The argument in favor of using filler text goes something like this: If you use real content in the Consulting Process, anytime you reach a review point you’ll end up reviewing and negotiating the content itself and not the design.
The technological advancements and the increasing use of smart devices in recent years have contributed to a data revolution. The quantum of existing data (business or personal) is growing at a relentless pace overwhelming every known computational mechanism or tool. To deal with this humongous data processing requirement, we need a robust solution. This is where the software platform Hadoop comes into the picture.
What Is Hadoop
Hadoop is an open-source software platform that stores a huge amount of data and runs multiple applications on various commodity software. It possesses a massive computational power, vast data storage facility, and the ability to handle various virtually unlimited tasks.
Its core aim is to support the expanding technologies such as Big Data, Data Mining, Machine Learning, and Predictive Analytics. It has the capability to handle several modes/types of data including structured, semi-structured, and unstructured. Thus, Hadoop offers the flexibility to collect, process, and finally, analyze data that the old data warehouses failed to do.
Overview of Hadoop Ecosystem
The Hadoop ecosystem comprises numerous components, which can be learnt in all their dimensions should one enrol in any reputed Hadoop training institute in Kolkata.
Some of the components are as follow:
Hadoop Distributed File System or HDFS is a storage system that operates on a Java-based programming language. This is used as the main storage device in Hadoop applications. HDFS has two primary components: Namenode and Datanode. These applications store a massive amount of data across several nodes in the Hadoop cluster.
Pig or PigLatin is a high-level procedural language, which is recommended for processing a huge quantum of semi-structured data. Pig performs as an alternative language to Java for MapReduce and thereby automatically generates MapReduce functions. Here, programmers can create various customized functions.
It comes in handy when developers are not familiar with high-level languages like Java. Nevertheless, one ought to have a strong scripting knowledge to excel in Pig language. That’s why you may enrol in any reputed Hadoop training institute in Kolkata to acquire the much-preferred scripting knowledge.
Hive is an open-source software for performing data query and analysis. It has three major functions: data summarization, query, and analysis. Hive uses HiveQL (HQL) language, which is akin to SQL. This language translates the SQL queries into MapReduce jobs. Hive has three main components: Metastore, Driver, and Compiler.
This is a type of NoSQL database. It offers a distributed and scalable database service. It has two major components including HBase Master and Regional Server.
The HBase Master performs some administration activities like offering an interface for creating, updating, and deleting tables. On the other hand, the Regional Server is a worker node that can read, write, and delete requests from the clients.
Every component of Hadoop has unique functions. To become an expert in Hadoop, you better learn these components and practice well. You may apply for Hadoop spark training from Samavetah Softteq Solutions - one of the leading software training institutes in Kolkata. To know more about the training programme, call 033 40674187 / 9674162544 or drop a mail at email@example.com / firstname.lastname@example.org.