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"IBM's Distributed Processing Capabilities For Large-Scale Data Base Systems, Part 1". Computerworld. Ronald G. Ross. "IBM's Distributed Processing Capabilities
Distributed_data_processing
Discrete, discontinuous representation of information
parallel distributed data processing across many commodity computers on a high bandwidth network. In such systems, the data is distributed across multiple computers
Digital_data
Computer programming paradigm
computer science, stream processing (also known as event stream processing, data stream processing, or distributed stream processing) is a programming paradigm
Stream_processing
Distributed data processing framework
for reliable, scalable, distributed computing. It provides a software framework for distributed storage and processing of big data using the MapReduce programming
Apache_Hadoop
System with multiple networked computers
Distributed computing is a field of computer science that studies distributed systems, defined as computer systems whose inter-communicating components
Distributed_computing
American software company
Automatic Data Processing, Inc. (ADP) is an American multinational provider of cloud-based human resources management, payroll processing, and professional
ADP_(company)
Computer network with multiple nodes to store information
cloud Data store Keyspace, the DDS schema Distributed hash table Distributed cache Cyber Resilience Yaniv Pessach, Distributed Storage (Distributed Storage:
Distributed_data_store
Organized collection of data in computing
including data modeling, efficient data representation and storage, query languages, security and privacy of sensitive data, and distributed computing
Database
Open-source data analytics cluster computing framework
expected even for bug fixes. Big data Comparison of machine learning software Distributed computing Distributed data processing List of Apache Software Foundation
Apache_Spark
Data synchronised across multiple sites
digital data is geographically spread (distributed) across many sites, countries, or institutions. In contrast to a centralized database, a distributed ledger
Distributed_ledger
Software architecture
implement a distributed file system. The designers of distributed applications must determine the best placement of the application's programs and data in terms
Distributed Data Management Architecture
Distributed_Data_Management_Architecture
Database whose data is stored in different physical locations
database Data grid Distributed cache Distributed data store Distributed hash table Routing protocol Distributed SQL "Definition: distributed database"
Distributed_database
Reference model in computer science
Reference Model of Open Distributed Processing (RM-ODP) is a reference model in computer science, which provides a co-ordinating framework for the standardization
RM-ODP
Class of parallel computing applications
additional distributed data processing capabilities which are designed to run using the Hadoop MapReduce architecture. These include HBase, a distributed column-oriented
Data-intensive_computing
Type of database system
to user requests and process them in real time. OLTP is contrasted with online analytical processing (OLAP), which focuses on data analysis (for example
Online_transaction_processing
Origins and events of data
Data lineage refers to the process of tracking how data is generated, transformed, transmitted and used across systems over time. It documents data's
Data_lineage
Topics referred to by the same term
image file format Distributed Data Processing, a 1970s term referring to one of IBM's combined offerings Distributed Data Protocol, a client-server protocol
DDP
Manipulation of data before it is analyzed
amount of processing time. Examples of methods used in data preprocessing include cleaning, instance selection, normalization, one-hot encoding, data transformation
Data_preprocessing
Concept in probability and statistics
statistics and finds application in many fields, such as data mining and signal processing. Statistics commonly deals with random samples. A random sample
Independent and identically distributed random variables
Independent_and_identically_distributed_random_variables
Facilities containing Google servers
incrementally on a continuous basis. Later Google revealed a distributed data processing system called "Percolator" which is said to be the basis of Caffeine
Google_data_centers
Open-source distributed stream processing
information sources and manipulations to allow batch, distributed processing of streaming data. The initial release was on 17 September 2011. A Storm
Apache_Storm
Sharing of data between running processes in a computer system
IPC mechanism. Merging data from two processes can often incur significantly higher costs compared to processing the same data on a single thread, potentially
Inter-process_communication
Unified programming model for data processing pipelines
programming model to define and execute data processing pipelines, including ETL, batch and stream (continuous) processing. Beam Pipelines are defined using
Apache_Beam
Aspect of Unisys OS 2200 operating system
so commonly used, distributed processing protocols, APIs, and development technology. The X/Open Distributed Transaction Processing model and standards
Unisys OS 2200 distributed processing
Unisys_OS_2200_distributed_processing
Database transaction between two or more networks
