Adding upstream version 26.19.0.
Signed-off-by: Daniel Baumann <daniel@debian.org>
This commit is contained in:
parent
873e685933
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GPG key ID:
FBB4F0E80A80222F
98 changed files with 67345 additions and 65319 deletions
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@ -16,6 +16,7 @@ from sqlglot.helper import logger as helper_logger
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from sqlglot.parser import logger as parser_logger
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from tests.dialects.test_dialect import Validator
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from sqlglot.optimizer.annotate_types import annotate_types
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from sqlglot.optimizer.qualify import qualify
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class TestBigQuery(Validator):
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@ -23,67 +24,6 @@ class TestBigQuery(Validator):
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maxDiff = None
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def test_bigquery(self):
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self.validate_all(
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"EXTRACT(HOUR FROM DATETIME(2008, 12, 25, 15, 30, 00))",
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write={
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"bigquery": "EXTRACT(HOUR FROM DATETIME(2008, 12, 25, 15, 30, 00))",
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"duckdb": "EXTRACT(HOUR FROM MAKE_TIMESTAMP(2008, 12, 25, 15, 30, 00))",
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"snowflake": "DATE_PART(HOUR, TIMESTAMP_FROM_PARTS(2008, 12, 25, 15, 30, 00))",
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},
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)
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self.validate_identity(
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"""CREATE TEMPORARY FUNCTION FOO()
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RETURNS STRING
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LANGUAGE js AS
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'return "Hello world!"'""",
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pretty=True,
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)
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self.validate_identity(
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"[a, a(1, 2,3,4444444444444444, tttttaoeunthaoentuhaoentuheoantu, toheuntaoheutnahoeunteoahuntaoeh), b(3, 4,5), c, d, tttttttttttttttteeeeeeeeeeeeeett, 12312312312]",
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"""[
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a,
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a(
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1,
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2,
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3,
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4444444444444444,
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tttttaoeunthaoentuhaoentuheoantu,
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toheuntaoheutnahoeunteoahuntaoeh
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),
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b(3, 4, 5),
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c,
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d,
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tttttttttttttttteeeeeeeeeeeeeett,
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12312312312
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]""",
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pretty=True,
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)
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self.validate_all(
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"SELECT STRUCT(1, 2, 3), STRUCT(), STRUCT('abc'), STRUCT(1, t.str_col), STRUCT(1 as a, 'abc' AS b), STRUCT(str_col AS abc)",
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write={
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"bigquery": "SELECT STRUCT(1, 2, 3), STRUCT(), STRUCT('abc'), STRUCT(1, t.str_col), STRUCT(1 AS a, 'abc' AS b), STRUCT(str_col AS abc)",
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"duckdb": "SELECT {'_0': 1, '_1': 2, '_2': 3}, {}, {'_0': 'abc'}, {'_0': 1, '_1': t.str_col}, {'a': 1, 'b': 'abc'}, {'abc': str_col}",
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"hive": "SELECT STRUCT(1, 2, 3), STRUCT(), STRUCT('abc'), STRUCT(1, t.str_col), STRUCT(1, 'abc'), STRUCT(str_col)",
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"spark2": "SELECT STRUCT(1, 2, 3), STRUCT(), STRUCT('abc'), STRUCT(1, t.str_col), STRUCT(1 AS a, 'abc' AS b), STRUCT(str_col AS abc)",
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"spark": "SELECT STRUCT(1, 2, 3), STRUCT(), STRUCT('abc'), STRUCT(1, t.str_col), STRUCT(1 AS a, 'abc' AS b), STRUCT(str_col AS abc)",
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"snowflake": "SELECT OBJECT_CONSTRUCT('_0', 1, '_1', 2, '_2', 3), OBJECT_CONSTRUCT(), OBJECT_CONSTRUCT('_0', 'abc'), OBJECT_CONSTRUCT('_0', 1, '_1', t.str_col), OBJECT_CONSTRUCT('a', 1, 'b', 'abc'), OBJECT_CONSTRUCT('abc', str_col)",
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# fallback to unnamed without type inference
