OK, so KScope17 was my first KScope, don’t be petty about it. I also know that it’s been already a month, but I’ve been doing a lot and didn’t have time to write. A week after KScope we’ve been to a family vacation in Alaska, then I went to a concert in Seattle (Counting Crows and Matchbox Twenty), then some work backlog…
Once in a while I get requests for some information about reading and analyzing an AWR report. I have been thinking for a long time about writing such a post, but always postponed it as it is a very tricky topic. The AWR (or statspack for that matter) report is huge and contains so much information that it’s easy to get lost. It also requires a lot of knowledge about the database and the different mechanisms so it’s very difficult to explain all of this in a blog post (or even a series of posts). In this post I’ll try to start from the beginning, explaining a little bit about the AWR report and the analysis process and we’ll see where it takes us.
The LIKE operator is a very useful one. It is used to match strings with partial match while using the underscore (‘_’) as a single character wildcard and the percentage sign (‘%’) as multiple character wildcard.
In February ’17 I participated in Mike Dietrich’s upgrade workshop and it was great! I don’t want to repeat stuff that he said there, you can read everything on his blog. This workshop made me think about upgrades I did in the past (and I did quite a few) and important things to think about before and after upgrading a database.
One of my customers is working with ASM and their database grows really fast. So every one in a while we need to add another ASM disk to the system.