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opatch investigations

This blogpost is about opatch and how to obtain information about the current oracle home(s), and how to obtain information about the patches to be applied.

Patches that can be applied using opatch are provided by oracle as zip files which have the following naming convention:
p[patchnumber]_[baseversion]_[platform]-[architecture].zip. The patch normally contains an XML file called ‘PatchSearch.xml’ and a directory with the patch number. Inside the patch number directory there is a README.txt which is lame, because it says ‘Refer to README.html’, and a README.html that contains the readme information that is also visible when the [README] button for this patch is selected in MOS.

Index Splits – 3

This is stored only for reference, and in case anyone wants to wade through the details. It’s the redo log dump from the 90/10 index leaf block split test from the previous blog posts running on on Linux. The first part is the full block dump, the second part is an extract of the Record and Change vector headings with the embedded opcode (opc:) for the undo records in the redo vectors, and a tiny note of what each change vector is doing.

opatch versions

This blogpost is about oracle’s patching tool for the database and grid infrastructure: opatch. I personally have a love/hate relationship with opatch. In essence, opatch automates a lot of things that would be very error prone if it were to be done by hand, which is a good thing. However, there are a lot of things surrounding opatch that I despise. An example of that is the version numbering of opatch itself.

Versions and more versions

To jump into the matter directly: versions. I don’t understand why this has to be this complicated. I would even go as far as saying that somebody needs to step in and clean this up.

Oracle LIKE predicate and cardinality estimations

A new blog post on the Databases at CERN blog about the optimizer estimations with a LIKE predicate:

Or why the cardinality estimation here is 1346 objects like ‘DBA_OBJECTS’ rather than 2:

Where / Having

There’s a very old mantra about the use of the “having” clause that tells us that if it’s valid (i.e. will always give the same results) then any predicate that could be moved from the having clause to the where clause should be moved. In recent versions of Oracle the optimizer will do this for itself in some cases but (for reasons that I’m not going to mention) I came across a silly example recently where a little manual editing produced a massive performance improvement.

Here’s a quick demo:

Join Cardinality – 5

So far in this series I’ve written about the way that the optimizer estimates cardinality for an equijoin where one end of the join has a frequency histogram and the other end has a histogram of type:

Index Splits – 2

In yesterday’s article I described the mechanism that Oracle for an index leaf block split when you try to insert a new entry into a leaf block that is already full, and I demonstrated that the “50-50” split and the “90-10” split work in the same way, namely:

Index splits

After writing this note I came to the conclusion that it will be of no practical benefit to anyone …  but I’m publishing it anyway because it’s just an interesting little observation about the thought processes of some Oracle designer/developer. (Or maybe it’s an indication of how it’s sensible to re-use existing code rather than coding for a particular boundary case, or maybe it’s an example of how to take advantage of “dead time” to add a little icing to the cake when the extra time required might not get noticed). Anyway, the topic came up in a recent thread on the OTN/ODC database forum and since the description given there wasn’t quite right I thought I’d write up a correction and a few extra notes.

What’s new in Oracle Database 19c and other #OOW18 feedback

Back from Oracle Open World #OOW18 and here are quick notes I’ve taken about what’s new. I focus on what was publicly announced, but with the ‘Safe Harbor’ statement: all this can be true, wrong or different (three-valued logic;) when 19c will be in General Availability. Rushing to publish those notes before entering the beta program as it will be hard to remember what was public or not.

Disclaimer: this was written before getting details on 19c, from content under ‘safe harbor statement’. This does not describe what will be actually implemented when 19c will be in general availability.

Upgrades – again

I’ve got a data set which I’ve recreated in and

I’ve generated stats on the data set, and the stats are identical.

I don’t have any indexes or extended stats, or SQL Plan directives or SQL Plan Profiles, or SQL Plan Baselines, or SQL Patches to worry about.

I’m joining two tables, and the join column on one table has a frequency histogram while the join column on the other table has a height-balanced histogram.  The histograms were created with estimate_percent => 100%. (which explains why I’ve got a height-balanced histogram in 12c rather than a hybrid histogram.)

Here are the two execution plans, first, pulled from memory by dbms_xplan.display_cursor():