Altering SELECT .. FROM Into FROM .. SELECT Does Not “Repair” SQL – Java, SQL and jOOQ.

From time to time, I see of us lament the SQL syntax’s peculiar disconnect between

Most just lately right here in a Youtube remark reply to a latest jOOQ/kotlin speak. Let’s take a look at why jOOQ didn’t fall into this lure of making an attempt to “repair” this, and why that is even a lure.

The English Language

SQL has a easy syntax mannequin. All instructions begin with a verb in crucial type, as we “command” the database to execute a press release. Frequent instructions embrace:

• SELECT
• INSERT
• UPDATE
• DELETE
• MERGE
• TRUNCATE
• CREATE
• ALTER
• DROP

All of those are verbs in crucial type. Take into consideration including an exclamation mark in every single place, e.g. INSERT [this record]!

The Order of Operations

We will argue that pure languages are very poor inspiration for laptop programming languages, which are usually extra mathematical (some greater than others). A whole lot of criticism concerning the SQL language is that it doesn’t “compose” (in its native type).

We will argue, that it might be significantly better for a extra composable SQL language to begin with FROM, which is the primary operation in SELECT based on the logical order of operations. E.g.

FROM guide
WHERE guide.title LIKE 'A%'
SELECT guide.id, guide.title

Sure, that may be higher within the sense that it might be extra logical. First, we declare the info supply, predicates, and so forth. and solely ultimately would we declare the projection. With the Java Stream API, we’d write:

books.stream()
     .filter(guide -> guide.title.startsWith("A"))
     .map(guide -> new B(guide.id, guide.title))

The advantages of this could be:

• No disconnect between syntax and logic
• Therefore: No confusion round syntax, specifially why you’ll be able to’t reference SELECT aliases in WHERE, for instance.
• Higher auto-completion (since you don’t write stuff that isn’t declared but, first)

In a approach, this ordering can be per what some RDBMS carried out when RETURNING knowledge from DML statements, comparable to:

INSERT INTO guide (id, title)
VALUES (3, 'The E-book')
RETURNING id, created_at

With DML statements, the command (“crucial”) continues to be INSERT, UPDATE, DELETE, i.e. a verb that clearly tells the database what to do with the info. The “projection” is extra of an afterthought. A utility that’s often helpful, therefore RETURNING might be positioned on the finish.

RETURNING looks as if a practical alternative of syntax, and isn’t even a part of the usual. The usual defines the <knowledge change delta desk>, as carried out by Db2 and H2, whose syntax is:

SELECT id, created_at
FROM FINAL TABLE (
  INSERT INTO guide (id, title)
  VALUES (3, 'The E-book')
) AS guide

I imply, why not. I don’t have a powerful choice for one or the opposite syntax (jOOQ helps each and emulates them into each other). SQL Server invented a 3rd variant, whose syntax might be the least intuitive (I all the time must lookup the precise location of the OUTPUT clause):

INSERT INTO guide (id, title)
OUTPUT id, created_at
VALUES (3, 'The E-book')

Cypher question language

In all probability value mentioning right here is that there exists a contemporary question language on the market that’s sufficiently widespread to be thought-about for such discussions: The Cypher Question Language from neo4j. With a easy “trick”, it each:

• Maintained the language mannequin the place a verb in crucial type begins a press release (the verb is MATCH, which has similarities to FROM, however it’s a verb), so it inherits SQL’s “power” of being intuitive additionally for non-programmers.
• Reversed the logical order of operations throughout the studying statements, to be of the shape MATCH .. RETURN, making RETURN the common type of projecting issues for all operations, not simply SELECT.
• Reused MATCH additionally for writing operations, together with DELETE or SET (which corresponds to SQL’s UPDATE)

Whereas working on a unique knowledge paradigm (the community mannequin versus the relational mannequin), I’ve all the time discovered the Cypher Question Language to be usually superior to SQL by way of syntax, a minimum of on a excessive stage. If I needed to truly “repair” SQL by creating SQL 2.0, I’d take inspiration right here.

