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2025년 2월 1일 (토)

• 12:352025년 2월 1일 (토) 12:35 차이 역사 +3,291‎ 새글 RAMCloud ‎ 새 문서: '''RAMCloud''' is a distributed in-memory storage system designed for low-latency and high-throughput applications. It provides persistent storage with sub-microsecond access times by keeping all data in DRAM while ensuring durability through fast logging to disk or flash. ==Overview== RAMCloud aims to combine: *'''Low-Latency Storage:''' Data is stored entirely in DRAM for rapid access. *'''High Availability:''' Data is replicated across servers for fault tolerance. *'''Durabil... 최신 태그: 시각 편집
• 12:342025년 2월 1일 (토) 12:34 차이 역사 +4,195‎ 새글 Resilient Distributed Datasets ‎ 새 문서: '''Resilient Distributed Datasets (RDDs)''' are the fundamental data structure in Apache Spark that provide fault-tolerant, parallel computation on large datasets. RDDs enable efficient distributed data processing while ensuring resilience to failures. ==Overview== RDDs are immutable, distributed collections of objects that can be processed in parallel. They are designed to optimize large-scale data processing by: *'''Fault Tolerance:''' Automatically recovering lost data us... 최신 태그: 시각 편집
• 10:532025년 2월 1일 (토) 10:53 차이 역사 +3,908‎ 새글 Distributed Shared Memory ‎ 새 문서: '''Distributed Shared Memory (DSM)''' is a memory management architecture that enables multiple distributed systems to share a logical memory space, allowing processes on different machines to access shared data as if they were on a single system. ==Overview== Distributed shared memory provides an abstraction that simplifies parallel and distributed computing by: *'''Providing a unified memory model:''' Applications access memory as if it were shared, even though it is physicall... 최신 태그: 시각 편집
• 10:522025년 2월 1일 (토) 10:52 차이 역사 +3,476‎ 새글 Piccolo ‎ 새 문서: '''Piccolo''' is a distributed in-memory computing framework designed to simplify the development of parallel applications. It provides a shared, distributed key-value store that allows workers to efficiently process large datasets while reducing communication overhead. ==Overview== Piccolo enables efficient distributed computing by: *'''In-Memory Data Storage:''' Uses a distributed key-value store to minimize disk I/O. *'''Fine-Grained Data Sharing:''' Allows workers to share s... 최신 태그: 시각 편집
• 05:532025년 2월 1일 (토) 05:53 차이 역사 +3,394‎ 새글 FlumeJava ‎ 새 문서: '''FlumeJava''' is a Java-based distributed data processing framework developed by Google for building and executing efficient, parallel, and distributed pipelines. It provides an abstraction over MapReduce and other parallel computation models, enabling users to write high-level data processing workflows. ==Overview== FlumeJava simplifies large-scale data processing by providing: *'''Lazy Evaluation:''' Pipelines are defined but not executed immediately, allowing for optimizati... 최신 태그: 시각 편집
• 05:442025년 2월 1일 (토) 05:44 차이 역사 +3,408‎ 새글 DryadLINQ ‎ 새 문서: '''DryadLINQ''' is a distributed computing framework developed by Microsoft that extends LINQ (Language Integrated Query) to work with large-scale data processing using the Dryad execution engine. It allows users to write data-parallel computations in C# or other .NET languages while leveraging distributed computing resources. ==Overview== DryadLINQ simplifies distributed data processing by combining: *'''Dryad''': A distributed execution engine that processes dataflow graphs ac... 최신 태그: 시각 편집