MapReduce is a programming model and implementation used for processing big data sets in parallel on a cluster. It consists of a map procedure for filtering and sorting data, and a reduce method for summarizing the results. The model is inspired by functional programming and is optimized for scalability and fault tolerance.
Stanford University
Winter 2022
CS 110 delves into advanced computer systems and program construction, focusing on designing large systems, software that spans multiple machines, and parallel computing. This course builds upon CS107 and requires good knowledge of C, C++, Unix, GDB, Valgrind, and Make. It covers Linux filesystems, multiprocessing, threading, networking, and more.
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+ 28 more conceptsUC Berkeley
Spring 2023
This project-heavy course covers access methods, data models, query languages, database services, and interfaces. It introduces transaction processing and requires CS 61A, CS 61B, and CS 61C as prerequisites/corequisites. It suggests proficiency in Java for project work.
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+ 23 more conceptsStanford University
Summer 2021
Requiring familiarity with C/C++ and Unix/Linux, delves into computer systems principles. Students will engage with a blend of C and C++ to interface with system resources and manage complex projects. The course covers a broad range of topics including filesystems, multiprocessing, synchronization, networking, and MapReduce.
No concepts data
+ 24 more conceptsUC Berkeley
Fall 2021
A graduate survey of systems managing computation and information. Topics include volatile and persistent memory management, system support for networking, security infrastructure, extensible systems, APIs, and large software system performance analysis. Students are expected to engage in quality systems research, culminating in a publishable group project.
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+ 31 more conceptsCarnegie Mellon University
Fall 2020
A course offering both theoretical understanding and practical experience in distributed systems. Key themes include concurrency, scheduling, network communication, and security. Real-world protocols and paradigms like distributed filesystems, RPC, MapReduce are studied. Course utilizes C and Go programming languages.
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+ 34 more conceptsUC Berkeley
Fall 2022
This course deepens students' understanding of computer architecture and the translation of high-level programs into machine language. Emphasis is on C and assembly language programming, computer organization, parallelism, CPU design, and warehouse-scale computing. Prerequisites include CS61A and CS61B or equivalent C-based programming experience.
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+ 51 more concepts