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Dataflow
In computing, dataflow is a broad concept, which has various meanings depending on the application and context. In the context of software architecture, data flow relates to stream processing or reactive programming. Software architecture Dataflow computing is a software paradigm based on the idea of representing computations as a directed graph, where nodes are computations and data flow along the edges. Dataflow can also be called stream processing or reactive programming. There have been multiple data-flow/stream processing languages of various forms (see Stream processing). Data-flow hardware (see Dataflow architecture) is an alternative to the classic von Neumann architecture. The most obvious example of data-flow programming is the subset known as reactive programming with spreadsheets. As a user enters new values, they are instantly transmitted to the next logical "actor" or formula for calculation. Distributed data flows have also been proposed as a programming abstrac ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dataflow Programming
In computer programming, dataflow programming is a programming paradigm that models a program as a directed graph of the data flowing between operations, thus implementing dataflow principles and architecture. Dataflow programming languages share some features of functional languages, and were generally developed in order to bring some functional concepts to a language more suitable for numeric processing. Some authors use the term ''datastream'' instead of '' dataflow'' to avoid confusion with dataflow computing or dataflow architecture, based on an indeterministic machine paradigm. Dataflow programming was pioneered by Jack Dennis and his graduate students at MIT in the 1960s. Considerations Traditionally, a program is modelled as a series of operations happening in a specific order; this may be referred to as sequential, procedural, control flow (indicating that the program chooses a specific path), or imperative programming. The program focuses on commands, in line with the v ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data-flow Analysis
In computing, dataflow is a broad concept, which has various meanings depending on the application and context. In the context of software architecture, data flow relates to stream processing or reactive programming. Software architecture Dataflow computing is a software paradigm based on the idea of representing computations as a directed graph, where nodes are computations and data flow along the edges. Dataflow can also be called stream processing or reactive programming. There have been multiple data-flow/stream processing languages of various forms (see Stream processing). Data-flow hardware (see Dataflow architecture) is an alternative to the classic von Neumann architecture. The most obvious example of data-flow programming is the subset known as reactive programming with spreadsheets. As a user enters new values, they are instantly transmitted to the next logical "actor" or formula for calculation. Distributed data flows have also been proposed as a programming abstrac ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dataflow Architecture
Dataflow architecture is a dataflow-based computer architecture that directly contrasts the traditional von Neumann architecture or control flow architecture. Dataflow architectures have no program counter, in concept: the executability and execution of instructions is solely determined based on the availability of input arguments to the instructions, so that the order of instruction execution is unpredictable, i.e., behavior is nondeterministic. Although no commercially successful general-purpose computer hardware has used a dataflow architecture, it has been successfully implemented in specialized hardware such as in digital signal processing, network routing, graphics processing, telemetry, and more recently in data warehousing, and artificial intelligence (as: polymorphic dataflow Convolution Engine, structure-driven, dataflow scheduling). It is also very relevant in many software architectures today including database engine designs and parallel computing frameworks. Synchr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Google Cloud Dataflow
Google Cloud Dataflow is a fully managed service for executing Apache Beam pipelines within the Google Cloud Platform ecosystem. History Google Cloud Dataflow was announced in June, 2014 and released to the general public as an open beta in April, 2015. In January, 2016 Google donated the underlying SDK, the implementation of a local runner, and a set of IOs ( data connectors) to access Google Cloud Platform data services to the Apache Software Foundation. The donated code formed the original basis for Apache Beam Apache Beam is an open source unified programming model to define and execute data processing pipelines, including ETL, batch and stream (continuous) processing. Beam Pipelines are defined using one of the provided SDKs and executed in one of .... References External links * Dataflow Cloud computing {{Google-stub ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Power Query
Power Query is an ETL tool created by Microsoft for data extraction, loading and transformation, and is used to retrieve data from sources, process it, and load them into one or more target systems. Power Query is available in several variations within the Microsoft Power Platform, and is used for business intelligence on fully or partially self-service platforms. It is found in software such as Excel, Power BI, Analysis Services, Dataverse, Power Apps, Azure Data Factory, SSIS, Dynamics 365, and in cloud services such as Microsoft Dataflows, including Power BI Dataflow used with the online Power BI Service or the somehwat more generic version of Microsoft Dataflow used with Power Automate. ETL is closely related to data modeling, and for transformation, Power Query can be used to develop a logical data model in those cases where the data does not already have one, or where there is a need to further develop the data model. History Power Query was included as an additional f ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Binary Modular Dataflow Machine
Binary Modular Dataflow Machine (BMDFM) is a software package that enables running an application in parallel on shared memory symmetric multiprocessing (SMP) computers using the multiple processors to speed up the execution of single applications. BMDFM automatically identifies and exploits parallelism due to the static and mainly ''dynamic scheduling'' of the dataflow instruction sequences derived from the formerly sequential program. The BMDFM dynamic scheduling subsystem performs a symmetric multiprocessing (SMP) emulation of a ''tagged-token dataflow machine'' to provide the transparent dataflow semantics for the applications. No directives for parallel execution are needed. Background Current parallel shared memory SMPs are complex machines, where a large number of architectural aspects must be addressed simultaneously to achieve high performance. Recent commodity SMP machines for technical computing can have many tightly coupled cores (good examples are SMP machines ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Power BI
