第六步:查看优化建议结果
通知函数dbms_advisor.get_task_report可以得到优化建议结果。
SQL> SET LONG 1000000 PAGESIZE 0 LONGCHUNKSIZE 1000SQL> COLUMN get_clob FORMAT a80SQL> SELECT dbms_advisor.get_task_report('DEMO_ADDM01', 'TEXT', 'ALL') FROM DUAL; DBMS_ADVISOR.GET_TASK_REPORT('-------------------------------------------------------------------------------- DETAILED ADDM REPORT FOR TASK 'DEMO_ADDM01' WITH ID 243 ------------------------------------------------------- Analysis Period: 23-NOV-2005 from 15:02:27 to 16:06:42 Database ID/Instance: 1712582900/1 Database/Instance Names: EDGAR/edgar Host Name: HUANGED Database Version: 10.2.0.1.0 Snapshot Range: from 65 to 66 Database Time: 1463 seconds Average Database Load: .4 active sessions ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ FINDING 1: 100% impact (1463 seconds)-------------------------------------Significant virtual memory paging was detected on the host operating system. RECOMMENDATION 1: Host Configuration, 100% benefit (1463 seconds) ACTION: Host operating system was experiencing significant paging but no particular root cause could be detected. Investigate processes that do not belong to this instance running on the host that are consuming significant amount of virtual memory. Also consider adding more physical memory to the host. FINDING 2: 100% impact (1463 seconds)-------------------------------------SQL statements consuming significant database time were found. RECOMMENDATION 1: SQL Tuning, 68% benefit (998 seconds) ACTION: Tune the PL/SQL block with SQL_ID "064wqx7c5b81z". Refer to the "Tuning PL/SQL Applications" chapter of Oracle's "PL/SQL User's Guide and Reference" RELEVANT OBJECT: SQL statement with SQL_ID 064wqx7c5b81z DECLARE v_var number; BEGIN FOR n IN 1..10000 LOOP select count(*) into v_var from bigtab b, smalltab a; END LOOP; END; RECOMMENDATION 2: SQL Tuning, 67% benefit (986 seconds) ACTION: Run SQL Tuning Advisor on the SQL statement with SQL_ID "fvqfghq71cqns". RELEVANT OBJECT: SQL statement with SQL_ID fvqfghq71cqns and PLAN_HASH 3281046854 SELECT COUNT(*) FROM BIGTAB B, SMALLTAB A RATIONALE: SQL statement with SQL_ID "fvqfghq71cqns" was executed 6 times and had an average elapsed time of 166 seconds. FINDING 3: 69% impact (1002 seconds)------------------------------------Time spent on the CPU by the instance was responsible for a substantial partof database time.
RECOMMENDATION 1: SQL Tuning, 67% benefit (986 seconds) ACTION: Run SQL Tuning Advisor on the SQL statement with SQL_ID "fvqfghq71cqns". RELEVANT OBJECT: SQL statement with SQL_ID fvqfghq71cqns and PLAN_HASH 3281046854 SELECT COUNT(*) FROM BIGTAB B, SMALLTAB A RATIONALE: SQL statement with SQL_ID "fvqfghq71cqns" was executed 6 times and had an average elapsed time of 166 seconds. RATIONALE: Average CPU used per execution was 162 seconds. RECOMMENDATION 2: SQL Tuning, 2.1% benefit (30 seconds) ACTION: Tune the PL/SQL block with SQL_ID "2b064ybzkwf1y". Refer to the "Tuning PL/SQL Applications" chapter of Oracle's "PL/SQL User's Guide and Reference" RELEVANT OBJECT: SQL statement with SQL_ID 2b064ybzkwf1y BEGIN EMD_NOTIFICATION.QUEUE_READY(:1, :2, :3); END; RATIONALE: SQL statement with SQL_ID "2b064ybzkwf1y" was executed 125 times and had an average elapsed time of 0.26 seconds. RATIONALE: Average CPU used per execution was 0.24 seconds. FINDING 4: 2.2% impact (33 seconds)-----------------------------------PL/SQL execution consumed significant database time. RECOMMENDATION 1: SQL Tuning, 2.2% benefit (33 seconds) ACTION: Tune the PL/SQL block with SQL_ID "2b064ybzkwf1y". Refer to the "Tuning PL/SQL Applications" chapter of Oracle's "PL/SQL User's Guide and Reference" RELEVANT OBJECT: SQL statement with SQL_ID 2b064ybzkwf1y BEGIN EMD_NOTIFICATION.QUEUE_READY(:1, :2, :3); END; RATIONALE: SQL statement with SQL_ID "2b064ybzkwf1y" was executed 125 times and had an average elapsed time of 0.26 seconds. RATIONALE: Average time spent in PL/SQL execution was 0.26 seconds. