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You can then trace each file back to the process that created it. If the operating system retains multiple versions of files, then ensure that the version limit is high enough to accommodate the number of trace files you expect the SQL Trace facility to generate. The generated trace files can be owned by an operating system user other than yourself. Enable the SQL Trace facility for the session by using one of the following:. The SQL Trace facility is automatically disabled for the session when the application disconnects from Oracle.
After the instance has been restarted with the updated initialization parameter file, SQL Trace is enabled for the instance and statistics are collected for all sessions. Concatenate the trace files, and then run TKPROF on the result to produce a formatted output file for the entire instance. Run the trcsess command-line utility to consolidate tracing information from several trace files, then run TKPROF on the result.
The input and output files are the only required arguments. Specifies the input file, a trace file containing statistics produced by the SQL Trace facility. This file can be either a trace file produced for a single session, or a file produced by concatenating individual trace files from multiple sessions. Specifies whether to record summary for any wait events found in the trace file. The default is YES. Sorts traced SQL statements in descending order of specified sort option before listing them into the output file.
If multiple options are specified, then the output is sorted in descending order by the sum of the values specified in the sort options. Sort options are listed as follows:. Lists only the first integer sorted SQL statements from the output file. This parameter does not affect the optional SQL script.
Creates a SQL script that stores the trace file statistics in the database. This script creates a table and inserts a row of statistics for each traced SQL statement into the table. Specifies the schema and name of the table into which TKPROF temporarily places execution plans before writing them to the output file.
These individuals can specify different TABLE values and avoid destructively interfering with each other's processing on the temporary plan table. Determines the execution plan for each SQL statement in the trace file and writes these execution plans to the output file. You can use this script to replay the user events from the trace file. This example is likely to be longer than a single line on the screen, and you might need to use continuation characters, depending on the operating system.
You can use this to get access paths and row source counts. In this way, you can ignore internal Oracle Database statements such as temporary table operations. For greatest efficiency, always use SORT parameters. While TKPROF provides a very useful analysis, the most accurate measure of efficiency is the actual performance of the application in question.
At the end of the TKPROF output is a summary of the work done in the database engine by the process during the period that the trace was running. Each row corresponds to one of three steps of SQL statement processing. Statistics are identified by the value of the CALL column. Translates the SQL statement into an execution plan, including checks for proper security authorization and checks for the existence of tables, columns, and other referenced objects.
Actual execution of the statement by Oracle. Retrieves rows returned by a query. The other columns of the SQL Trace facility output are combined statistics for all parses, all executes, and all fetches of a statement.
Total CPU time in seconds for all parse, execute, or fetch calls for the statement. Total elapsed time in seconds for all parse, execute, or fetch calls for the statement. Total number of data blocks physically read from the data files on disk for all parse, execute, or fetch calls.
Total number of buffers retrieved in consistent mode for all parse, execute, or fetch calls. Usually, buffers are retrieved in consistent mode for queries. Total number of buffers retrieved in current mode. Statistics about the processed rows appear in the ROWS column. Total number of rows processed by the SQL statement. This total does not include rows processed by subqueries of the SQL statement. Row source operations provide the number of rows processed for each operation executed on the rows and additional row source information, such as physical reads and writes.
The following is a sample:. To ensure that wait events information is written to the trace file for the session, run the following SQL statement:. Timing statistics have a resolution of one hundredth of a second; therefore, any operation on a cursor that takes a hundredth of a second or less might not be timed accurately. Keep this in mind when interpreting statistics. In particular, be careful when interpreting the results from simple queries that execute very quickly. Sometimes, to execute a SQL statement issued by a user, Oracle Database must issue additional statements.
Such statements are called recursive calls or recursive SQL statements. For example, if you insert a row into a table that does not have enough space to hold that row, then Oracle Database makes recursive calls to allocate the space dynamically. Recursive calls are also generated when data dictionary information is not available in the data dictionary cache and must be retrieved from disk.
You can suppress the listing of Oracle Database internal recursive calls for example, space management in the output file by setting the SYS command-line parameter to NO. The statistics for a recursive SQL statement are included in the listing for that statement, not in the listing for the SQL statement that caused the recursive call.
