15.1 – Introduction to physical-Query-plan operators Presented BY: Jason Chee

Query processor Query Processor: Group of components of a DBMS that turns user queries and data-modification commands into a sequence of database operations and executes those operations

Query Compilation (Ch 16) Three parts: Parsing: Construct parse tree Query rewrite: parse tree -> query algebra -> logical query plan (faster) Physical plan generation: Converts logical query plan to physical query plan by selecting appropriate algorithms and order of execution.

Physical-query-plan operators Physical Operators often are implementations of relational algebra operators Examples of non-relational operators: Scan: bring into memory each tuple of some relation Iterators: method by which operators comprising a physical query plan can pass requests for tuples and answers among themselves

Scanning tables Reading the contents of a relation R Table-scan: Relation R is stored in secondary memory Blocks containing tuples of R are known, and it is possible to get the blocks one by one Index-scan If there is an index on any attribute of R, we may be able to use this index to get all the tuples of R.

Sorting while scanning tables Sort relation as we read tuples for multiple reasons. Examples: ORDER BY clause Operations requiring relations to be sorted Physical-query-plan operator sort-scan can be implemented many ways. One example is a B-tree index on sorted attribute a.

Computational model for physical operators Query is made of several operations of relational algebra, and query plan composed of several physical operators. Estimate cost by number of disk I/O’s. To compare algorithms, we assume that the arguments of any operator are found on disk, but the result of the operator is left in main memory. Because size of result doesn’t depend on algorithm Final write is cost of query, not algorithm

Parameters for measuring costs M: Number of main memory buffers (size of block) available to operator. Could be smaller than total main memory if several operators share memory. B or B(R): Size of relation R – number of blocks to hold all tuples of R T or T(R): Number of tuples in R. T/B = tuples per block V(R,[a1,a2,…an]): number of distinct values in a column, or columns for multiple attributes

i/o cost for scan operators Table-scan: If R is clustered, need B disk I/Os If R is not clustered, could be up to T disk I/Os – as many blocks as there are tuples Index-scan: If column data is contained in the index SELECT category_id FROM tbl WHERE category_id BETWEEN 10 AND 100; Don’t need to access the table Often smaller than B

Iterators for implementation of physical operators Design pattern to implement physical operators Three Methods 1) Open(): Initializes data structures 2) GetNext(): Returns the next tuple in the result and adjusts data structures as necessary. If no more tuples, return not found 3) Close(): Ends the iteration for all tuples. Calls close on any arguments of the operator.

Table-scan Iterator methods

Thank you Please feel free to ask any questions.