COALESCE should infer correct non-null return type

[judahrand]

#19730

This is adding a test to demonstrate that the issue still exists and needs fixing. I'm yet to identify a fix.

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[judahrand]

R: @damccorm

I'm struggling to get the tests to run locally on an M1 MacBook so was hoping to be able to use the CI to demonstrate the issue. But it looks like the extensions unit tests don't run by default.

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[damccorm]

From the conversation in https://issues.apache.org/jira/browse/BEAM-7610 and related PRs, this should have been fixed by #14146

@apilloud could you take a look at this one since you have more context here?

[judahrand]

From the conversation in https://issues.apache.org/jira/browse/BEAM-7610 and related PRs, this should have been fixed by #14146

@apilloud could you take a look at this one since you have more context here?

It's an issue we're definitely having in Dataflow SQL. A query which looks roughly like this:

SELECT
    window_start,
    window_end,
    COALESCE(ARRAY_AGG(foo), []) AS col1
FROM HOP(
    (SELECT * FROM pubsub.topic.`project_id`.`topic`),
    DESCRIPTOR(event_timestamp),
    "INTERVAL 5 MINUTE",
    "INTERVAL 15 MINUTE"
) as data
GROUP BY window_start, window_end

results in an error downstream which says that Data Catalog does not support NULLABLE ARRAYS. This means that the output schema of the query must not be correctly handling the COALESCE.

[judahrand]

In fact, does the basic test not prove that this is still broken?

beam/sdks/java/extensions/sql/zetasql/src/test/java/org/apache/beam/sdk/extensions/sql/zetasql/ZetaSqlDialectSpecTest.java

Lines 458 to 476 in cf56af2

	@Test
	public void testCoalesceBasic() {
	String sql = "SELECT COALESCE(@p0, @p1, @p2) AS ColA";
	ImmutableMap<String, Value> params =
	ImmutableMap.of(
	"p0",
	Value.createSimpleNullValue(TypeKind.TYPE_STRING),
	"p1",
	Value.createStringValue("yay"),
	"p2",
	Value.createStringValue("nay"));
	PCollection<Row> stream = execute(sql, params);
	final Schema schema = Schema.builder().addNullableField("field1", FieldType.STRING).build();
	PAssert.that(stream).containsInAnyOrder(Row.withSchema(schema).addValues("yay").build());
	pipeline.run().waitUntilFinish(Duration.standardMinutes(PIPELINE_EXECUTION_WAITTIME_MINUTES));
	}

Given that the final value of the COALESCE in this test is a STRING the return type should be STRING NOT NULL but the test asserts that it is NULLABLE.

[judahrand]

This is another important detail for our particular query: according to the ZetaSQL spec[1] a NULL array and an empty array are distinct and so our query should work.

[1] https://github.com/google/zetasql/blob/master/docs/data-types.md#nulls-and-the-array-type

[damccorm]

Sorry, I wasn't clear. I'm not making a claim about whether or not this is actively an issue; I was just saying that given the conversation around the calcite upgrade I'm surprised that it is still a problem. I would have expected that upgrade to fix the problem given my loose understanding of the issue

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Codecov Report

Merging #24249 (cf56af2) into master (cf56af2) will not change coverage.
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  Misses      24286    24286           
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[damccorm]

Looks like Andrew is on vacation, @kileys could you weigh in here?

[apilloud]

Your new test is running in the SQL Precommit and passing: https://ci-beam.apache.org/job/beam_PreCommit_SQL_Commit/5807/testReport/org.apache.beam.sdk.extensions.sql.zetasql/ZetaSqlDialectSpecTest/testCoalesceNotNull/

Beam ZetaSQL has significant issues with null handling, so an issue like this existing wouldn't surprise me. I think you need a schema that supports nullable fields though? Try this:
final Schema schema = Schema.builder().addNullableField("field1", FieldType.STRING).build();

The latest release of Dataflow SQL is based on df6efe3 (somewhere between v2.38.0 and v2.39.0), which is several months old so it is possible that it has been fixed since. I know #17387 is more recent, which fixes some null bugs. Possibly try rebasing on that commit?

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[judahrand]

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I think this is still an issue.

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This pull request has been closed due to lack of activity. If you think that is incorrect, or the pull request requires review, you can revive the PR at any time.