Fixing this in an API like jOOQ isn’t value it

As mentioned earlier than, SQL has some apparent shortcomings, and there exist higher languages like Cypher fixing the identical sort of downside. However SQL is right here, and it’s 50 years outdated, and it’ll keep. It gained’t be fastened.

That’s one thing that simply must be accepted:

SQL gained’t be fastened

It will likely be amended. It incorporates new concepts, together with:

It all the time does so in an idiomatic, SQL fashion approach. Should you’re studying the SQL normal, or for those who’re working with PostgreSQL, which may be very near the usual, you’ll really feel that SQL is kind of constant as a language. Or, it’s constantly bizarre, relying in your tastes.

For jOOQ, one of many major success elements has all the time been to be as shut as attainable to this imaginative and prescient of what SQL actually is by way of syntax. A whole lot of of us are very efficient writing native SQL. Since Java has textual content blocks, it has turn out to be much more bearable to simply copy paste a static SQL question out of your SQL editor into your Java program, and e.g. execute it with JDBC or with jOOQ’s plain SQL templating API:

for (File document : ctx.fetch(
    """
    SELECT id, title
    FROM guide
    WHERE title LIKE 'A%'
    """
)) {
    System.out.println(document);
}

This method is ample for very easy functions on the market. In case your “utility” runs a complete of 5 distinct SQL queries, you are able to do it with JDBC alone (though, when you’ve began to get a hold of jOOQ, you’ll most likely use jOOQ even for these functions as nicely).

However jOOQ actually shines when your utility has 100s of queries, together with many dynamic ones, and your database has 100s of tables, in case of which the kind security and mannequin security advantages actually assist. Nonetheless, it could shine solely when your SQL question interprets 1:1 to the jOOQ API. Randomly fixing SQL to some extent on this most vital assertion (SELECT) gained’t do the trick.

As a result of: The place will you cease fixing SQL? SQL continues to be bizarre even for those who change to FROM .. SELECT. For instance, the semantics of GROUP BY continues to be bizarre. Or the connection between DISTINCT and ORDER BY. E.g. this could seem like significantly better at first (e.g. to separate SELECT and DISTINCT, which shouldn’t be situated so intently collectively):

FROM guide
WHERE guide.title LIKE 'A%'
SELECT guide.title
DISTINCT
ORDER BY guide.title

However the bizarre caveats would nonetheless not disappear, particularly that you may ORDER BY expressions that aren’t listed in SELECT within the absence of DISTINCT, however not within the presence of DISTINCT (see our earlier article about that).

Various syntaxes in different DSL APIs

So, the place does the “fixing” of SQL cease? When will SQL be “fastened?” It would by no means be fastened, and as such, an API like jOOQ can be a lot more durable to study that it needs to be. Some competing APIs comply with this mannequin, e.g.

Each of those APIs are primarily based on the concept that SQL wants “fixing,” and {that a} extra “native,” a extra “idiomatic” really feel of the API can be considerably higher. Some examples:

Slick:

Right here’s an instance from the getting began information:

This corresponds to the next SQL:

SELECT max(worth)
FROM coffees

It’s arguably a bit extra idiomatic. It seems like extraordinary Scala assortment API utilization, eradicating the SQL really feel from the equation. In any case, the standard map(x => y) assortment strategies actually correspond to a SQL SELECT clause (a “projection”).

Uncovered:

Right here’s an instance from Baeldung:

StarWarsFilms
  .slice(StarWarsFilms.sequelId.depend(), StarWarsFilms.director)
  .selectAll()
  .groupBy(StarWarsFilms.director)

The API introduces new phrases, e.g.

