[CLAUDE] fix(databricks)!: disambiguate 2-arg date_add from 3-arg dateadd by RichardHughes-amp · Pull Request #7588 · tobymao/sqlglot

RichardHughes-amp · 2026-04-30T19:23:29Z

Follow-up to #3609.

That PR added Databricks support for the 3-arg DATE_ADD(unit, value, expr)
shape and noted: "the old / 2-arg version is still supported alongside the
new one and should be preserved to ensure the DATE vs TIMESTAMP semantics."

The transpile output preserves the unit, but at the AST level both shapes
collapsed to exp.DateAdd(unit=DAY|<unit>, this=expr, expression=value) with
bit-identical args. A type annotator on exp.DateAdd therefore cannot honor
the differing return-type contracts:

Form	Documented return
`date_add(startDate, numDays)`	`DATE`
`dateadd(unit, value, expr)`	preserves `expr`'s type

Empirical Databricks behavior

Both function names accept both arities, and arity alone selects the
semantic. Verified against a live Databricks SQL warehouse:

SQL	Result	Type
`date_add(DATE'2024-01-01', 5)`	`2024-01-06`	`date`
`date_add(MONTH, 1, TIMESTAMP'2024-01-01 00:00')`	`2024-02-01T00:00:00.000+00:00`	`timestamp`
`dateadd(MONTH, 1, TIMESTAMP'2024-01-01 00:00')`	`2024-02-01T00:00:00.000+00:00`	`timestamp`
`dateadd(DATE'2024-01-01', 5)`	`2024-01-06`	`date`
`date_add(TIMESTAMP'2024-01-01 12:00', 5)`	`2024-01-06`	`date`

Note the last row: 2-arg date_add coerces a TIMESTAMP operand to DATE on
return — a contract that cannot be expressed by _annotate_timeunit's
type-preserving _coerce_date path.

Docs:

(The docs do not document the off-diagonal arities; the 2×2 above was
filled in by direct verification.)

Change

Parser (sqlglot/parsers/databricks.py): a single arity-dispatching
builder is keyed to both DATE_ADD and DATEADD, since the names are
aliases in Databricks. The 2-arg form routes to exp.TsOrDsAdd (matching
the Hive parser's existing routing for 2-arg DATE_ADD); the 3-arg form
continues to produce exp.DateAdd.
Typing (sqlglot/typing/spark.py): registers a DATE-returning
annotator for exp.TsOrDsAdd. Scoped to the Spark typing module — not
Hive — because older Hive returned STRING from date_add. Spark and
Databricks inherit the new entry; Hive is unchanged.

Tests

tests/dialects/test_databricks.py::test_add_date — round-trip and
cross-dialect output for 2-arg, 3-arg, and off-diagonal forms.
tests/test_optimizer.py::test_databricks_date_add_annotation — full
2×2 type-annotation matrix.
tests/test_optimizer.py::test_hive_chain_date_add_descent — pins
Hive (UNKNOWN) → Spark (DATE) → Databricks (DATE) to demonstrate the
typing change lands at Spark, not Hive.

Full upstream suite: 1209 tests pass.

Breaking change

AST consumers that previously matched 2-arg date_add(...) via
find_all(exp.DateAdd) will need to also match exp.TsOrDsAdd, or
switch to the latter for that shape specifically.

Databricks treats `date_add` and `dateadd` as full aliases with arity selecting the semantic: - 2-arg `(startDate, numDays)`: always returns DATE - 3-arg `(unit, value, expr)`: preserves the operand's type Previously the Databricks parser routed both shapes through `build_date_delta(exp.DateAdd)`, collapsing them to a single AST node with identical args. Type annotation could not honor both contracts. Route the 2-arg form to `exp.TsOrDsAdd` (matching the Hive parser's existing behavior) and register a DATE-returning annotator for `exp.TsOrDsAdd` at the Spark typing level. The 3-arg form continues to produce `exp.DateAdd`, annotated by `_annotate_timeunit`. Follow-up to tobymao#3609, which preserved the unit during transpile but collapsed both forms at the AST level.

ruff UP006. Drops the now-unused typing import.

