Parallel database

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A parallel database system seeks to improve performance through parallelization of various operations, such as loading data, building indexes and evaluating queries. [1] Although data may be stored in a distributed fashion, the distribution is governed solely by performance considerations. Parallel databases improve processing and input/output speeds by using multiple CPUs and disks in parallel. Centralized and client–server database systems are not powerful enough to handle such applications. In parallel processing, many operations are performed simultaneously, as opposed to serial processing, in which the computational steps are performed sequentially. Parallel databases can be roughly divided into two groups, the first group of architecture is the multiprocessor architecture, the alternatives of which are the following:

Shared-memory architecture
Where multiple processors share the main memory (RAM) space but each processor has its own disk (HDD). If many processes run simultaneously, the speed is reduced, the same as a computer when many parallel tasks run and the computer slows down.
Shared-disk architecture
Where each node has its own main memory, but all nodes share mass storage, usually a storage area network. In practice, each node usually also has multiple processors.
Shared-nothing architecture
Where each node has its own mass storage as well as main memory.

The other architecture group is called hybrid architecture, which includes:

in this switches or hubs are used to connect different computers its most cheapest way and simplest way only simple topologies are used to connect different computers . much smarter if switches are implemented.

Types of parallelism

Intraquery parallelism
A single query that is executed in parallel using multiple processors or disks. [2]
Independent parallelism
Execution of each operation individually in different processors only if they can be executed independent of each other. For example, if we need to join four tables, then two can be joined at one processor and the other two can be joined at another processor. Final join can be done later.
Pipe-lined parallelism
Execution of different operations in pipe-lined fashion. For example, if we need to join three tables, one processor may join two tables and send the result set records as and when they are produced to the other processor. In the other processor the third table can be joined with the incoming records and the final result can be produced.
Intraoperation parallelism
Execution of single complex or large operations in parallel in multiple processors. For example, ORDER BY clause of a query that tries to execute on millions of records can be parallelized on multiple processors.

Related Research Articles

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In computing, a database is an organized collection of data stored and accessed electronically. Small databases can be stored on a file system, while large databases are hosted on computer clusters or cloud storage. The design of databases spans formal techniques and practical considerations, including data modeling, efficient data representation and storage, query languages, security and privacy of sensitive data, and distributed computing issues, including supporting concurrent access and fault tolerance.

Process (computing) Particular execution of a computer program

In computing, a process is the instance of a computer program that is being executed by one or many threads. It contains the program code and its activity. Depending on the operating system (OS), a process may be made up of multiple threads of execution that execute instructions concurrently.

Multiprocessing is the use of two or more central processing units (CPUs) within a single computer system. The term also refers to the ability of a system to support more than one processor or the ability to allocate tasks between them. There are many variations on this basic theme, and the definition of multiprocessing can vary with context, mostly as a function of how CPUs are defined.

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The Earth Simulator (ES), developed by the Japanese government's initiative "Earth Simulator Project", was a highly parallel vector supercomputer system for running global climate models to evaluate the effects of global warming and problems in solid earth geophysics. The system was developed for Japan Aerospace Exploration Agency, Japan Atomic Energy Research Institute, and Japan Marine Science and Technology Center (JAMSTEC) in 1997. Construction started in October 1999, and the site officially opened on 11 March 2002. The project cost 60 billion yen.

Parallel computing Programming paradigm in which many processes are executed simultaneously

Parallel computing is a type of computation in which many calculations or processes are carried out simultaneously. Large problems can often be divided into smaller ones, which can then be solved at the same time. There are several different forms of parallel computing: bit-level, instruction-level, data, and task parallelism. Parallelism has long been employed in high-performance computing, but has gained broader interest due to the physical constraints preventing frequency scaling. As power consumption by computers has become a concern in recent years, parallel computing has become the dominant paradigm in computer architecture, mainly in the form of multi-core processors.

Flynn's taxonomy is a classification of computer architectures, proposed by Michael J. Flynn in 1966 and extended in 1972. The classification system has stuck, and it has been used as a tool in design of modern processors and their functionalities. Since the rise of multiprocessing central processing units (CPUs), a multiprogramming context has evolved as an extension of the classification system. Vector processing, covered by Duncan's taxonomy, is missing from Flynn's work because the Cray-1 was released in 1977: Flynn's second paper was published in 1972.