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"trino": "SELECT ROW(1, 2, 3), ROW(), ROW('abc'), ROW(1, t.str_col), CAST(ROW(1, 'abc') AS ROW(a INTEGER, b VARCHAR)), ROW(str_col)",
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},
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)
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self.validate_all(
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"PARSE_TIMESTAMP('%Y-%m-%dT%H:%M:%E6S%z', x)",
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write={
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"bigquery": "PARSE_TIMESTAMP('%Y-%m-%dT%H:%M:%E6S%z', x)",
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"duckdb": "STRPTIME(x, '%Y-%m-%dT%H:%M:%S.%f%z')",
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},
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)
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self.validate_identity(
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"PARSE_TIMESTAMP('%Y-%m-%dT%H:%M:%E*S%z', x)",
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"PARSE_TIMESTAMP('%Y-%m-%dT%H:%M:%E*S%z', x)",
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)
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for prefix in ("c.db.", "db.", ""):
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with self.subTest(f"Parsing {prefix}INFORMATION_SCHEMA.X into a Table"):
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table = self.parse_one(f"`{prefix}INFORMATION_SCHEMA.X`", into=exp.Table)
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@ -115,6 +55,7 @@ LANGUAGE js AS
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select_with_quoted_udf = self.validate_identity("SELECT `p.d.UdF`(data) FROM `p.d.t`")
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self.assertEqual(select_with_quoted_udf.selects[0].name, "p.d.UdF")
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self.validate_identity("PARSE_TIMESTAMP('%Y-%m-%dT%H:%M:%E*S%z', x)")
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self.validate_identity("SELECT ARRAY_CONCAT([1])")
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self.validate_identity("SELECT * FROM READ_CSV('bla.csv')")
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self.validate_identity("CAST(x AS STRUCT<list ARRAY<INT64>>)")
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@ -320,7 +261,80 @@ LANGUAGE js AS
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"SELECT CAST(1 AS BYTEINT)",
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"SELECT CAST(1 AS INT64)",
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)
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self.validate_identity(
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"""CREATE TEMPORARY FUNCTION FOO()
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RETURNS STRING
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LANGUAGE js AS
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'return "Hello world!"'""",
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pretty=True,
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)
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self.validate_identity(
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"[a, a(1, 2,3,4444444444444444, tttttaoeunthaoentuhaoentuheoantu, toheuntaoheutnahoeunteoahuntaoeh), b(3, 4,5), c, d, tttttttttttttttteeeeeeeeeeeeeett, 12312312312]",
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"""[
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a,
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a(
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1,
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2,
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3,
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4444444444444444,
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tttttaoeunthaoentuhaoentuheoantu,
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toheuntaoheutnahoeunteoahuntaoeh
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),
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b(3, 4, 5),
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c,
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d,
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tttttttttttttttteeeeeeeeeeeeeett,
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12312312312
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]""",
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pretty=True,
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)
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self.validate_all(
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"SELECT purchases, LAST_VALUE(item) OVER item_window AS most_popular FROM Produce WINDOW item_window AS (PARTITION BY purchases ORDER BY purchases ROWS BETWEEN 2 PRECEDING AND 2 FOLLOWING)",
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write={
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"bigquery": "SELECT purchases, LAST_VALUE(item) OVER item_window AS most_popular FROM Produce WINDOW item_window AS (PARTITION BY purchases ORDER BY purchases ROWS BETWEEN 2 PRECEDING AND 2 FOLLOWING)",
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"clickhouse": "SELECT purchases, LAST_VALUE(item) OVER item_window AS most_popular FROM Produce WINDOW item_window AS (PARTITION BY purchases ORDER BY purchases NULLS FIRST ROWS BETWEEN 2 PRECEDING AND 2 FOLLOWING)",
