hadoop architecture SOFTWARE

Apache Hadoop HDFS Architecture follows a Master/Slave Architecture, where a cluster comprises of a single NameNode (Master node) and all the other nodes are DataNodes (Slave nodes). HDFS can be deployed on a broad spectrum of machines that support Java.

The hadoop distributed file system: Architecture and design
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The Hadoop File System (HDFS) is as a distributed file system running on commodity hardware. It has many similarities with existing distributed file systems. However, the differences from other distributed file systems are significant. HDFS is highly fault-tolerant

Hadoop architecture and its usage at facebook
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Page 1. Hadoop Architecture and its Usage at Facebook Dhruba Borthakur Project Lead, Apache Hadoop Distributed File System dhruba@apache.org Presented at Microsoft Research, Seattle October 16 Page 2. Outline Introduction Architecture of Hadoop Distributed File System ▪

A Big Data Hadoop Architecture for Online Analysis
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Big Data is a collection of data that is large or complex to process using on-hand database management tools or data processing applications. Big Data has recently become one of the issues important in the networking world. Hadoop is a distributed paradigm used to

Hadoop Architecture and Fault Tolerence Based Hadoop Clusters in Geographically Distributed Data Center
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In todays epoch of computer science storing and computing data is a very important phase. In recent days even a petabyte and exabytes of data is not adequate for storing large number of databases which contains large data sets. Therefore organizations today use

Hadoop based enhanced cloud architecture
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Explosion of biological data due to large-scale genomic research and advances in high throughput data generation tools result in massive distributed datasets. Analysis of such large nonrelational, heterogeneous, and distributed datasets is emerging challenge in data

Hadoop architecture and its functionality
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Hadoop is nothing but a framework of tools and it is a java based programming framework (In simple terms it is not software). The main target of hadoop is to process the large data sets into smaller distributed computing. It is part of the Apache project sponsored by the

Unified big data Lambda Architecture with Hadoop /Flume/Spark SQL Streaming/Scala/Cassandra
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Big data is a term that describes the large volume of both structured and unstructured data that inundates a business on a day-to-day basis. Due to the fact that the database systems like RDBMS can process the unstructured data but RDBMS finds it challenging to handle

A brief review on Hadoop architecture and its issues
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With enormous data present all over the world, the need of managing the data has also risen. Hadoop is used to maintain and process such large amount of data. Hadoop is an Apache framework which is used to store and process large amount of data. The data is

Design of HBase and hybrid Hadoop ecosystem architecture in transportation data management
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Analyze voluminous complex traffic data Infer knowledge from noisy and heterogeneous sources Enhance data quality and search engine capability Reduce cost and time to get actionable insights Achieve a high fault-tolerance traffic management system with no

Improvisation of Incremental Computing in Hadoop Architecture with File Caching
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Incremental data is a difficult problem, as it requires the continues development of well defined algorithms and a runtime system to support the continuous progress in computation. Many online data sets are elastic in nature. New entries get added with respect to the

Enhancement Data Integrity Checking Using Combination MD5 and SHA1 Algorithm in Hadoop Architecture
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The use of Big Data in decision-making is critical, in line with the growing size of data storage, either online or offline. However, there are only a few software applications that are capable to process large-capacity data such as Hadoop . Hadoop is open-source software

Architecture Design for Hadoop No-SQL and Hive
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Big data came into existence when the traditional relational database systems were not able to handle the unstructured data (weblogs, videos, photos, social updates, human behaviour) generated today by organisation, social media, or from any other data generating source

Improving the scalability of movement monitoring workflows: An architecture for the integration of the hadoop file system into e-science central
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Understanding patient activity levels is important to assessing key lifestyle variables linked to obesity, diabetes and cardiovascular disease. The MOVEeCloud project makes use of wrist worn accelerometers to measure movement data over three axes at approximately

Architecture for Hadoop Distributed File Systems
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The Hadoop Distributed File System (HDFS) is designed to store very large data sets reliably, and to stream those data sets at high bandwidth to user applications. In a large cluster, thousands of servers both host directly attached storage and execute user

The Hadoop Distributed File System: Architecture and Internals
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Hadoop is a popular for storage and implementation of the large datasets. Implementation is done by MapReduce but for that we need proper management and storage of datasets. This responsibility to store large datasets is taken by HDFS. In this paper, we describe the high

An In-Memory RDMA-Based Architecture for the Hadoop Distributed Filesystem
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In the past years, there has been a growing interest in realtime and low-latency data processing systems for the cloud. To accommodate those emerging demands, the underlying data storage systems should be fundamentally designed to make better use of

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ABSTRACT Big Data Analytics is now a key ingredient for success in many business organizations, scientific and engineering disciplines and government endeavors. The data management has become a challenging issue for network centric applications which need

Satellite image processing using CUDA and Hadoop architecture
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With the advancement in digitalization vast amount of Image data is uploaded and used via Internet in todays world. With this revolution in uses of multimedia data, key problem in the area of Image processing, Computer vision and big data analytics is how to analyze

Improvisation of Incremental Computing In Hadoop Architecture -A Literature
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Automatic increment in data is a difficult problem, as it requires the development of well- defined algorithms and a runtime system to support performance code. Many online data sets grow incrementally over time as new entries are slowly added and existing entries are

Parallel Image Processing from Cloud using CUDA and HADOOP Architecture : A Novel Approach
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In There is an increased, large quantity if data with the super-resolution quality data, hence there is an increased demand in high quality image data. This requirements causes a challenge in disk space in single PC or computers. A primary solution to employ the storage