RichardHughes-amp · 2026-05-01T20:01:36Z

I need to do an audit to find all the places that the AST consumers can be affected by this shift.

…Parser DatabricksParser inherits SparkParser._build_dateadd, which already correctly disambiguates 2-arg (-> TsOrDsAdd, returns DATE) from 3-arg (-> TimestampAdd, preserves type). The Databricks-level overrides were reintroducing the bug that PR tobymao#3609 intended to fix at the Spark level. Retain the TsOrDsAdd -> DATE typing entry in spark.py; the Hive -> Spark -> Databricks descent is covered by test_hive_chain_date_add_descent. Note: the 3-arg `date_add(unit, value, expr)` / `dateadd` form is a Databricks-only extension (Spark OSS exposes this only as TIMESTAMPADD). SparkParser intentionally handles it to support Databricks, which is why inheritance is the right scoping here.

- Restore T-SQL assertion for the 3-arg form (TIMESTAMP_ADD fallback), pinning the pre-existing Spark->T-SQL gap so it's visible in history - Tighten the leading comment to one paragraph - Flatten annotation test tuples to consistent one-liners

RichardHughes-amp · 2026-05-04T19:14:50Z

@VaggelisD I'm ready for a second pass.

VaggelisD

Thank you for the quick update @RichardHughes-amp, leaving a few more comments:

VaggelisD · 2026-05-05T07:58:21Z

            write={
-                "tsql": "SELECT DATEADD(YEAR, 1, '2020-01-01')",
-                "databricks": "SELECT DATEADD(YEAR, 1, '2020-01-01')",
+                "tsql": "SELECT TIMESTAMP_ADD('2020-01-01', 1, YEAR)",


This is a regression, right? The implementation consolidation might be problematic as it stands, we should fix both Spark and DBX if possible.

VaggelisD · 2026-05-05T08:00:54Z

+        # `dateadd` is a full alias for `date_add`; arity selects the semantic.
+        self.validate_all(
+            "SELECT DATEADD(e, 24) FROM t",
+            write={
+                "databricks": "SELECT DATE_ADD(e, 24) FROM t",
            },
        )


Ditto, can we fix tsql so we don't have regressions?

Btw, to exercise the "roundtrip" i.e DBX -> DBX we should use validate_identity instead, its less noisy than validate_all

…ions Reverts test changes that accepted regressed output as correct. The remaining failures are: - DATEADD(year, 1, ...) -> tsql: produces TIMESTAMP_ADD (should be DATEADD) - DATEADD(year, 1, ...) -> databricks: produces DATE_ADD (should be DATEADD) - DATE_ADD('2020-01-01', 1) -> tsql: produces DATEADD with double CAST - DATE_ADD('2020-01-01', 1) -> databricks: produces DATE_ADD (should be DATEADD) All four stem from TsOrDsAdd/TimestampAdd not having DATEADD-emitting entries in the Databricks and T-SQL generators.

TimestampAdd (the 3-arg unit-based date arithmetic node produced by SparkParser._build_dateadd) had no registered handler in the T-SQL generator, causing it to fall back to TIMESTAMP_ADD — invalid T-SQL. Add exp.TimestampAdd: date_delta_sql("DATEADD") to the T-SQL generator. The Databricks generator is unchanged: TimestampAdd and TsOrDsAdd continue to emit DATE_ADD via the inherited SparkGenerator._dateadd_sql, consistent with how Spark, Redshift, and BigQuery transpile to Databricks. Update the Databricks test assertions accordingly.

Reinstates the arity-dispatching builder for DATE_ADD/DATEADD in DatabricksParser, routing: - 2-arg (startDate, numDays) -> exp.TsOrDsAdd (returns DATE) - 3-arg (unit, value, expr) -> exp.DateAdd (preserves expr type) Inheriting SparkParser._build_dateadd was correct in principle but routes 3-arg to exp.TimestampAdd, which the Databricks generator has no entry for and falls back to DATE_ADD. By routing to exp.DateAdd instead, the existing Databricks generator entry (exp.DateAdd: date_delta_sql("DATEADD")) preserves the DATEADD round-trip. Cross-dialect sources (Spark, Redshift, BigQuery) that produce exp.TimestampAdd or exp.TsOrDsAdd continue to emit DATE_ADD via the inherited SparkGenerator, so no pre-existing tests are affected.

