How Would You Improve SQL?
theodp asks: "It was the best of languages, it was the worst of languages. SQL's handy, but it can also drive you nuts. For example, if you want all 100 columns from a table, 'SELECT *' works quite nicely. However, if you want all but 1 of the 100 columns, be prepared to spell out 99 column names. Wouldn't it not make sense to provide a Google-like shorthand notation like 'SELECT * -ColumnName' (or DROP=syntax like SAS)? So how would you improve SQL?"
Extremely useful when you need to produce a result tree instead of a result list (e.g. Slashdot's nested comments). Oracle does this with "CONNECT BY", there is also a PostgreSQL patch available. Of course there are hacks to do this, such as adding extra fields to keep track of where you are in the tree, but they are a real pain in the arse compared with using the information that's already present in the database.
Bogtha Bogtha Bogtha
If this is your main problem with SQL, then you have other problems as well. Who in their right mind needs a table with 100 columns? If you have 100 columns, you seriously need to normalize your database.
Ok, I might not be a database buff. Actually, my experience with SQL is purely academical (although I've worked with object-oriented databases). But if I were to improve SQL, my attempts would be in the direction of making it into a more pure mapping of a relational database, not in adding yet more syntactic sugar.
Did you know there have been people working on a general algebra for data management for, what 40 years now? Did you know, this is basically a SOLVED PROBLEM? Ever heard of "D"? Or Tutorial D? The Third Manifesto?
.. it tells the computer what you want, it doesn't tell it how to do it and in what order, and 2) algebraic notation is *completely general*. You can nest arbitrarily with parentheses, and you can clearly see what's a variable and what's a value and what's an operator. Easy to create, understand, and *optimize*.
You know, I totally understand why Fabian Pascal is always pissed off.
Here's something for you to chew on:
Why do programmers write this:
A + 3
when they want to add 3 to A? Why do we not write some lovely crap like:
OPERATE ON A WITH 3 USING ADDITION
why do we write:
(A + 3) * 2
and not:
OPERATE ON (OPERATE ON A WITH 3 USING ADDITION) WITH 2 USING MULTIPLICATION
Why do we do that?? Because algebraic notation is 1) declarative
Do you agree with me that the verbose syntax clouds your thinking? Keeps you from seeing the underlying operations? Makes it difficult to apply the basic algebraic skills you learned in high school? Makes it difficult for the compiler writer to do the same?
Now I ask you, why do we write:
SELECT * FROM Order
and not
Order
Why do we write:
SELECT * FROM Order JOIN OrderItem WHERE Order.order_id = OrderItem.order_id
and not
Order JOIN OrderItem
And here you are, dwelling on some little detail about projecting columns.. this is an easy one: use an "ALL BUT" operator for example:
RelvarWith100Attributes ALL BUT (Attribute100)
Once you see that relational algebra is just values, variables, and operators nested in any arbitrary way, just like arithmetic, you have opened the door a little more to understanding the fundamental theory of data management and how backwards and primitive "modern" data management is.
And let's not even get into all the crap that SQL gives us like duplicate rows, NULLs, brain-dead table-oriented storage, lack of 100% updateable views, lack of arbitrary constraints, (often) lack of composite types (why the hell do we splat objects into MULTIPLE COLUMNS?? They should be stored in ONE column). SQL also confuses logical and physical layers (keys vs. indexes), and has basically kept the database industry in the dark ages for decades now.
So the answer to your question is pretty simple: I would ditch SQL and use something that looks like relational algebra, which has been understood and documented for a probably longer than you've been *alive*. No offense.
In what way isn't it relational?
.. I think this is related to lack of table equality.
1. SQL syntax doesn't look like relational algebra (see my long rant above). This clouds thinking and hides the simplicity of the underlying model.
2. Relations are sets. SQL allows duplicate rows, so its tables aren't sets, and therefore aren't relations. (This property alone is enough to make it "not relational" by the way).
3. Relation *attributes* (the column names) are also sets. SQL allows columns with the SAME NAME in a query result!!
4. SQL has no "table equality" operator. You'd think the first operator you'd implement for a data type, especially a fundamental data type, would be equality! Imagine a programming language with no integer equality for instance.
5. Relations require each attribute to be drawn from a single type or domain. SQL allows NULLs, which are values not drawn from the column's type. And SQL gives you very little to help you work without NULLs. To add insult to injury, the default for columns is NULLable.
6. (related) Relational algebra requires boolean logic. SQL uses three-valued logic because of NULLs. And it uses it *inconsistently*.
7. The relational model does not specify a type system, it just requires one. Yet SQL specifies it's own particular type system (integers, chars, etc). What if you want to store XML or audio in one of your columns?
8. The relational model specifies nothing about physical implementation. Yet, almost every SQL product stores the columns of tables "together" in such a way that makes joins needlessly expensive.
9. SQL distinguishes between "base tables" and "views". The relational model requires them to be indistinguishable to the end user. Specifically, most SQL implementations don't let you update views! Pretty unbelievable. Imagine a programming language that didn't let you pass arguments to any function for instance.
10. SQL lets you do meaningless things like multiply the primary key values of two tables or add a weight to a height. This is related to the type system issues.
11. SQL confuses KEYs (logical) with INDEXes (physical implementation).
12. (This one gets me all the time) SQL has an EXISTS operator (is this statement true for at least one value of this result?) but not a FOREACH operator (is this statement true for all values in this result?)
