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CLIENT_RESULT_CACHE_LAG: Determines the Client Query Result Cache lag time. A low value means more round-trips to the database from the OCI client library. Set this parameter to a low value if your application accesses the database infrequently. An optional client configuration file overrides any client caching configuration parameters you set. You can set the client-side configuration parameters in the sqlnet.ora file on the client. You can set the following client-side configuration parameters: OCI_RESULT_CACHE_MAX_SIZE: Specifies the maximum size of the query cache for a single process OCI_RESULT_CACHE_MAX_RSET_SIZE: Enables you to specify the maximum size of a single result in bytes for a process OCI_RESULT_CACHE_MAX_RST_ROWS: Sets the maximum size of a query result in rows for a single process You can also insert the RESULT_CACHE and NO_RESULT_CACHE hints in OCI applications. Use the CLIENT_RESULT_CACHE view to see the settings of the result cache and the usage statistics for the Client Query Result Cache.

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You can t cache queries that use the following types of objects, even though you may be able to cache them in a server-side result cache: Views Remote objects Complex types in the select list Flashback queries Queries that include PL/SQL functions Queries that reference VPD policies on the tables

Whether you use manual methods such as EXPLAIN PLAN, SQL Trace, and TKPROF, or more sophisticated methods such as the SQL Tuning Advisor, you need to understand that optimizing SQL statements can improve performance significantly. In the following sections, I summarize a simple methodology you can follow to tune your SQL statements.

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In many cases, the interrogator makes a polling pass over all the respondents and then goes on to do other things The interrogator only polls again when some condition applies, such as the passage of a certain amount of time or the detection of an event Polling requires a certain amount of faith in the respondents If a respondent hangs for any reason, by crashing or waiting for results from another process, it might hang the entire polling loop In the simplest round-robin polling scheme, the polling sequence is fixed Consider a scenario in which multiple respondents have new data simultaneously If one respondent has a greater chance of having new information, or if its information is more important than that of other respondents, the interrogator might need to poll that respondent more frequently than the others or poll the respondents in a certain order.

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This chapter has shown you many ways you can identify your slow-running or most resource-intensive SQL statements. For instance, you can use dynamic performance views such as V$SQL to find out your worst SQL statements, as shown earlier. Statements with high buffer gets are the CPU-intensive statements and those with high disk reads are the high I/O statements. Alternatively, you can rely on the AWR report and the ADDM analysis to figure out which of your SQL statements need to be written more efficiently. Obviously, you want to start (and maybe end) with tuning these problem statements.

The next step is to locate the inefficiency in the SQL statements. To do this, you need to collect information on how the optimizer is executing the statement. That is, you must first walk through the EXPLAIN PLAN for the statement. This step helps you find out if there are any obvious problems, such as full table scans due to missing indexes. In addition to analyzing the EXPLAIN PLAN output or using the V$SQL_PLAN view, collect the performance information, if you can, by using the SQL Trace and TKPROF utilities. Review each EXPLAIN PLAN carefully to see that the access and join methods and the join order are optimal. Specifically, check the plans with the following questions in mind: Are there any inefficient full table scans Are there any unselective range scans Are the indexes appropriate for your queries Are the indexes selective enough If there are indexes, are all of them being used Are there any later filter operations Does the driving table in the join have the best filter Are you using the right join method and the right join order Do your SQL statements follow basic guidelines for writing good SQL statements (see the section Writing Efficient SQL in this chapter) In most cases, a structured analysis of the query will reveal the source of the inefficiency.

Because the interrogator is in control, it can decide when and how often to check respondents and in what order A complication may arise if the respondents have dynamically changing priorities or highly variable traffic patterns, in which cases push interactions are often more suitable..

Use the Database Control s SQL Access Advisor to get index and materialized view recommendations. Review the access path for the tables in the statement and the join order. Consider the use of hints to force the optimizer to use a better execution plan. You can also use the SQL Tuning Advisor to get recommendations for more efficient SQL statements.

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