that distributed transactions are not limited to databases. The Open Group, a vendor consortium, proposed the X/Open Distributed Transaction Processing Model
Distributed_transaction
Communications System was one of the first distributed computing platforms. The 3790 was developed by IBM's Data Processing Division (DPD) and announced in 1974
IBM_3790
Centralized storage of knowledge
historic data through ETL processes that periodically migrate data from the operational systems to the warehouse. Online analytical processing (OLAP) is
Data_warehouse
Sharing information to ensure consistency in computing
distributed concurrency control must be used, such as a distributed lock manager. Load balancing differs from task replication, since it distributes a
Replication_(computing)
Computerized control system with distributed decision-making
A distributed control system (DCS) is a control system used to control industrial processes in which control functions are distributed among multiple autonomous
Distributed_control_system
Relational database programming language
defined by the Distributed Data Management Architecture. Distributed SQL processing ala DRDA is distinctive from contemporary distributed SQL databases
SQL
Type of geographic information system
people. In terms of data, the concept has been extended to include volunteered geographical information. Distributed processing allows improvements to
Distributed_GIS
System design objective
hierarchical structure, configuration, or model of a communications or distributed data processing system. It enables system description, design, development, installation
Open_systems_architecture
Set of events in a distributed application or protocol
Distributed data flow (also abbreviated as distributed flow) refers to a set of events in a distributed application or protocol. Distributed data flows
Distributed_data_flow
NASA program capability
capabilities transport the data to the science operations facilities. EOSDIS comprises processing facilities and Distributed Active Archive Centers across
EOSDIS
Computing technique employed to achieve parallelism
microarchitecture. These processors have multiple processing cores (up to 61 as of 2015) that can execute different instructions on different data. Most parallel
Multiple instruction, multiple data
Multiple_instruction,_multiple_data
Memory used temporarily in data transfers
used. In a distributed computing environment, data buffers are often implemented in the form of burst buffers, which provide distributed buffering services
Data_buffer
Multiprocessing memory architecture
programming distributed memory systems is how to distribute the data over the memories. Depending on the problem solved, the data can be distributed statically
Distributed_memory
Parallel programming model
model and an associated implementation for processing and generating big data sets with a parallel and distributed algorithm on a cluster. A MapReduce program
MapReduce
Programming paradigm in which many processes are executed simultaneously
exists. A distributed computer (also known as a distributed memory multiprocessor) is a distributed memory computer system in which the processing elements
Parallel_computing
Parallelization across multiple processors in parallel computing environments
Data parallelism is parallelization across multiple processors in parallel computing environments. It focuses on distributing the data across different
Data_parallelism
Abstract data type in computer science
and distributed memory architectures are considered. In the case of a shared memory model, the graph representations used for parallel processing are
Graph_(abstract_data_type)
Information processing broken up into indivisible operations
In computer science, transaction processing is information processing that is divided into individual, indivisible operations called transactions. Each
Transaction_processing
Type of data structure
In distributed computing, a conflict-free replicated data type (CRDT) is a data structure that is replicated across multiple computers in a network, with
Conflict-free replicated data type
Conflict-free_replicated_data_type
Mathematical signal manipulation by computers
Digital signal processing (DSP) is the use of digital processing, such as by computers or more specialized digital signal processors, to perform a wide
Digital_signal_processing
management, (2) global query of independent databases, and (3) distributed data processing. The word metadatabase is an addition to the dictionary. Originally
Metadatabase
Framework and distributed processing engine
stream-processing and batch-processing framework developed by the Apache Software Foundation. The core of Apache Flink is a distributed streaming data-flow
Apache_Flink
Subfield of artificial intelligence
require large data, by distributing the problem to autonomous processing nodes (agents). To reach the objective, DAI requires: A distributed system with
Distributed artificial intelligence
Distributed_artificial_intelligence
Category of programming languages
data. A data-centric programming language includes built-in processing primitives for accessing data stored in sets, tables, lists, and other data structures
Data-centric programming language
Data-centric_programming_language
Ability to seamlessly add computer resources to a given node
data, map reduce, or distributed storage system and is often associated with the infrastructure required to run large distributed sites such as Google
Hyperscale_computing
Standard for data transmission in a local area network
Fiber Distributed Data Interface (FDDI) is a standard for data transmission in a local area network. It uses optical fiber as its standard underlying physical
Fiber Distributed Data Interface
Fiber_Distributed_Data_Interface
In-memory data grid
a Hazelcast grid, data is evenly distributed among the nodes of a computer cluster, allowing for horizontal scaling of processing and available storage
Hazelcast
typically has the following components: Processing unit The unit of scalability and fail-over. Normally, a processing unit is built out of a POJO (plain old
Space-based_architecture
Software architecture model
opportunities. Online event processing (OLEP) uses asynchronous distributed event logs to process complex events and manage persistent data. OLEP allows reliably
Event-driven_architecture
Transaction that reverses the effects of a prior, committed transaction
In transaction processing and distributed computing, a compensating transaction is a transaction that reverses the effects of a previously committed transaction
Compensating_transaction
Method of analysing information about events
Event processing is a method of tracking and analyzing (processing) streams of information (data) about things that happen (events), and deriving a conclusion
Complex_event_processing
Open source platform
distributed machine learning and predictive analytics platform developed by the company H2O.ai (previously 0xdata). The software uses a distributed architecture
H2O_(software)
Processing mode
the processing step (data load) can be quite lengthy, especially on large data volumes. This is usually remedied by doing only incremental processing, i
Online_analytical_processing
Field of study to extract knowledge from data
Data science is an interdisciplinary academic field that uses statistics, scientific computing, scientific methods, processing, scientific visualization
Data_science
Type of parallel processing
multiple data (SIMD) is a type of parallel computing (processing) in Flynn's taxonomy. SIMD describes computers with multiple processing elements that
Single instruction, multiple data
Single_instruction,_multiple_data
Relational database management system
a subset of the data. They include components such as distributed concurrency control, flow control, and distributed query processing. The second category
NewSQL
The International Parallel and Distributed Processing Symposium (or IPDPS) is an annual conference for engineers and scientists to present recent findings
International Parallel and Distributed Processing Symposium
International_Parallel_and_Distributed_Processing_Symposium
Software bus for high-volume data feeds
Apache Kafka is a distributed event store and stream-processing platform. It is an open-source system developed by the Apache Software Foundation written
Apache_Kafka
Software company
data, analytics, and modernization portfolio. Vertica is a column-oriented analytical database that uses massively parallel processing to distribute storage
Vertica
Computing technique used to achieve parallelism
different data. In SIMD the same operation (instruction) is applied on multiple data to manipulate data streams (a version of SIMD is vector processing where
Single_program,_multiple_data
Distributed query engine
re-branded to Trino) is a distributed query engine for big data using the SQL query language. Its architecture allows users to query data sources such as Hadoop
Presto_(SQL_query_engine)
Cognitive science approach
wave blossomed in the late 1980s, following a 1987 book Parallel Distributed Processing by James L. McClelland, David E. Rumelhart, et al., which introduced
Connectionism
Repository of data stored in a raw format
or a distributed file system such as Apache Hadoop distributed file system (HDFS). There is a gradual academic interest in the concept of data lakes
Data_lake
Process of linking data objects in distinct models
In computing and data management, data mapping is the process of creating data element mappings between two distinct data models. Data mapping is used
Data_mapping
Specialized electronic circuit that accelerates graphics
A graphics processing unit (GPU) is a specialized electronic circuit designed for digital image processing and to accelerate computer graphics, being
Graphics_processing_unit
Italian astrophysicist
the LISA Consortium, the LISA Science Team (LST), and the LISA Distributed Data Processing Center (DDPC). Sesana received his Laurea from the Università
Alberto_Sesana
Facility used to house computer servers
latency data processing is needed. Modularity and flexibility are key elements in allowing a data center to grow and change over time. Data center modules
Data_center
Computer application for controlling unattended background program execution of jobs
system, distributed resource management system (DRMS), distributed resource manager (DRM), and, commonly today, workload automation (WLA). The data structure
Job_scheduler
Database management system
transaction processing, and query processing. SingleStore stores relational data, JSON data, geospatial data, key-value vector data, and time series data. It
SingleStore
High-performance computer cluster
data-parallel processing for applications utilizing big data. The HPCC platform includes system configurations to support both parallel batch data processing
HPCC
Additional storage that enables faster access to main storage
applications, for example in the processing of indexes, data dictionaries, and frequently used subsets of data. A distributed cache uses networked hosts to
