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CHAPTER 19 IMPROV IN G DA TA BAS E PERFORMAN CE: SQL QUERY OPTIMIZA TION
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Let s analyze the formatted output created by TKPROF. Listing 19-12 shows the parts of the TKPROF output showing the parse, execute, and fetch counts. Listing 19-12. The Parse, Execute, and Fetch Counts SQL> select e.last_name,e.first_name,d.department_name from teste e,testd d where e.department_id=d.department_id; call count cpu elapsed disk query current rows ------- ------ ------ ---------- -- ---------- ---------- -------Parse 1 0.00 0.00 0 0 0 0 Execute 1 0.00 0.00 0 0 0 0 Fetch 17322 1.82 1.85 3 136 5 259806 ------- ------ -------- ---------- ---------- ---------- ---------total 17324 1.82 1.85 3 136 5 259806 Misses in library cache during parse: 0 Optimizer goal: CHOOSE Parsing user id: 53 In Listing 19-12 CPU stands for total CPU time in seconds. Elapsed is the total time elapsed in seconds. Disk denotes total physical reads. Query is the number of consistent buffer gets. Current is the number of database block gets. Rows is the total number of rows processed for each type of call. From Listing 19-12, you can draw the following conclusions: The SQL statement shown previously was parsed once, so a parsed version wasn t available in the shared pool before execution. The Parse column shows that this operation took less than 0.01 seconds. Note that the lack of disk I/Os and buffer gets indicates that there were no data dictionary cache misses during the parse operation. If the Parse column showed a large number for the same statement, it would be an indicator that bind variables weren t being used. The statement was executed once and execution took less than 0.01 seconds. Again, there were no disk I/Os or buffer gets during the execution phase. It took me a lot longer than 0.01 seconds to get the results of the SELECT statement back. The Fetch column answers this question of why that should be: it shows that the operation was performed 17,324 times and took up 1.82 seconds of CPU time. The Fetch operation was performed 17,324 times and fetched 259,806 rows. Because the number of rows is far greater than the number of fetches, you can deduce that Oracle used array fetch operations. There were three physical reads during the fetch operation. If there s a large difference between CPU time and elapsed time, it can be attributed to time taken up by disk reads. In this case, the physical I/O has a value of only 3, and it matches the insignificant gap between CPU time and elapsed time. The fetch required 136 buffer gets in the consistent mode and only 5 DB block gets. The CBO was being used, because the optimizer goal is shown as CHOOSE.
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CHAPTER 19 IM PR OVING DA TA BAS E PERFORM ANC E: S QL QUE RY OPTIMIZA TION
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The following output shows the execution plan that was explicitly requested when TKPROF was invoked. Note that instead of the cost estimates that you get when you use the EXPLAIN PLAN tool, you get the number of rows output by each step of the execution. Rows ------259806 1161 1161 259806 Row Source Operation ----------------------MERGE JOIN SORT JOIN TABLE ACCESS FULL TESTD SORT JOIN
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Finally, TKPROF summarizes the report, stating how many SQL statements were traced. Here s the summary portion of the TKPROF-formatted output: Trace file: ORA02344.TRC Trace file compatibility: 9.00.01 Sort options: default 2 sessions in trace file. 18 user SQL statements in trace file. 104 internal SQL statements in trace file. 72 SQL statements in trace file. 33 unique SQL statements in trace file. 18182 lines in trace file. The TKPROF output makes it easy to identify inefficient SQL statements. TKPROF can order the SQL statements by elapsed time (time taken for execution), which tells you which of the SQL statements you should focus on for optimization. The SQL Trace utility is a powerful tool in tuning SQL, because it goes far beyond the information produced by using EXPLAIN PLAN. It provides you with hard information about the number of the various types of calls made to Oracle during statement execution, and how the resource use was allocated to the various stages of execution.
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Note It s easy to trace individual user sessions using the OEM Database Control. I explain how you can trace and view user sessions using the Database Control in the section Using the Database Control for End-to-End Tracing. You can trace a session as well as read the output file directly from the Database Control.
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