Information Integration(cntd.) Nikita Ramesh

Agenda Capability based optimization Notations for describing source capabilities Examples Capability based query plan selection Adding cost based optimization

Capability based optimization Query optimization: Optimize query to obtain efficiency Cost based optimization: Optimizer looks at all possible ways or scenarios in which a query can be executed. Each scenario is assigned a cost, which indicates how efficiently it can be run. Cost based optimizer will pick the least cost and execute the query using that scenario.

Capability based optimization When mediator is given a query, it has little knowledge about the time it will take to answer the query Often, data sources will only answer subset of the query Hence optimization cannot rely on cost measures alone Hence, capability based optimization is used Central issue is not cost, but whether query plan can be executed at all If plans are executable, find cost

Capability based optimization Problem of limited source capabilities: Many sources only have a Web based interface These sources permit querying through a query form Do not accept SQL queries (eg: Amazon) Legacy systems Security Indexing makes certain queries feasible while others too expensive

Notations for describing source capabilities f(free): attribute can be specified or not, as we choose b(bound): we must specify a value for the attribute, any value is allowed u(unspecified): we are not permitted to specify value for the attribute c[S]: choice from set S o[S]: optional from set S We place a prime e.g. f’ on a code if the attribute is not a part of the output query

Cars(serialNo, model, color, autoTrans, navi) Example 1 Cars(serialNo, model, color, autoTrans, navi) User specifies serial no. All other attributes are produced as output Adornment is: b’uuuu i.e. 1st attribute must be specified, and is not part of the output Other attributes must not be specified and are part of the output

Cars(serialNo, model, color, autoTrans, navi) Example 2 Cars(serialNo, model, color, autoTrans, navi) User specifies a model and color, and perhaps whether or not automatic transmission and navigation system are wanted All attributes printed for matching cars Adornment is: ubbo[yes, no]o[yes, no] i.e. 1st attribute must be specified, and is not part of the output Other attributes must not be specified and are part of the output

Capability based query plan selection capability-based query optimizer first considers what queries it can ask at the sources to help answer the query some more queries at the sources are possible repeat the process till: We have asked enough queries at the sources to resolve all the conditions of the mediator queries. Such a plan is called feasible We can construct no more valid forms of source queries. In which case the mediator must give up

Capability based query plan selection Autos(serial, model, color) Options(serial, option) ubf : adornment for Autos bu and uc[autoTrans, navi] : adornments for Options Find serial numbers and colors for Toyota models with a navigation system Specifying that the model is Toyota, query Autos and get the serial numbers and colors of all Toyotas. Then, using the bu adornment for Options, for each such serial number, find the options for that car and filter to make sure it has a navigation system Specifying the navigation-system option, query Options using the uc[autoTrans, navi] adornment and get all the serial numbers for cars with a navigation system. Query Autos to get serial numbers and colors, and intersect the two sets of serial numbers.

Adding cost based optimization After capabilities of the source are examined, feasible plans are found. After this, cost based optimization is added. Different costs are determined for the feasible plans.

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