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"Q" Networking Definitions & Concepts...

Quad .. to .. Queue

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Quad:

A cable with four wires, consisting of two twisted pairs, each insulated separately.

Quality Assurance:

The main objective of quality assurance is to avoid problems, or to detect them as soon as possible in the development process. Poor quality can result from inaccurate requirements engineering, design problems, coding errors, faulty documentation, and ineffective or no testing.

In an effort to achieve high standards of quality, software and systems developers should consider software and systes engineering concepts and internationally recognized quality standards.

Software and Systems Engineering:

Because quality is so important, you can use an approach called software or systems engineering to manage and improve the quality of the finished system. Software and systems engineering is a software or systems development process that stresses solid design; based on sound engineering concepts and principals (theory and practice), effective structure, accurate documentation, and careful testing and reporting.

Here is the Web site for the Software Engineering Institute (SEI) at Carnegie Mellon University. SEI is a leader in software engineering and provides quality standards and suggested procedures for software developers and systems analysts. SEI's primary objective is to find better, faster, and less expensive methods of software development. To achieve that goal, SEI designed Capability Maturity Models (CMMs)®, which improve quality, reduce development time, and cut costs.

A CMM® tracks an organization's software development goals and practices, using five maturity levels, from Level 1 (relatively unstable, ineffective software), to Level 5 (software that is refined, efficient, and reliable).

The CMM frameworks help organizations increase the maturity of their human resources, process, and technology assets to improve long-term business perforance. The SEI has developed CMMs for software, people, and software acquisition, land helped develop CMMs for systems engineering and integrated product development. The latest development in CMMs is the CMM Integration (CMMI) Product Suite.

International Organization for Standardization (ISO):

The International Organization for Standardization (ISO) is a worldwide body that establishes quality standards for products and services. The ISO standards include everything from the dashboard symbols in your car to the ISBN numbers used in books. In addition, ISO seeks to offer a global consensus of what constitutes good management practices -- practices that can help firms deliver consistently high-quality products and services.

Because software is so important to a company's success, many firms seek assurances that software systems, either purchased or developed in-house, will meet rigid quality standards. In 1991, ISO established a set of guidelines called ISO 9000-3, which provided a quality assurance framework for developing and maintaining software. This since been updated to ISO 9000-3:1997. From the ISO Web site ISO 9000-3:1997 is a quality management and quality assurance standards -- Part 3: Guidelines for the application of ISO 9001:1994 to the development, supply, installation and maintenance of computer software.

A company can specify ISO 9000-3 standards when it purchases software from a supplier, or use ISO guidelines for in-house software development to ensure that the final result measures up to ISO standards. ISO requires a specific development plan, which outlines a step-by-step process for transforming user requirements into a finished product. ISO standards can be quite detailed. For example, ISO requires that a software supplier document all testing and maintain records of all test results. If problems are encountered, they must be resolved and any modules affected must be retested. Additionally, software and hardware specifications of all test equipment must be documented and included in the test records.

Quality-of-Service (QoS):

In ATM (Asynchronous Transfer Mode) networks, a set of parameters for describing a transmission. These parameters include values such as allowable delay variation in cell transmission and allowable cell loss (in relation to total cells transmitted). The parameters apply to virual channel connections (VCC) and virtual path connections (VPC), which specify paths between two entities.

Quantizing:

In digital-signal processing, quantizing is the process of converting a PAM (Pulse Amplitude Modulation) signal into PCM (Pulse Code Modulation) form. This converts a signal from a level to a bit sequence.

Query Language:

In a database management system, a programming language that allows a user to extract and display specific information from the database. For example, SQL (Structured Query Language) is an international database query language that allows the user to create or modify data or the database structure.

SEE ALSO

SQL (Structured Query Language)

Query Optimizer:

Is the portion of a DBMS or DDBMS application that determines the most efficient sequence of relational algebra operations to perform on a query.

The database appliction has an optimizer that attempts to pick the best strategy for executing each query. The best strategy is the one that gets the results in the shortest period of time. The optimizer determines the cost of each strategy by estimating the number of disk reads and writes required. The strategy with the lowest cost is chosen.

The optimizer must decide which order to access the tables in a query, and whether or not to use an index for each table. If a query joins N tables, there are N factorial possible ways to access the tables. The optimizer will estimate the cost of executing the query in the different ways and use the ordering with the lowest cost estimate.

A query processor is a module in the DBMS or DDBMS that performs the tasks to process, to optimize, and to generate execution strategy for a high-level query.

For a DDBMS, the query processor also does data localization for the query based on the fragmentation scheme and generates the execution strategy that incorporates the communication operations involved in processing the query.

Queries expressed in SQL can have multiple equivalent relational algebra query expressions. The distributed query optimizer must select the ordering of relational algebra operations, sites to process data, and possibly the way data should be transferred. This makes distributed query processing significantly more difficult.

