If you go about choosing a Hadoop company from the numerous options that are available you’re the one who has to choose, and that choice should be based on a set of criteria designed to help you make the best decision possible. Thus it will be difficult for an individual to choose the right company based on all the factors.
Apache Hadoop is a framework used to develop data processing applications which are executed in a distributed computing environment.HADOOP is an open source software framework. Applications built using HADOOP are run on large data sets distributed across clusters of commodity computers. Data resides in a distributed file system which is called as a Hadoop Distributed File system.
Hadoop Architecture based on the two main components namely MapReduce and HDFS.MapReduce is a computational model and software framework for writing applications which are run on Hadoop. These MapReduce programs are capable of processing enormous data in parallel on large clusters of computation nodes.
HDFS takes care of the storage part of Hadoop applications. MapReduce applications consume data from HDFS. HDFS creates multiple replicas of data blocks and distributes them on compute nodes in the cluster. This distribution enables reliable and extremely rapid computations.
Hadoop helps to execute a large amount of processing where the user can connect together multiple commodity computers to a single-CPU, as a single functional distributed system and have the particular set of clustered machines that read the dataset in parallel and provide intermediate, and after integration gets the desired output.
Hadoop runs code across a cluster of computers. Data are initially divided into files and directories. Then the files are distributed across various cluster nodes for further processing of data. Job tracker starts its scheduling programs on individual nodes. Once all the nodes are done with scheduling then the output is returned back.
Apache Hadoop has some major features.Here are some of them.
It is distributed processing. The data storage is maintained in a distributed manner in HDFS across the cluster, data is processed in parallel on the cluster of nodes.
Hadoop’s fault tolerant can be examined in such cases when any node goes down, the data on that node can be recovered easily from other nodes.
Due to the replication of data in the cluster, data can be reliable which is stored on the cluster of machine despite machine failures.
Hadoop is highly scalable and in a unique way, hardware can be easily added to the nodes.
Hadoop works on data locality principle which states that the movement of computation of data instead of data to computation.