In a world where data is fueling the growth of organizations, it wont be wrong to assume that companies ingest raw data in large volumes from numerous sources. But, how can they identify the data which is both useful and insightful? This is where Big Data comes to play. Hadoop is an open source framework that is used to process Big Data. The average salary of a Big Data analyst in the US is around $61,000.
Big Data and Hadoop Tutorial covers Introduction to Big Data,Overview of Apache Hadoop,The Intended Audience and Prerequisites, The Ultimate Goal of this Tutorial, The Challenges at Scale and the Scope of Hadoop, Comparison to Existing Database Technologies,The Hadoop Architecture & Module, Introduction to Hadoop Distributed File System, Hadoop Multi Node Clusters, HDFS Installation and Shell Commands, Hadoop MapReduce – Key Features & Highlights, Hadoop YARN Technology, Introduction to Pig, Sqoop and Hive.
This clearly specifies the kind of potential the field of Big Data has. After learning these facts you must be curious to know about Big Data. Let’s know the applications of big data briefly –
|Areas||Big Data applications|
|Targeting customers||Big Data helps understanding customers and target them in personalized fashion.|
|Science and Research||Big Data helps make machines smarter. For example, Google’s Self-driving cars|
|Security||Big Data is used to keep track of the terrorists and anti-national agencies|
|Finance||Big Data algorithms are used to analyze market and trading opportunities|
After successful completion of this Tutorial, you as an individual will have enough working knowledge and proficiency in the following:
The ultimate goal of this Tutorial is to help you become a professional in the field of Big Data and Hadoop and ensuring you have enough skills to work in an industrial environment and solve real world problems to come up with solutions that make a difference to this world.
The term Big Data refers to all the data that is being generated across the globe at an unprecedented rate. This data could be either structured or unstructured. Today’s business enterprises owe a huge part of their success to an economy that is firmly knowledge-oriented. Data drives the modern organizations of the world and hence making Read More
In the last decade mankind has seen a pervasive amount of growth in data. Then we started looking for ways to put these data in use. Analyzing and Learning from these data has opened many doors of opportunities. That is how Big Data became a buzzword in IT industry. Then we are introduced to different Read More
Apache Hadoop is a Big Data framework that is part of the Apache Software Foundation. Hadoop is an open source software project that is extensively used by some of the biggest organizations in the world for distributed storage and processing of data on a level that is just enormous in terms of volume. That’s the reason Read More
Big Data and analytics are some of the most envied jobs of our generation. The simple reason for this being today there is an urgent need for Big Data and Hadoop professionals regardless of the organization’s industry segmentation or vertical. So this Tutorial is intended towards those individuals who are awed by the sheer might of Big Data Read More
Big Data by its very nature is hugely challenging to work with. But the rewards of making sense of Big Data is hugely rewarding too. All Big Data can be categorized into: Structured –that which can be stored in rows and columns like relational data sets Unstructured – data that cannot be stored in rows Read More
Most database management systems are not up to scratch for operating at such lofty levels of Big data exigencies either due to the sheer technical inefficiency or the insurmountable financial challenges posed. When the type of data is totally unstructured, the volume of data is humongous, the results needed are at breakneck speeds, then Read More
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 volumes of data. Then there are Read More
Hadoop stores petabytes of data using the HDFS technology. Using HDFS it is possible to connect commodity hardware or personal computers, also known as nodes in Hadoop parlance. These nodes are connected over a cluster on which the data files are stored in a distributed manner. Using the power of HDFS the whole cluster and the Read More
Installing Java Syntax of java version command $ java -version Following output is presented. java version "1.7.0_71" Java(TM) SE Runtime Environment (build 1.7.0_71-b13) Java HotSpot(TM) Client VM (build 25.0-b02, mixed mode) Creating User Account System user account on both master and slave systems should be created to use the Hadoop installation. # useradd hadoop Read More
Setting up of the Hadoop cluster: Here you will learn how to successfully install Hadoop and configure the clusters which could range from just a couple of nodes to even tens of thousands over huge clusters. So for that, first you need to install Hadoop on a single machine. The requirement for that is you need to install Java if Read More
MapReduce is the framework that is used for processing large amounts of data on commodity hardware on a cluster ecosystem. The MapReduce is a powerful method of processing data when there are very huge amounts of node connected to the cluster. The two important tasks of the MapReduce algorithm are, as the name suggests Read More
The Apache Hadoop YARN stands for Yet Another Resource Negotiator. It is a very efficient technology to manage the Hadoop cluster. YARN is a part of Hadoop 2 version under the aegis of the Apache Software Foundation. YARN is a completely new way of processing data and is now rightly at the centre of The Hadoop Read More
Apache Pig The Apache Pig is a platform for managing large sets of data which consists of high-level programming to analyze the data. Pig also consists of the infrastructure to evaluate the programs. The advantages of Pig programming is that it can easily handle parallel processes for managing very large amounts of data. The programming on this platform is basically Read More
Hadoop is one of the trending technologies which is used by a wide variety of organizations for research and production. This helps the user leverage several servers that offer computation and storage. Now, let us understand what MapReduce is and why it is important. MapReduce is something which comes under Hadoop. It is a programming Read More
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