Here’s one of those little details that I might have known once, or maybe it wasn’t true in earlier versions of oracle, or maybe I just never noticed it and it’s “always” been true; and it’s a detail I’ll probably have forgotten again a couple of years from now. Consider the following two ways of creating a table with primary key:
I received an email recently describing a problem with a query which was running a full tablescan but: “almost all the waits are on ‘db file sequential read’ and the disk read is 10 times the table blocks”. Some further information supplied was that the tablespace was using ASSM and 16KB block size; the table had 272 columns (ouch!) and the Oracle version was 126.96.36.199.
From time to time I read a question (or, worse, an answer) on OTN and wonder how someone could have managed to misunderstand some fundamental feature of Oracle – and then, as I keep telling people everyone should do – I re-read the manuals and realise that that sometimes the manuals make it really easy to come to the wrong conclusion.
Having nothing exciting to do on the plane to Bucharest today, I decided it was time to read the Concepts manual again – 12c version – to remind myself of how much I’ve forgotten. Since I was reading the mobi version on an iPad mini I can’t quote page numbers, but at “location 9913 of 16157″ I found the following text in a sidebar:
“LGWR can write redo log entries to disk before a transaction commits. The redo entries become permanent only if the transaction later commits.”
Everyone gets caught out some of the time with NOT IN.
This came up in a (fairly typical) question on OTN recently where someone had the task of “deleting 6M rows from a table of 18M”. A common, and perfectly reasonable, suggestion for dealing with a delete on this scale is to consider creating a replacement table holding the data you do want rather than deleting the data you don’t want. In this case, however, the query for deleting the data looked like this:
DELETE FROM EI.CASESTATUS WHERE CASEID NOT IN (SELECT CASEID FROM DO.STG_CASEHEADER);
The suggested code for creating the kept data was this:
There was a little conversation on Oracle-L about ASH (active session history) recently which I thought worth highlighting – partly because it raised a detail that I had got wrong until Tim Gorman corrected me a few years ago.
Once every second the dynamic performance view v$active_session_history copies information about active sessions from v$session. (There are a couple of exceptions to the this rule – for example if a session has called dbms_lock.sleep() it will appear in v$session as state = ‘ACTIVE’, but it will not be recorded in v$active_session_history.) Each of these snapshots is referred to as a “sample” and may hold zero, one, or many rows.
Some time ago I wrote a blog note describing a hack for refreshing a large materialized view with minimum overhead by taking advantage of a single-partition partitioned table. This note describes how Oracle 12c now gives you an official way of doing something similar – the “out of place” refresh.
I’ll start by creating a matieralized view and creating a couple of indexes on the resulting underlying table; then show you three different calls to refresh the view. The materialized view is based on all_objects so it can’t be made available for query rewrite (ORA-30354: Query rewrite not allowed on SYS relations) , and I haven’t created any materialized view logs so there’s no question of fast refreshes – but all I intend to do here is show you the relative impact of a complete refresh.
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:
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.