Khushi Software Services is the trusted Hadoop app development company offering scalable solutions to businesses. We leverage the power of this open-source software framework to develop data processing applications that efficiently store and process large datasets. Our developers have diverse expertise in providing big data solutions that help businesses make decisions faster and attain greater agility.
The Hadoop Common module is the base of the framework. It contains the Java Archive (JAR) files and scripts needed to start Hadoop. It is an essential module responsible for basic processes. It features a set of common utilities and libraries used by other modules of Hadoop.
Hadoop YARN or Yet Another Resource Negotiator module is responsible for job scheduling and managing the cluster. It performs a variety of tasks, like ensuring the clusters are working properly. It allows various data processing engines to run and process data stored in HDFS.
This module is responsible for writing applications that can process big data in parallel on multiple nodes. It splits the input dataset into small chunks that are processed separately. Hadoop Map Reduce processes data in three stages - map, shuffle, and reduce.
Hadoop Distributed File System (HDFS) is the most important module. It is designed to store large data sets running on commodity hardware by breaking the files into blocks. This module makes applications available for parallel processing.
Our team specializes in designing highly scalable Hadoop architecture that seamlessly integrates with other systems. We use our rich experience and cutting-edge technology to deliver the best results.
Implement and manage the security model of your business with our Hadoop integration services. Our integration solutions accelerate the ingestion of big data files and enable high-speed file transfer.
Khushi Software Services is a leading Software Development Company in Hyderabad. We connect the business to technology gap, through Local counseling presence utilizing industry experts.
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