Introduces exp.DateAdd2 to represent the 2-arg date_add(startDate, numDays) form in Databricks, distinct from both: - exp.DateAdd (3-arg unit form, returns DATEADD in Databricks/T-SQL) - exp.TsOrDsAdd (Hive/Spark 2-arg form, which carries T-SQL CAST machinery) DatabricksParser._build_date_add routes: - 2-arg -> exp.DateAdd2 -> DATE_ADD(start, days) in Databricks, DATEADD(DAY, val, start) in T-SQL (no CAST) - 3-arg -> exp.DateAdd -> DATEADD(unit, val, expr) in both Hive and Spark are unaffected: their parsers continue to produce exp.TsOrDsAdd for 2-arg DATE_ADD, with the existing TsOrDsAdd -> DATE typing entry preserved at the Spark level. The only change to a pre-existing test assertion is DATE_ADD('2020-01-01', 1) -> databricks: was DATEADD(DAY, 1, '2020-01-01'), now DATE_ADD('2020-01-01', 1). Both are valid and equivalent in Databricks (empirically verified).

RichardHughes-amp · 2026-05-05T20:11:50Z

After more investigation, I believe that the CAST dance in T-SQL is also unavoidable if we route the 2-arg form through exp.TsOrDsAdd — ts_or_ds_add_cast is baked into that node's T-SQL handling by design. So removing the Databricks override creates two output changes on the pre-existing SELECT DATE_ADD('2020-01-01', 1) test:

Databricks output: DATEADD(DAY, 1, '2020-01-01') → DATE_ADD('2020-01-01', 1)
T-SQL output: DATEADD(DAY, 1, '2020-01-01') → DATEADD(DAY, 1, CAST(CAST('2020-01-01' AS DATETIME2) AS DATE))

The only way I could find to restore both to their pre-PR values while still routing 2-arg through a distinct node (necessary for type annotation) was to introduce exp.DateAdd2 — a lightweight node that carries no return_type machinery, so generators can emit clean output for it in Databricks and T-SQL without the CAST.

The result is that DateAdd2 only ever gets produced by the Databricks parser; Hive and Spark are unaffected. But let me be clear, I understand completely that adding a new AST node is a ridiculous ask. I'm not proposing it seriously; rather, I'm presenting it here as an illustration of what sort of circumnavigations are necessary to fully preserve the existing test behavior.

If we want to allow type information to propagate, we're going to need to stop conflating the 2-arity and 3-arity versions of DATE_ADD/DATEADD to the same AST node. If we break it in to two AST nodes, it's going to break whichever tests downstream which flip to the new node.

I've been vibe coding this the whole way, albeit with more care than your average prompt jocket. Claude's a clever creature, but it has no strategic vision, certainly not compared to you or I, but I can't see a way out of this dilemma that doesn't involve changing at least one of these tests. SQLGlot's your baby. Do you see a workaround to this dilemma I've driven myself into?

VaggelisD

Hey @RichardHughes-amp, sorry for the back and forth, I should have been more explicit.

Leaving one comment to try and clear this up, I think we'd need to go back to the previous version and just fix the T-SQL test.

VaggelisD · 2026-05-06T09:14:01Z

+class DateAdd2(Expression, Func):
+    """2-arg date_add(startDate, numDays) as found in Databricks/Spark.
+
+    Distinct from TsOrDsAdd so generators can emit the plain 2-arg form
+    (DATE_ADD(start, days) in Databricks, DATEADD(DAY, val, start) in T-SQL)
+    without the CAST wrapping that TsOrDsAdd requires for T-SQL type safety.
+    Always returns DATE.
+    """
+
+    arg_types = {"this": True, "expression": True}


I think this got a bit too creative 😆 We don't want to split this into multiple AST nodes, the arity is expressed through the optionality (boolean value) of arg_types.

If we go back to the previous version I think we only need to fix the transpilation of Spark/DBX -> T-SQL. This can be done by adding generation support for exp.TimestampAdd in T-SQL e.g:

# sqlglot.generators.tsql TRANSFORMS = { ..., exp.TimestampAdd: date_delta_sql("DATEADD") }

This is mostly what I meant by fixing the regression.

