Hadoop is a framework for distributed storage and processing of large datasets across clusters of commodity hardware. It includes HDFS, a distributed file system, and MapReduce, a programming model for large-scale data processing. HDFS stores data reliably across clusters and allows computations to be processed in parallel near the data. The key components are the NameNode, DataNodes, JobTracker and TaskTrackers. HDFS provides high throughput access to application data and is suitable for applications handling large datasets.
Best Hadoop Institutes : kelly tecnologies is the best Hadoop training Institute in Bangalore.Providing hadoop courses by realtime faculty in Bangalore.
We Provide Hadoop training institute in Hyderabad and Bangalore with corporate training by 12+ Experience faculty.
Real-time industry experts from MNCs
Resume Preparation by expert Professionals
Lab exercises
Interview Preparation
Experts advice
Big Data Architecture Workshop - Vahid Amiridatastack
Big Data Architecture Workshop
This slide is about big data tools, thecnologies and layers that can be used in enterprise solutions.
TopHPC Conference
2019
Data Lake and the rise of the microservicesBigstep
By simply looking at structured and unstructured data, Data Lakes enable companies to understand correlations between existing and new external data - such as social media - in ways traditional Business Intelligence tools cannot.
For this you need to find out the most efficient way to store and access structured or unstructured petabyte-sized data across your entire infrastructure.
In this meetup we’ll give answers on the next questions:
1. Why would someone use a Data Lake?
2. Is it hard to build a Data Lake?
3. What are the main features that a Data Lake should bring in?
4. What’s the role of the microservices in the big data world?
Best Hadoop Institutes : kelly tecnologies is the best Hadoop training Institute in Bangalore.Providing hadoop courses by realtime faculty in Bangalore.
We Provide Hadoop training institute in Hyderabad and Bangalore with corporate training by 12+ Experience faculty.
Real-time industry experts from MNCs
Resume Preparation by expert Professionals
Lab exercises
Interview Preparation
Experts advice
Big Data Architecture Workshop - Vahid Amiridatastack
Big Data Architecture Workshop
This slide is about big data tools, thecnologies and layers that can be used in enterprise solutions.
TopHPC Conference
2019
Data Lake and the rise of the microservicesBigstep
By simply looking at structured and unstructured data, Data Lakes enable companies to understand correlations between existing and new external data - such as social media - in ways traditional Business Intelligence tools cannot.
For this you need to find out the most efficient way to store and access structured or unstructured petabyte-sized data across your entire infrastructure.
In this meetup we’ll give answers on the next questions:
1. Why would someone use a Data Lake?
2. Is it hard to build a Data Lake?
3. What are the main features that a Data Lake should bring in?
4. What’s the role of the microservices in the big data world?
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
TECHNICAL TRAINING MANUAL GENERAL FAMILIARIZATION COURSEDuvanRamosGarzon1
AIRCRAFT GENERAL
The Single Aisle is the most advanced family aircraft in service today, with fly-by-wire flight controls.
The A318, A319, A320 and A321 are twin-engine subsonic medium range aircraft.
The family offers a choice of engines
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
Contact with Dawood Bhai Just call on +92322-6382012 and we'll help you. We'll solve all your problems within 12 to 24 hours and with 101% guarantee and with astrology systematic. If you want to take any personal or professional advice then also you can call us on +92322-6382012 , ONLINE LOVE PROBLEM & Other all types of Daily Life Problem's.Then CALL or WHATSAPP us on +92322-6382012 and Get all these problems solutions here by Amil Baba DAWOOD BANGALI
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Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
3. Operating systems
• Operating system - Software that supervises
and controls tasks on a computer. Individual
OS:
– Batch processing jobs are collected, placed in
a queue, no interaction with job during processing
– Time shared computing resources are provided
to different users, interaction with program during
execution
– RT systems fast response, can be interrupted
4. Distributed Systems
• Consists of a number of computers that are connected and
managed so that they automatically share the job processing
load among the constituent computers.
• A distributed operating system is one that appears to its users as
a traditional uniprocessor system, even though it is actually
composed of multiple processors.
• It gives a single system view to its users and provides a single
service.
• Users are transparent to location of files. It provides a virtual
computing env.
Eg The Internet, ATM banking networks, mobile computing
networks, Global Positioning Systems and Air Traffic Control
DISTRIBUTED SYSTEM IS A COLLECTION OF INDEPENDENT
COMPUTERS THAT APPEARS TO IS USERS AS A SINGLE
COHERENT SYSTEM
5. Network Operating System
• In a network operating system the users are aware
of the existence of multiple computers.
