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Oracle database operating system memory allocation management for PGA – part 2: Oracle 11.2

This is the second part of a series of blogpost on Oracle database PGA usage. See the first part here. The first part described SGA and PGA usage, their distinction (SGA being static, PGA being variable), the problem (no limitation for PGA allocations outside of sort, hash and bitmap memory), a resolution for Oracle 12 (PGA_AGGREGATE_LIMIT), and some specifics about that (it doesn’t look like a very hard limit).

But this leaves out Oracle version 11.2. In reality, the vast majority of the database that I deal with at the time of writing is at version 11.2, and my guess is that this is not just the databases I deal with, but a general tendency. This could change in the coming time with the desupport of Oracle 11.2, however I suspect the installed base of Oracle version 12 to increase gradually and smoothly instead of in a big bang.

Line Numbers

One of the presentations I went to at the DOAG conference earlier on this month was called “PL/SQL Tuning, finding the perf. bottleneck with hierarchical profiler” by Radu Parvu from Finland. If you do a lot of PL/SQL programming and haven’t noticed the dbms_hprof package yet make sure you take a good look at it.

A peripheral question that came up at the end of the session asked about problems with line numbers in pl/sql procedures; why, when you get a run-time error, does the reported line number sometimes look wrong, and how do you find the right line. I can answer (or give at least one reason for) the first part, but not the second part; Julian Dontcheff had an answer for the second bit, but unfortunately I failed to take a note of it.

HOWTO: Create a Structured XMLIndex, using the In-Memory Column Store

In Oracle database version 12.1.0.2, Oracle introduced the Oracle In-Memory Database option. It is possible…

Audio semi-Visual Presentation on Clustering Data in Oracle

I suppose it had to happen eventually but one of my presentations has ended up on YouTube. It’s a recent presentation I did for the Oracle Midlands user group in September.

The topic is (as the title of this blog post hints at!)Boosting select performance by clustering data. The video consists of the slides I presented, changing as the presentation progresses, with my audio over the top. It goes on for a bit, close to an hour, but you could watch a section and then go and do something else before watching a bit more.

I have to say, it is very odd hearing my voice (and the slight touch of the “brummie” {Birmingham} accent coming through) and I do wince at the places where I blather or say something slightly wrong or make a joke that involved a visual element that is lost. Oh well, at least you don’t see me wandering around and jumping up,literally, to point out bits on the slides.

HPC versus HDFS: Scientific versus Social

There have been rumblings from the HPC community indicating a general suspicion of and disdain for Big Data technology which would lead one to believe that whatever Google, Facebook and Twitter do with their supercomputers is not important enough to warrant seriousness—that social supercomputing is simply not worthy.  A little of this emotion seems to […]

Oracle OpenWorld 2014 – Datatype context…?!

The native JSON database functionality presentations are done. If you want to experience first hand…

Oracle OpenWorld 2014 – In the middle of it…

It’s funny this might be one of the first time in years that my strange…

Oracle IO wait events: db file sequential read

(the details are investigated and specific to Oracle’s database implementation on Linux x86_64)

Exadata IO: This event is not used with Exadata storage, ‘cell single block physical read’ is used instead.
Parameters:
p1: file#
p2: block#
p3: blocks

Despite p3 listing the number of blocks, I haven’t seen a db file sequential read event that read more than one block ever. Of course this could change in a newer release.

In-memory Aggregation

The title of this piece is the name given to a new feature in 12.1.0.2, and since I’ve recently blogged about a limitation of the in-memory option I thought I’d pick this feature as the next obvious thing to blog about. This is a bit of a non sequitur, though, as the feature seems to have nothing whatsoever to do with the in-memory option; instead it’s a cunning mechanism combining aspects of the star-transformation (but without the bitmap indexes), Bloom filters, and “group-by” placement to minimise the cost of aggregation over high-volume joins.

Here’s a small data set I’ll use to demonstrate the feature: