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

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

Most just lately right here in a Youtube remark reply to a current jOOQ/kotlin discuss. Let’s take a look at why jOOQ didn’t fall into this entice of attempting 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 type, as we “command” the database to execute an announcement. Widespread instructions embody:

• 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 typically extra mathematical (some greater than others). Quite a lot of criticism concerning the SQL language is that it doesn’t “compose” (in its native type).

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

FROM e book
WHERE e book.title LIKE 'A%'
SELECT e book.id, e book.title

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

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

The advantages of this may 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 method, this ordering can be in line with what some RDBMS carried out when RETURNING information from DML statements, comparable to:

INSERT INTO e book (id, title)
VALUES (3, 'The Guide')
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 information. The “projection” is extra of an afterthought. A utility that’s often helpful, therefore RETURNING will be positioned on the finish.

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

SELECT id, created_at
FROM FINAL TABLE (
  INSERT INTO e book (id, title)
  VALUES (3, 'The Guide')
) AS e book

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 at all times must lookup the precise location of the OUTPUT clause):

INSERT INTO e book (id, title)
OUTPUT id, created_at
VALUES (3, 'The Guide')

Cypher question language

Most likely value mentioning right here is that there exists a contemporary question language on the market that’s sufficiently standard to be thought of 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 an announcement (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 distinct information paradigm (the community mannequin versus the relational mannequin), I’ve at all times discovered the Cypher Question Language to be usually superior to SQL by way of syntax, no less than on a excessive degree. 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 type of drawback. However SQL is right here, and it’s 50 years previous, and it’ll keep. It gained’t be fastened.

That’s one thing that simply needs to be accepted:

SQL gained’t be fastened

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

It at all times does so in an idiomatic, SQL type method. For those who’re studying the SQL customary, or if you happen to’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 persistently bizarre, relying in your tastes.

For jOOQ, one of many principal success components has at all times been to be as shut as attainable to this imaginative and prescient of what SQL actually is by way of syntax. Quite a lot of of us 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 document : ctx.fetch(
    """
    SELECT id, title
    FROM e book
    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 in all probability use jOOQ even for these functions as properly).

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. Nevertheless, it could 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 if you happen to 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 may seem like a lot better at first (e.g. to separate SELECT and DISTINCT, which shouldn’t be situated so carefully collectively):

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

However the bizarre caveats would nonetheless not disappear, particularly that 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’ll by no means be fastened, and as such, an API like jOOQ can be a lot more durable to be taught that it needs to be. Some competing APIs observe 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(value)
FROM coffees

It’s arguably a bit extra idiomatic. It seems to be like abnormal Scala assortment API utilization, eradicating the SQL really feel from the equation. In any case, the same old 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.rely(), StarWarsFilms.director)
  .selectAll()
  .groupBy(StarWarsFilms.director)

The API introduces new phrases, e.g.

• slice which suggests 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”, equivalent to SQL WHERE

Artificial comfort syntax as an alternative of “fixing” SQL

jOOQ doesn’t observe down this street and by no means will. SQL is what it’s, and jOOQ gained’t have the ability 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 can help you write precisely what you take into account by way of SQL characteristic. I imply, would it not actually make sense to help CONNECT BY in Slick or Uncovered? Most likely 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 is just not obtainable is as a result of it’s not attainable 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 circumstances, it’s not very highly effective for complicated ones. I a lot choose customary 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, fully invented by jOOQ be for customers? As I mentioned earlier than.

When will the “fixing” cease?

It’ll by no means cease. The 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 at all times straightforward 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 kinds of superior SQL use-cases. Simply take a look at their challenge trackers for characteristic requests like CTEs. The reply is at all times: “Use native SQL.”

Even “easy” SQL options, comparable to UNION change into extra complicated as soon as fundamental SQL syntax is modified. The semantics is already difficult sufficient in SQL (and it’s fully SQL’s fault, certain), however “fixing” these items is rarely 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.” 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 can have, ultimately). Identical to there exist SQL dialects, which “improve” the SQL customary, e.g.

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

In each circumstances, 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 comparable
• A SELECT * projection declaration, or one thing comparable

Conclusion

The concept jOOQ ought to keep on with SQL syntax on a 1:1 foundation was of venture I took 13 years in the past, after I made jOOQ. I wished to design jOOQ in a method that everybody who already knew SQL would don’t have any issues studying jOOQ, as a result of every little thing 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: