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dbms_random

In a recent ODC thread someone had a piece of SQL that was calling dbms_random.string(‘U’,20) to generate random values for a table of 100,000,000 rows. The thread was about how to handle the ORA-30009 error (not enough memory for operation) that is almost inevitable when you use the “select from dual connect by level <= n” strategy for generating very large numbers of rows, but this example of calling dbms_random.string() so frequently prompted me to point out an important CPU saving , and then publicise through this blog a little known fact (or deduction) about the dbms_random.string() function.

Massive Delete

The question of how to delete 25 million rows from a table of one billion came up on the ODC database forum recently. With changes in the numbers of rows involved it’s a question that keeps coming back and I wrote a short series for AllthingsOracle a couple of years ago that discusses the issue. This is note is just a catalogue of links to the articles:

“Call me!” Many many times!

Some readers might recall that classic Blondie track “Call me”.  Of course, some readers might be wishing that I wouldn’t harp on about great songs from the 80’s. But bear with me, there is a (very tenuous) link to this post. If you haven’t heard the song, you can jump to the chorus right here.  Go on, I’ll wait until you get back. Smile

This Week in PostgreSQL – May 31

Since last October I’ve been periodically writing up summaries of interesting content I see on the internet related to PostgreSQL (generally blog posts). My original motivation was just to learn more about PostgreSQL – but I’ve started sharing them with a few colleagues and received positive feedback.  Thought I’d try posting one of these digests here on the Ardent blog – who knows, maybe a few old readers will find it interesting? Here’s the update that I put together last week – let me know what you think!


Hello from California!

Part of my team is here in Palo Alto and I’m visiting for a few days this week. You know… for all the remote work I’ve done over the years, I still really value this in-person, face-to-face time. These little trips from Seattle to other locations where my teammates physically sit are important to me.

This Week in PostgreSQL – May 31

Since last October I’ve been periodically writing up summaries of interesting content I see on the internet related to PostgreSQL (generally blog posts). My original motivation was just to learn more about PostgreSQL – but I’ve started sharing them with a few colleagues and received positive feedback.  Thought I’d try posting one of these digests here on the Ardent blog – who knows, maybe a few old readers will find it interesting? Here’s the update that I put together last week – let me know what you think!


Hello from California!

Part of my team is here in Palo Alto and I’m visiting for a few days this week. You know… for all the remote work I’ve done over the years, I still really value this in-person, face-to-face time. These little trips from Seattle to other locations where my teammates physically sit are important to me.

This Week in PostgreSQL – May 31

Since last October I’ve been periodically writing up summaries of interesting content I see on the internet related to PostgreSQL (generally blog posts). My original motivation was just to learn more about PostgreSQL – but I’ve started sharing them with a few colleagues and received positive feedback.  Thought I’d try posting one of these digests here on the Ardent blog – who knows, maybe a few old readers will find it interesting? Here’s the update that I put together last week – let me know what you think!


Hello from California!

Part of my team is here in Palo Alto and I’m visiting for a few days this week. You know… for all the remote work I’ve done over the years, I still really value this in-person, face-to-face time. These little trips from Seattle to other locations where my teammates physically sit are important to me.

Index Bouncy Scan 4

There’s always another hurdle to overcome. After I’d finished writing up the “index bouncy scan” as an efficient probing mechanism to find the combinations of the first two columns (both declared not null) of a very large index a follow-up question appeared almost immediately: “what if it’s a partitioned index”.

Min/Max upgrade

Here’s a nice little optimizer enhancement that appeared in 12.2 to make min/max range scans (and full scans) available in more circumstances. Rather than talk through it, here’s a little demonstration:

Index Bouncy Scan 2

I wrote a note some time last year about taking advantage of the “index range scan (min/max)” operation in a PL/SQL loop to find the small number distinct values in a large single column index efficiently (for example an index that was not very efficient but existed to avoid the “foreign key locking” problem. The resulting comments included pointers to other articles that showed pure SQL solutions to the same problem using recursive CTEs (“with” subqueries) from Markus Winand and Sayan Malakshinov: both writers also show examples of extending the technique to cover more cases than the simple list of distinct values.

Attribute clustering….super cool

I’ve spoken about attribute clustering before here, here and here. So from that you can probably glean that I’m a fan.

I recently spoke about an example of this as well during my AskTOM Office Hours session which you can watch below: