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Friday Philosophy – “Technical Debt” is a Poor Term. Try “Technical Burden”?

Recently my friend Sabine Heimsath asked a few of us native English speakers what the opposite of “technical debt” was. My immediate reaction was to say:

I’d say (sarcastically) “proper development” or “decent designer” or even “what we did 25 bloody years ago when we were allowed to take pride in the software we created!”

But my next comment was less reactive and more considered. And that was to say that I did not like the phrase “Technical Debt”:

A debt is when you owe something to someone, to be paid back. You do not owe anything to someone when you build poor systems, you are actually creating a “technical burden” – something those in the future will need to live with and may eventually have to sort out. Those who created the bad app or design will probably not be the ones fixing it – as in paying the debt.

Why oh Why Do We Still Not Have a Fast Bulk “SQL*Unloader” Facility?

Way back in 2004 I was working at the UK side of the Human Genome project. We were creating a massive store of DNA sequences in an Oracle database (this was one of two world-wide available stores of this information, for free & open use by anyone {* see note!}). The database was, for back then, enormous at 5-6TB. And we knew it would approx double every 12 months (and it did, it was 28TB when I had to migrate it to Oracle 10 in 2006, over 40TB 6 months later and grew to half a petabyte before it was moved to another organisation). And were contemplating storing similar massive volumes in Oracle – Protein, RNA and other sequence stores, huge numbers of cytological images (sorry, microscope slides).

Extra session at OUG Ireland – Oracle Lego.

I’m now doing a second session at OUG Ireland 2015. {This is because one of the accepted speakers had to drop out – it sometimes happens that, despite your best intentions, you can’t make the conference and it is better to let them know as soon as you can, as they did}. This will be a talk called “Oracle Lego” and it is one I put together a couple of years ago when I decided to try and do more introductory talks – talks aimed at those who are not {yet} experts and who I think tend to get ignored by most conference and user group agenda. So it is aimed at those new to oracle or experts in other areas who have never really touched on the subject.

Row Level Security 3 – In Pictures!

<..Part one intro and examples
<….Part two Permissions

I’ve noticed that there has not been a lot of traffic on this series on Row Level Security (data masking) so far – maybe due to how I am presenting the material? So here is a summary to date in picture/diagram format:

Row Level Security Part 1

I’ve been working a little on Row Level Security (RLS) recently and wanted to mention a few things, so first some groundwork.

If you want to limit the rows certain users can see, you might think to use views or you might think to use RLS (part of VPD – Virtual Private Database). You can also (from V10 I think) limit which columns users can see. An example is probably the best way to show this. I’m doing this on Oracle

I have two users, MDW and MDW_OFFSHORE. MDW has DBA-type privileges and MDW_OFFSHORE has connect, resource and one or two other simple privs. I will now demonstrate creating and populating a simple table under MDW, adding RLS to it and how it alters what MDW_OFFSHORE sees.

Exclusion of Unioned SQL in Views – Followup

Last week I put up a post about how Oracle can filter out sections of a union view..

Within the comments I put up another example where the CBO did not filter out all but one of the Union views despite my replicating the exact WHERE clause of one of the unioned statements. Jonathan Lewis posted a followup to say “Oracle can be very touchy about how it plays this game” and made a prediction of how the CBO would handle a slightly different scenario.

This was the extra scenario and I include brief details on creating the unioned view too. NB all on Oracle {non-Exadata :-) }

Dropped Tables, Hiding Extents and Slow DBA_FREE_SPACE Queries

My last post was on slow dictionary queries caused by having many, many thousands of extents in your database. This post is about a special case of this problem, which I encountered recently. It was on an Exadata box – Exadata is not particularly relevant to the issue, but I’m curious to see if mentioning Exadata will make this post more popular :-)

I was querying the used and free space on a very small database on the client’s X2-2 1/4 rack Exadata machine. The query was really slow, taking about 30 seconds. This is a FAST box, what is going on?

I quickly realised that the problem was specific to one tablespace:

Oracle Nostalgia

When preparing the material for my “Oracle Lego – an introduction to Database Design” presentation for the UKOUG last week, I was looking back at my notes from a course on the topic from “a few years back”. There were a few bits which made me smile.

Oracle’s [SQL] implementation conforms to ANSI standard, although referential integrity will not be enforced until version 7

Lack of Index and Constraint Comments

Something I’ve just reminded myself of is that under Oracle you cannot add a comment on an index or a constraint. You can only add comments on tables, views, materialized views, columns of those object types and a couple of esoteric things like Operators, Editions and Indextypes.

Here is an example of adding comments to tables and columns:

Index Organized Tables – the Basics.

IOT2 – Examples and proofs..>
IOT3 – Greatly reducing IO with IOTs….>
IOT4 – Boosting Buffer Cache Efficiency……>

I think Index Organized Tables(IOTs) are a much under-used and yet very useful feature of Oracle. Over the next few postings I’m going to cover some aspect of Index Organised Tables, both good and not-so-good. I am going to cover some benefits of IOTs that I think many people are unaware of. In this first post I am just going to run through the basics of IOTs.

The idea behind an IOT is simple. You hold all the data for the table in the ordered structure of an index. Why would you want to do that? Let us consider a very common requirement, accessing a row in a “large” table via a known, unique key.

Traditionally you have a heap table holding the data you want to access and a standard index to support access to that table. See the first diagram below. The 4-layer triangle represents the index, with a root block, two levels of branch blocks and then the leaf blocks at the “bottom”. The blue rectangle represents the table with the squares being individual rows. Of course, in a large table there would be thousands or millions of “squares”, this is just a simple diagram to show the idea.

When you issue a SQL statement to select the row via the indexed column(s) then oracle will read the root block (1), find the relevent block in the first level of branch blocks (2), then the relevant block in the second level of branch blocks (3) and finally (as far as the index is concerned) the relevant Leaf Block for the unique key. The leaf block holds the indexed column(s) and also the rowid. The rowid is the fastest way to look up a record, it states the file, block and row offset for the row. This allows oracle to go straight to the block and get the row. That is read number (5).
The number of branch blocks {and thus the number of blocks that need to be read to find a row} will vary depending on how much data is indexed, the number and size of the columns in the index, how efficiently the space has been used in the blocks and one or two other factors. In my experience most indexes for tables with thousands or millions of rows have one, two or three levels of branch blocks.

The second diagram shows a representation of the Index Organized Table. The table has in effect disappeared as a distinct object and the information has been moved into the leaf blocks of the index {part of me feels Index Organized Tables should really be called Table Organized Indexes or Table Containing Indexes as that would better indicate what is physically done}:

So with the IOT oracle reads the root block (1), the two branch level blocks (2 and 3) and finally the leaf block (4). The leaf block does not hold the rowid but rather the rest of the columns for the table {this can be changed, a more advanced feature allows you to store some or all the extra columns in an overflow segment}. Thus to access the same data, Oracle has to read only 4 blocks, not 5. Using an IOT saves one block read per unique lookup.

This saving of block reads is probably the main feature that IOTs are known for, but there are others which I will cover in later posts. Two things I will mention now is that, firstly, the use of IOTs is potentially saving disc space. An index is in effect duplication of data held in the table. When you create an index no new information is created but space is used up holding some of the table information in a structure suitable for fast lookup. Secondly, the index and table have to be maintained whenever a change is made to the columns that are indexed. IOTs reduce this maintenance overhead as there is only one thing to maintain.

Now for some drawbacks.

  • The IOT has to be indexed on the primary key. There is no option to create an IOT based on other indexes. As such you have to either be accessing the table via the primary key to get the benefit – or you have to be a little cunning.
  • The index is going to be larger than it was and very often larger than the original table. This can slow down range scans or full scans of the index and a “full table scan” will now be a full index scan on this large object, so that can also negatively impact performance. However, if a range scan would then have resulted in access to the table to get extra columns, the IOT gives a similar benefit in reducing IO to that for single row lookups.
  • I just want to highlight that you now have no rowid for the rows.
  • Secondary indexes are supported but will potentially be less efficient due to this lack of rowid.

So, a brief summary is that Index Organised Tables effectively move the table data into the Primary Key index, reduce the number of block lookups needed to select one row, can save some disc space. But you can only organize the table via the Primary Key and it can make full or partial table scans and lookups via other indexes slower.

There are several more important benefits to IOTs {in my opinion} which I will come to over the next week or two.