Adding upstream version 20.9.0.
Signed-off-by: Daniel Baumann <daniel@debian.org>
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144 changed files with 78309 additions and 59609 deletions
133
tests/fixtures/optimizer/optimizer.sql
vendored
133
tests/fixtures/optimizer/optimizer.sql
vendored
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@ -626,8 +626,7 @@ SELECT
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"_q_0"."G" AS "G",
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"_q_0"."'x'" AS "'x'",
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"_q_0"."'y'" AS "'y'"
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FROM "U" AS "U" PIVOT(SUM("U"."F") FOR "U"."H" IN ('x', 'y')) AS "_q_0"
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;
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FROM "U" AS "U" PIVOT(SUM("U"."F") FOR "U"."H" IN ('x', 'y')) AS "_q_0";
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# title: selecting all columns from a pivoted source and generating spark
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# note: spark doesn't allow pivot aliases or qualified columns for the pivot's "field" (`h`)
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@ -644,6 +643,110 @@ FROM (
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FROM `u` AS `u` PIVOT(SUM(`u`.`f`) FOR `h` IN ('x', 'y'))
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) AS `_q_0`;
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# title: selecting all columns from a pivoted source, pivot has column aliases
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# execute: false
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# dialect: snowflake
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WITH source AS (
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SELECT
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id,
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key,
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value,
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timestamp_1,
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timestamp_2
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FROM DB_NAME.SCHEMA_NAME.TABLE_NAME
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),
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enriched AS (
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SELECT * FROM source
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PIVOT(MAX(value) FOR key IN ('a', 'b', 'c'))
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AS final (id, timestamp_1, timestamp_2, col_1, col_2, col_3)
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)
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SELECT id, timestamp_1 FROM enriched;
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WITH "SOURCE" AS (
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SELECT
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"TABLE_NAME"."ID" AS "ID",
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"TABLE_NAME"."KEY" AS "KEY",
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"TABLE_NAME"."VALUE" AS "VALUE",
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"TABLE_NAME"."TIMESTAMP_1" AS "TIMESTAMP_1",
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"TABLE_NAME"."TIMESTAMP_2" AS "TIMESTAMP_2"
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FROM "DB_NAME"."SCHEMA_NAME"."TABLE_NAME" AS "TABLE_NAME"
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)
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SELECT
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"FINAL"."ID" AS "ID",
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"FINAL"."TIMESTAMP_1" AS "TIMESTAMP_1"
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FROM "SOURCE" AS "SOURCE" PIVOT(MAX("SOURCE"."VALUE") FOR "SOURCE"."KEY" IN ('a', 'b', 'c')) AS "FINAL"("ID", "TIMESTAMP_1", "TIMESTAMP_2", "COL_1", "COL_2", "COL_3");
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# title: unpivoted table source with a single value column, unpivot columns can't be qualified
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# execute: false
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# dialect: snowflake
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SELECT * FROM m_sales AS m_sales(empid, dept, jan, feb) UNPIVOT(sales FOR month IN (jan, feb)) ORDER BY empid;
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SELECT
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"_q_0"."EMPID" AS "EMPID",
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"_q_0"."DEPT" AS "DEPT",
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"_q_0"."MONTH" AS "MONTH",
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"_q_0"."SALES" AS "SALES"
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FROM "M_SALES" AS "M_SALES"("EMPID", "DEPT", "JAN", "FEB") UNPIVOT("SALES" FOR "MONTH" IN ("JAN", "FEB")) AS "_q_0"
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ORDER BY
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"_q_0"."EMPID";
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# title: unpivoted table source, unpivot has column aliases
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# execute: false
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SELECT * FROM (SELECT * FROM m_sales) AS m_sales(empid, dept, jan, feb) UNPIVOT(sales FOR month IN (jan, feb)) AS unpiv(a, b, c, d);
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SELECT
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"unpiv"."a" AS "a",
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"unpiv"."b" AS "b",
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"unpiv"."c" AS "c",
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"unpiv"."d" AS "d"
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FROM (
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SELECT
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"m_sales"."empid" AS "empid",
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"m_sales"."dept" AS "dept",
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"m_sales"."jan" AS "jan",
