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<h1 class="topictitle1">Analyzing summary monitor information</h1>
<div><p>Once data has been collected in the monitor, it can be analyzed.</p>
<div class="section">You can analyze information in a summary monitory by right-clicking
the summary monitor in the right pane and selecting <span class="uicontrol">Analyze</span>.
A summary monitor must be ended or paused in order to analyze the data.</div>
<div class="section"><p>The following is an overview of the information that you can obtain
from the predefined reports.</p>
<dl><dt class="dlterm">General Summary</dt>
<dd>Contains information that summarizes all SQL activity. This information
provides the user with a high level indication of the nature of the SQL statements
used. For example, how much SQL is used in the application? Are the SQL statements
mainly short-running or long running? Is the number of results returned small
or large?</dd>
<dt class="dlterm">Job Summary</dt>
<dd>Contains a row of information for each job. Each row summarizes all SQL
activity for that job. This information can be used to tell which jobs on
the system are the heaviest users of SQL, and hence which ones are perhaps
candidates for performance tuning. The user may then want to start a separate
detailed performance monitor on an individual job to get more detailed information
without having to monitor the entire system.</dd>
<dt class="dlterm">Operation Summary</dt>
<dd>Contains a row of summary information for each type of SQL operation.
Each row summarizes all SQL activity for that type of SQL operation. This
information provides the user with a high level indication of the type of
SQL statements used. For example, are the applications mainly read-only, or
is there a large amount of update, delete, or insert activity. This information
can then be used to try specific performance tuning techniques. For example,
if a large amount of INSERT activity is occurring, perhaps using an <span class="cmdname">OVRDBF</span> command
to increase the blocking factor or perhaps use of the <span class="apiname">QDBENCWT</span> API
is appropriate.</dd>
<dt class="dlterm">Program Summary</dt>
<dd>Contains a row of information for each program that performed SQL operations.
Each row summarizes all SQL activity for that program. This information can
be used to identify which programs use the most or most expensive SQL statements.
Those programs are then potential candidates for performance tuning. Note
that a program name is only available if the SQL statements are embedded inside
a compiled program. SQL statements that are issued through ODBC, JDBC, or
OLE DB have a blank program name unless they result from a procedure, function,
or trigger.</dd>
</dl>
<p>Additionally, you can select more Detailed Results:</p>
<dl><dt class="dlterm">Basic statement information</dt>
<dd>This information provides the user with basic information about each SQL
statement. The most expensive SQL statements are presented first in the list
so at a glance the user can see which statements (if any) were long running.</dd>
<dt class="dlterm">Access plan rebuild information</dt>
<dd>Contains a row of information for each SQL statement that required the
access plan to be rebuilt. Reoptimization will occasionally be necessary for
one of several reasons such as a new index being created or dropped, the apply
of a PTF, and so on. However, excessive access plan rebuilds may indicate
a problem.</dd>
<dt class="dlterm">Optimizer information</dt>
<dd>Contains a row of optimization information for each subselect in an SQL
statement. This information provides the user with basic optimizer information
about those SQL statements that involve data manipulation (Selects, opens,
updates, and so on) The most expensive SQL statements are presented first
in the list.</dd>
<dt class="dlterm">Index create information</dt>
<dd>Contains a row of information for each SQL statement that required an
index to be created. Temporary indexes may need to be created for several
reasons such as to perform a join, to support scrollable cursors, to implement
ORDER BY or GROUP BY, and so on. The created indexes may only contain keys
for rows that satisfy the query (such indexes are known as sparse indexes).
In many cases, the index create may be perfectly normal and the most efficient
way to perform the query. However, if the number of rows is large, or if the
same index is repeatedly created, you may be able to create a permanent index
to improve performance of this query. This may be true whether an index was
advised.</dd>
<dt class="dlterm">Index used information</dt>
<dd>Contains a row of information for each permanent index that an SQL statement
used. This can be used to quickly tell if any of the permanent indexes were
used to improve the performance of a query. Permanent indexes are typically
necessary to achieve optimal query performance. This information can be used
to determine how often a permanent index was used by in the statements that
were monitored. Indexes that are never (or very rarely) used should probably
be dropped to improve the performance of inserts updates and deletes to a
table. Before dropping the index you may also want to look at the last used
date in the Description information for the index.</dd>
<dt class="dlterm">Open information</dt>
<dd>Contains a row of information for each open activity for each SQL statement.
The first time (or times) a open occurs for a specific statement in a job
is a full open. A full open creates an Open Data Path (ODP) that will be then
be used to fetch, update, delete, or insert rows. Since there will typically
be many fetch, update, delete, or insert operations for an ODP, as much processing
of the SQL statement as possible is done during the ODP creation so that same
processing does not need to be done on each subsequent I/O operation. An ODP
may be cached at close time so that if the SQL statement is run again during
the job, the ODP will be reused. Such an open is called a pseudo open and
is much less expensive than a full open. You can control the number of ODPs
that are cached in the job and then number of times the same ODP for a statement
should be created before caching it.</dd>
<dt class="dlterm">Table scan</dt>
<dd>Contains a row of information for each subselect that required records
to be processed in arrival sequence order. Table scans of large tables can
be time-consuming. If the SQL statement is long running, it may indicate that
an index might be necessary to improve performance.</dd>
<dt class="dlterm">Sort information</dt>
<dd>Contains a row of information for each sort that an SQL statement performed.
Sorts of large result sets in an SQL statement may be a time consuming operation.
In some cases, an index can be created that will eliminate the need for a
sort.</dd>
<dt class="dlterm">Temporary file information</dt>
<dd>Contains a row of information for each SQL statement that required a temporary
result. Temporary results are sometimes necessary based on the SQL statement.
If the result set inserted into a temporary result is large, you may want
to investigate why the temporary result is necessary. In some cases, the
SQL statement can be modified to eliminate the need for the temporary result.
For example, if a cursor has an attribute of INSENSITIVE, a temporary result
will be created. Eliminating the keyword INSENSITIVE will typically remove
the need for the temporary result, but your application will then see changes
as they are occur in the database tables.</dd>
<dt class="dlterm">Data conversion information</dt>
<dd>Contains a row of information for each SQL statement that required data
conversion. For example, if a result column has an attribute of INTEGER, but
the variable the result is being returned to is DECIMAL, the data must be
converted from integer to decimal. A single data conversion operation is very
inexpensive, but repeated thousands or millions of times can add up. In some
cases, it is a simple task to change one of the attributes so a faster direct
map can be performed. In other cases, the conversion is necessary because
there is no exact matching data type available.</dd>
<dt class="dlterm">Subquery information</dt>
<dd>Contains a row of subquery information. This information can indicate
which subquery in a complex SQL statement is the most expensive.</dd>
</dl>
<p>Finally, you can select the Composite view.</p>
<dl><dt class="dlterm">Summary data </dt>
<dd>Contains resource and other general information about monitored jobs. </dd>
<dt class="dlterm">Statement text </dt>
<dd>Contains the SQL text that monitored jobs call. </dd>
<dt class="dlterm">Table scan </dt>
<dd>Contains the table scan data for the monitored jobs. </dd>
<dt class="dlterm">Data sorts </dt>
<dd>Contains details of data sorts that monitored jobs perform.</dd>
<dt class="dlterm">Host variable use </dt>
<dd>Contains the values of host variables that monitored jobs use.</dd>
<dt class="dlterm">Optimizer time out/access paths considered</dt>
<dd>Contains details of any occurrences of time outs of monitored jobs.</dd>
<dt class="dlterm">Indexes used</dt>
<dd>Contains details of how indexes are used by monitored jobs. </dd>
<dt class="dlterm">Index creation</dt>
<dd>Contains details of the creation of indexes by monitored jobs.</dd>
<dt class="dlterm">Subselect processing</dt>
<dd>Contains information about each subselect in an SQL statement.</dd>
<dt class="dlterm">Temporary file use </dt>
<dd>Contains details of temporary files that monitored jobs created. </dd>
</dl>
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<div class="familylinks">
<div class="parentlink"><strong>Parent topic:</strong> <a href="rzajqnavsummon.htm" title="You can work with summary monitors from the iSeries Navigator interface. A summary monitor creates a Memory-Resident Database monitor (DBMon), found on the native interface.">Using iSeries Navigator with summary monitors</a></div>
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