I wanted to go to Hotsos Symposium for quite some time, having heard so many great topics from there for years. And every time I was a bit lazy to think about what I can talk about. Apparently I thought that everything I know is well covered elsewhere, so why would I be accepted. Plus all these complexities of budget, getting a visa, travel arrangements, jet lag, and personal matters in between. Last year, when call for papers was still open, I realized that there’s a good chance I can make it to Hotsos in 2016: I had a budget, visa is a doable thing, and most importantly I knew I had a topic to talk about which most likely will not be in competition with other speakers.
In this last overview post I will give you a first glance of the Oracle…
In this post I will give you a first glance of a demo environment of…
A while ago I created a first post about the Oracle Management Cloud ( #OMC…
There are some questions about Oracle that are like the mythical Hydra – you think you’ve killed it, but for every head you cut off another two grow. The claim that “the optimizer will switch between using an index and doing a tablescan when you access more than X% of the data” re-appeared on the OTN database forum a little while ago – it doesn’t really matter what the specific value of X was – and it’s a statement that needs to be refuted very firmly because it’s more likely to cause problems than it is to help anyone understand what’s going on.
Can you spot anything that might appear to be a little surprising about this (continuous) extract from a trace file ? The example is from 10.2.0.5, but 11g and 12c could produce similar results (or direct path read equivalents):
Oracle Management Cloud is a new Oracle Cloud offering launched during Oracle Open World 2015,…
As a picture is worth a thousand words, we may want to visualise the oracle performance metrics. There is already several tools to do so, but what if you could do it the way you want? build your own graph? Let’s try to achieve this with 3 layers:
Let’s install InfluxDB and grafana that way (for example on the same host, namely influxgraf):
I received an email a couple of days ago that was a little different from usual – although the obvious answer was “it’s the data”. A connect by query with any one of several hundred input values ran in just a few seconds, but with one specific input it was still running 4,000 seconds later using the same execution plan – was this a bug ?
There’s nothing to suggest that it should be, with skewed data anything can happen: even a single table access by exact index could take 1/100th of a second to return a result if there was only one row matching the requirement and 1,000 seconds if there were 100,000 rows in 100,000 different table blocks (and the table was VERY big). The same scaling problem could be true of any type of query – and “connect by” queries can expose you to a massive impact because their run time can increase geometrically as the recursion takes place.
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