Instruction-level parallelism Ability of computer instructions to be executed simultaneously with correct results

Instruction-level parallelism (ILP) is the parallel or simultaneous execution of a sequence of instructions in a computer program. More specifically ILP refers to the average number of instructions run per step of this parallel execution.

In computing, single program, multiple data (SPMD) is a technique employed to achieve parallelism; it is a subcategory of MIMD. Tasks are split up and run simultaneously on multiple processors with different input in order to obtain results faster. SPMD is the most common style of parallel programming. It is also a prerequisite for research concepts such as active messages and distributed shared memory.

Microarchitecture Component of computer engineering

In computer engineering, microarchitecture, also called computer organization and sometimes abbreviated as µarch or uarch, is the way a given instruction set architecture (ISA) is implemented in a particular processor. A given ISA may be implemented with different microarchitectures; implementations may vary due to different goals of a given design or due to shifts in technology.

Data (computing) Quantities, characters, or symbols on which operations are performed by a computer

In computing, data is any sequence of one or more symbols; datum is a single symbol of data. Data requires interpretation to become information. Digital data is data that is represented using the binary number system of ones (1) and zeros (0), instead of analog representation. In modern (post-1960) computer systems, all data is digital.

In computing, a parallel programming model is an abstraction of parallel computer architecture, with which it is convenient to express algorithms and their composition in programs. The value of a programming model can be judged on its generality: how well a range of different problems can be expressed for a variety of different architectures, and its performance: how efficiently the compiled programs can execute. The implementation of a parallel programming model can take the form of a library invoked from a sequential language, as an extension to an existing language, or as an entirely new language.

Concurrent computing is a form of computing in which several computations are executed concurrently—during overlapping time periods—instead of sequentially—with one completing before the next starts.

Query optimization is a feature of many relational database management systems and other databases such as graph databases. The query optimizer attempts to determine the most efficient way to execute a given query by considering the possible query plans.

Database tuning describes a group of activities used to optimize and homogenize the performance of a database. It usually overlaps with query tuning, but refers to design of the database files, selection of the database management system (DBMS) application, and configuration of the database's environment.

SAP IQ is a column-based, petabyte scale, relational database software system used for business intelligence, data warehousing, and data marts. Produced by Sybase Inc., now an SAP company, its primary function is to analyze large amounts of data in a low-cost, highly available environment. SAP IQ is often credited with pioneering the commercialization of column-store technology.

Data parallelism 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 nodes, which operate on the data in parallel. It can be applied on regular data structures like arrays and matrices by working on each element in parallel. It contrasts to task parallelism as another form of parallelism.

Task parallelism is a form of parallelization of computer code across multiple processors in parallel computing environments. Task parallelism focuses on distributing tasks—concurrently performed by processes or threads—across different processors. In contrast to data parallelism which involves running the same task on different components of data, task parallelism is distinguished by running many different tasks at the same time on the same data. A common type of task parallelism is pipelining, which consists of moving a single set of data through a series of separate tasks where each task can execute independently of the others.

Microsoft SQL Server is a relational database management system developed by Microsoft. As a database server, it is a software product with the primary function of storing and retrieving data as requested by other software applications—which may run either on the same computer or on another computer across a network. Microsoft markets at least a dozen different editions of Microsoft SQL Server, aimed at different audiences and for workloads ranging from small single-machine applications to large Internet-facing applications with many concurrent users.

Computer cluster Set of computers configured in a distributed computing system

A computer cluster is a set of computers that work together so that they can be viewed as a single system. Unlike grid computers, computer clusters have each node set to perform the same task, controlled and scheduled by software.

Data-intensive computing is a class of parallel computing applications which use a data parallel approach to process large volumes of data typically terabytes or petabytes in size and typically referred to as big data. Computing applications which devote most of their execution time to computational requirements are deemed compute-intensive, whereas computing applications which require large volumes of data and devote most of their processing time to I/O and manipulation of data are deemed data-intensive.

References

  1. ↑ Dewitt, David; Gray, Jim (1992). "Parallel database systems: The future of high performance database systems" (PDF). Communications of the ACM. 35 (6): 85. CiteSeerX   10.1.1.119.8427 . doi:10.1145/129888.129894.
  2. ↑ Kandasamy, Saravanakumar. "Parallel Database - Intraquery Parallelism - Advanced Database Management System". Blogger . Retrieved September 10, 2017.


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