Infrastructure

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Tablespace HWM

The following question appeared the Oracle-L list-server recently:

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Flashback Logging

One of the waits that is specific to ASSM (automatic segment space management) is the “enq: FB – contention” wait. You find that the “FB” enqueue has the following description and wait information when you query v$lock_type, and v$event_name:

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Flashback logging

When database flashback first appeared many years ago I commented (somewhere, but don’t ask me where) that it seemed like a very nice idea for full-scale test databases if you wanted to test the impact of changes to batch code, but I couldn’t really see it being a good idea for live production systems because of the overheads.

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255 columns

You all know that having more than 255 columns in a table is a Bad Thing ™ – and surprisingly you don’t even have to get to 255 to hit the first bad thing about wide tables. If you’ve ever wondered what sorts of problems you can have, here are a few:

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In-memory DB

A recent thread on the OTN database forum supplied some code that seemed to show that In-memory DB made no difference to performance when compared with the traditional row-store mechanism and asked why not.  (It looked as if the answer was that almost all the time for the tests was spent returning the 3M row result set to the SQL*Plus client 15 rows at a time.)

The responses on the thread led to the question:  Why would the in-memory (column-store) database be faster than simply having the (row-store) data fully cached in the buffer cache ?

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LOB Space

Following on from a recent “check the space” posting, here’s another case of the code not reporting what you thought it would, prompted by a question on the OTN database forum about a huge space discrepancy in LOBs.

There’s a fairly well-known package called dbms_space that can give you a fairly good idea of the space used by a segment stored in a tablespace that’s using automatic segment space management. But what can you think when a piece of code (written by Tom Kyte, no less) reports the following stats about your biggest LOB segment:

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Spatial space

One thing you (ought to) learn very early on in an Oracle career is that there are always cases you haven’t previously considered. It’s a feature that is frequently the downfall of “I found it on the internet” SQL.  Here’s one (heavily paraphrased) example that appeared on the OTN database forum a few days ago:

select table_name,round((blocks*8),2)||’kb’ “size” from user_tables where table_name = ‘MYTABLE';

select table_name,round((num_rows*avg_row_len/1024),2)||’kb’ “size” from user_tables where table_name = ‘MYTABLE';

The result from the first query is 704 kb,  the result from the second is 25.4 kb … fragmentation, rebuild, CTAS etc. etc.

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Just in case

For those who don’t read Oracle-l and haven’t found Nikolay Savvinov’s blog, here’s a little note pulling together a recent question on Oracle-L and a relevant (and probably unexpected) observation from the blog. The question (paraphrased) was:

The developers/data modelers are creating all the tables with varchar2(4000) as standard by default “Just in case we need it”. What do you think of this idea?

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Shrink Tablespace

If you start moving objects around to try and reclaim space in a tablespace there are all sorts of little traps that make it harder than you might hope to get the maximum benefit with the minimum effort.  I’ve written a couple of notes in the past about how to proceed and, more recently, one of the difficulties involved. This is just a brief note about a couple of ideas to make life a little easier.

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Quiz night

Prompted by an email from Yves Colin (who’ll be presenting on the Tuesday of UKOUG Tech14) I was prompted to dig out a little script I wrote some years ago and re-run an old test, leading to this simple question:  what’s the largest size array insert that Oracle will handle ?

If you’re tempted to answer, watch out – it’s not exactly a trick question, but there is a bit of a catch.

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