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It would be a mistake to treat all CPU time as equal. CPU time is generally understood as the processor time taken to perform various tasks, such as the following: Loading SQL statements into the library cache Searching the shared pool for parsed versions of SQL statements Parsing the SQL statements Querying the data dictionary Reading data from the buffer cache Traversing index trees to fetch index keys The total CPU time used by an instance (or a session) can be viewed as the sum of the following components: total CPU time = parsing CPU usage + recursive CPU usage + other CPU usage Ideally, your total CPU usage numbers should show a small proportion of the first two categories of CPU usage parsing and recursive CPU usage. For example, for a session-wide estimate of CPU usage, you can run the query shown in Listing 20-11. Listing 20-11. Decomposition of Total CPU Usage SQL> SELECT name,value FROM V$SYSSTAT 2 WHERE NAME IN ('CPU used by this session', 3 'recursive cpu usage', 4 *'parse time cpu'); NAME ------------------------recursive cpu usage CPU used by this session parse time cpu 3 rows selected. SQL> VALUE --------4713085 98196187 132947

1 2, 3, 4, 5 6

In this example, the sum of recursive CPU usage and parse time CPU usage is a small proportion of total CPU usage. You need to be concerned if the parsing or recursive CPU usage is a significant part of total CPU usage. Let s see how you can go about reducing the CPU usage attributable to these various components.

Note In the following examples, you can examine CPU usage at the instance level by using the V$SYSSTAT view or at an individual session level by using the V$SESSTAT view. Just remember that the column total CPU used by this session in the V$SYSSTAT view refers to the sum of the CPU used by all the sessions combined.

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As you learned at the beginning of this chapter, parsing is an expensive operation that you should reduce to a minimum. In the following example, the parse time CPU usage is quite low as a percentage of total CPU usage. The first query tells you that the total CPU usage in your instance is 49159124: SQL> SELECT name, value FROM V$SYSSTAT 2* WHERE name LIKE '%CPU%'; NAME --------------------------CPU used when call started CPU used by this session 2 rows selected. SQL> VALUE -------13220745 49159124

Fetch Size (Level Inherited From)

number, while the secret key can be an alphanumeric string. Multiples of the ntp authentication-key and ntp trusted-key commands are allowed in Cisco configurations to facilitate redundant authenticated servers and/or peers. Listing 5-13 demonstrates the configuration of authentication on Cisco routers. Router1 is a client of Router4. The show ntp associations detail command at the end of the example illustrates that the synchronization exchanges between Router1 (client) and Router4 (NTP server that s configured as the local master ) are authenticated.

The next query shows that the parse time CPU usage is 96431, which is an insignificant proportion of total CPU usage in your database: SQL> SELECT name, value FROM V$SYSSTAT 2 WHERE name LIKE '%parse%'; NAME -------------------parse time cpu parse time elapsed parse count (total) parse count (hard) 4 rows selected. SQL> VALUE -------96431 295451 3147900 29139

Listing 20-12 shows an example of a session whose CPU usage is predominantly due to high parse time. Listing 20-12. Determining Parse Time CPU Usage SQL> 2 3 4 5 6 7 8 SELECT a.value " Tot_CPU_Used_This_Session", b.value "Total_Parse_Count", c.value "Hard_Parse_Count", d.value "Parse_Time_CPU" FROM v$sysstat a, v$sysstat b, v$sysstat c, v$sysstat d

20 (PreparedStatement) 20 (PreparedStatement) 20 (PreparedStatement)

9 10 11 12*

used by this session' count (total)' count (hard)' time cpu';

Tot_CPU_Used Total_Parse_Count Hard_Parse_Count Parse_Time_CPU This_Session ------------- ----------------- ------------------ --------------2240 53286 281 1486 SQL> Parse time CPU in the preceding example is fully two-thirds of the total CPU usage. Obviously, you need to be concerned about the high rates of parsing, even though most of the parses are soft parses. The next section shows you what you can do to reduce the amount of parsing in your database.

First, we create an object type, item, as follows: benchmark@ORA10G> create or replace type item as object 2 ( 3 id number, 4 name varchar2(20), 5 description varchar2(50) 6 ) 7 / Type created. We then create a table, item_table, that contains item objects, and we insert one row into it (later, we will select this row from our JDBC program): benchmark@ORA10G> create table item_table of item; Table created. benchmark@ORA10G> insert into item_table values ( 1, 'item1', 'item1 desc' ); 1 row created. benchmark@ORA10G> commit; Commit complete.

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