• The operating system of individual computers must
have facilities to have communication and
functionality.
• Each machine runs its own OS and has its own user.
• Remote login and file access
• Less transparent but more independency
Applicatio
n
Applicatio
n
Applicatio
n
Distributed Operating System Services
Application Application Application
Network
OS
Network
OS
Network
OS
Distributed OS Networked OS
6. DFS
• Resource sharing is the motivation behind distributed
Systems. To share files file system
• File System is responsible for the organization, storage,
retrieval, naming, sharing, and protection of files.
• The file system is responsible for controlling access to
the data and for performing low-level operations such as
buffering frequently used data and issuing disk I/O
requests
• The goal is to allow users of physically distributed
computers to share data and storage resources by
using a common file system.
7. Hadoop
What is Hadoop?
It's a framework for running applications on large clusters of
commodity hardware which produces huge data and to
process it
Apache Software Foundation Project
Open source
Amazon’s EC2
alpha (0.18) release available for download
Hadoop Includes
HDFS a distributed filesystem
Map/Reduce HDFS implements this programming model. It
is an offline computing engine
Concept
Moving computation is more efficient than moving large
data
8. • Data intensive applications with Petabytes of data.
• Web pages - 20+ billion web pages x 20KB = 400+
terabytes
– One computer can read 30-35 MB/sec from disk
~four months to read the web
– same problem with 1000 machines, < 3 hours
• Difficulty with a large number of machines
– communication and coordination
– recovering from machine failure
– status reporting
– debugging
– optimization
– locality
9. FACTS
Single-thread performance doesn’t matter
We have large problems and total throughput/price more
important than peak performance
Stuff Breaks – more reliability
• If you have one server, it may stay up three years (1,000 days)
• If you have 10,000 servers, expect to lose ten a day
“Ultra-reliable” hardware doesn’t really help
At large scales, super-fancy reliable hardware still fails, albeit
less often
– software still needs to be fault-tolerant
– commodity machines without fancy hardware give better
perf/price
DECISION : COMMODITY HARDWARE.
DFS : HADOOP – REASONS?????
10. HDFS Why? Seek vs Transfer
• CPU & transfer speed, RAM & disk size double every 18
- 24 months
• Seek time nearly constant (~5%/year)
• Time to read entire drive is growing vs transfer rate.
• Moral: scalable computing must go at transfer rate
• BTree (Relational DBS)
– operate at seek rate, log(N) seeks/access
-- memory / stream based
• sort/merge flat files (MapReduce)
– operate at transfer rate, log(N) transfers/sort
-- Batch based
12. Characteristics
• Fault tolerant, scalable, Efficient, reliable distributed
storage system
• Moving computation to place of data
• Single cluster with computation and data.
• Process huge amounts of data.
• Scalable: store and process petabytes of data.
• Economical:
– It distributes the data and processing across clusters of
commonly available computers.
– Clusters PCs into a storage and computing platform.
– It minimises no of CPU cycles, RAM on individual
machines etc.
• Efficient:
– By distributing the data, Hadoop can process it in parallel on
the nodes where the data is located. This makes it extremely
rapid.
– Computation is moved to place where data is present.
• Reliable:
– Hadoop automatically maintains multiple copies of data
– Automatically redeploys computing tasks based on failures.
14. • Data Model
– Data is organized into files and directories
– Files are divided into uniform sized blocks and
distributed across cluster nodes
– Replicate blocks to handle hardware failure
– Checksums of data for corruption detection
and recovery
– Expose block placement so that computes
can be migrated to data
• large streaming reads and small random reads
• Facility for multiple clients to append to a file
15. • Assumes commodity hardware that fails
– Files are replicated to handle hardware
failure
– Checksums for corruption detection and
recovery
– Continues operation as nodes / racks added
/ removed
• Optimized for fast batch processing
– Data location exposed to allow computes to
move to data
– Stores data in chunks/blocks on every node
in the cluster
– Provides VERY high aggregate bandwidth
16. • Files are broken in to large blocks.
– Typically 128 MB block size
– Blocks are replicated for reliability
– One replica on local node,
another replica on a remote rack,
Third replica on local rack,
Additional replicas are randomly placed
• Understands rack locality
– Data placement exposed so that computation can be
migrated to data
• Client talks to both NameNode and DataNodes
– Data is not sent through the namenode, clients
access data directly from DataNode
– Throughput of file system scales nearly linearly with
the number of nodes.
