Re: Dreaming About Redesigning SQL

Anthony W. Youngman wrote:

>In article <bn4cca$dj0$1(at)nyytiset(dot)pp(dot)htv(dot)fi>, Lauri Pietarinen
><lauri(dot)pietarinen(at)atbusiness(dot)com> writes
>
>
>>Anthony W. Youngman wrote:
>>
>>
>>
>>>Fine. But MV *doesn't* *need* much of a cache. Let's assume both SQL and
>>>MV have the same amount of RAM to cache in - i.e. *not* *much*. I did
>>>say the spec said "extract maximum performance from the hardware
>>>available".
>>>
>>>
>>>
>>So what's wrong with gettng a machine with lots of memory? How much
>>does 2G of
>>memory for an Intel-box cost now a days? Is this some kind of new
>>ultimate sport, trying
>>to get along with as little memory as possible?
>>
>>
>
>I presume you didn't read the bit below ... what if you have SEVERAL
>tables, and EACH of them is a gigabyte or two in size?
>
OK, I get your point.

>>Well, if it is normalised, how easy is it for you to change the
>>customer_id of an order? Anyway,
>>
>>
>
>Incredibly easy. Just update the "customer_id" field of the invoice
>record. A single change to a single "row"
>
And I presume the system will automatically move all related stuff
(order details etc.) into
the same block as the new customer? How long will that take? What if
there is no room for it there?

>>if we stick to your example and even if we don't normalise using e.g.
>>clustering features of Oracle,
>>as Bob pointed out, we are getting at most the same number of I/O's.
>>So, answer to your
>>question: our formula is at least as good as yours.
>>
>>
>
>Except I think Bob said we could "optimise to favour *certain*
>transactions". I think actually ANY transaction benefits. You're relying
>on stuff that's outwith your theory, we're relying on stuff that's
>inherent to our model.
>
That certainly is not true. The theory says NOTHING about how data
should be arranged on disk.
You are talking about how modern SQL-databases behave. The DBMS is at
liberty to do whatever
it pleases with the data, even save it in a PICK database. Hey, wadda
you think? Would that be
a good idea? We get to keep our SQL but with the speed of PICK ;-)

>>>>Now, that was a *conservative* estimate, and we assumed that we did not have
>>>>any rows lying around in the (global!) cache. As the size of the cache grows
>>>>
>>>>
>>in
>>
>>
>>>>proportion to the size of the total database we can assume less and less disk
>>>>I/O.
>>>>
>>>>
>>>>
>>>>
>>>You're relying on the hardware to bale you out :-) We can do the same!
>>>
>>>
>>>
>>Well why don't you?
>>
>>
>
>We let the hardware help us out if it can. There's a big difference. If
>you can't get the hardware, you're stuffed. We don't need it, so while
>we may have a hard time of it it's nowhere near as bad for us.
>
>And again, relational separates the physical from the logical. You're
>being hypocritical if you call upon the physical representation to help
>out with the (speed of the) logical presentation.
>
My goodness, no I'm not! Its the same as claiming that if you have a
drawing for a house, you
have to make that house out of paper?!?

>>I want a list with all products with corresponding total sales, read
>>
>>
>>from order detail e.g.
>
>
>>Hammer 10000$
>>Nail 5000$
>>Screw 1200$
>>
>>How many disk reads (or head movements)?
>>
>>
>
>Actually, probably the same as you here.
>

>If we're indexed on order
>detail. If Hammer appears in N invoices, then T = (1+N) * ST * 1.05 for
>hammers, and the same for all the other products.
>
>Theory favours us, in that if a product appears X times in one invoice,
>that's one read for us and X for you, but hardware will probably help
>you more than us (that is, assuming thrashing cuts in) in that you stand
>a marginally higher chance of getting multiple instances of a product in
>any given read.
>
So for each product you get T = (1+N) * ST * 1.05.

Now, for our SQL-DBMS, presuming that we build indexes for detail and
product:

order_detail(product_id, qty, unit_price) = 20 bytes/row
product(product_id, product_name) = 50 bytes/row

With 2 disk reads I would get
8K/20 = 400 order detail rows and
8K/50 = 160 product rows

Since all rows are in product_id order, no need for random disk reads so
T = 1 + N/400 + P/160 (N=number of details, P=number of products)
for ALL products and details.

And, because of sequential prefetch, we probably would not have to wait
for I/O's at all.

Really, however you calculate it, it is an order of magnitude less
than your alternative.