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ADDITIONAL INFORMATION ---------------------- Wait class "Application" was not consuming significant database time.Wait class "Commit" was not consuming significant database time.Wait class "Concurrency" was not consuming significant database time.Wait class "Configuration" was not consuming significant database time.Wait class "Network" was not consuming significant database time.Wait class "User I/O" was not consuming significant database time.Session connect and disconnect calls were not consuming significant databasetime.
Hard parsing of SQL statements was not consuming significant database time. The analysis of I/O performance is based on the default assumption that theaverage read time for one database block is 10000 micro-seconds.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ TERMINOLOGY ----------- DATABASE TIME: This is the ADDM's measurement of throughput. From the user's point of view: this is the total amount of time spent by users waiting for a response from the database after issuing a call (not including networking). From the database instance point of view: this is the total time spent by forground processes waiting for a database resource (e.g., read I/O), running on the CPU and waiting for a free CPU (run-queue). The target of ADDM analysis is to reduce this metric as much as possible, thereby reducing the instance's response time. AVERAGE DATABASE LOAD: At any given time we can count how many users (also called 'Active Sessions') are waiting for an answer from the instance. This is the ADDM's measurement for instance load. The 'Average Database Load' is the average of the the load measurement taken over the entire analysis period. We get this number by dividing the 'Database Time' by the analysis period. For example, if the analysis period is 30 minutes and the 'Database Time' is 90 minutes, we have an average of 3 users waiting for a response. IMPACT: Each finding has an 'Impact' associated with it. The impact is the portion of the 'Database Time' the finding deals with. If we assume that the problem described by the finding is completely solved, then the 'Database Time' will be reduced by the amount of the 'Impact'. BENEFIT: Each recommendation has a 'benefit' associated with it. The ADDM analysis estimates that the 'Database Time' can be reduced by the 'benefit' amount if all the actions of the recommendation are performed.说明:
其中第五步到第六步可以直接执行$ORACLE_HOME/rdbms/admin/addmrpt.sql来得到,这个脚本的执行过程和statspack脚本执行过程类似:
SQL> @addmrpt Current Instance~~~~~~~~~~~~~~~~ DB Id DB Name Inst Num Instance----------- ------------ -------- ------------ 1712582900 EDGAR 1 edgar Instances in this Workload Repository schema~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ DB Id Inst Num DB Name Instance Host------------ -------- ------------ ------------ ------------* 1712582900 1 EDGAR edgar HUANGED Using 1712582900 for database IdUsing 1 for instance number Specify the number of days of snapshots to choose from~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~Entering the number of days (n) will result in the most recent(n) days of snapshots being listed. Pressing withoutspecifying a number lists all completed snapshots.
Listing the last 3 days of Completed Snapshots SnapInstance DB Name Snap Id Snap Started Level------------ ------------ --------- ------------------ -----edgar EDGAR 7 22 Nov 2005 00:00 1
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本文介绍了如何使用Oracle的自动数据库诊断监控(ADDM)工具获取优化建议报告,并详细解析了报告内容,包括发现的主要问题、推荐的优化措施及其预期效益。
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