Several years ago I wrote the following in “Cost Based Oracle – Fundamentals” (p.47):
The maxthr and slavethr figures relate to throughput for parallel execution slaves. I believe that the figures somehow control the maximum degree of parallelism that any given query may operate at by recording the maximum rate at which slaves have historically been able to operate—but I have not been able to verify this.
Browsing the internet recently, I discovered that that no-one else seems to have published anything to verify my comment, so I decided it was about time I did so myself. I’m going to work up to it in two blog notes , so if you do happen to know of any document that describes the impact of maxthr and slavethr on the optimizer’s costing algorithms please give me a reference in the comments – that way I might not have to write the second note.
Parallel DML is not enabled by default, and it’s easy to forget this and think you’ve made an operation “as parallel as possible” by declaring objects parallel or putting in hints for parallelism.
A recent question on OTN asked about speeding up a materialized view refresh that seemed to be spending a lot of its time waiting on “PX Deq Credit: send blkd”. The manuals describe this as an “idle event”; but that’s not always true. The OP had supplied the output from tkprof for one of the sessions showing the “insert as select” that was the (complete) refresh and it was clear that the select was running in parallel, but the insert wasn’t – and that’s one case in which the “PX Deq Credit: send blkd” is arguably an “idle” wait (with a timeout of 2 seconds). It’s possible that the refresh could go faster if the OP enabled parallel DML.
A few years ago (2007) I wrote about a problem that could appear when you mixed parallel execution with system managed extent allocation. A couple of years later I added a note that Christian Antognini had observed a patch in 22.214.171.124 that addressed the specific issue I had raised. Today, thanks to an email exchange with Christo Kutrovsky of Pythian, I can report that there is a variation of this issue still available even in 126.96.36.199.
The basic problem is that you can end up with a very large number of very small extents, leading to poor performance in parallel queries and a significant waste of space in a data segment. Here’s a simple, though not particularly realistic, way to demonstrate the problem.
I’ve said in the past that one of the best new features, in my view, in 11g was the appearance of proper virtual columns; and I’ve also been very keen on the new “approximate NDV” that makes it viable to collect stats with the “auto_sample_size”.
Who’d have guessed that if you put them both together, then ran a parallel stats collection it would break :(
The bug number Karen quotes (10013177.8) doesn’t (appear to) mention extended stats – but since virtual columns, function-based indexes, and extended stats share a number of implementation details I’d guess that they might be affected as well.
There’s a posting on the OTN database forum asking for suggestions about restricting a query to data from one datafile of a tablespace. It seems to be a slightly odd thing to do, but it reminded me of a “pseudo-parallel” trick I once used (and described) more than 10 years ago on a system running Oracle version 7. It was a long time ago, but I think I needed to do this because I wanted to execute a massive update with as many parallel threads as possible in the days when parallel DML wasn’t possible.
At least twice in the last few weeks, there’s been a question on OTN about a mismatch between dba_extents and dba_segments after rebuilding some indexes.
Here’s one of the threads, where Randolf Geist supplies the explanation for the anomaly.
Doug Burn’s sent me an email a couple of days ago about a question that had appeared on his blog in response to a comment I made several months ago.
I’ve followed up with an answer, of course, but reading the blog reminded me that some interesting stuff had come up about direct path reads and writes, as well as some comments on parallel query. So I thought I’d publish a link to the item so you could see the whole discussion.
Here’s a surprising anomaly that showed up in a question on the OTN forums a little while ago. Consider a simple query that uses a hash join between two tables.
pq_distribute(t2 hash hash)
from t1, t2
where t2.n1 = t1.n1
and t2.small_vc = t1.small_vc
When it runs serially the join completes in memory and the only I/O you see comes from the two tablescans. When the query runs parallel something causes a spill to the temporary tablespace.
When Oracle tries to optimize a complex SQL statement one of the first steps it takes is to transform it into something simpler. The ideal target (from the optimizer’s perspective) is to eliminate any subqueries and in-line views so that your SQL statement ends up as a list of tables in a single from clause. Every in-line view and subquery is a separate query block, and the optimizer really wants to turn the whole thing into a single query block. Unfortunately this isn’t always possible, and sometimes it isn’t even a good idea – which is why 10g introduced ‘cost base query transformation’.
Here’s a quirky little set of results from trace files. First a 10391 at level 64 – this shows the way in which an object was broken into granules for a parallel tablescan. I’ve just listed the first few granules: (more…)
Or as Doug Burns put it on his blog: how can I tell the actual DOP used for my parallel query”
As Doug points out, you first have to ask “When are you asking the question”. Immediately after you have run the query you could check v$pq_tqstat to see what happened, but apart from that you have very little hope of finding out in retrospect what happened in a specific query.
In the 9i Database Performance Tuning Guide and Reference part no: A96533-01, there is a convenient list of features that “require the CBO” on page 1-15, with the note
“Use of any of these features enables the CBO, even if the parameter OPTIMIZER_MODE is set to RULE.”
The list is as follows:
If you look at a 10053 trace file, you will find references to Resc and Resp (sometimes rsc and rsp) lurking in the background whenever the trace file mentions Cost. When you get to the 10gR2 trace file, you see these described in the “Legend” section as: (more…)
Looking back at some of my previous posts I was reminded how easy it is to overlook one important feature when trying to comment on another. In particular, in this case, a short posting on indexed access paths omitted any mention of parallel execution until a comment from David Aldridge jogged my memory. So here’s an important thought about parallel execution.