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Apache Hadoop is a software platform that is open source and it distributes processing and storage of huge data on a computer built through commodity hardware. It provides data processing, data security, data storage, data access, operations, and data governance.  BookMyEssay is the best platform for students who are searching “write my assignment for me” to complete the assigned jobs. Our main goal is meeting the expectations of the students and delivery them top-notch Apache Hadoop assignment help.

Apache Hadoop Modules

Apache Hadoop has the following modules that are discussed in our Apache Hadoop case study assignment help as follows:

• Hadoop Common – It consists of utilities and libraries that are needed by other modules.
• Hadoop Yarn – It is a platform that has the responsibility to manage to compute resources and use them for user’s applications.
• Hadoop Distributed File System – This system saves data on a commodity machine and it offers great bandwidth in a cluster.
• Hadoop MapReduce – It is a programming model needed to huge scale processing of data.

All Hadoop modules are designed based on the criteria that hardware failures are common and they should be handled by the framework. The HDFS components and MapReduce of Hadoop are derived originally from the Google File System and Google MapReduce papers.

Apart from YARN, HDFS, and MapReduce, the complete Hadoop platform is considered to comprise of several projects: Apache Hive, Apache Pig, Apache Hbase, and many more. Our best Australian experts hold many years of practical experience to complete Apache Hadoop homework writing tasks.

Advantages of Apache Hadoop

Many organizations use Hadoop because of it has the capability to manage, store, and analyze plenty of structured as well as unstructured data reliably, rapidly, and at low-cost. Some of its benefits are highlighted in Apache Hadoop homework help online as follows:

• Performance and scalability – It distributes data locally to every node in clusters that enable Apache Hadoop to analyze, manage, store, and process data at a high scale.
• Reliability – Large computational clusters can fail in a cluster. Hadoop is resilient. In case of failure of any node, processing happens at the remaining nodes and thus data gets re-replicated automatically for node failures in the future.
• Flexibility – Unlike conventional database management systems, here you do not have to make structured schemas prior to data storage. You may store data in every format such as unstructured and semi-structured format and then apply it to data.
• Low-cost – Hadoop is an open source platform and it runs on very low-cost hardware.

Why Use Apache Hadoop?

The old method to cleanse information from systems and placing it neatly into data warehouses may not work in a period where there are huge volumes of data from various sources in formats, which are changing constantly.

Storage needs are exploding because of regulatory and legal mandates that are extending retention periods from years to decades. The costs of previously made data warehouses were too high. With Apache Hadoop, the costs have reduced by over 90 percent. This removes technical barriers thus enabling data agility.

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