For many years, Oracle DBAs have been trying to get answers to questions on the usage of various database segments (i.e. tables and indexes) within their databases. They often wonder if an index is being used, or which table is accessed the most, or which table has the most changes applied to it. There have been many esoteric methods employed to try to answer these questions. The 9i release of the Oracle RDBMS finally gives us a definitive source to determine many statistics on any database segment, the V$SEGMENT_STATISTICS dynamic performance view.
Segments and Statistics
In the Oracle database, a segment is any database object that requires physical storage space, aside from the DDL of that object. Segments include tables, indexes, clusters, partitions, temporary segments, undo segments, and LOB segments. Objects like views, procedures, triggers are not included in the list of segments. These objects do not need to allocate an extent to reside in the database. They are only stored in the data dictionary. While the definition of all segments reside in the data dictionary, the segment itself lives outside the data dictionary, hopefully in a non-SYSTEM tablespace.
Before Oracle 9i, there was no easy way to get information, or statistics, about the usage of various segments. If one wanted to know how many physical reads or writes occurred on a specific table, the only way to know for sure was to place that table in its own tablespace and then query the PHYRDS or PHYWRTS columns of the V$FILESTAT view. If other tables were in this tablespace, their physical read and write counts would show up for that tablespace as well. The problem with this method was that a segment must be the only object in that tablespace for the method to work accurately.
Many people also wanted to answer the question of whether a particular index was ever used. If an index is not being used, then we want to remove it so that it does not unnecessarily hamper performance of DML statements. The answer to this question often was to query V$BH, which shows the blocks currently in the database buffer cache. If the index had any block in the buffer cache then it must have been used at one time. But what happens when the index block gets aged out of the cache? One had to make sure to query V$BH with a short interval between samples to see if any index block was in the cache. This method could never guarantee that the index block was not aged out of the cache between queries on V$BH. Oracle 9i addressed this issue with the ALTER INDEX MONITORING USAGE command and the V$OBJECT_USAGE view. This is a much better solution, but you do have to turn on monitoring for that index some time before you can query V$OBJECT_USAGE to see if the index has ever been used.
Oracle 9i introduces the new V$SEGMENT_STATISTICS dynamic performance view. This view lets you see many different statistics on the usage of segments since instance startup. You do not have to turn on monitoring or take any special steps to begin using this view to answer your questions. The query below shows the statistics that you can get with the Oracle 188.8.131.52 release:
SQL> select distinct statistic_name from v$segment_statistics; STATISTIC_NAME ---------------------------------------- ITL waits buffer busy waits db block changes global cache cr blocks served global cache current blocks served logical reads physical reads physical reads direct physical writes physical writes direct row lock waits 11 rows selected.
Future release of the Oracle RDBMS may include more statistics.
Oracle 9i has included the V$SEGMENT_STATISTICS view to help give definitive answers to many questions. We can now know exactly if an index has been used, without turning on monitoring. We can also know which tables have the highest physical I/O activity.
If you want to know if an index has ever been used since instance startup, the solution is quite easy. Simply query V$SEGMENT_STATISTICS to see if there has even been a physical read on the index in question. Queries similar to the following can help:
SQL> select statistic_name,value 2 from v$segment_statistics 3 where owner='SDE' and object_name='LAYERS_PK' 4 and statistic_name='physical reads'; STATISTIC_NAME VALUE ---------------------------------------- ---------- physical reads 6094 SQL> select statistic_name,value 2 from v$segment_statistics 3 where owner='SDE' and object_name='LAYERS_IX1' 4 and statistic_name='physical reads'; no rows selected
The first query shows that 6,094 physical reads have been performed on the LAYERS_PK index. This index has obviously been used before. The second query shows that no physical reads have ever occurred on the LAYERS_IX1 index. If there have never been any physical reads on this index then it has never been used.
Next, we'll see how to use V$SEGMENT_STATISTICS to determine the top 10 tables that have incurred the most physical I/O operations.