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"databricks": "SELECT purchases, LAST_VALUE(item) OVER item_window AS most_popular FROM Produce WINDOW item_window AS (PARTITION BY purchases ORDER BY purchases ROWS BETWEEN 2 PRECEDING AND 2 FOLLOWING)",
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"duckdb": "SELECT purchases, LAST_VALUE(item) OVER item_window AS most_popular FROM Produce WINDOW item_window AS (PARTITION BY purchases ORDER BY purchases NULLS FIRST ROWS BETWEEN 2 PRECEDING AND 2 FOLLOWING)",
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"mysql": "SELECT purchases, LAST_VALUE(item) OVER item_window AS most_popular FROM Produce WINDOW item_window AS (PARTITION BY purchases ORDER BY purchases ROWS BETWEEN 2 PRECEDING AND 2 FOLLOWING)",
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"oracle": "SELECT purchases, LAST_VALUE(item) OVER item_window AS most_popular FROM Produce WINDOW item_window AS (PARTITION BY purchases ORDER BY purchases NULLS FIRST ROWS BETWEEN 2 PRECEDING AND 2 FOLLOWING)",
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"postgres": "SELECT purchases, LAST_VALUE(item) OVER item_window AS most_popular FROM Produce WINDOW item_window AS (PARTITION BY purchases ORDER BY purchases NULLS FIRST ROWS BETWEEN 2 PRECEDING AND 2 FOLLOWING)",
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"presto": "SELECT purchases, LAST_VALUE(item) OVER (PARTITION BY purchases ORDER BY purchases NULLS FIRST ROWS BETWEEN 2 PRECEDING AND 2 FOLLOWING) AS most_popular FROM Produce",
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"redshift": "SELECT purchases, LAST_VALUE(item) OVER (PARTITION BY purchases ORDER BY purchases NULLS FIRST ROWS BETWEEN 2 PRECEDING AND 2 FOLLOWING) AS most_popular FROM Produce",
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"snowflake": "SELECT purchases, LAST_VALUE(item) OVER (PARTITION BY purchases ORDER BY purchases NULLS FIRST ROWS BETWEEN 2 PRECEDING AND 2 FOLLOWING) AS most_popular FROM Produce",
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"spark": "SELECT purchases, LAST_VALUE(item) OVER item_window AS most_popular FROM Produce WINDOW item_window AS (PARTITION BY purchases ORDER BY purchases ROWS BETWEEN 2 PRECEDING AND 2 FOLLOWING)",
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"trino": "SELECT purchases, LAST_VALUE(item) OVER item_window AS most_popular FROM Produce WINDOW item_window AS (PARTITION BY purchases ORDER BY purchases NULLS FIRST ROWS BETWEEN 2 PRECEDING AND 2 FOLLOWING)",
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"tsql": "SELECT purchases, LAST_VALUE(item) OVER item_window AS most_popular FROM Produce WINDOW item_window AS (PARTITION BY purchases ORDER BY purchases ROWS BETWEEN 2 PRECEDING AND 2 FOLLOWING)",
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},
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)
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self.validate_all(
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"EXTRACT(HOUR FROM DATETIME(2008, 12, 25, 15, 30, 00))",
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write={
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"bigquery": "EXTRACT(HOUR FROM DATETIME(2008, 12, 25, 15, 30, 00))",
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"duckdb": "EXTRACT(HOUR FROM MAKE_TIMESTAMP(2008, 12, 25, 15, 30, 00))",
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"snowflake": "DATE_PART(HOUR, TIMESTAMP_FROM_PARTS(2008, 12, 25, 15, 30, 00))",
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},
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)
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self.validate_all(
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"SELECT STRUCT(1, 2, 3), STRUCT(), STRUCT('abc'), STRUCT(1, t.str_col), STRUCT(1 as a, 'abc' AS b), STRUCT(str_col AS abc)",
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write={
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"bigquery": "SELECT STRUCT(1, 2, 3), STRUCT(), STRUCT('abc'), STRUCT(1, t.str_col), STRUCT(1 AS a, 'abc' AS b), STRUCT(str_col AS abc)",
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"duckdb": "SELECT {'_0': 1, '_1': 2, '_2': 3}, {}, {'_0': 'abc'}, {'_0': 1, '_1': t.str_col}, {'a': 1, 'b': 'abc'}, {'abc': str_col}",
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"hive": "SELECT STRUCT(1, 2, 3), STRUCT(), STRUCT('abc'), STRUCT(1, t.str_col), STRUCT(1, 'abc'), STRUCT(str_col)",
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"spark2": "SELECT STRUCT(1, 2, 3), STRUCT(), STRUCT('abc'), STRUCT(1, t.str_col), STRUCT(1 AS a, 'abc' AS b), STRUCT(str_col AS abc)",
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"spark": "SELECT STRUCT(1, 2, 3), STRUCT(), STRUCT('abc'), STRUCT(1, t.str_col), STRUCT(1 AS a, 'abc' AS b), STRUCT(str_col AS abc)",
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"snowflake": "SELECT OBJECT_CONSTRUCT('_0', 1, '_1', 2, '_2', 3), OBJECT_CONSTRUCT(), OBJECT_CONSTRUCT('_0', 'abc'), OBJECT_CONSTRUCT('_0', 1, '_1', t.str_col), OBJECT_CONSTRUCT('a', 1, 'b', 'abc'), OBJECT_CONSTRUCT('abc', str_col)",
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# fallback to unnamed without type inference
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"trino": "SELECT ROW(1, 2, 3), ROW(), ROW('abc'), ROW(1, t.str_col), CAST(ROW(1, 'abc') AS ROW(a INTEGER, b VARCHAR)), ROW(str_col)",
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},
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)
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self.validate_all(