The relational algebra is used to express the output of the query. The complexity of relational algebra operations play a role in defining some of the principles of query optimization. All complexity measures are based on the cardinality of the relation.

Operations Complexity:

Select, Project (w/o duplicate elimination): COST O(n)
Project (with duplicate elimination), Group: COST O(n logn)
Join, Semi-join, Division, Set Operators: COST O(n logn)
Cartesian Product: COST O(n2)

Languages:

Input language can be relational algebra or calculus; output language is relational algebra (annotated with communication primitives). The query processor must efficiently map input language to output language.

Types of Optimization:

The output language specification represents the execution strategy. There can be many such strategies, the best one can be selected through exhaustive search, or by applying heuristic (minimize size of intermediate relations). For distributed databases semi_joins can be applied to reduce data transfer.

When to Optimize:

Static: done before executing the query (at compilation time), cost of optimization amortized over multiple executions, mostly based on exhaustive search. Since sizes of intermediate relations need to be estimated, it can result in sub-optimal strategies.

Dynamic: done at run time; every time the query is executed, can make use of exact sizes of intermediate relations, expensive, based on heuristics.

Hybrid: mixes static and dynamic approaches; the approach is mainly static, but dynamic query optimization may take place when high difference between predicted and actual sizes are detected.

Characteristics of Query Processors:

Statistics:

  • Fragment cardinality and size
  • size and number of distinct values for each attribute. detailed ahistograms of attribute values for better selectivity estimation.
Decision Sites:
  • One site or several sites participate in selection of strategy
Exploitation of network topology:
  • Wide Area Network _ communication cost
  • Local Area Network _ parallel execution
Exploitation of replicated fragments:
  • larger number of possible strategies
  • Use of Semijoins
  • reduce size of data transfer
  • increase # of messages and local processing
  • good for fast or slow networks?

Layers of Query Processing:

myLayersOfQueryProc


Query Decomposition:

Normalization:

  • The calculus query is written in a normalized form (CNF or DNF) for subsequent manipulation.
Analysis
  • The query is analyzed for semantic correctness
Simplification
  • Redundant predicates are eliminated to obtain simplified queries.
Restructuring
  • The calculus query is translated to optimal algebraic query representation.

Query Decomposition: Normalization:

Lexical and syntactic analysis

  • check validity
  • check for attributes and relations
  • type checking on the qualification

There are two possible forms of representing the predicates in query qualification: Conjunctive Normal Form (CNF) or Disjunctive Normal Form (DNF). Where ∨ is a logical or, and ∧ is a logical and.

  • CNF: (p11 ∨ p12 ∨... ∨ p1n) ∧ ... ∧ (pm1 ∨ pm2 ∨...∨ pmn)
  • DNF: (p11 ∧ p12 ∧... ∧ p1n) ∨ ... ∨ (pm1 ∧ pm2 ∧... ∧ pmn)
  • OR's mapped into union
  • AND's mapped into join or selection

Queries are rejected because,

  • The attributes or relations are not defined in the global schema; or
  • Operations used in qualifiers are semantically incorrect
For only those queries that do not use disjunction or negation semantic correctness can be determined by using query graph

One node of the query graph represents result sites, others operand relations, edge between nodes operand nodes represent joins, and edge between operand node and result node represents project

Query Graph and Join Graph:

Translating SQL Queries into Relational Algebra

In practice, SQL is the query language that is used in most commercial RDBMSs. An SQL query is first translated into an equivalent extended relational algebra expression—represented as a query tree data structure—that is then optimized. 

  • SQL queries are first decomposed into query blocks, which form the basic units that can be translated into an extended relational algebra expression and then optimized.
  • A query block contains a single SELECT-FROM-WHERE expression, that is, nested queries are not query blocks.

Consider the following SQL query on the EMPLOYEE relation 

Queue:

In data handling, a temporary holding structure in which values can be stored until needed. A queue is organized in such a way that the first item added to the queue is also the first item out of the queue. This processing is known as FIFO, for first-in, first-out. Job and print queues are perhaps the best known for those who work with computers when dealing with FIFO queuing.

Quiescent Point (Q-Point, Electronics)

The point Vo in the diagram below is where the output signal would be taken. For simplicity, the input signal and coupling capacitors have been omitted. For minimum distortion and clipping it is desirable to bias this point to half the supply voltage, 10 volts dc in this case. This is also known as the quiescent point. The ac output signal would then be superimposed on the dc bias voltage. The Q-point is sometimes indicated on the output characteristics curves for a transistor amplifier. The quiescent point also refers to the dc conditions (bias conditions) of a circuit without an input signal.

myQuiescentPoint




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This page was last updated on 09/18/2005
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