And please don't tell me that using indexes is not fair or not in the
spirit of the
relational model ;-)

>>>>And: what if I was just reading customer-data. Would the same formula
>>>>apply (= (2+N)*ST*1.05)?
>>>>
>>>>
>>>>
>>>>
>>>Nope. If I understand you correctly, you want attributes that belong to
>>>the entity "customer", not the entity "invoice". T = ST * 1.05. (By the
>>>way, billing and/or invoice address (for example) are invoice
>>>attributes, not company attributes.)
>>>
>>>
>>>
>>No, I want you to give me a list of all your customers. How many disk
>>reads?
>>
>>
>
>T = N * 1.05 where N is the number of customers. What do you want to
>know about those customers? Address? Phone number*s*? Anything else?
>That's *all* at no extra cost.
>
Well, no thanks. I just wanted their names this time.
The relational alternative, with an index on customer_name, would be
again an order
of magnitune less disk reads.

>>>>>But as I understand relational theory, such a question is completely
>>>>>outside the scope of the theory. Seeing as it tries to divorce the
>>>>>database logic from the practical implementation ...
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>The theory, indeed, does not say anything about buffer pools, but by
>>>>
>>>>
>>decoupling
>>
>>
>>>>logic
>>>>
>>>>
>>>>
>>>>
>>>>from implementation we leave the implementor (DBMS) to do as it feels fit to
>>>
>>>
>>do.
>>
>>
>>>
>>>
>>>
>>>
>>>>As DBMS technology advances, we get faster systems without having to change
>>>>
>>>>
>>our
>>
>>
>>>>programs.
>>>>
>>>>
>>>>
>>>>
>>>But with MV, if our database is too large for current technology, we
>>>kick the shit out of relational for speed ...
>>>
What is "too large"?

>>>Don't forget. You've already said that, if nothing is cached, my average
>>>case exceeds your best. And my case is *already* assuming that the
>>>system is seriously stressed and struggling ...
>>>
It does?

>>>>When we design databases we can decouple logical planning from performance
>>>>considerations, which, you must agree, are two separate issues.
>>>>
>>>>
>>>>
>Yes. BUT what's the point of having a database that is logically
>perfect, and who's performance is slow to the point of being unusable?
>
>Don't forget - in practice MultiValue ends up with a database that is
>*inherently* optimised such that it almost invariably outperforms an
>equivalent SQL database, AND we don't normally have DBAs to help us
>achieve that nirvana ...
>
Frankly, it may well be that PICK systems run faster and cheaper than
relational ones, but certainly
not for the reasons you state.

>>>>
>>>>
>>>>
>>>I can't find the post now :-( but is Christopher reading this? You know
>>>I compared that relational system on a twin Xeon 800, to an MV system
>>>running on a P90? Christopher made the (reasonable in the circumstances)
>>>assumption that the relational consultants must be crap, and the MV guy
>>>a guru. Actually, I'd come to exactly the OPPOSITE conclusion. My MV
>>>experience tells me that MV query was probably thrown together, by an
>>>average programmer, in 30 seconds. On the other hand, those SQL
>>>consultants had an axe to grind and a point to prove. They couldn't
>>>afford to let this "old fashioned" system beat them. That SQL query
>>>would have been optimised to within an inch of its life over weeks.
>>>Don't forget how proud they were to beat this MV system! Yet with
>>>hardware that was so much more powerful and a query that was heavily
>>>optimised, they had great difficulty beating a query that was thrown
>>>together in seconds by an average MV guy (or even just a luser!).
>>>
>>>Don't forget. I said I am a database *engineer*. Engineers believe in
>>>elegance, they believe in beauty. And when I look at relational, all I
>>>see is the theorists pleading "power", "hardware", "brute force", to get
>>>them out of trouble.
>>>
>>>
>>>
>You said that logical planning and performance are separate issues. And
>I wouldn't expect you to address the above example in a discussion of
>relational, because performance is irrelevant to relational.
>
I would have to know a lot more details to address it properly.
Performance is irrelevant to the model.
It's like E=mc**2. Nice theory and it actually works. But to get
performance out of it
(=exploding bomb) you have to solve lots of practical details. However,
without the theory
you could experiment for a milloin years without being able to build an
atom bomb.

>But surely, the fact that I am SUPREMELY CONFIDENT that I can get
>superior performance from inferior hardware should give you pause for
>thought that maybe, just maybe, the relational model is flawed from an
>engineer's or scientist's viewpoint?
>
That's OK with me. But the most you can claim is that todays
IMPLEMENTATIONS are flawed,
and you would be 100% correct. How would you go and prove that the model
is flawed?
You should prove that a relational DBMS could not POSSIBLY be efficient.

>From the mathematician's (or logician's) viewpoint I agree it's
>flawless. But that's true of plenty of broken scientific theories...
>
Could you give me some other examples?

best regards,
Lauri Pietarinen

>
>Cheers,
>Wol
>
>