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"PARSE_TIMESTAMP('%Y-%m-%dT%H:%M:%E6S%z', x)",
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write={
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"bigquery": "PARSE_TIMESTAMP('%Y-%m-%dT%H:%M:%E6S%z', x)",
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"duckdb": "STRPTIME(x, '%Y-%m-%dT%H:%M:%S.%f%z')",
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},
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)
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self.validate_all(
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"SELECT DATE_SUB(CURRENT_DATE(), INTERVAL 2 DAY)",
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write={
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@ -1684,6 +1698,39 @@ WHERE
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"EXPORT DATA WITH CONNECTION myproject.us.myconnection OPTIONS (URI='gs://path*.csv.gz', FORMAT='CSV') AS SELECT * FROM all_rows"
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)
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self.validate_all(
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"SELECT * FROM t1, UNNEST(`t1`) AS `col`",
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read={
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"duckdb": 'SELECT * FROM t1, UNNEST("t1") "t1" ("col")',
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},
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write={
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"bigquery": "SELECT * FROM t1, UNNEST(`t1`) AS `col`",
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"redshift": 'SELECT * FROM t1, "t1" AS "col"',
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},
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)
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self.validate_all(
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"SELECT * FROM t, UNNEST(`t2`.`t3`) AS `col`",
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read={
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"duckdb": 'SELECT * FROM t, UNNEST("t1"."t2"."t3") "t1" ("col")',
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},
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write={
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"bigquery": "SELECT * FROM t, UNNEST(`t2`.`t3`) AS `col`",
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"redshift": 'SELECT * FROM t, "t2"."t3" AS "col"',
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},
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)
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self.validate_all(
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"SELECT * FROM t1, UNNEST(`t1`.`t2`.`t3`.`t4`) AS `col`",
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read={
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"duckdb": 'SELECT * FROM t1, UNNEST("t1"."t2"."t3"."t4") "t3" ("col")',
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},
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write={
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"bigquery": "SELECT * FROM t1, UNNEST(`t1`.`t2`.`t3`.`t4`) AS `col`",
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"redshift": 'SELECT * FROM t1, "t1"."t2"."t3"."t4" AS "col"',
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},
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)
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def test_errors(self):
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with self.assertRaises(TokenError):
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transpile("'\\'", read="bigquery")
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@ -2489,3 +2536,20 @@ OPTIONS (
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information_schema_sql[table_meta["start"] : table_meta["end"] + 1]
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== "`region.INFORMATION_SCHEMA.COLUMNS`"
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)
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def test_override_normalization_strategy(self):
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sql = "SELECT * FROM p.d.t"
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ast = self.parse_one(sql)
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qualified = qualify(ast.copy(), dialect="bigquery,normalization_strategy=uppercase")
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self.assertEqual(qualified.sql("bigquery"), "SELECT * FROM `P`.`D`.`T` AS `T`")
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from sqlglot.dialects import BigQuery
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from sqlglot.dialects.dialect import NormalizationStrategy
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try:
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BigQuery.NORMALIZATION_STRATEGY = NormalizationStrategy.UPPERCASE
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qualified = qualify(ast.copy(), dialect="bigquery,normalization_strategy=uppercase")
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self.assertEqual(qualified.sql("bigquery"), "SELECT * FROM `P`.`D`.`T` AS `T`")
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finally:
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BigQuery.NORMALIZATION_STRATEGY = NormalizationStrategy.CASE_INSENSITIVE
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