In article <[EMAIL PROTECTED]>, Lauri PietarinenOK, I get your point.
<[EMAIL PROTECTED]> writes
Anthony W. Youngman wrote:
So what's wrong with gettng a machine with lots of memory? How much does 2G ofFine. 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".
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?
And I presume the system will automatically move all related stuff (order details etc.) intoWell, 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"
the same block as the new customer? How long will that take? What if there is no room for it there?
That certainly is not true. The theory says NOTHING about how data should be arranged on disk.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.
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 ;-)
My goodness, no I'm not! Its the same as claiming that if you have a drawing for a house, youinNow, 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
Well why don't you?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!
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.
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.
So for each product you get T = (1+N) * ST * 1.05.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.
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 ;-)
Well, no thanks. I just wanted their names this time.No, I want you to give me a list of all your customers. How many disk reads?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.)
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.
The relational alternative, with an index on customer_name, would be again an order
of magnitune less disk reads.
What is "too large"?decouplingThe theory, indeed, does not say anything about buffer pools, but byBut 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 ...
do.logic
from implementation we leave the implementor (DBMS) to do as it feels fit to
our
As DBMS technology advances, we get faster systems without having to change
programs.
But with MV, if our database is too large for current technology, we kick the shit out of relational for speed ...
It does?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 ...
Frankly, it may well be that PICK systems run faster and cheaper than relational ones, but certainlyWhen 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 ...
not for the reasons you state.
I would have to know a lot more details to address it properly. Performance is irrelevant to the model.
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.
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.
That's OK with me. But the most you can claim is that todays IMPLEMENTATIONS are flawed,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?
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.
Could you give me some other examples?From the mathematician's (or logician's) viewpoint I agree it's flawless. But that's true of plenty of broken scientific theories...
best regards, Lauri Pietarinen
Cheers,
Wol
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