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2024년 12월 14일 (토)
04:26 | 사용자 만들기 기록 Bekil kupil *982 cswiki.net n9 토론 기여 계정이 생성되었습니다 |
2024년 12월 13일 (금)
새글 01:40 | Multiversion Concurrency Control 차이역사 +3,490 Scapegoat 토론 기여 (Created page with "'''Multiversion Concurrency Control (MVCC)''' is a concurrency control method used in database systems that allows multiple versions of a data item to exist simultaneously. It ensures consistent reads without locking and provides high concurrency by maintaining transaction isolation. ==Key Concepts== *'''Data Versioning:''' MVCC creates a new version of a data item for every write operation, enabling transactions to access consistent snapshots. *'''Timestamps:''' Each tr...") |
새글 01:39 | Timestamp-Based Protocol 차이역사 +3,700 Scapegoat 토론 기여 (Created page with "'''Timestamp-Based Protocol''' is a concurrency control mechanism in database systems that uses timestamps to order transactions, ensuring serializability. Each transaction is assigned a unique timestamp when it begins, and the protocol uses these timestamps to determine the execution order of conflicting operations. ==Key Concepts== *'''Timestamp:''' A unique identifier (usually based on the system clock or a counter) assigned to each transaction when it starts. *'''Rea...") |
새글 01:35 | Lock-Based Protocol 차이역사 +3,804 Scapegoat 토론 기여 (Created page with "'''Lock-Based Protocol''' is a concurrency control mechanism in database systems that ensures transaction isolation by managing access to data items through locks. Locks prevent simultaneous transactions from interfering with each other, ensuring data consistency and serializability. ==Key Concepts== *'''Lock:''' A mechanism that restricts access to a data item for concurrent transactions. *'''Lock Modes:''' **'''Shared Lock (S):''' Allows multiple transactions to read a...") |
새글 01:33 | Two-Phase Locking 차이역사 +3,740 Scapegoat 토론 기여 (Created page with "'''Two-Phase Locking (2PL)''' is a concurrency control protocol used in database systems to ensure serializability of transactions. It operates in two distinct phases where locks are acquired and released in a specific order, preventing conflicts between concurrent transactions. ==Key Concepts== *'''Locking Protocol:''' Transactions acquire locks on data items before accessing them and release locks when no longer needed. *'''Serializability:''' 2PL guarantees that the r...") |
새글 01:31 | Concurrency Control 차이역사 +3,880 Scapegoat 토론 기여 (Created page with "'''Concurrency Control''' is a mechanism in database management systems (DBMS) that ensures correct and consistent transaction execution in a multi-user environment. It prevents issues such as data inconsistencies and anomalies by managing simultaneous access to the database. ==Key Concepts== *'''Transaction:''' A sequence of database operations that are executed as a single logical unit of work. *'''Isolation:''' Ensures that each transaction is executed independently w...") |
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새글 01:28 | Isolation Level (Database) 2개 바뀜 역사 +4,095 [Scapegoat (2×)] | |||
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01:28 (최신 | 이전) +472 Scapegoat 토론 기여 | ||||
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01:28 (최신 | 이전) +3,623 Scapegoat 토론 기여 (Created page with "'''Isolation Level''' is a property in database transaction management that defines the extent to which transactions are isolated from each other. It determines how and when changes made by one transaction are visible to other concurrent transactions, affecting the trade-off between consistency and concurrency. ==Key Concepts== *'''Transaction Isolation:''' Ensures that concurrent transactions do not interfere with each other inappropriately. *'''Anomalies:''' Lower isol...") 태그: 시각 편집 |
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새글 01:26 | Non-Repeatable Read 2개 바뀜 역사 +3,785 [Scapegoat (2×)] | |||
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01:26 (최신 | 이전) +22 Scapegoat 토론 기여 태그: 시각 편집 | ||||
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01:26 (최신 | 이전) +3,763 Scapegoat 토론 기여 (Created page with "'''Non-Repeatable Read''' is a concurrency problem in database systems that occurs when a transaction reads the same data twice and gets different results due to modifications made by another transaction in the meantime. This inconsistency arises when isolation levels do not guarantee stability for repeated reads of the same data. ==Key Concepts== *'''Unstable Reads:''' The data read by a transaction changes during its execution because another transaction modifies it. *...") 태그: 시각 편집 |
