has mainly two tasks which are divided phase-wise: Map TaskReduce Task /a00-274-sas-certified-visual-modeling-using-sas-visual-statistics-8-4/ Let us understand it with … Continue reading MapReduce – Understanding With Real-Life Example
Today tons of Companies are adopting Hadoop Big Data tools to solve their Big Data queries and their customer market segments. There are lots of other tools also available in the Market like HPCC developed by LexisNexis Risk Solution, Storm, Qubole, Cassandra, Statwing, CouchDB, Pentaho, Openrefine, Flink, etc. Then why Hadoop is so popular among … Continue reading Hadoop – Features of Hadoop Which Makes It Popular
As the world becomes more information-driven than ever before, a major challenge has become how to deal with the explosion of data. Traditional frameworks of data management now buckle under the gargantuan volume of today's datasets. Fortunately, a rapidly changing landscape of new technologies is redefining how we work with data at super-massive scale. These … Continue reading What is Hadoop? What is MapReduce? What is NoSQL?
What is Hadoop MapReduce? Map reducing is a technical program that is used for distributed systems and it is based on Java. The algorithm of map-reduce contains two tasks which are known as Map and Reduce. The tasks carried out by map are as follows: map takes a set of data and converts it into … Continue reading What is Hadoop MapReduce?
However with time we have progressed beyond MapReduce to handle big data with Hadoop. MapReduce, however exceptionally powerful becomes complex and time consuming when doing complete analysis on distributed network. Today, we have many more system which can work in conjunction with MapReduce or simply on HDFS to complete such complex functionalities. Our focus of … Continue reading Hadoop beyond traditional MapReduce – Simplified
Hadoop Architecture In this post, we are going to discuss about Apache Hadoop 2.x Architecture and How it’s components work in detail. Hadoop 2.x Architecture Apache Hadoop 2.x or later versions are using the following Hadoop Architecture. It is a Hadoop 2.x High-level Architecture. We will discuss in-detailed Low-level Architecture in coming sections. Hadoop Common … Continue reading Hadoop Architecture – YARN, HDFS and MapReduce
The Apache Hadoop Module: Hadoop Common: this includes the common utilities that support the other Hadoop modules HDFS: the Hadoop Distributed File System provides unrestricted, high-speed access to the application data. Hadoop YARN: this technology accomplishes scheduling of job and efficient management of the cluster resource. MapReduce: highly efficient methodology for parallel processing of huge … Continue reading The Hadoop Module & High-level Architecture