So, when you are calculating the total resources required to process a SQL statement, consider the statistics for that statement and those for recursive calls caused by that statement. These statistics appear on separate lines following the tabular statistics. The key is the number of block visits, both query that is, subject to read consistency and current that is, not subject to read consistency. Segment headers and blocks that are going to be updated are acquired in current mode, but all query and subquery processing requests the data in query mode.
You can find high disk activity in the disk column. If it is acceptable to have 7. You can also see that 10 unnecessary parse call were made because there were 11 parse calls for this one statement and that array fetch operations were performed. You know this because more rows were fetched than there were fetches performed.
You might want to keep a history of the statistics generated by the SQL Trace facility for an application, and compare them over time. This script contains:. The script then inserts the new rows into the existing table. Most output table columns correspond directly to the statistics that appear in the formatted output file. The columns in Table help you identify a row of statistics. This is the date and time when the row was inserted into the table. This value is not exactly the same as the time the statistics were collected by the SQL Trace facility.
This indicates the level of recursion at which the SQL statement was issued. For example, a value of 0 indicates that a user issued the statement. A value of 1 indicates that Oracle Database generated the statement as a recursive call to process a statement with a value of 0 a statement issued by a user. A value of n indicates that Oracle Database generated the statement as a recursive call to process a statement with a value of n This identifies the user issuing the statement.
This value also appears in the formatted output file. Oracle database uses this column value to keep track of the cursor to which each SQL statement was assigned. The output table does not store the statement's execution plan.
The following query returns the statistics from the output table. If you are not aware of the values being bound at run time, then it is possible to fall into the argument trap.
If the bind variable is actually a number or a date, then TKPROF can cause implicit data conversions, which can cause inefficient plans to be executed. To avoid this situation, experiment with different data types in the query.
The next example illustrates the read consistency trap. Without knowing that an uncommitted transaction had made a series of updates to the NAME column, it is very difficult to see why so many block visits would be incurred. Cases like this are not normally repeatable: if the process were run again, it is unlikely that another transaction would interact with it in the same way.
This example shows an extreme and thus easily detected example of the schema trap. At first, it is difficult to see why such an apparently straightforward indexed query needs to look at so many database blocks, or why it should access any blocks at all in current mode. Two statistics suggest that the query might have been executed with a full table scan.
These statistics are the current mode block visits, plus the number of rows originating from the Table Access row source in the execution plan. The explanation is that the required index was built after the trace file had been produced, but before TKPROF had been run. One of the marked features of this correct version is that the parse call took 10 milliseconds of CPU time and 20 milliseconds of elapsed time, but the query apparently took no time at all to execute and perform the fetch.
These anomalies arise because the clock tick of 10 milliseconds is too long relative to the time taken to execute and fetch the data. In such cases, it is important to get lots of executions of the statements, so that you have statistically valid numbers. Sometimes, as in the following example, you might wonder why a particular query has taken so long.
Again, the answer is interference from another transaction. It takes a fair amount of experience to diagnose that interference effects are occurring. On the one hand, comparative data is essential when the interference is contributing only a short delay or a small increase in block visits in the previous example. However, if the interference contributes only modest overhead, and if the statement is essentially efficient, then its statistics may not require analysis.
Portions have been edited out for the sake of brevity. Skip Headers. HR Service - specifies a group of applications with common attributes, service level thresholds, and priorities; or a single application, such as ACCTG for an accounting application Module - specifies a functional block, such as Accounts Receivable or General Ledger, of an application Action - specifies an action, such as an INSERT or UPDATE operation, in a module Session - specifies a session based on a given database session identifier SID , on the local instance Instance - specifies a given instance based on the instance name After tracing information is written to files, you can consolidate this information with the trcsess utility and diagnose it with an analysis utility such as TKPROF.
You can gather statistics by the following criteria: Statistic Gathering for Client Identifier Statistic Gathering for Service, Module, and Action The default level is the session-level statistics gathering. OE' ; In the example, OE. OE' ;. You can enable tracing for specific diagnosis and workload management by the following criteria: Tracing for Client Identifier Tracing for Service, Module, and Action Tracing for Session Tracing for Entire Instance or Database With the criteria that you provide, specific trace information is captured in a set of trace files and combined into a single output trace file.
Interpret the output file created in Step 3. Optionally, run the SQL script produced in Step 3 to store the statistics in the database. The following sections discuss each step in depth.
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