새글 01:26 | Dirty Read (Database) 차이역사 +3,626 Scapegoat 토론 기여 (Created page with "'''Dirty Read''' is a concurrency problem in database systems that occurs when a transaction reads uncommitted changes made by another transaction. This can lead to inconsistent or incorrect data being used in the reading transaction, especially if the changes are later rolled back. ==Key Concepts== *'''Uncommitted Data:''' Data modified by a transaction that has not yet been committed to the database. *'''Concurrency Issue:''' Dirty reads are a type of Database Anomal...") |
새글 01:23 | Precedence Graph 차이역사 +2,874 Scapegoat 토론 기여 (Created page with "'''Precedence Graph''', also known as a '''Serializability Graph''', is a directed graph used in database systems to determine the serializability of a transaction schedule. The graph represents the order of operations across transactions and helps identify potential conflicts that could prevent a schedule from being equivalent to a serial schedule. ==Key Concepts== *'''Nodes:''' Represent individual transactions in the schedule. *'''Edges:''' Indicate a precedence (or d...") |
01:20 | 사용자 만들기 기록 Scapegoat 토론 기여 계정이 생성되었습니다 |
2024년 12월 12일 (목)
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16:40 | (사용자 만들기 기록) [Phiker mik *547 cswiki.net fg; By jeong] | |||
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16:40 By jeong 토론 기여 계정이 생성되었습니다 | ||||
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16:20 Phiker mik *547 cswiki.net fg 토론 기여 계정이 생성되었습니다 |
새글 07:49 | Serializable (Database) 차이역사 +4,608 Betripping 토론 기여 (Created page with "'''Serializable''' is the highest level of isolation in database transaction management, ensuring that the outcome of concurrent transactions is equivalent to some sequential (serial) execution of those transactions. It prevents issues like dirty reads, non-repeatable reads, and phantom reads, guaranteeing the consistency of the database. ==Key Concepts== *'''Isolation Level:''' Serializable is one of the Isolation Levels defined in the SQL standard, providing the st...") |
2024년 12월 11일 (수)
15:29 | 사용자 만들기 기록 오오라블랙 토론 기여 계정이 생성되었습니다 |
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06:41 | Main Page 2개 바뀜 역사 +635 [Betripping (2×)] | |||
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06:41 (최신 | 이전) +40 Betripping 토론 기여 태그: 시각 편집: 전환됨 | ||||
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06:36 (최신 | 이전) +595 Betripping 토론 기여 태그: 시각 편집: 전환됨 |
새글 06:33 | ARIES (Database) 차이역사 +19 Betripping 토론 기여 (Redirected page to ARIES) |
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06:29 | ARIES 4개 바뀜 역사 +4,217 [Betripping (4×)] | |||
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06:29 (최신 | 이전) −11 Betripping 토론 기여 태그: 시각 편집 | ||||
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06:26 (최신 | 이전) +711 Betripping 토론 기여 태그: 시각 편집: 전환됨 | ||||
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06:02 (최신 | 이전) +452 Betripping 토론 기여 태그: 시각 편집: 전환됨 | ||||
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06:01 (최신 | 이전) +3,065 Betripping 토론 기여 태그: 시각 편집 |
새글 06:23 | Write-Ahead Logging 차이역사 +3,853 Betripping 토론 기여 (Created page with "'''Write-Ahead Logging (WAL)''' is a technique used in database management systems (DBMS) to ensure the '''durability''' and '''atomicity''' of transactions. WAL ensures that all changes to the database are recorded in a log before the changes are written to the database itself. This enables reliable crash recovery and consistency in case of a failure. ==Key Concepts== *'''Sequential Logging:''' All modifications are recorded sequentially i...") |
새글 06:19 | Durability (ACID) 차이역사 +2,966 Betripping 토론 기여 (Created page with "'''Durability''' is one of the four key properties in the ACID Properties of database transactions, ensuring that once a transaction has been committed, its changes are permanently saved in the database. This guarantees that data is not lost even in the event of a system crash, power failure, or hardware malfunction. ==Key Concepts== *'''Transaction Commit:''' Durability ensures that when a transaction is committed, its effects are persisted. *'''Non-...") |