SQL> select table_name,total_phys_io 2 from ( select owner||'.'||object_name as table_name, 3 sum(value) as total_phys_io 4 from v$segment_statistics 5 where owner!='SYS' and object_type='TABLE' 6 and statistic_name in ('physical reads','physical reads direct', 7 'physical writes','physical writes direct') 8 group by owner||'.'||object_name 9 order by total_phys_io desc) 10* where rownum <=10; TABLE_NAME TOTAL_PHYS_IO ----------------------------------- ------------- WEBMAP.SDE_BLK_1103 43152119 SRTM.SDE_BLK_1101 35526039 WEBMAP.SDE_BLK_1046 35155063 WEBMAP.SDE_BLK_1110 20941514 WEBMAP.SDE_BLK_1106 15487605 WEBMAP.SDE_BLK_1102 10414181 NED.SDE_BLK_1002 9247263 SRTM.SDE_BLK_1104 6386630 NED.SDE_BLK_1068 5313627 WEBMAP.SDE_BLK_804 5175899 10 rows selected.
The query above eliminated any data dictionary tables from the results. It should now be clear what the exact table is that experiences the most physical I/O operations. Appropriate actions can now be taken to isolate this potential hotspot from other highly active database segments.
If you've ever dealt with wait events, you may have seen the 'buffer busy waits' event. This event occurs when one session is waiting on another session to read the buffer into the cache, or some other session is changing the buffer. This even can often be seen when querying V$SYSTEM_EVENT. If I query my database, I have approximately 13 million waits on this specific event.
GASP SQL> select event,total_waits from v$system_event 2 where event='buffer busy waits'; EVENT TOTAL_WAITS ---------------------------------------- ----------- buffer busy waits 12976210
The big question is to determine which segments are contributing to this overall wait event. Querying V$SEGMENT_STATISTICS can help us determine the answer.
SQL> select segment_name,object_type,total_buff_busy_waits 2 from ( select owner||'.'||object_name as segment_name,object_type, 3 value as total_buff_busy_waits 4 from v$segment_statistics 5 where statistic_name in ('buffer busy waits') 6 order by total_buff_busy_waits desc) 7* where rownum <=10 GASP SQL> / SEGMENT_NAME OBJECT_TYPE TOTAL_BUFF_BUSY_WAITS ----------------------------------- ------------- --------------------- WEBMAP.SDE_BLK_1103 TABLE 10522135 WEBMAP.SDE_BLK_804 TABLE 1176185 SRTM.SDE_BLK_1101 TABLE 651175 WEBMAP.SDE_BLK_804_UK INDEX 100242 SYS.DBMS_LOCK_ALLOCATED TABLE 64695 NED.SDE_BLK_1002 TABLE 48582 WEBMAP.BTS_ROADS_MD TABLE 27068 WEBMAP.SDE_BLK_1103_UK INDEX 25707 ARCIMS.SDE_LOGFILE_DATA_IDX1 INDEX 24618 NED.SDE_BLK_62 TABLE 14710 10 rows selected.
From the query above, we can see that one specific table contributed 10.5 million, or approximately 80%, of the total waits. Without V$SEGMENT_STATISTICS, we would have not been able to get this accurate of a picture. It would have been very difficult to get determine that one table was contributing 80% of the buffer busy wait events.
Hopefully, I've shown how the Oracle 9i database has gone another step forward by giving DBAs the information that they need to solve some of their problems. The V$SEGMENT_STATISTICS dynamic performance view gives many statistics about each and every segment that is used by the database. One can now accurately tell if an index has been used, and how much. One can easily determine the top-N "hot" segments to aid in performance tuning.
About the Author
Mr. Peasland has been in the IT field for 15 years working as a Computer Operator, Operations Analyst, Systems Administrator, Application Developer, and finally a Database Administrator. He holds a B.S. in Computer Science and a M.S. in Computer Science specializing in Database Systems. Additionally Mr. Peasland holds OCP DBA credentials for Oracle 7.3, 8, and 8i. He currently works for SGT, Inc. as a Database Administrator.
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