In this architecture, messages are processed and prioritized asynchronously. Messages have headers that include priority information, address and identification number. The message server links to the relational DBMS and other data sources. Messaging systems are alternative for wireless infrastructures. Three tier with an application server This architecture allows the main body of an application to run on a shared host rather than in the user system interface client environment. The application server shares business logic, computations and a data retrieval engine. In this architecture applications are more scalable and installation costs are less on a single server than maintaining each on a desktop client. 3-tier architecture provides A greater degree of flexibility Increased security, as security can be defined for each service, and at each level Increased performance, as tasks are shared between servers Two Phase Commit A commit operation is, by definition, an all-or-nothing affair. If a series of operations bound as a transaction cannot be completed, the rollback must restore the system (or cooperating systems) to the pre-transaction state. In order to ensure that a transaction can be rolled back, a software system typically logs each operation, including the commit operation itself. A transaction/recovery manager uses the log records to undo (and possibly redo) a partially completed transaction. When a transaction involves multiple distributed resources, for example, a database server on each of two different network hosts, the commit process is somewhat complex because the transaction includes operations that span two distinct software systems, each with its own resource manager, log records, and so on. (In this case, the distributed resources are the database servers.) Two-phase commit is a transaction protocol designed for the complications that arise with distributed resource managers. With a two-phase commit protocol, the distributed transaction manager employs a coordinator to manage the individual resource managers. The commit process proceeds as follows: Phase 1 Each participating resource manager coordinates local operations and forces all log records out: If successful, respond "OK" If unsuccessful, either allow a time-out or respond "OOPS" Phase 2
dimensions (all products sold in the Eastern region above a certain price during a certain time period) and display them. such as time periods can be broken down into sub attributes. OLAP can be used for or the discovery of previously undiscerned relationships between data items. An OLAP database does not need to be as large as a , since not all transactional data is needed for trend analysis. Using Open Database Connectivity (), data can be imported from existing relational databases to create a multidimensional database for OLAP. OLTP OLAP Defination OLTP stands for On Line Transaction Processing and is a data modeling approach typically used to facilitate and manage usual business applications. Most of applications you see and use are OLTP based OLAP stands for On Line Analytic Processing and is an approach to answer queries. OLAP was conceived for Management Information Systems and Decision Support Systems Horizon OLTP System deals with operational data. Operational data are those data involved in the operation of a particular system. OLAP deals with Historical Data or Archival Data. Historical data are those data that are archived over a long period of time. Refresh OLPT requires instant update. When you cash some money from an ATM you balance shall be immediately updated OLAP has not require instant refresh. Nobody instant information to make strategic business decision. Data Model & Schema OLTP perfectly fits traditional or object-oriented models. We usually refer to information as attributes related to entities, objects or classes, like product price, invoice amount or client name. Mapping can be with a simple, one argument function OLAP solution is use an hybrid approach based sitting on conventional relational technology. This model employs so called star-schema instead of traditional normalization. Emphasis OLPT emphasis is on update. Transaction level isolation assures that database is always in a consistent state. This can imply in some overhead to coordinate concurrent updates but is necessary even in small applications. OLAP can be updated by periodic (daily) processes that work in standalone mode thus consistency can be assured through update process. Example In a banking System, you withdraw amount through an ATM. Then account Number,ATM PIN Number,Amount you If we collect last 10 data about flight reservation, The data can give us many meaningful information such as the trends in