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Hadoop

Hadoop is an open-source software framework for distributed storage and processing of large datasets across clusters of computers. It uses MapReduce as a programming model and HDFS as a distributed file system. HDFS stores large files across clusters and replicates data for reliability, while MapReduce allows parallel processing of datasets in a fault-tolerant manner. A typical Hadoop cluster integrates these components, with a master node running job and name nodes and slave nodes running task and data nodes.

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62 views7 pages

Hadoop

Hadoop is an open-source software framework for distributed storage and processing of large datasets across clusters of computers. It uses MapReduce as a programming model and HDFS as a distributed file system. HDFS stores large files across clusters and replicates data for reliability, while MapReduce allows parallel processing of datasets in a fault-tolerant manner. A typical Hadoop cluster integrates these components, with a master node running job and name nodes and slave nodes running task and data nodes.

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jefferyleclerc
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Hadoop/MapReduce

Object-oriented framework presentation


CSCI 5448
Casey McTaggart
What is Apache Hadoop?
• Large scale, open source software framework
▫ Yahoo! has been the largest contributor to date
• Dedicated to scalable, distributed, data-intensive
computing
• Handles thousands of nodes and petabytes of data
• Supports applications under a free license
• 3 Hadoop subprojects:
▫ Hadoop Common: common utilities package
▫ HFDS: Hadoop Distributed File System with high
throughput access to application data
▫ MapReduce: A software framework for distributed
processing of large data sets on computer clusters
Hadoop MapReduce
• MapReduce is a programming model and software
framework first developed by Google (Google’s
MapReduce paper submitted in 2004)
• Intended to facilitate and simplify the processing of
vast amounts of data in parallel on large clusters of
commodity hardware in a reliable, fault-tolerant
manner
▫ Petabytes of data
▫ Thousands of nodes
• Computational processing occurs on both:
▫ Unstructured data : filesystem
▫ Structured data : database
Hadoop Distributed File System (HFDS)
• Inspired by Google File System
• Scalable, distributed, portable filesystem written in Java for
Hadoop framework
▫ Primary distributed storage used by Hadoop applications
• HFDS can be part of a Hadoop cluster or can be a stand-alone
general purpose distributed file system
• An HFDS cluster primarily consists of
▫ NameNode that manages file system metadata
▫ DataNode that stores actual data
• Stores very large files in blocks across machines in a large
cluster
▫ Reliability and fault tolerance ensured by replicating data across
multiple hosts
• Has data awareness between nodes
• Designed to be deployed on low-cost hardware
More on Hadoop file systems

• Hadoop can work directly with any distributed


file system which can be mounted by the
underlying OS
• However, doing this means a loss of locality as
Hadoop needs to know which servers are closest
to the data
• Hadoop-specific file systems like HFDS are
developed for locality, speed, fault tolerance,
integration with Hadoop, and reliability
Typical Hadoop cluster integrates
MapReduce and HFDS
• Master/slave architecture
• Master node contains
▫ Job tracker node (MapReduce layer)
▫ Task tracker node (MapReduce layer)
▫ Name node (HFDS layer)
▫ Data node (HFDS layer)
• Multiple slave nodes contain
▫ Task tracker node (MapReduce layer)
▫ Data node (HFDS layer)
• MapReduce layer has job and task tracker nodes
• HFDS layer has name and data nodes
Hadoop simple cluster graphic
MapReduce layer HFDS layer

Master Node

JobTracker TaskTracker Name Data

Slave Node
1..*
TaskTracker Data

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