Power BI is an interactive data visualization software product developed by Microsoft with a primary focus on business intelligence. It is part of the Microsoft Power Platform. Power BI is a collection of software services, apps, and connectors that work together to turn unrelated sources of data into coherent, visually immersive, and interactive insights. Data may be input by reading directly from a database, webpage, or structured files such as spreadsheets, CSV, XML, and JSON. General Power BI provides cloud-based BI (business intelligence) services, known as "Power BI Services", along with a desktop-based interface, called "Power BI Desktop". It offers data warehouse capabilities including data preparation, data discovery, and interactive dashboards. In March 2016, Microsoft released an additional service called Power BI Embedded on its Azure cloud platform. One main differentiator of the product is the ability to load custom visualizations. History This application was o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Kahn Process Networks
A Kahn process network (KPN, or process network) is a distributed ''model of computation'' in which a group of deterministic sequential processes communicate through unbounded first in, first out channels. The model requires that reading from a channel is blocking while writing is non-blocking. Due to these key restrictions, the resulting process network exhibits deterministic behavior that does not depend on the timing of computation nor on communication delays. Kahn process networks were originally developed for modeling parallel programs, but have proven convenient for modeling embedded systems, high-performance computing systems, signal processing systems, stream processing systems, dataflow programming languages, and other computational tasks. KPNs were introduced by Gilles Kahn in 1974. Execution model KPN is a common model for describing signal processing systems where infinite streams of data are incrementally transformed by processes executing in sequence or paralle ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Reactive Programming
In computing, reactive programming is a declarative programming paradigm concerned with data streams and the propagation of change. With this paradigm, it's possible to express static (e.g., arrays) or dynamic (e.g., event emitters) data streams with ease, and also communicate that an inferred dependency within the associated execution model exists, which facilitates the automatic propagation of the changed data flow. For example, in an ''imperative'' programming setting, a := b + c would mean that a is being assigned the result of b + c in the instant the expression is evaluated, and later, the values of b and c can be changed with no effect on the value of a. On the other hand, in ''reactive'' programming, the value of a is automatically updated whenever the values of b or c change, without the program having to explicitly re-execute the statement a := b + c to determine the presently assigned value of a. Another example is a hardware description language such as Verilog, wh ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Stream Processing
In computer science, stream processing (also known as event stream processing, data stream processing, or distributed stream processing) is a programming paradigm which views data streams, or sequences of events in time, as the central input and output objects of computation. Stream processing encompasses dataflow programming, reactive programming, and distributed data processing. Stream processing systems aim to expose parallel processing for data streams and rely on streaming algorithms for efficient implementation. The software stack for these systems includes components such as programming models and query languages, for expressing computation; stream management systems, for distribution and scheduling; and hardware components for acceleration including floating-point units, graphics processing units, and field-programmable gate arrays. The stream processing paradigm simplifies parallel software and hardware by restricting the parallel computation that can be performed. Given ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computer Architecture
In computer engineering, computer architecture is a description of the structure of a computer system made from component parts. It can sometimes be a high-level description that ignores details of the implementation. At a more detailed level, the description may include the instruction set architecture design, microarchitecture design, logic design, and implementation. History The first documented computer architecture was in the correspondence between Charles Babbage and Ada Lovelace, describing the analytical engine. When building the computer Z1 in 1936, Konrad Zuse described in two patent applications for his future projects that machine instructions could be stored in the same storage used for data, i.e., the stored-program concept. Two other early and important examples are: * John von Neumann's 1945 paper, First Draft of a Report on the EDVAC, which described an organization of logical elements; and *Alan Turing's more detailed ''Proposed Electronic Calculator'' ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Stream Processing
In computer science, stream processing (also known as event stream processing, data stream processing, or distributed stream processing) is a programming paradigm which views data streams, or sequences of events in time, as the central input and output objects of computation. Stream processing encompasses dataflow programming, reactive programming, and distributed data processing. Stream processing systems aim to expose parallel processing for data streams and rely on streaming algorithms for efficient implementation. The software stack for these systems includes components such as programming models and query languages, for expressing computation; stream management systems, for distribution and scheduling; and hardware components for acceleration including floating-point units, graphics processing units, and field-programmable gate arrays. The stream processing paradigm simplifies parallel software and hardware by restricting the parallel computation that can be performed. Given ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
