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Spark, Databricks: port upstream interval PRs #2614 and #2616 - #19
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This reverts commit bae1cb2.
)" This reverts commit ee51174.
Spark's multi-units interval syntax lets the string carry its own units, as in INTERVAL '1 YEAR 2 DAYS 3 HOURS', so no unit follows the literal. Databricks Runtime parses with the same grammar. A unit after a literal is still read; the expression form this gives up (INTERVAL 1 + 1 DAY) is not Spark syntax.
Address review: turning require_interval_qualifier off accepted INTERVAL 1 and read SELECT interval FROM t as SELECT INTERVAL FROM AS t. Keep it on and add supports_interval_string_without_qualifier: the value must be a literal, and only an unsigned string may omit the qualifier. INTERVAL is not reserved for these dialects, so SELECT interval FROM t reads a column.
…ter interval is arithmetic Address review: a double-quoted string is a Spark string literal, so it may be an interval value and may omit the qualifier (INTERVAL "2 months", INTERVAL "1" DAY). Only a bare number or a string after INTERVAL keeps the interval error; a signed number falls back to the identifier, so interval - 1 and INTERVAL -1 are arithmetic on the column, as in Spark. A string window frame bound stays a string literal in these dialects (RANGE BETWEEN '1 day' PRECEDING), as in Spark, rather than being read as an interval without a qualifier.
Spark's multi-units interval syntax lists several value / unit pairs, INTERVAL 10 YEAR 20 MONTH, documented as the same as the string form INTERVAL '10 YEAR 20 MONTH'. A new supports_interval_multi_units hook, enabled for SparkSqlDialect and DatabricksDialect, reads the extra pairs into that string form, so the AST is unchanged.
A double-quoted string is a Spark string literal, so it may be any value of a multi-units interval, e.g. INTERVAL "1" DAY "2" HOUR.
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Replaces #16 and #17 with the versions under upstream review, apache/datafusion-sqlparser-rs#2614 and #2616, which went further after review:
INTERVALis a column name when no literal follows (SELECT interval FROM t,interval - 1), a double-quoted string is an interval value, a bare number still requires a unit, and a string window frame bound stays a string literal.Reverts #17 and #16, then cherry-picks the five upstream commits unchanged. The
src/and test changes are identical, line for line, to the upstream PRs; only conflict context in imports and test-file tails differs. The fork's full suite (--all-features), fmt and clippy are clean.🤖 Generated with Claude Code
Note
Medium Risk
Changes core expression parsing for INTERVAL across Spark/Databricks and shared parser paths; misclassification could affect downstream SQL planners, though behavior is heavily test-covered.
Overview
Aligns Spark and Databricks interval parsing with upstream semantics by splitting “require a unit” from “unit may live inside the string literal.”
Adds
Dialect::supports_interval_string_without_qualifier()and turns it on for Spark/Databricks together withrequire_interval_qualifier() = true. Those dialects also overrideis_reserved_for_identifiersoINTERVALcan name a column when it is not followed by a literal (SELECT interval FROM t,interval - 1).Parser updates:
parse_interval()uses a newparse_interval_literal_value()path for string-without-qualifier dialects; bare numericINTERVAL 1stays an error;INTERVAL 1 + 1 DAYis rejected for that mode; double-quoted interval values are accepted; window frame bounds keep'1 day'as a string instead ofINTERVALwhen the dialect supports string intervals without qualifiers; failedINTERVALparses no longer fall back to identifiers when a number/string literal follows.Tests in common, Spark, and Databricks cover the new matrix and tighten existing interval tests to exclude the new dialect behavior.
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