Analyze the optimization exceptions that were detected
for HISAM databases. For SHISAM databases, no optimization exceptions
are issued.
Before you begin
Ensure that you can access the Sensor Data
Statistics report that contains the latest sensor data. If you cannot
access this report, run the FF DB Sensor Printing utility to generate
the report.
About this task
In the following procedure, you will analyze
each optimization exception that you received for HISAM and SHISAM
databases.
For each exception that was reported,
you will first identify the relevant data elements to understand the
condition of the database. Then you will analyze the relevant IMS Tools reports to learn more about
the database state. Finally, if you use Management Console
or Administration Console and if
relevant sensor data charts are available, you will analyze historical
trends of sensor data to understand the trend characteristics of the
sensor data that was obtained from the database.
By completing
these steps, you will determine the possible causes of the optimization
exceptions. The causes can be the that LRECL size of the primary data
set, the CI size of the overflow data set for HISAM, or both do not
match the length of database records or segments.
Procedure
Follow the instructions to analyze the AVERAGE_DB_RECORD_LENGTH exception.
- Exception class name: AVERAGE_DB_RECORD_LENGTH
- This exception indicates that the average database record length has exceeded the threshold
value.
- The average record length can be used to determine the logical record length of the primary data
set of HISAM databases.
- A HISAM database is considered to be in its optimal state when root segments and dependent
segments that belong to the same database record exist in the same logical record. However, when IMS applications add dependent segments, and if the space in the
logical records is insufficient to store dependent segments, the dependent segments will be stored
in a logical record in the overflow data set.
- If the length of a database record is longer than the logical record length (KSDS LRECL), the
database record is divided and stored in the primary data set and the overflow data set, which
results in increased I/O operations.
- Optimizing HISAM databases typically includes tuning the logical record length and the CI size
of the primary database data set to decrease the number of segments in the overflow data set.
- Complete these steps to analyze this exception:
- Locate the following data elements in the Sensor Data Statistics report:
- DB_AVG_DBREC_LENGTH
- The value for this data element indicates the average length of database records.
- DB_NUM_ROOT
- The value for this data element indicates the number of root segments (that is, the number of
database records).
- DB_NUM_SEG
- The value for this data element indicates the number of segments in a data set.
- By comparing the numbers of segments in the primary data set and in the overflow data set, you
can determine the ratio of segments that exist in the overflow.
- DB_BLOCK_SIZE
- DB_LRECL_SIZE
- The values for these data elements indicate the CI size and logical record length of data set.
- By comparing the CI size and the logical record length of the primary data set with the average
database length, you can determine if the CI size and the logical record length of the primary data
set are long enough.
- DB_ESTIMATED_DBREC_IO
- The value for this data element indicates the estimated number of I/O operations that are
required to read a database record (that is, the average number of reading CIs to read the root
segment and all dependent segments by tracking the hierarchical path). This value is used later in
optimization tuning.
Note: The value is an estimated value; the actual I/O count might be
different.
When this value is small, most of the segments that belong to the same database
record are in the same CI. Even if the average length of database records is long, you do not
necessarily need to resolve this exception. If this value is large, consider taking actions to
resolve this exception.
- Optional: To obtain more information about the segment distribution, run the HD Pointer Checker
utility of IMS HP Pointer Checker, or IMS HP Image Copy with the HDPC=YES option, and generate the HISAM Data Set
Statistics report.
By analyzing this report, you can determine the number of occurrences for each
segment type in the primary and the overflow data sets.
- Optional: To view the trend of data over time, locate the
following charts in Management Console
or Administration Console:
- Average Database Record Length chart
- Number of Database Records chart
Understanding the trend over time can help you anticipate
the future behavior of the data sets. Use this knowledge to determine
when you might need to take preventative action and to establish efficient
maintenance plans.
- You have now obtained information about the current database state that caused this exception.
You will use this information later to determine the appropriate action to resolve the exception.
- In Step c, you also identified the
sensor data chart that can help you establish maintenance plans to prevent this exceptional state
from occurring in the future.
What to do next
If you received other exceptions that belong to other
exception categories, see the following topics to determine your next
step:
If the only exceptions that you received are optimization
exceptions, continue with Resolving optimization exceptions for HISAM and SHISAM databases.