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12c

In-memory limitation

I’ve been struggling to find time to have any interaction with the Oracle community for the last couple of months – partly due to workload, partly due to family matters and (okay, I’ll admit it) I really did have a few days’ holiday this month. So making my comeback with a bang – here’s a quick comment about the 12.1.0.2 in-memory feature, and how it didn’t quite live up to my expectation; but it’s also a comment about assumptions, tests, and inventiveness.

Exadata Zone Maps

Just a quick post on a new Exadata feature called Zone Maps. They’re similar to storage indexes on Exadata, but with more control (you can define the columns and how the data is refreshed for example). People have complained for years that storage indexes provided no control mechanisms, but now we have a way to exert our God given rights as DBA’s to control yet another aspect of the database. Here’s a link to the 12.1.0.2 documentation which resides in the Data Warehousing Guide: Zone Map Documentation

Zone Maps are restricted to Exadata storage by the way (well probably they work on ZFS and Pillar too). Have a look at the Oracle error messages file:

To PDB or not to PDB : The final decision

After yesterday’s to PDB or not to PDB post, I decided the answer was “to PDB”. Here’s what I did…

To PDB or not to PDB

I’m about to start a Proof of Concept (POC) for a 12c upgrade of one of our databases. The production database in question is running on Oracle Linux inside a VMware virtual machine, so the starting point I’ve been given for the POC is a clone of the whole VM…

Probably the biggest decision I’ve got to make is “to PDB or not to PDB” *. I mentioned it on Twitter earlier and got some conflicting opinions. I guess the pros and cons of the PDB approach go something like this in my head.

Pros:

Analogy – 2

I suggested a little while ago that thinking about the new in-memory columnar store as a variation on the principle of bitmap indexes was quite a good idea. I’ve had a couple of emails since then asking me to expand on the idea because “it’s wrong” – I will follow that one up as soon as I can, but in the meantime here’s another angle for connecting old technology with new technology:

Visualizing AWR data using python

In my earlier post, I talked about, how tableau can be used to visualize the data. In some cases, I find it useful to query AWR base tables directly using Python and graph it using matplotlib package quickly. Since python is preinstalled in almost all computers, I think, this method will be useful for almost everyone. Of course, you may not have all necessary packages installed in your computer, you can install the packages using install python packages . Of course, if you improve the script, please send it to me, I will share it in this blog entry.

Script is available as a zip file: plotdb.py

Usage:

inmemory area is another sub-heap of the top-level SGA heap

I blogged earlier about heap dump shared pool heap duration and was curious to see how the inmemory – 12.1.0.2 new feature – is implemented. This is a short blog entry to discuss the inmemory area heap.

Parameters

I have set the initialization parameters sga_target=32G and inmemory_size=16G, meaning, out of 32GB SGA, 16GB will be allocated to inmemory area and the remaining 16GB will be allocated to the traditional areas such as buffer_cache, shared_pool etc. I was expecting v$sgastat view to show the memory allocated for inmemory area, unfortunately, there are no rows marked for inmemory area (Command “show sga” shows the inmemory area though). However, dumping heapdump at level 2 shows that the inmemory area is defined as a sub-heap of the top level SGA heap. Following are the commands to take an heap dump.

EM Cloud Control 12c : The 24 Hour DBA

I think I’ve lived through all the ages of Enterprise Manager. I used the Java console version back in the days when admitting you used it got you excommunicated from the church of DBA. I lived through the difficult birth of the web-based Grid Control. I’ve been there since the start of Cloud Control. I’ll no doubt be there when it is renamed to Big Data Cloud Pixie Dust Manager (As A Service).

I was walking from the pool to work this morning, checking my emails on my phone and it struck me (not for the first time) that I’m pretty much a 24 hour DBA these days. I’m not paid to be on call, I’m just a 9-5 guy, but all my Cloud Control notifications come through to my phone and tablet. I know when backups have completed (or failed). I know when a Tnsping takes too long. I know when we have storage issues. I know all this because Cloud Control tells me.

Analogy

So 12.1.0.2 is out with a number of interesting new features, of which the most noisily touted is the “in-memory columnar storage” feature. As ever the key to making best use of a feature is to have an intuitive grasp of what it gives you, and it’s often the case that a good analogy helps you reach that level of understanding; so here’s the first thought I had about the feature during one of the briefing days run by Maria Colgan.

“In-memory columnar storage gives you bitmap indexes on OLTP systems without the usual disastrous locking side effects.”

12.1.0.2 Released With Cool Indexing Features (Short Memory)

Oracle Database 12.1.0.2 has finally been released and it has a number of really exciting goodies from an indexing perspective which include: Database In-Memory Option, which enables specific portions of the database to be in dual format, in both the existing row based format and additionally into an efficient memory only columnar based format. This in […]