July 8, 2013
I’ve been recently working with a couple of customers who were dropping database columns from their schema on Oracle, and the drops were taking a long time to complete. In one instance, the customer estimated it would take 50 hours to drop a bunch of columns from their contact table. In another, a customer observed that dropping two columns from table_site_part took over two hours. Dropping 3 columns from table_contact took over 1 hour. These long execution times can disrupt normal operations – especially those environments with limited maintenance windows. Dovetail’s schema editing tool (Schema Editor) and Amdocs schema editing tools (ddcomp, SchemaManager) all do the same basic operations when it comes to dropping columns. Basically they all do this: ALTER TABLE table_name DROP COLUMN column_name; There’s a better way. Set Unused On large tables the process of physically…
SchemaEditor improvements when dropping columns on Oracle
July 8, 2013
I’ve been recently working with a couple of customers who were dropping database columns from their schema on Oracle, and the drops were taking a long time to complete. In one instance, the customer estimated it would take 50 hours to drop a bunch of columns from their contact table. In another, a customer observed that dropping two columns from table_site_part took over two hours. Dropping 3 columns from table_contact took over 1 hour. These long execution times can disrupt normal operations – especially those environments with limited maintenance windows. Dovetail’s schema editing tool (Schema Editor) and Amdocs schema editing tools (ddcomp, SchemaManager) all do the same basic operations when it comes to dropping columns. Basically they all do this: ALTER TABLE table_name DROP COLUMN column_name; There’s a better way. Set Unused On large tables the process of physically…
August 6, 2010
Great changes are happening with our Dovetail Seeker search product. I wanted to talk about a core change to the product. By moving our application architecture to use messaging we are seeing increased flexibility, testability and performance. Why Messaging? Based on our experience building Dovetail Carrier (pdf), our messaging oriented enterprise integration solution, we decided messaging was a great fit for Seeker’s search indexing windows service. We decomposed the indexer’s behaviors into work (message) producers and consumers. For example to keep your database in-sync with the search index we have a service which watches the database for changes to the objects Seeker is indexing. When a database item is added or updated a message is created which gets put onto a work queue. We have many message consumer threads standing by waiting for work to munch on. Our message consumers…