Apache hadoop & map reduce

Feb 28, 20130 likes656 views

This document discusses Apache Hadoop and how it provides solutions for big data problems through MapReduce and HDFS. It outlines key issues like hardware failure and combining data when implementing parallelism for big data storage and analysis. Hadoop overcomes these issues using HDFS for reliable shared storage and MapReduce for reliable analysis through processing data in parallel using keys and values. MapReduce is a batch query processor that is already used by companies to handle large datasets, providing an alternative to traditional RDBMS for big data applications.

Apache Hadoop, BigData & MapReduce

WHY BIG DATA:

“More data usually beats better algorithm.”

GOOD NEWS:

“Big data is here.”

BAD NEWS:

We are struggling to store and analyze it.

KEY PROBLEM:

“Storage increased, not Speed.”

SOLUTION:

 Parallelism

But, while implementing parallelism we may face some noteworthy problems like;

Hardware failure

Combining data

These problems have been overcome by Hadoop because of use of –

HDFS ( Hadoop Distributed File System)

MapReduce ( use of keys and values)

In a nutshell,

Hadoop provides - A reliable Shared Storage (by HDFS)

-A reliable Analysis System (by MapReduce)

MAPREDUCE:

Entire database or a good portion of it is processed for each query.

MapReduce is a batch query processor.

Already used by Mailtrust , Rackspace’s mail division for handling big data.

MAPREDUCE VS RDBMS:

CONCLUSION:

Though a thorough understanding is absent here, more research will make it more clarified and

distinguished as well. Some more valuable information will enrich it in the coming days.

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Report writing(long)Md. Mahedi Mahfuj

This document discusses the organization and structure of long, formal reports. It covers the typical components of such reports, including a title page, executive summary, table of contents, introduction, body, conclusion, and appendix. The introduction defines the problem and purpose of the report and outlines the scope and sources of information. The body presents and analyzes the findings. Conclusions and recommendations are stated at the end. For longer reports, coherence is improved through previews, section introductions, summaries, and an overall concluding summary. Maintaining a clear structural plan helps ensure the reader understands the content.

Job search_resumeMd. Mahedi Mahfuj

- Assisted customers with mailing needs and questions. - Processed mail and packages for delivery. - Maintained clean and organized work area. 1996-1997 McDonald's, Indianapolis. Worked as a Crew Member: - Prepared and served food to customers in a timely manner. - Operated cash register and accepted payments from customers. - Maintained cleanliness standards in food preparation and dining areas. Education: 1999-Present Indiana University, Indianapolis, IN. Pursuing a Bachelor of Science in Business Administration. 26 4/1/2013 Functional Resume Style  Groups experiences and skills by function or skill area rather than chron

Job search_interviewMd. Mahedi Mahfuj

This document provides tips for job interviews, including investigating the company beforehand, making a good appearance, anticipating questions and preparing answers, controlling the dialogue, following up after the interview, and continuing job search activities. It discusses researching the company's history, products, competitors, growth, reputation and culture. It also offers advice on writing thank you notes, follow ups, accepting or declining a job offer, resigning from a current role, and maintaining resumes and reading industry publications.

R languageMd. Mahedi Mahfuj

R is an open source programming language and software environment for statistical computing and graphics. It is widely used for developing statistical software and analyzing data. The document outlines some basic R commands, including getting the working directory, assigning values, calculating mean and variance, creating linear models, plotting graphs, summarizing models, listing variables, and reading files. Integrating R with Hadoop will allow for more efficient management of big data.

Big dataMd. Mahedi Mahfuj

Big data is large amounts of data that are difficult to manage and process using traditional database tools. It is characterized by high volume, velocity, and variety. Big data is now commonly found in data warehouses, online transaction processing systems, social networks, and scientific devices. To effectively filter big data, it must be extracted from raw feeds, transformed into a usable set of data, and loaded into systems. While big data enables better decision making and new opportunities, it also poses risks like being overwhelmed by the data or privacy issues that require mitigation through the right expertise, focus, and regulations.

Chatbot Artificial IntelligenceMd. Mahedi Mahfuj

The document discusses artificial text chatting machines (chatbots). It provides an overview of chatbots, including their history starting with ELIZA from 1966. Common approaches to developing chatbots include pattern matching and using the Artificial Intelligence Markup Language (AIML). The document outlines some challenges in developing human-like intelligence for chatbots and possibilities for future work, before concluding with a demonstration.

Cloud testing v1Md. Mahedi Mahfuj

The document summarizes two papers on software testing in the cloud. The first paper discusses the generalized procedure for cloud testing, including user login, resource provisioning, payment, and implementation through functional, performance, load and stress testing. It also outlines the pros of cost savings and improved efficiency, and the cons of security and restrictions. The second paper uses grounded theory and snowball sampling to identify application, management, legal and financial issues for cloud-based software testing, such as test data ownership, pricing models, and quality assurance across cloud providers. Both papers note that challenges in cloud testing implementation and standardization require further research.

Distributed deadlockMd. Mahedi Mahfuj

Distributed deadlock occurs when processes are blocked while waiting for resources held by other processes in a distributed system without a central coordinator. There are four conditions for deadlock: mutual exclusion, hold and wait, non-preemption, and circular wait. Deadlock can be addressed by ignoring it, detecting and resolving occurrences, preventing conditions through constraints, or avoiding it through careful resource allocation. Detection methods include centralized coordination of resource graphs or distributed probe messages to identify resource waiting cycles. Prevention strategies impose timestamp or age-based priority to resource requests to eliminate cycles.

Paper review Md. Mahedi Mahfuj

The document reviews 3 papers on cloud computing and software testing as a service. Paper 1 provides an overview of cloud testing and discusses which types of testing can be done, benefits, and a general process. Paper 2 identifies research issues around cloud testing from application, management, legal and financial perspectives but neglects security. Paper 3 deals with cloud interoperability protocols and implicit communication between clouds. The review concludes cloud computing will continue enabling more online software testing and further research on standardizing cloud testing is needed.

Parallel computing(1)Md. Mahedi Mahfuj

Message passing interfaceMd. Mahedi Mahfuj

Advanced computer architectureMd. Mahedi Mahfuj

Database management system chapter16Md. Mahedi Mahfuj

Database management system chapter15Md. Mahedi Mahfuj

Database management system chapter12Md. Mahedi Mahfuj

Strategies in job search processMd. Mahedi Mahfuj

Report writing(short)Md. Mahedi Mahfuj

Report writing(long)Md. Mahedi Mahfuj

Job search_resumeMd. Mahedi Mahfuj

Job search_interviewMd. Mahedi Mahfuj

R languageMd. Mahedi Mahfuj

Big dataMd. Mahedi Mahfuj

Chatbot Artificial IntelligenceMd. Mahedi Mahfuj

Cloud testing v1Md. Mahedi Mahfuj

Distributed deadlockMd. Mahedi Mahfuj

Paper review Md. Mahedi Mahfuj

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