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IDS 14.10 contains this important new feature:
"Partial indexes avoid indexing common values. As the query searching for a common value wil...
Increase supported ADMIN_MODE_USERS by moving list from onconfig to table
Parameter ADMIN_MODE_USERS handy during migrations. the ability to make the database available for a subset of users is great for post migration validation. However the length of the field (127 bytes) is a limitation that ends up being somewhat mi...
Allow triggers install/updates without taking an outage for the box
Currently to install new triggers on a table or update triggers on a table requires outage for the box which impacts our end user customer. Our operations are 24X7X365 and don't have any outage window to work with.
HammerDB is a leading benchmarking tool to benchmark database performance. This tool enables DBA to verify configuration of the OS/database and assess the impact of any hardware or database configuration changes.
HammerDB supports DB2 however ...
Config for the server to refuse to start if shared memory segments do not use huge pages.
When shared memory segments are not using huge pages there can be performance impact I would like an option for the engine to abort startup similar to FULL_DISK_INIT=0 if huge pages cannot be used for shared memory segments. Scenario: sysmaster sy...
use raw table to bulk load/huge files in Informix cluster
raw table load and copy of raw table data availability read only secondary, RSS sec. in a HDR cluster. A big one for us. How do we load billion + row table in a HDR cluster without consuming too many logical logs? Is there a way to load a raw tabl...
Since Lock resource (memory) would be automatically allocated when Informix engine defect that it's not enough. But these memory will be existing forever once allocate, unless restart Informix engine. Could these automatically allocated memory cou...
Just recently while working on a customer we were able to speedup a very slow query by using the recently introduced OLAP functions. The query looks like this: SELECT col1, col2, col3, col4, rank() over (partition by col1, col2 order by col4 desc)...
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