A mechanism is provided for generating statistical information for query optimization in a data processing system. The mechanism comprises a first database engine maintaining a current first dataset currently being stored, a second database engine maintaining a second dataset. The second dataset is ...
由于SQL是声明式语言(declarative),用户只告诉了DBMS想要获取什么,但没有指出如何计算。因此,DBMS需要将SQL语句转换成可执行的查询计划(Query Plan)。但是对同样的数据可以有多种查询方案,性能也差距很大,查询优化器(Query Optimizer)的任务就是从给定的查询中选择一个最优的方案。 最早的查询优化器实现是IBM在1970s...
In SQL Server, theOPTION (LOOP JOIN)hint specifies the join method: SELECT*FROMordersINNERJOINcustomersONorders.customer_id=customers.idOPTION(LOOPJOIN); These hints override the default query optimization, improving performance in specific scenarios. ...
P. Gassner, G. M. Lohman and K. B. Schiefer, Query Optimization in IBM's DB2 Family of DBMSs,IEEE Data Engineering Bulletin, 16(4), December 1993. G. Graefe, The Cascades Framework for Query Optimization,Bulletin of the Technical Committee on Data Engineering, Vol 18 No. 3, September ...
4.1.2Cost-Based Optimization Query optimizationis the process of choosing the most efficient means of executing a SQL statement. SQL is a nonprocedural language, so the optimizer is free to merge, reorganize, and process in any order. The database optimizes each SQL statement based on statistic...
In predicate pushing, the optimizer "pushes" the relevant predicates from the containing query block into the view query block. For views that are not merged, this technique improves the subplan of the unmerged view because the database can use the pushed-in predicates to access indexes or to...
When the database finds a user query compatible with the query associated with a materialized view, then the database can rewrite the query in terms of the materialized view. This technique improves query execution because most of the query result has been precomputed. The query transformer looks...
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models are applied: improving performance of index structures and consequently data manipulation algorithms, query optimization tasks, and externally controlling query optimizers through parameter tuning. Furthermore, we discuss the key challenges associated with implementing deep learning algorithms in DBMS. ...
Eliminating or reducing the errors in cardinality is the first step to build a capable optimizer as Lohman [61 ] says “Theroot of all evil, the Achilles Heel of query optimization, is the estimation of the size of intermediate results, known as cardinalities” . ...