13. SQL implementations don't have ANY brains whatsoever. They don't know that book_id from column A and book_id from column B are equal in a join, and that you don't need both of them in the query result. They don't "look inside" your CHECKs and foreign keys to deduce information about your database and use that information to optimize queries.
I'm sure if you picked up a basic theory book you'd find plenty of other nitpicks for the syntax, the semantics, and the basic underlying model of SQL.
And these aren't just "theoretical" problems, I run into them every day because I know there's something "more" out there. Here's a simple query you should try to do in one line of SQL: "give me a list of all customers who bought every product in product line X". Someone who knows relational theory just thinks up the solution (you just need to create a list P of all products in product line X, and pull out the list of orders where P is a subset of the order items, then join with the list of customers). Someone who only knows SQL will immediately run for the application layer, where you can't just *declare* your problem and have the app solve it, you literally have to write loops and procedural code to solve the problem.
If you are interested in learning more, get Date's O'Reilly book "Database in Depth". It's very short, roughly 200 pages, and tells you all you need to know about data management theory.
Actually, it'd be faster if you listed out every column name. If you're talking about faster to write out the code for, you're obviously not writing a query for a program that's intended to be used much. There's absolutely no reason you should be deploying code containing a query that does "select *" or anything like it. You're making the database do the work of looking up the list of columns names every time that query runs. There are much more useful things to spend your caching space on (if you have any).
If you really can't stand to write queries containing the actual column names, you should be using some type of abstraction layer in whatever language you're writing your code in.
If you're not writing code and just making queries by hand to test the results, then you're even further off your rocker. (this also applies in general to the statement you made) Why would you ever NOT want to select that last value out of 100? is it going to keep your output from wrapping? (lol)
Also, those of you saying that you should never have 100 columns in your table, you're certifiable lunatics as well. If you have 100 columns that are used in every record and have very little or no duplication per row, there is no reason you should break this up into multiple tables!!! Then the database has to do joins, which again require more processing power and disk usage. It's also hard to maintain multiple tables when you really have one table after you normalize it.
For those of you that say this isn't normalized... I'm not even really sure how to answer that.... If you have several tables all with a strict 1:1 relationship, they should be in ONE table. Anything else is considered denormalized, not yet normalized. (aside from being just plain BAD!)
For those of you that say you'd never need that many columns in one table or split across multiple tables, however you'd like to think the world should work. I have an example of just that. My wife does genetic research, primarily statistical analysis of sequence data (in various forms, but that's the easiest way to sum it up). We've had discussions on this particular topic, where she had been told by someone else that she would get better performance in Oracle if she split her one table into several tables containing a smaller number of columns, each.
This is just simply not true. It also is a perfect example of a situation where you would actually need a large number of columns. There were specific bits of data that needed to be looked up quickly (like, 45'ish). You can't store it all in one column (or even just a few) and use regexes to find the bits you're looking for. You also don't want to be doing a lot of joins unless you really need to, you know.. when you actually have data that would fit into some form of normalization. Technically, you CAN do this stuff, but not if you want decent performance. If you didn't want decent performance, you could just leave the data in a text file and shell out a grep command. *sigh*
Anyway, enough ranting, but seriously people... Get a clue. Get some experience with these issues. Don't just pipe up because "hey, I've worked with databases and while I probably don't understand them very well, I don't know anybody else that understands them at all, so I'm kind of an expert!"
Lets look at something a little more realist:
c e.InvoiceNum,
SELECT
Lease.LeaseNum,
Lease.LesseeNum,
Invoice.InvoiceNum,
Invoice.AmountBilled
FROM
Lease INNER JOIN
Invoice ON
Lease.LeaseNum = Invoice.InvoiceNum
WHERE
Lease.LeaseNum = "1234"
ORDER BY
LeaseNum, InvoiceNum
Okay, that's pretty big to get some basic lease and invoice info. Now how you you write that?
Lease.LeaseNum,
Lease.LesseeNum,
Invoi
Invoice.AmountBilled
Lease JOIN
Invoice ON
Lease.LeaseNum AND Invoice.LeaseNum
Lease.LeaseNum = "1234"
Lease.LeaseNum
Invoice.InvoiceNum
??? All that's been accomplished is the removal of key words. I'm not seeing any benefit, and I'm seeing the pitfall of it being hard as hell to read.
-Rick
"Most people in the U.S. wouldn't know they live in a tyrannical state if it walked up and grabbed their junk." - MyFirs
2 row(s) returned.
John
No doubt it has defects, but SQL has a strong theoretical underpinning in set theory. This has made it a very durable language and one that scales to sizes probably unimagined by Dr Codd when he outlined its roots in 1970 in his article "A relational model of data for large shared data banks".
Computings needs for well structured access and manipulation of large data sets has been well served by SQL.
A clear replacement has yet to emerge. There are pretenders to the throne, of which Tutorial D is certainly technically nice, XQuery is a mess and ODBMSs (and their query tools) really haven't caught on.
Its just that SQL passes a simple test - its good enough for the job and relatively ubiquitous. And standards do exist (that every major vendor breaks. sigh.).
violets are blue
you just did a Cartesian Product
your DBA will be talking to you
thank you, thank you, shows at 7 and 10, remember to tip the waitstaff