Cache_(computing)
Set of computers configured in a distributed computing system
Advantages include enabling data recovery in the event of a disaster and providing parallel data processing and high processing capacity. In terms of scalability
Computer_cluster
Extremely large or complex datasets
Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing software. Data with many entries
Big_data
Mechanism to allow software to execute a remote procedure
continues its process. While the server is processing the call, the client is blocked (it waits until the server has finished processing before resuming
Remote_procedure_call
OLAP database developed by Kinetica DB, Inc
Kinetica is a distributed, memory-first OLAP database developed by Kinetica DB, Inc. Kinetica is designed to use GPUs and modern vector processors to improve
Kinetica_(software)
Computing system for indivisible operations
A transaction processing system (TPS) is a software system, or software/hardware combination, that supports transaction processing. The first transaction
Transaction_processing_system
Distributed transaction processing standard
1991 by X/Open (which later merged with The Open Group) for distributed transaction processing (DTP). The goal of XA is to guarantee atomicity in "global
X/Open_XA
Scientific visualization software
using ParaView's batch processing capabilities. ParaView was developed to analyze extremely large datasets using distributed memory computing resources
ParaView
Computer science transaction algorithm
commitment protocol (ACP). It is a distributed algorithm that coordinates all the processes that participate in a distributed atomic transaction on whether
Two-phase_commit_protocol
Name used for several lines of minicomputers
Programmed Data Processor (PDP), referred to by some customers, media and authors as "Programmable Data Processor," is a term used by the Digital Equipment
Programmed_Data_Processor
Data-processing architecture
ordering of the data. Lambda architecture describes a system consisting of three layers: batch processing, speed (or real-time) processing, and a serving
Lambda_architecture
Technology to correct measurements in industrial processes
and systematic errors Normally distributed measurements without bias. Normally distributed measurements with bias. Data originates typically from measurements
Data validation and reconciliation
Data_validation_and_reconciliation
Scientific journal
sharing, and analytics; big data technologies; data visualization; architectures for massively parallel processing; data mining tools and techniques;
Journal_of_Big_Data
Classification of computer architectures
different data. MIMD architectures include multi-core superscalar processors, and distributed systems, using either one shared memory space or a distributed memory
Flynn's_taxonomy
Use of a GPU for computations typically assigned to CPUs
General-purpose computing on graphics processing units (GPGPU, or less often GPGP) is the use of a graphics processing unit (GPU), which typically handles
General-purpose computing on graphics processing units
General-purpose_computing_on_graphics_processing_units
centralized search engines, work such as crawling, data mining, indexing, and query processing is distributed among several peers in a decentralized manner
Distributed_search_engine
Computer company
to a single mass storage disc operating system and enhanced Distributed Data Processing. Proprietary operating systems included DOS and RMS (Resource
Datapoint
Chinese-American businessman and computer engineer
used in data processing mode and word processing mode. They were user-programmable in data-processing mode and used the same word processing software
An_Wang
Process of ensuring computer data is both correct and useful
complex processing. Such complex processing may include the testing of conditional constraints for an entire complex data object or set of process operations
Data_validation
Data collection system
processors. While data sovereignty may require that records about a nation's citizens or residents follow its personal or financial data processing laws
Data_localization
Swedish computer scientist
computer scientist and entrepreneur, specializing in distributed systems, big data and data management. He is a co-founder and CEO of Databricks and
Ali_Ghodsi
Free and open-source multi-model NoSQL database developed by Apple
software portal Ordered key-value store Database transaction Distributed database Distributed transaction List of formerly proprietary software "Releases
FoundationDB
Peer-to-peer Internet platform for censorship-resistant communication
censorship-resistant, anonymous communication. It uses a decentralized distributed data store to keep and deliver information, and has a suite of free software
Hyphanet
Computer memory architecture
to access than non-distributed shared memory and must provide additional protection against simultaneous accesses to shared data. DSM may incur a performance
Distributed_shared_memory
Open-Source Workflow Management Platform
local and cloud resources. Many scientific data analyses require a significant amount of sequential processing steps. Custom scripts may suffice when developing
Nextflow
Multi-source interconnected computing
Distributed networking is a distributed computing network system where components of the program and data depend on multiple sources. Distributed networking
Distributed_networking
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