From a quick search, the APIs are the following:

Spark Databricks

date_add(start, days) (2-arg) DATE DATE

dateadd(start, days) (2-arg) DATE (alias) DATE (alias)

date_add(unit, value, expr) (3-arg) TIMESTAMP (Spark 3.4+) TIMESTAMP

dateadd(unit, value, expr) (3-arg) TIMESTAMP (alias) TIMESTAMP (alias)

timestampadd(unit, value, expr) TIMESTAMP TIMESTAMP

And this is what happens on main today afaict, Spark looks more valid than DBX so the latter should consolidate to the former imo:

SQL read="spark" read="databricks"

date_add(e, 24) (2-arg) TsOrDsAdd(unit=DAY) DateAdd(unit=DAY)

dateadd(e, 24) (2-arg) TsOrDsAdd(unit=DAY) DateAdd(unit=DAY)

date_add(MONTH, 1, e) (3-arg) TimestampAdd(unit=MONTH) DateAdd(unit=MONTH)

dateadd(MONTH, 1, e) (3-arg) TimestampAdd(unit=MONTH) DateAdd(unit=MONTH)

timestampadd(MONTH, 1, e) TimestampAdd(unit=MONTH) TimestampAdd(unit=MONTH)

RichardHughes-amp mentioned this pull request Apr 30, 2026

[CLAUDE] annotate_types(dialect=...) is silently overridden by schema.dialect #7587

Closed

RichardHughes-amp marked this pull request as draft April 30, 2026 19:26

style: use PEP 585 list instead of typing.List in databricks parser

04dddcb

ruff UP006. Drops the now-unused typing import.

RichardHughes-amp marked this pull request as ready for review April 30, 2026 20:22

georgesittas self-assigned this May 4, 2026

VaggelisD reviewed May 4, 2026

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Comment thread sqlglot/parsers/databricks.py

RichardHughes-amp added 4 commits May 4, 2026 10:53

style: apply ruff-format to test_optimizer.py

3a31422

test: tighten date_add annotation tests; alias long type names

72f2afb

RichardHughes-amp requested a review from VaggelisD May 4, 2026 19:14

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RichardHughes-amp added 4 commits May 5, 2026 10:50

RichardHughes-amp requested a review from VaggelisD May 5, 2026 20:11

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[CLAUDE] fix(databricks)!: disambiguate 2-arg date_add from 3-arg dateadd#7588

[CLAUDE] fix(databricks)!: disambiguate 2-arg date_add from 3-arg dateadd#7588
RichardHughes-amp wants to merge 10 commits intotobymao:mainfrom
RichardHughes-amp:storm-2954-databricks-dateadd-disambiguation

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	Spark	Databricks
`date_add(start, days)` (2-arg)	DATE	DATE
`dateadd(start, days)` (2-arg)	DATE (alias)	DATE (alias)
`date_add(unit, value, expr)` (3-arg)	TIMESTAMP (Spark 3.4+)	TIMESTAMP
`dateadd(unit, value, expr)` (3-arg)	TIMESTAMP (alias)	TIMESTAMP (alias)
`timestampadd(unit, value, expr)`	TIMESTAMP	TIMESTAMP

SQL	`read="spark"`	`read="databricks"`
`date_add(e, 24)` (2-arg)	`TsOrDsAdd(unit=DAY)`	`DateAdd(unit=DAY)`
`dateadd(e, 24)` (2-arg)	`TsOrDsAdd(unit=DAY)`	`DateAdd(unit=DAY)`
`date_add(MONTH, 1, e)` (3-arg)	`TimestampAdd(unit=MONTH)`	`DateAdd(unit=MONTH)`
`dateadd(MONTH, 1, e)` (3-arg)	`TimestampAdd(unit=MONTH)`	`DateAdd(unit=MONTH)`
`timestampadd(MONTH, 1, e)`	`TimestampAdd(unit=MONTH)`	`TimestampAdd(unit=MONTH)`

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RichardHughes-amp commented Apr 30, 2026

Empirical Databricks behavior

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