You can optimize the number of retrieved results entries
of your saved searches, and you can optimize your process searches
by using the saved search acceleration tools.
Optimize the number of loaded search result entries
You
can optimize the number of retrieved results entries of your saved
searches.
The saved searches are optimized to process 500 result
entries. The displayed pages of the result contain up to 500 entries,
which are retrieved from the server. In addition, the total number
of entries is displayed.
If you expect more
than 500 records for a call, for example, if you are using the TWSearch
function or the saved search in an API format, you can increase this
number.
To retrieve a different number of entries, complete
the following steps:
- Insert the following section into the 100custom.xml file:
<properties>
<server merge="mergeChildren">
<process-search-engine-count-optimization merge="replace">500</process-search-engine-count-optimization>
</server>
</properties>
- Adjust the 500 value to meet your needs. The larger the value,
the more memory and time is needed to retrieve the entries.
- After saving changes to the 100custom.xml file,
restart the server.
Optimize saved searches with business data variables
You
can optimize your process searches by using the saved search acceleration
tools.
For systems that have a large amount of business data
and are used in searches (for example 10+) the Process Portal tasks
and instance queries might operate slower than expected. When you
use the save search acceleration tools to optimize your process searches,
Process Portal searches that constrain on business data are faster.
Tip: You optimize a process search only on runtime
or production systems. It is suggested that you do not optimize process
searches on systems that are used for development, or for systems
where changes happen frequently to deployed applications.
You
use the following two search acceleration tools to optimize a process
search:
- SchemaGenerator tool - This tool generates two new tables: LSW_BPD_INSTANCE_VAR_NAMES
(variables table), and LSW_BPD_INSTANCE_VARS_PIVOT (pivot table) .
It also generates the schema for each table.
- DataLoad tool - This tool populates the variables table data from
the BPD instances that are currently in progress.
- The pivot and variables tables
The pivot and variables tables ensure that your query runs
efficiently once your process search has been optimized. The tables
present data in the following format, with each item in its own column:
- The pivot table
- Instance ID
- Every searchable business data variable defined in all currently
deployed BPDs
- Every business data variable defined in LSW_BPD_INSTANCE_VARIABLES
- The variables table
- Variable name
- Column name
- Data type
- Process search optimization overview
A process search optimization can consist of three unique process
- Enabling an optimization
- Disabling an optimization
- Re-enabling an optimization
To enable process search optimization, you must run the
optimization tools:
To disable optimization, complete the following steps:
- Shut down the server
- Remove the pivot and variables tables from your database.
- Restart the server.
To re-enable optimization, complete the following steps:
- Deploy all BPD updates.
- Stop the server.
- Remove the pivot and variables tables from your database.
- Rerun the SchemaGenerator and DataLoad tools.
- Restart the server.
- System requirements and restrictions
The following requirements and restrictions apply:
The following restrictions apply to a DB2 database.
- The pivot table copies of all string values are truncated if they
exceed 128 bytes. This affects only Inbox queries.
- The sizes of all unique business data variables, when added together,
must be less than 32767 bytes. This means if all your business data
variables were strings, you would be limited to 255. This restriction
is on all unique business data variables defined across all of your
deployed BPDs. For example, if you had three BPDs deployed that each
had six business data variables, but one of them was defined in exactly
the same way in all three BPDs, then you would have a total of 16
unique business data variables.