새글 05:39 | 분류:Database 차이역사 +1,769 Betripping 토론 기여 (Created page with "Database category includes topics related to the design, implementation, and management of databases. It covers various database types, concepts, protocols, and tools that enable efficient storage, retrieval, and manipulation of data. ==Topics in This Category== The following are key areas within the database category: ===Database Concepts=== *Relational Databases *NoSQL Databases *Data Warehousing *Database Normalization *ACID Properties *Database...") |
새글 05:38 | Multiple Granularity Locking 차이역사 +4,134 Betripping 토론 기여 (Created page with "'''Multiple Granularity Locking''' is a concurrency control mechanism used in database systems to improve performance and manage locks at various levels of granularity, such as tuples, pages, tables, or the entire database. By allowing transactions to lock data items at different granular levels, this method optimizes the balance between concurrency and locking overhead. ==Key Concepts== *'''Lock Granularity:''' Refers to the size of the data item on which a lock is appl...") |
새글 05:34 | Phantom Record 차이역사 +4,455 Betripping 토론 기여 (Created page with "'''Phantom Record''' refers to a data entry that appears in a dataset but does not correspond to a real-world entity or valid data point. Phantom records can occur due to system errors, data corruption, improper database handling, or intentional insertion during testing or attacks. ==Causes of Phantom Records== Phantom records can arise from various sources: *'''Data Entry Errors:''' Manual input mistakes resulting in duplicate or incorrect records. *'''System Errors:'''...") |
2024년 12월 9일 (월)
05:32 | 사용자 만들기 기록 Bekil kupil *982 cswiki.net zp 토론 기여 계정이 생성되었습니다 |
2024년 12월 8일 (일)
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새글 03:56 | Neural Processing Unit 2개 바뀜 역사 +3,907 [162.158.159.66 (2×)] | |||
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03:56 (최신 | 이전) +12 162.158.159.66 토론 태그: 시각 편집: 전환됨 | ||||
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03:56 (최신 | 이전) +3,895 162.158.159.66 토론 (새 문서: '''Neural Processing Unit (NPU)''' is a specialized hardware accelerator designed to perform computations for artificial intelligence (AI) and machine learning (ML) workloads, particularly neural network operations. NPUs are optimized for tasks like matrix multiplications and convolutional operations, which are central to deep learning models. == Key Features of NPUs == NPUs offer the following features: * '''High Performance:''' Accelerate AI computations, providing significan...) |
새글 03:55 | Open Neural Network Exchange 차이역사 +3,972 162.158.159.65 토론 (새 문서: '''ONNX (Open Neural Network Exchange)''' is an open-source format for representing machine learning models. It enables interoperability between different machine learning frameworks and tools, allowing developers to train models in one framework and deploy them in another. ONNX supports a wide range of machine learning and deep learning models. == Key Features of ONNX == * '''Interoperability:''' Facilitates seamless model transfer between frameworks like PyTorch, TensorFlow,...) |
새글 03:54 | LM Studio 차이역사 +3,580 162.158.63.106 토론 (새 문서: '''LM Studio''' is an advanced tool for developing, training, and deploying large language models (LLMs). It provides an integrated platform for researchers and developers to experiment with state-of-the-art natural language processing (NLP) models. LM Studio simplifies the process of handling large-scale datasets, configuring model architectures, and optimizing performance for various applications. ==Key Features== *'''Model Training:''' Enables training of large language model...) |
새글 03:52 | Lmstudio.js 차이역사 +3,792 162.158.158.113 토론 (새 문서: '''lmstudio.js''' is a JavaScript library designed for building, managing, and deploying machine learning models directly within web browsers. It provides tools for creating lightweight machine learning applications, enabling client-side inference and integrating pre-trained models into web-based platforms. With its focus on usability and performance, lmstudio.js simplifies machine learning workflows for web developers. ==Key Features== *'''Client-Side Machine Learning:''' Perfo...) |