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end of its execution by popping the record out of the stack. The stack data structure is used to implement the automatic memory of the program, and since different threads execute different functions at the same time, a separate stack is assigned to each of them.

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Now we are ready to see what measurable difference we could expect to see. Using AUTOTRACE, we ll get a feeling for the change: ops$tkyte%ORA11GR2> set autotrace traceonly ops$tkyte%ORA11GR2> select * 2 from emp, heap_addresses 3 where emp.empno = heap_addresses.empno 4 and emp.empno = 42; Execution Plan ---------------------------------------------------------Plan hash value: 4163174643 ----------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | ----------------------------------------------------------------------| 0 | SELECT STATEMENT | | 4 | 356 | | 1 | NESTED LOOPS | | 4 | 356 | | 2 | TABLE ACCESS BY INDEX ROWID| EMP | 1 | 43 | |* 3 | INDEX UNIQUE SCAN | EMP_PK | 1 | | | 4 | TABLE ACCESS BY INDEX ROWID| HEAP_ADDRESSES | 4 | 184 | |* 5 | INDEX RANGE SCAN | SYS_C0019080 | 4 | | ----------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------3 - access("EMP"."EMPNO"=42) 5 - access("HEAP_ADDRESSES"."EMPNO"=42) Statistics ---------------------------------------------------------0 recursive calls 0 db block gets 11 consistent gets 0 physical reads 0 redo size 1153 bytes sent via SQL*Net to client 419 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 4 rows processed That is a pretty common plan: go to the EMP table by primary key; get the row; then using that EMPNO, go to the address table; and using the index, pick up the child records. We did 11 I/Os to retrieve this data. Now running the same query, but using the IOT for the addresses ops$tkyte%ORA11GR2> select * 2 from emp, iot_addresses 3 where emp.empno = iot_addresses.empno

and emp.empno = 42;

Figure 17-2 Memory organization of a running CLR program Dynamic memory is allocated in the heap, which is a data structure where data resides for an amount of time not directly related to the events of program execution The memory is explicitly allocated by the program, and it is deallocated either explicitly or automatically depending on the strategy adopted by the run time to manage the heap In the CLR, the heap is managed by a garbage collector, which is a program that tracks memory usage and reclaims memory that is no longer used by the program Data in the heap is always referenced from the stack or other known areas such as static memory either directly or indirectly The garbage collector can deduce the memory potentially reachable by program execution in the future, and the remaining memory can be collected.

Execution Plan ---------------------------------------------------------Plan hash value: 1490857195 -------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | -------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 4 | 356 | | 1 | NESTED LOOPS | | 4 | 356 | | 2 | TABLE ACCESS BY INDEX ROWID| EMP | 1 | 43 | |* 3 | INDEX UNIQUE SCAN | EMP_PK | 1 | | |* 4 | INDEX RANGE SCAN | SYS_IOT_TOP_93124 | 4 | 184 | -------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------3 - access("EMP""EMPNO"=42) 4 - access("IOT_ADDRESSES".

"EMPNO"=42) Statistics ---------------------------------------------------------0 recursive calls 0 db block gets 7 consistent gets 0 physical reads 0 redo size 1153 bytes sent via SQL*Net to client 419 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 4 rows processed we did four fewer I/Os (the four should have been guessable); we skipped four TABLE ACCESS (BY INDEX ROWID) steps The more child records we have, the more I/Os we would anticipate skipping So, what is four I/Os Well, in this case it was over one-third of the I/O performed for the query, and if we execute this query repeatedly, it would add up.