• slice which suggests the identical factor as map() or SELECT, although international to each SQL or kotlin assortment APIs
• selectAll, which corresponds to the relational algebra time period “choice”, equivalent to SQL WHERE

Artificial comfort syntax as an alternative of “fixing” SQL

jOOQ doesn’t comply with down this highway and by no means will. SQL is what it’s, and jOOQ gained’t be capable of “repair” that. The 1:1 mapping between SQL syntax and jOOQ API signifies that even if you wish to use one thing subtle, like:

Even then, jOOQ gained’t allow you to down and can mean you can write precisely what you keep in mind by way of SQL characteristic. I imply, wouldn’t it actually make sense to help CONNECT BY in Slick or Uncovered? In all probability not. They must invent their very own syntax to provide entry to SQL recursion. However will or not it’s full? That’s an issue jOOQ gained’t have.

The one cause why some syntax will not be accessible is as a result of it’s not attainable but (and please do ship a characteristic request). The instance of FOR XML is a superb one. SQL Server invented this FOR clause, and whereas it’s handy for easy instances, it’s not very highly effective for advanced ones. I a lot choose normal SQL/XML and SQL/JSON syntax, (which jOOQ additionally helps). However whereas I don’t very very like the syntax, jOOQ gained’t choose. What good would a 3rd syntax, solely invented by jOOQ be for customers? As I stated earlier than.

When will the “fixing” cease?

It would by no means cease. The alternate options I’ve talked about will run into very troublesome questions down the road after they begin including extra options, if they begin including extra options. Whereas it’s all the time simple to implement a easy SELECT .. FROM .. WHERE question builder, and help that performance utilizing arbitrary API, claiming SQL has been “fastened,” it’s a lot more durable to evolve this API, addressing all types of superior SQL use-cases. Simply take a look at their difficulty trackers for characteristic requests like CTEs. The reply is all the time: “Use native SQL.”

Even “easy” SQL options, comparable to UNION turn out to be extra advanced as soon as fundamental SQL syntax is modified. The semantics is already tough sufficient in SQL (and it’s solely SQL’s fault, certain), however “fixing” this stuff isn’t so simple as it could take a look at first.

Now, there are 2 exceptions to this rule:

Artificial syntax

One exception is: “Artificial syntax.” Probably the most highly effective artificial syntax in jOOQ are implicit joins. Implicit joins aren’t “fixing” SQL, they’re “enhancing” SQL with a syntax that SQL itself might need (hopefully can have, ultimately). Similar to there exist SQL dialects, which “improve” the SQL normal, e.g.

jOOQ may be very conservative about such artificial syntax. There are a variety of good concepts, however few are ahead appropriate. Every one in all these syntaxes makes different SQL transformation options extra advanced, and every one has flaws that will not have been addressed but (e.g. as of jOOQ 3.16, implicit joins are usually not attainable in DML statements comparable to UPDATE, DELETE, even when they make a variety of sense there as nicely. See difficulty #7508).

Comfort syntax

One other kind of enchancment is what I name “comfort syntax.” For instance, no matter the underlying RDBMS, jOOQ permits you to write:

choose(someFunction()); // No FROM clause
selectFrom(someTable);  // No express SELECT checklist

In each instances, customers can omit clauses that could be obligatory within the underlying SQL dialect, and jOOQ fills the generated SQL with an inexpensive default:

• A FROM DUAL desk declaration, or one thing related
• A SELECT * projection declaration, or one thing related

Conclusion

The concept jOOQ ought to stick with SQL syntax on a 1:1 foundation was a raffle I took 13 years in the past, once I made jOOQ. I needed to design jOOQ in a approach that everybody who already knew SQL would haven’t any issues studying jOOQ, as a result of all the things is totally easy. The method behind this API design is described right here.

Others have tried to “repair” SQL by both making their API very idiomatic contemplating the goal language, or by inventing a brand new language.

13 years later, I’ve discovered that the 1:1 mimicking method is the one viable one, as I preserve discovering new, arcane SQL options: