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Causal Consistency
Causal consistency is one of the major memory consistency models. In concurrent programming, where concurrent processes are accessing a shared memory, a consistency model restricts which accesses are legal. This is useful for defining correct data structures in distributed shared memory or distributed transactions. Causal Consistency is “Available under Partition”, meaning that a process can read and write the memory (memory is Available) even while there is no functioning network connection (network is Partitioned) between processes; it is an asynchronous model. Contrast to strong consistency models, such as sequential consistency or linearizability, which cannot be both safe and live under partition, and are slow to respond because they require synchronisation. Causal consistency was proposed in 1990s Ahamad, M., Neiger, G., Burns, J. E., Kohli, P., & Hutto, P. W. (1995). Causal memory: Definitions, implementation, and programming. Distributed Computing, 9(1), 37-49. as ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Consistency Model
In computer science, a consistency model specifies a contract between the programmer and a system, wherein the system guarantees that if the programmer follows the rules for operations on memory, memory will be consistent and the results of reading, writing, or updating memory will be predictable. Consistency models are used in distributed systems like distributed shared memory systems or distributed data stores (such as filesystems, databases, optimistic replication systems or web caching). Consistency is different from coherence, which occurs in systems that are cached or cache-less, and is consistency of data with respect to all processors. Coherence deals with maintaining a global order in which writes to a single location or single variable are seen by all processors. Consistency deals with the ordering of operations to multiple locations with respect to all processors. High level languages, such as C++ and Java, maintain the consistency contract by translating memory operat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Eventual Consistency
Eventual consistency is a consistency model used in distributed computing to achieve high availability that informally guarantees that, if no new updates are made to a given data item, eventually all accesses to that item will return the last updated value. Eventual consistency, also called optimistic replication, is widely deployed in distributed systems and has origins in early mobile computing projects. A system that has achieved eventual consistency is often said to have converged, or achieved replica convergence. Eventual consistency is a weak guarantee – most stronger models, like linearizability, are trivially eventually consistent. Eventually-consistent services are often classified as providing BASE semantics (basically-available, soft-state, eventual consistency), in contrast to traditional ACID (atomicity, consistency, isolation, durability). In chemistry, a base is the opposite of an acid, which helps in remembering the acronym. According to the same resource, thes ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dependency Graph
In mathematics, computer science and digital electronics, a dependency graph is a directed graph representing dependencies of several objects towards each other. It is possible to derive an evaluation order or the absence of an evaluation order that respects the given dependencies from the dependency graph. Definition Given a set of objects S and a transitive relation R \subseteq S \times S with (a,b) \in R modeling a dependency "''a'' depends on ''b''" ("''a'' needs ''b'' evaluated first"), the dependency graph is a graph G = (S, T) with T \subseteq R the transitive reduction of ''R''. For example, assume a simple calculator. This calculator supports assignment of constant values to variables and assigning the sum of exactly two variables to a third variable. Given several equations like "''A'' = ''B''+''C''; ''B'' = 5+''D''; ''C''=4; ''D''=2;", then S=\ and R=\. You can derive this relation directly: ''A'' depends on ''B'' and ''C'', because you can add two variables if and o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
PRAM Consistency
PRAM consistency (pipelined random access memory) also known as '' FIFO consistency''. All processes see memory writes from one process in the order they were issued from the process. Writes from different processes may be seen in a different order on different processes. Only the write order needs to be consistent, thus the name ''pipelined''. PRAM consistency is easy to implement. In effect it says that there are no guarantees about the order in which different processes see writes, except that two or more writes from a single source must arrive in order, as though they were in a pipeline. P1:W(x)1 P2: R(x)1W(x)2 P3: R(x)1R(x)2 P4: R(x)2R(x)1 Time ----> Fig: A valid sequence of events for PRAM consistency. The above sequence is not valid for Causal consistency Causal consistency is one of the major memory consistency models. In concurrent programming, where concurrent processes are accessing a shared memory, a consist ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
MongoDB
MongoDB is a source-available cross-platform document-oriented database program. Classified as a NoSQL database program, MongoDB uses JSON-like documents with optional schemas. MongoDB is developed by MongoDB Inc. and licensed under the Server Side Public License (SSPL) which is deemed non-free by several distributions. History 10gen software company began developing MongoDB in 2007 as a component of a planned platform as a service product. In 2009, the company shifted to an open-source development model, with the company offering commercial support and other services. In 2013, 10gen changed its name to MongoDB Inc. On October 20, 2017, MongoDB became a publicly traded company, listed on NASDAQ as MDB with an IPO price of $24 per share. MongoDB is a global company with US headquarters in New York City, USA and International headquarters in Dublin, Ireland. On October 30, 2019, MongoDB teamed up with Alibaba Cloud, who will offer its customers a MongoDB-as-a-service solutio ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
CAP Theorem
In theoretical computer science, the CAP theorem, also named Brewer's theorem after computer scientist Eric Brewer, states that any distributed data store can provide only two of the following three guarantees:Seth Gilbert and Nancy Lynch"Brewer's conjecture and the feasibility of consistent, available, partition-tolerant web services" ''ACM SIGACT News'', Volume 33 Issue 2 (2002), pg. 51–59. . ; Consistency: Every read receives the most recent write or an error. ; Availability: Every request receives a (non-error) response, without the guarantee that it contains the most recent write. ; Partition tolerance: The system continues to operate despite an arbitrary number of messages being dropped (or delayed) by the network between nodes. When a network partition failure happens, it must be decided whether to do one of the following: * cancel the operation and thus decrease the availability but ensure consistency * proceed with the operation and thus provide availability but risk i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Spanner (database)
