One of the optimizer enhancements that appeared in 12.2 for SQL is the “band join”. that makes certain types of merge join much more efficient. Consider the following query (I’ll supply the SQL to create the demonstration at the end of the posting) which joins two tables of 10,000 rows each using a “between” predicate on a column which (just to make it easy to understand the size of the result set) happens to be unique with sequential values though there’s no index or constraint in place:
I ran across an article from 2013 from Straight Talk on Agile Development by Alex Kuznetsov and it reminded me how long we’ve been battling for easier ways of doing agile in a RDBMS environments.
For general SLOB information, please visit: https://kevinclosson.net/slob.
This is just a quick blog entry to showcase a few of the publications from IT vendors showcasing SLOB. SLOB allows performance engineers to speak in short sentences. As I’ve pointed out before, SLOB is not used to test how well Oracle handles transaction. If you are worried that Oracle cannot handle transactions then you have bigger problems than what can be tested with SLOB. SLOB is how you test whether–or how well–a platform can satisfy SQL-driven database physical I/O.
There’s a thread running on OTN at present about deleting huge volumes of duplicated data from a table (to reduce it from 1.1 billion to about 22 million rows). The thread isn’t what I’m going to talk about, though, other than quoting some numbers from it to explain what this post is about.
There are more configurations for AWS than there are fish in the sea, but as the rush of folks arrive to test out the incredibly cool AWS Trial for Delphix, I’ll add my rendition of what to look for to know you’re AWS setup is prepped to successfully deploy.
I’ve been at Delphix for just over six months now. In that time, I was working with a number of great people on a number of initiatives surrounding competitive, the company roadmap and some new initiatives.
I’ve written a couple of articles in the past about the problems of ASSM spending a lot of time trying to find blocks with usable free space. Without doing a bit of rocket science with some x$ objects, or O/S tracing for the relevant calls, or enabling a couple of nasty events, it’s not easy proving that ASSM might be a significant factor in a performance problem – until you get to 12c Release 2 where a staggering number of related statistics appear in v$sysstat.
I’ve published the full list of statistics (without explanation) at the end of this note, but here’s just a short extract showing the changes in my session’s ASSM stats due to a little PL/SQL loop inserting 10,000 rows, one row at a time into an empty table with a single index:
I don’t know how I missed it but Randolf Geist has been doing writing a series of posts on the performance of Oracle’s DBaaS offering, using a series of long-running tests to capture not only raw performance figures but also an indication of consistency. You can find all of these tests with a search URL on his blog, but I’ve also created a little index here to make it easier for me to access them in order.
I wrote a short series a little while ago about some of the nasty things that can happen (and can’t really be avoided) with Basicfile LOBs and recently realised that it needed a directory entry so that I didn’t have to supply 6 URLs if I wanted to point someone to it; so here’s the catalogue:
This blog post is about two things: one how you can monitor who is bringing you database up and down (there is a twist at the end!) and two how you can very conveniently do that with aggregated logs in a browser with a tool called ‘Kibana’, which is the K in ELK.