A, OLTP, OLAP concept
the On-Line the Transaction Processing online transaction processing (OLTP)
also known as transaction-oriented processing, which is substantially characterized in reception of user data may be immediately transferred to the receiving computing center for processing,
and the processing is given in a very short period of time As a result, the operation is one of the ways the user quick response.
the On-Line Analytical Processing online analytical processing
that enables analysts to quickly, consistent, interactive observation information from all aspects, in order to achieve in-depth understanding of the data.
Two, OLTP, OLAP contrast
Concept of online analytical processing (OLAP) EFCodd was first proposed in 1993 by the father of the relational database, he also proposed 12 guidelines for the OLAP. OLAP proposes caused a great response, OLAP as a separate class of products with online transaction processing (OLTP) obvious.
Today's data processing can be roughly divided into two categories: online transaction processing OLTP (on-line transaction processing) , online analytical processing OLAP (On-Line Analytical Processing) . The main application is the traditional OLTP relational database, mainly basic, routine transactions, such as banking transactions.
OLAP data warehouse system is the main application that supports sophisticated analysis operations, focusing on decision support, and provides intuitive query results.
The following table shows the comparison between OLTP and OLAP.
Three, OLAP12 guidelines
1: Multidimensional conceptual view OLAP model must provide a multidimensional conceptual view
User-analysts would view an enterprise as being multidimensional in nature - for example, profits could be viewed by region , product, time period, or scenario (such as actual, budget, or forecast). Multi-dimensional data models enable more straightforward and intuitive manipulation of data by users, including "slicing and dicing".
analyze the user can naturally view enterprises a multi-dimensional model, for example, profits can be viewed by region, product, time, or programs (such as the actual, budget or forecast). Multidimensional data model allows the user to more direct and convenient operation data, including "slice and dice"
2: transparency Transparency
When OLAP forms part of the users' customary spreadsheet or graphics package, this should be transparent to the user. OLAP should be part of an open systems architecture which can be embedded in any place desired by the user without adversely affecting the functionality of the host Tool.
at the the user should not bE Exposed to at the Source of at the the Data Supplied to at the OLAP Tool, which May bE homogeneous or Heterogeneous.
when OLAP provides a spreadsheet or graphical display in a manner user habits, which should be transparent to the user. OLAP should be part of the development of system architecture, this architecture can be embedded in accordance with the needs of users anywhere, without tools will feature a host of side effects. Users should not come into contact with OLAP tools provided to a data source, the data may be homogeneous or heterogeneous
3: Accessibility Guidelines access capability
The OLAP tool should be capable of applying its own logical structure to access heterogeneous sources of data and perform any conversions necessary to present a coherent view to the user. The tool (and not the user) should be concerned with where the physical data comes from .
the OLAP tools should be able to use its own access to the logical structure of heterogeneous data sources, and performs the necessary conversion to the user to provide a coherent display. Is an OLAP tool rather than the user needs to be concerned about the physical data source
4: Consistent reporting performance and stable reporting capabilities
. Performance of the OLAP tool should not suffer significantly as the number of dimensions is increased
performance of OLAP tools should not increase due to the dimension and was significantly impact
5: client / server architecture client / server architecture
The server component of OLAP tools should be sufficiently intelligent that the various clients can be attached with minimum effort. The server should be capable of mapping and consolidating data between disparate databases.
Server OLAP tools should be smart enough to let more customers to a minimum the cost of connection. Mapping server should have the ability to consolidate data from different databases and
6: Generic dimensionality dimensional equivalence criteria
. Every data dimension should be equivalent in its structure and operational capabilities
of each dimension of the data should have a capacity equivalent structures and operations
7: Dynamic sparse matrix dynamic handling of sparse matrix handling
the OLAP server's physical structure should have optimal sparse matrix handling.
physical structure of OLAP server should be able to handle the optimal sparse matrix
8: multi-user support multi-user support capability
The Provide the MUST Concurrent Retrieval Tools OLAP and Update Access, Integrity and Security.
OLAP should provide concurrent access and update access, to ensure the integrity and security capabilities
9: Unrestricted cross-dimensional operations unrestricted cross-dimensional operation
Computational facilities must allow calculation and data manipulation across any number of data dimensions, and must not restrict any relationship between data cells.
computing device must allow computing across dimensionality of the data and data manipulation, can not restrict the relationship between any of the data unit
10: intuitive data manipulation intuitive data manipulation
data manipulation inherent in the consolidation path, such as drilling down or zooming out, should be accomplished via direct action on the analytical model's cells, and not require use of a menu or multiple trips across the user interface.
data operation to be at a fixed path, such as a drill or reduced, be done directly by the unit analysis model, without requiring user interaction of multiple directories goods
11: Flexible reporting and flexible report generator
Reporting facilities should present information in any the user wants to view it way.
Reports device should be able to show the information in any way the user needs
12:. Unlimited dimensions and aggregation levels unlimited dimensions and aggregation level
the number of data dimensions supported should, to all intents and purposes, be unlimited. each generic dimensions should enable an essentially unlimited number of user-defined aggregation levels within any given consolidation path.
the number of data dimensions should be unlimited users per aggregation aggregation level defined on the universal dimension should be unlimited.
Concept of online analytical processing (OLAP) EFCodd was first proposed in 1993 by the father of the relational database, he also proposed 12 guidelines for the OLAP. OLAP proposes caused a great response, OLAP as a separate class of products with online transaction processing (OLTP) obvious.
Today's data processing can be roughly divided into two categories: online transaction processing OLTP (on-line transaction processing) , online analytical processing OLAP (On-Line Analytical Processing) . The main application is the traditional OLTP relational database, mainly basic, routine transactions, such as banking transactions.
OLAP data warehouse system is the main application that supports sophisticated analysis operations, focusing on decision support, and provides intuitive query results.
The following table shows the comparison between OLTP and OLAP.