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

Every so often, I see people lament the SQL syntax’s peculiar disconnect between

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

The English Language

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

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

All of those are verbs in crucial kind. Take into consideration including an exclamation mark all over the 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 typically extra mathematical (some greater than others). A whole lot of criticism concerning the SQL language is that it doesn’t “compose” (in its native kind).

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

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

Sure, that will be higher within the sense that it might be extra logical. First, we declare the info supply, predicates, and so forth. and solely in the long run would we declare the projection. With the Java Stream API, we might 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 may’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 manner, this ordering can be according to what some RDBMS carried out when RETURNING knowledge from DML statements, resembling:

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 sometimes helpful, therefore RETURNING could be positioned on the finish.

RETURNING looks as if a realistic 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 desire 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 should 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 price mentioning right here is that there exists a contemporary question language on the market that’s sufficiently common 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 kind begins a press release (the verb is MATCH, which is analogous to FROM, however it’s a verb), so it inherits SQL’s “energy” 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 distinct knowledge paradigm (the community mannequin versus the relational mannequin), I’ve all the time discovered the Cypher Question Language to be typically superior to SQL when it comes to 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 price it

As mentioned earlier than, SQL has some apparent shortcomings, and there exist higher languages like Cypher fixing the identical type of drawback. 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

Will probably be amended. It incorporates new concepts, together with:

It all the time does so in an idiomatic, SQL model manner. For those who’re studying the SQL commonplace, or should you’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 primary success components has all the time been to be as shut as potential to this imaginative and prescient of what SQL actually is when it comes to syntax. A whole lot of people are very efficient writing native SQL. Since Java has textual content blocks, it has change into much more bearable to only 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 report : ctx.fetch(
    """
    SELECT id, title
    FROM guide
    WHERE title LIKE 'A%'
    """
)) {
    System.out.println(report);
}

This method is ample for very easy functions on the market. In case your “software” 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 dangle of jOOQ, you’ll in all probability use jOOQ even for these functions as nicely).

However jOOQ actually shines when your software 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 might shine solely when your SQL question interprets 1:1 to the jOOQ API. Randomly fixing SQL to some extent on this most necessary assertion (SELECT) gained’t do the trick.

As a result of: The place will you cease fixing SQL? SQL continues to be bizarre even should you swap 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 look like a lot better at first (e.g. to separate SELECT and DISTINCT, which shouldn’t be positioned 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 which you could 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).

Different syntaxes in different DSL APIs

So, the place does the “fixing” of SQL cease? When will SQL be “fastened?” It’s going to by no means be fastened, and as such, an API like jOOQ can be a lot tougher to be taught that it ought to be. Some competing APIs comply with this mannequin, e.g.

Each of those APIs are primarily based on the concept 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 unusual Scala assortment API utilization, eradicating the SQL really feel from the equation. In spite of everything, 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 implies the identical factor as map() or SELECT, although overseas to each SQL or kotlin assortment APIs
• selectAll, which corresponds to the relational algebra time period “choice”, comparable to SQL WHERE

Artificial comfort syntax as an alternative of “fixing” SQL

jOOQ doesn’t comply with down this street and by no means will. SQL is what it’s, and jOOQ gained’t be capable to “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 assist you to write precisely what you bear in mind when it comes to SQL characteristic. I imply, would it not actually make sense to assist 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 purpose why some syntax will not be obtainable is as a result of it’s not potential but (and please do ship a characteristic request). The instance of FOR XML is a wonderful 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 favor commonplace SQL/XML and SQL/JSON syntax, (which jOOQ additionally helps). However whereas I don’t very very similar to the syntax, jOOQ gained’t decide. What good would a 3rd syntax, totally invented by jOOQ be for customers? As I stated earlier than.

When will the “fixing” cease?

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

Even “easy” SQL options, resembling UNION change into extra advanced as soon as fundamental SQL syntax is modified. The semantics is already tough sufficient in SQL (and it’s totally SQL’s fault, certain), however “fixing” this stuff is rarely so simple as it might have a look at first.

Now, there are 2 exceptions to this rule:

Artificial syntax

One exception is: “Artificial syntax.” Essentially 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 may need (hopefully could have, finally). Similar to there exist SQL dialects, which “improve” the SQL commonplace, e.g.

jOOQ may be very conservative about such artificial syntax. There are a whole lot of good concepts, however few are ahead suitable. Every one among these syntaxes makes different SQL transformation options extra advanced, and every one has flaws that won’t have been addressed but (e.g. as of jOOQ 3.16, implicit joins are usually not potential in DML statements resembling UPDATE, DELETE, even when they make a whole lot of sense there as nicely. See challenge #7508).

Comfort syntax

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

choose(someFunction()); // No FROM clause
selectFrom(someTable);  // No specific SELECT record

In each instances, customers can omit clauses which may be necessary within the underlying SQL dialect, and jOOQ fills the generated SQL with an affordable default:

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

Conclusion

The concept jOOQ ought to keep on with SQL syntax on a 1:1 foundation was a big gamble I took 13 years in the past, once I made jOOQ. I wished to design jOOQ in a manner that everybody who already knew SQL would haven’t any issues studying jOOQ, as a result of every part is totally simple. The approach 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: