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FK on delete

This is part 1 of a short reference note about the work load created by referential integrity constraints when you delete from a parent table. It was prompted by a question on the Oracle Developer Community forum about how to handle a very large delete from a table which (a) included a column of type CLOB and (b) had 9 child tables.

The 9 referential integrity constraints were declared with “on delete cascade”, but the delete was taking too long even though all the related child data had been deleted before the parent delete. In outline the process was designed to operate in batches as follows:

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Order By

This is a brief note with an odd history – and the history is more significant than the note.

While searching my library for an example of an odd costing effect for the “order by” clause I discovered a script that looked as if I’d written for in 2008 to demonstrate a redundant sort operation appearing in an execution plan; and then I discovered a second script written for in 2014 demonstrating a variant of the same thing (presumably because I’d not found the original script in 2014) and the second script referenced a MOS bug number


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Index Engineering

This is a case study based on a question that appeared on the Oracle Developer Community forum a few days ago.

What I’m aiming to present in this note is the pattern of thinking that you should adopt in cases like this. The final suggestion in this note isn’t necessarily the best answer to the question posed (at the time of writing the OP hadn’t supplied enough information to allow anyone to come up with a best solution), but the point of the exercise is to talk about the journey and (perhaps) remind you of some of the extreme engineering you can do with indexes.

The (massaged) problem statement is as follows:

I have a table of more than 200 million rows that is used for inserts, updates and queries. I have a query on this table and want to know what index I could create to speed up the query.

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A few days ago I published a little note of a script I wrote some time ago to estimate the clustering_factor of an index before it had been built. At the time I pointed out that one of its limitations was that it would not handle cases where you were planning to set the table_cached_blocks preference, but a couple of days later I decided that I’d write another version of the code that would cater for the new feature – and that’s how I made an embarrassing discovery.

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Originally drafted July 2018

“How do you find out what the clustering_factor of an index would be without first creating the index ?”

I’m not sure this is really a question worth asking or answering[1], but since someone asked it (and given the draft date I have no idea who, where, when or why), here’s an answer for simple heap tables in the good old days before Oracle made public the table_cached_blocks preference. It works by sorting the columns you want in the index together with the table rowid, and then comparing the file/block component of the rowid (cutting the relevant characters from the string representation of the rowid) with the previous one to see if the current row is in the same block as the previous row.  If the row is in a different block we count one, otherwise zero.  Finally we sum the ones.

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Updatable Join Views

Here’s a quick “how to”.

If you want to update a column in table A with a column value from table B, then there’s a simple way to check if the required result can be achieved through an updatable join view.

Step 1: write a query that joins table A to table B and reports the rows in table A that you want to update, with the value from table B that should be used to update them, e.g.

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Optimizer Tricks 1

I’ve got a number of examples of clever little tricks the optimizer can do to transform your SQL before starting in on the arithmetic of optimisation. I was prompted to publish this one by a recent thread on ODC. It’s worth taking note of these tricks when you spot one as a background knowledge of what’s possible makes it much easier to interpret and trouble-shoot from execution plans. I’ve labelled this one “#1” since I may publish a few more examples in the future, and then I’ll have to catalogue them – but I’m not making any promises about that.

Here’s a table definition, and a query that’s hinted to use an index on that table.

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Here’s a question just in from Oracle-L that demonstrates the pain of assuming things work consistently when sometimes Oracle development hasn’t quite finished a bug fix or enhancement. Here’s the problem – which starts from the “scott.emp” table (which I’m not going to create in the code below):

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Timestamp Oddity

[Editorial note: this is something I started writing in 2013, managed to complete in 2017, and still failed to publish. It should have been a follow-on to another posting on the oddities of timestamp manipulation.]

Just as national language support used to be, timestamps and time-related columns are still a bit of a puzzle to the Oracle world – so much so that OEM could cripple a system if it was allowed to do the check for “failed logins over the last 30 minutes”. And, just like NLS, it’s one of those things that you use so rarely that you keep forgetting what went wrong the last time you used it. Here’s one little oddity that I reminded myself about recently:

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I’ve made use of the function a few times in the past, for example in this posting on the dangers of using reverse key indexes, but every time I’ve mentioned it I’ve only been interested in the “leaf blocks per key” option. There are actually four different variations of the function, relevant to different types of index and controlled by setting a flag parameter to one of 4 different values.

The call to sys_op_lbid() take 3 parameters: index (or index [sub]partition object id, a flag vlaue, and a table “rowid”, where the flag value can be one of L, R, O, or G. The variations of the call are as follows:

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