oracle - "TABLE ACCESS BY LOCAL INDEX ROWID"高估计成本

Question

我在 Oracle 中有一个查询导致 OLAP 系统中的估计成本很高。估计行数只有 100K，但成本是一个巨大的数字。请问cost的数量是怎么计算的，在什么情况下会出现超高的预估成本？

执行计划:

  17 TABLE ACCESS BY LOCAL INDEX ROWID /BIC/FZ3PM_C01                                 
|    ( Estim. Costs = 1,299,922,942,955,190 , Estim. #Rows = 104,711 )                
|    Pstart: 1 Pstop: 471                                                             
|    Estim. CPU-Costs = 18,446,744,073,709,601,000 Estim. IO-Costs = 86,157,375,      
|                                                                                     
---   16 BITMAP CONVERSION TO ROWIDS                                                  
    |                                                                                 
    ---   15 BITMAP AND                                                               
        |                                                                             
        |--   7 BITMAP MERGE                                                          
        |   |                                                                         
        |   ---   6 BITMAP KEY ITERATION                                              
        |       |                                                                     
        |       |--   4 BUFFER SORT                                                   
        |       |   |                                                                 
        |       |   ------3 TABLE ACCESS FULL /BIC/DZ3PM_C012                         
        |       |           ( Estim. Costs = 4 , Estim. #Rows = 180 )                 
        |       |           Estim. CPU-Costs = 1,093,126 Estim. IO-Costs = 4          
        |       |           Filter Predicates                                         
        |       |                                                                     
        |       ------5 BITMAP INDEX RANGE SCAN /BIC/FZ3PM_C01~050                    
        |               Pstart: 1 Pstop: 471                                          
        |               Search Columns: 1                                             
        |               Access Predicates                                             
        |                                                                             
        ---   14 BITMAP MERGE                                                         
            |                                                                         
            ---   13 BITMAP KEY ITERATION                                             
                |                                                                     
                |--   11 BUFFER SORT                                                  
                |   |                                                                 
                |   ---   10 HASH JOIN                                                
                |       |    ( Estim. Costs = 2,492 , Estim. #Rows = 1,264,100 )      
                |       |    Estim. CPU-Costs = 801,483,146 Estim. IO-Costs = 2,407   
                |       |    Access Predicates                                        
                |       |                                                             
                |       |-----8 TABLE ACCESS FULL /BI0/XMATERIAL                      
                |       |       ( Estim. Costs = 1,470 , Estim. #Rows = 50,880 )      
                |       |       Estim. CPU-Costs = 403,451,418 Estim. IO-Costs = 1,427
                |       |       Filter Predicates                                     
                |       ------9 TABLE ACCESS FULL /BIC/DZ3PM_C011                     
                |               ( Estim. Costs = 1,007 , Estim. #Rows = 1,264,100 )   
                |               Estim. CPU-Costs = 259,249,328 Estim. IO-Costs = 980  
                |                                                                     
                ------12 BITMAP INDEX RANGE SCAN /BIC/FZ3PM_C01~040                   
                         Pstart: 1 Pstop: 471                                         
                         Search Columns: 1                                            
                         Access Predicates                                            

Answer 1

100,000 行估计是输出。它可能需要做很多工作来过滤一个大数据集，甚至更多的工作来总结一个大数据集。也就是说，这些成本是天文数字(即使数据库的数据大小需要 400 多个分区)

尝试执行解释计划，然后执行 SELECT * FROM TABLE(DBMS_XPLAN.DISPLAY)

这提供了一个更具可读性的计划。您希望所有访问和过滤谓词都能看到它在做什么，以及汇总起来的成本。