Spanner is a distributed SQL database management and storage service developed by Google. It provides features such as global transactions, strongly consistent reads, and automatic multi-site replication and failover. Spanner is used in Google F1, the database for its advertising business Google Ads. Features Spanner stores large amounts of mutable structured data. Spanner allows users to perform arbitrary queries using SQL with relational data while maintaining strong consistency and high availability for that data with synchronous replication. Key features of Spanner: * Transactions can be applied across rows, columns, tables, and databases within a Spanner universe. * Clients can control the replication and placement of data using automatic multi-site replication and failover. * Replication is synchronous and strongly consistent. * Reads are strongly consistent and data is versioned to allow for stale reads: clients can read previous versions of data, subject to garbage collec ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Abstract Data Type
In computer science, an abstract data type (ADT) is a mathematical model for data types. An abstract data type is defined by its behavior (Semantics (computer science), semantics) from the point of view of a ''User (computing), user'', of the data, specifically in terms of possible values, possible operations on data of this type, and the behavior of these operations. This mathematical model contrasts with data structures, which are concrete representations of data, and are the point of view of an implementer, not a user. Formally, an ADT may be defined as a "class of objects whose logical behavior is defined by a set of values and a set of operations"; this is analogous to an algebraic structure in mathematics. What is meant by "behaviour" varies by author, with the two main types of formal specifications for behavior being ''axiomatic (algebraic) specification'' and an ''abstract model;'' these correspond to axiomatic semantics and operational semantics of an abstract machine, r ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Happened-before
In computer science, the happened-before relation (denoted: \to \;) is a relation between the result of two events, such that if one event should happen before another event, the result must reflect that, even if those events are in reality executed out of order (usually to optimize program flow). This involves ordering events based on the potential causal relationship of pairs of events in a concurrent system, especially asynchronous distributed systems. It was formulated by Leslie Lamport. The happened-before relation is formally defined as the least strict partial order on events such that: * If events a \; and b \; occur on the same process, a \to b\; if the occurrence of event a \; preceded the occurrence of event b \;. * If event a \; is the sending of a message and event b \; is the reception of the message sent in event a \;, a \to b\;. If two events happen in different isolated processes (that do not exchange messages directly or indirectly via third-party processes), then ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Concurrent Programming
Concurrent means happening at the same time. Concurrency, concurrent, or concurrence may refer to: Law * Concurrence, in jurisprudence, the need to prove both ''actus reus'' and ''mens rea'' * Concurring opinion (also called a "concurrence"), a legal opinion which supports the conclusion, though not always the reasoning, of the majority. * Concurrent estate, a concept in property law * Concurrent resolution, a legislative measure passed by both chambers of the United States Congress * Concurrent sentences, in criminal law, periods of imprisonment that are served simultaneously Computing * Concurrency (computer science), the property of program, algorithm, or problem decomposition into order-independent or partially-ordered units * Concurrent computing, the overlapping execution of multiple interacting computational tasks * Concurrence (quantum computing), a measure used in quantum information theory * Concurrent Computer Corporation, an American computer systems manufacturer ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Safety And Liveness Properties
Properties of an execution of a computer program —particularly for concurrent and distributed systems— have long been formulated by giving ''safety properties'' ("bad things don't happen") and ''liveness properties'' ("good things do happen"). A simple example will illustrate safety and liveness. A program is totally correct with respect to a precondition P and postcondition Q if any execution started in a state satisfying P terminates in a state satisfying Q. Total correctness is a conjunction of a safety property and a liveness property: * The safety property prohibits these "bad things": executions that start in a state satisfying P and terminate in a final state that does not satisfy Q. For a program C, this safety property is usually written using the Hoare triple \ C \. * The liveness property, the "good thing", is that execution that starts in a state satisfying P terminates. Note that a ''bad thing'' is discrete, since it happens at a particular place during execution. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Linearizability
In concurrent programming, an operation (or set of operations) is linearizable if it consists of an ordered list of invocation and response events (event), that may be extended by adding response events such that: # The extended list can be re-expressed as a sequential history (is serializable). # That sequential history is a subset of the original unextended list. Informally, this means that the unmodified list of events is linearizable if and only if its invocations were serializable, but some of the responses of the serial schedule have yet to return. In a concurrent system, processes can access a shared object at the same time. Because multiple processes are accessing a single object, there may arise a situation in which while one process is accessing the object, another process changes its contents. Making a system linearizable is one solution to this problem. In a linearizable system, although operations overlap on a shared object, each operation appears to take place i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