19. Components
• DFS Master “Namenode”
– Manages the file system namespace
– Controls read/write access to files
– Manages block replication
– Checkpoints namespace and journals
namespace changes for reliability
Metadata of Name node in Memory
– The entire metadata is in main memory
– No demand paging of FS metadata
Types of Metadata:
List of files, file and chunk namespaces; list of
blocks, location of replicas; file attributes etc.
20. DFS SLAVES or DATA NODES
• Serve read/write requests from clients
• Perform replication tasks upon instruction by
namenode
Data nodes act as:
1) A Block Server
– Stores data in the local file system
– Stores metadata of a block (e.g. CRC)
– Serves data and metadata to Clients
2) Block Report: Periodically sends a report of all
existing blocks to the NameNode
3) Periodically sends heartbeat to NameNode (detect
node failures)
4) Facilitates Pipelining of Data (to other specified
DataNodes)
21. • Map/Reduce Master “Jobtracker”
– Accepts MR jobs submitted by users
– Assigns Map and Reduce tasks to Tasktrackers
– Monitors task and tasktracker status, re-
executes tasks upon failure
• Map/Reduce Slaves “Tasktrackers”
– Run Map and Reduce tasks upon instruction
from the Jobtracker
– Manage storage and transmission of
intermediate output.
22. SECONDARY NAME NODE
• Copies FsImage and Transaction Log from
NameNode to a temporary directory
• Merges FSImage and Transaction Log into
a new FSImage in temporary directory
• Uploads new FSImage to the NameNode
– Transaction Log on NameNode is purged
23. HDFS Architecture
• NameNode: filename, offset> blockid, block > datanode
• DataNode: maps block > local disk
• Secondary NameNode: periodically merges edit logs
Block is also called chunk
25. HDFS API
• Most common file and directory operations
supported:
– Create, open, close, read, write, seek, list,
delete etc.
• Files are write once and have exclusively
one writer
• Some operations peculiar to HDFS:
– set replication, get block locations
• Support for owners, permissions
26. DATA CORRECTNESS
• Use Checksums to validate data
– Use CRC32
• File Creation
– Client computes checksum per 512 byte
– DataNode stores the checksum
• File access
– Client retrieves the data and checksum from
DataNode
– If Validation fails, Client tries other replicas
27. MUTATION ORDER AND LEASES
• A mutation is an operation that changes the
contents / metadata of a chunk such as append /
write operation.
• Each mutation is performed at all replicas.
• Leases (order of mutations) are used to maintain
consistency
• Master grants chunk lease to one replica
(primary)
• Primary picks the serial order for all mutations to
the chunk
• All replicas follow this order (consistency)
28.
29. Software Model - ???
• Parallel programming improves performance and
efficiency.
• In a parallel program, the processing is broken up into
parts, each of which can be executed concurrently
• Identify whether the problem can be parallelised (fib)
• Matrix operations with independency
30. Master/Worker
• The MASTER:
– initializes the array and splits it up according
to the number of available WORKERS
– sends each WORKER its subarray
– receives the results from each WORKER
• The WORKER:
– receives the subarray from the MASTER
– performs processing on the subarray
– returns results to MASTER
31. The area of the square, denoted
As = (2r)^2 or 4r^2.
The area of the circle, denoted
Ac, is pi * r2.
• pi = Ac / r^2
• As = 4r^2
• r^2 = As / 4
• pi = 4 * Ac / As
• pi= 4 * No of pts on
the circle / num of
points on the square
CALCULATING PI
32. • Randomly generate points in the square
• Count the number of generated points that are
both in the circle and in the square MAP
(find ra = No of pts on the circle / num of points
on the square)
• ra = the number of points in the circle divided
by the number of points in the square
gather all ra
• PI = 4 * r REDUCE
Parallelised calculation of points on the circle
(MAP)
Then merged in to find PI REDUCE
34. WHAT IS MAP REDUCE PROGRAMMING
• Restricted parallel programming model meant
for large clusters
– User implements Map() and Reduce()
• Parallel computing framework (HDFS lib)
– Libraries take care of EVERYTHING else
(abstraction)
• Parallelization
• Fault Tolerance
• Data Distribution
• Load Balancing
• Useful model for many practical tasks