what does commodity hardware in hadoop world mean

by Rylan Nicolas Sr. Published 3 years ago Updated 2 years ago

The Hadoop Distributed File System (HDFS) is a distributed file system designed to run on hardware based on open standards or what is called commodity hardware. This means the system is capable of running different operating systems (OSes) such as Windows or Linux without requiring special drivers.

Full Answer

Why do we use commodity hardware in Hadoop?

Another benefit of using commodity hardware in Hadoop is scalability. Commodity hardware is readily available in market. Whenever we need to scale up our operations in Hadoop cluster we can obtain more commodity hardware. In case of high-end machines, we have to raise purchase orders and get them built on demand.

What is commodity hardware?

Commodity hardware, sometimes known as off-the-shelf hardware, is a computer device or IT component that is relatively inexpensive, widely available and basically interchangeable with other hardware of its type. Generally, commodity hardware can evolve from any technologically mature product.

Why did Hadoop start?

So hadoop started from idea of getting distributed parallel processing and storage to commodity computer/machine which are affordable than humongous servers. This is the reason hadoop used to run on commodity hardware in past.

What Hardware do I need to install Hadoop?

Hadoop can be installed on any commodity hardware. We don't need super computers or high-end hardware to work on Hadoop. Commodity hardware includes RAM because there will be some services which will be running on RAM.

What is commodity hardware?

Can Hadoop be installed on any hardware?

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What is a commodity hardware?

Commodity hardware, in an IT context, is a device or device component that is relatively inexpensive, widely available and more or less interchangeable with other hardware of its type.

What is a commodity hardware used for?

1. What does Commodity Hardware mean? Commodity hardware, some of the time known as off-the-shelf hardware, is an IT component or computer device that is generally economical, basically interchangeable and widely available with other hardware of its sort.

Is Namenode in Hadoop a commodity hardware?

The namenode is the commodity hardware that contains the GNU/Linux operating system and the namenode software. It is a software that can be run on commodity hardware. The system having the namenode acts as the master server and it does the following tasks: Manages the file system namespace.

Is Namenode also a commodity hardware?

Is Namenode also a commodity? No. Namenode can never be a commodity hardware because the entire HDFS rely on it. It is the single point of failure in HDFS.

What is a commodity software?

Commodity Software means commonly available, off-the-shelf software (excluding Open Source Materials) with aggregate value of less than $10,000 that is licensed non-exclusively to the Company in object code form only on generally available terms and is not part of or directly used to enable any product or service of ...

What are commodity systems?

The commodity system framework includes the major linkages that hold the system together such as transportation, contractual coordination, vertical integration, joint ventures, tripartite marketing arrangements, and financial arrangements.

What is NameNode and DataNode?

The main difference between NameNode and DataNode in Hadoop is that the NameNode is the master node in Hadoop Distributed File System that manages the file system metadata while the DataNode is a slave node in Hadoop distributed file system that stores the actual data as instructed by the NameNode.

What is pig in big data?

Pig is an open-source high level data flow system. It provides a simple language called Pig Latin, for queries and data manipulation, which are then compiled in to MapReduce jobs that run on Hadoop.

How many Namenodes are there in HDFS?

You can have only a single name node in a cluster. Detail - In Yarn / Hadoop 2.0 they have come with a concept of active name node and standby name node. ( This is where most of the people get confused. They consider them to be 2 nodes in a cluster).

What if a NameNode has no data?

What happens to a NameNode that has no data? Answer:There does not exist any NameNode without data. If it is a NameNode then it should have some sort of data in it.

What is a NameNode in Hadoop?

NameNode is the master node in the Apache Hadoop HDFS Architecture that maintains and manages the blocks present on the DataNodes (slave nodes). NameNode is a very highly available server that manages the File System Namespace and controls access to files by clients.

What is metadata in HDFS?

Metadata is the data about the data. Metadata is stored in namenode where it stores data about the data present in datanode like location about the data and their replicas.

Hadoop Pig MCQ Questions And Answers - Letsfindcourse

Hadoop Pig MCQ Questions. Hadoop Pig MCQs : This section focuses on "PIG" in Hadoop. These Multiple Choice Questions (MCQ) should be practiced to improve the hadoop skills required for various interviews (campus interviews, walk-in interviews, company interviews), placements, entrance exams and other competitive examinations.

Big Data MCQ Questions And Answers - Letsfindcourse

Big Data MCQ Questions And Answers. Big Data MCQs : This section focuses on "Big Data" in Hadoop. These Multiple Choice Questions (MCQ) should be practiced to improve the Hadoop skills required for various interviews (campus interviews, walk-in interviews, company interviews), placements, entrance exams and other competitive examinations.

Big Data MCQ [Free PDF] - Objective Question Answer for Big Data Quiz ...

The correct answer is option 1. Important Points. In Relational Databases, all the required schemas must be defined before adding any data.SQL is used to query the database. Non-Relational databases do not use tabular schemas like rows and columns. Hence no schema is required before you add data. NoSQL is used to query the database.

HHAADDOOOOPP MMOOCCKK TTEESSTT - Tutorials Point

A - Hdfs-site.xml B - Hdfs-defaukt.xml C - Core-site.xml D - Mapred-site.xml Q 28 - The namenode loses its only copy of fsimage file. We can recover this from

What is Hadoop used for?

But the reality is that a lot of companies are using both of them, Hadoop for maintaining and implementing big data analytics and Spark for ETL and SQL batch operations over huge datasets, IoT, and ML assignments.

How did Hadoop start?

So hadoop started from idea of getting distributed parallel processing and storage to commodity computer/machine which are affordable than humongous servers.

Which is better: Hadoop or Spark?

These frameworks are two of the most noticeable spread systems for processing Big data in business. Hadoop is generally used for disk-heavy services with the MapReduce paradigm, while Spark is more manageable, but more high-priced in-memory processing framework. Both are Apache top-level services, are usually used coincidentally, though it’s necessary to know the peculiarities of each when choosing them.

What is HDFS in architecture?

HDFS, a system for putting big data across various nodes in a classified architecture.

Why is a general platform important in big data?

Having a general platform is even more important in big data, because data is so expensive to move across systems! In this case, Spark shows that many of the tricks used in specialized systems today (e.g. column-oriented processing, graph partitioning tricks) can be implemented on a general platform.

What cloud is used for big data?

Eventually as big data grew to larger extent people started using instances hosted on clouds (AWS,Azure) or they have on premise cluster of better server machines in production environment.

What are some examples of commodity hardware?

In short your day to day machine (desktop,laptop) are few example of commodi ty hardware .

Why should mapred.reduce.slowstart.completed.maps be above 0.9?

Typically, keep mapred.reduce.slowstart.completed.maps above 0.9 if the system ever has multiple jobs running at once. This way the job doesn’t hog up reducers when they aren’t doing anything but copying data . If we have only one job running at a time, doing 0.1 would probably be appropriate.

Is a reducer always in a predictable order?

A. The keys given to a reducer aren’t in a predictable order, but the values associated with those keys always are.

Can HDFS read parallel?

20. HDFS data blocks can be read in parallel. ( A )

Is it necessary to default all the properties in Hadoop config files?

It is necessary to default all the properties in Hadoop config files.

What is commodity hardware?

Commodity Hardware: Computer hardware that is affordable and easy to obtain. Typically it is a low-performance system that is IBM PC-compatible and is capable of running Microsoft Windows, Linux, or MS-DOS without requiring any special devices or equipment. [. Click to see full answer.

Can Hadoop be installed on any hardware?

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