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"m_sales"."feb" AS "feb"
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FROM "m_sales" AS "m_sales"
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) AS "m_sales" UNPIVOT("sales" FOR "month" IN ("m_sales"."jan", "m_sales"."feb")) AS "unpiv"("a", "b", "c", "d");
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# title: unpivoted derived table source with a single value column
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# execute: false
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# dialect: snowflake
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SELECT * FROM (SELECT * FROM m_sales) AS m_sales(empid, dept, jan, feb) UNPIVOT(sales FOR month IN (jan, feb)) ORDER BY empid;
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SELECT
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"_q_0"."EMPID" AS "EMPID",
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"_q_0"."DEPT" AS "DEPT",
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"_q_0"."MONTH" AS "MONTH",
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"_q_0"."SALES" AS "SALES"
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FROM (
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SELECT
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"M_SALES"."EMPID" AS "EMPID",
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"M_SALES"."DEPT" AS "DEPT",
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"M_SALES"."JAN" AS "JAN",
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"M_SALES"."FEB" AS "FEB"
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FROM "M_SALES" AS "M_SALES"
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) AS "M_SALES" UNPIVOT("SALES" FOR "MONTH" IN ("JAN", "FEB")) AS "_q_0"
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ORDER BY
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"_q_0"."EMPID";
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# title: unpivoted table source with a single value column, unpivot columns can be qualified
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# execute: false
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# dialect: bigquery
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# note: the named columns aren't supported by BQ but we add them here to avoid defining a schema
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SELECT * FROM produce AS produce(product, q1, q2, q3, q4) UNPIVOT(sales FOR quarter IN (q1, q2, q3, q4));
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SELECT
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`_q_0`.`product` AS `product`,
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`_q_0`.`quarter` AS `quarter`,
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`_q_0`.`sales` AS `sales`
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FROM `produce` AS `produce` UNPIVOT(`sales` FOR `quarter` IN (`produce`.`q1`, `produce`.`q2`, `produce`.`q3`, `produce`.`q4`)) AS `_q_0`;
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# title: unpivoted table source with multiple value columns
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# execute: false
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# dialect: bigquery
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SELECT * FROM produce AS produce(product, q1, q2, q3, q4) UNPIVOT((first_half_sales, second_half_sales) FOR semesters IN ((Q1, Q2) AS 'semester_1', (Q3, Q4) AS 'semester_2'));
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SELECT
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`_q_0`.`product` AS `product`,
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`_q_0`.`semesters` AS `semesters`,
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`_q_0`.`first_half_sales` AS `first_half_sales`,
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`_q_0`.`second_half_sales` AS `second_half_sales`
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FROM `produce` AS `produce` UNPIVOT((`first_half_sales`, `second_half_sales`) FOR `semesters` IN ((`produce`.`q1`, `produce`.`q2`) AS 'semester_1', (`produce`.`q3`, `produce`.`q4`) AS 'semester_2')) AS `_q_0`;
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# title: quoting is maintained
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# dialect: snowflake
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with cte1("id", foo) as (select 1, 2) select "id" from cte1;
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@ -1144,3 +1247,29 @@ WITH "x" AS (
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LIMIT 10
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)
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LIMIT 10;
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# title: avoid producing DAG cycle when pushing down predicate to join
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# execute: false
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SELECT
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a.company,
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b.num
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FROM route AS a(num, company, pos, stop)
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JOIN route AS b(num, company, pos, stop) ON (a.num = b.num)
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JOIN stops AS c(id, name) ON (c.id = b.stop)
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JOIN stops AS d(id, name) ON (d.id = c.id)
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WHERE
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c.name = 'Craiglockhart'
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OR d.name = 'Tollcross';
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SELECT
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"a"."company" AS "company",
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"b"."num" AS "num"
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FROM "route" AS "a"("num", "company", "pos", "stop")
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JOIN "route" AS "b"("num", "company", "pos", "stop")
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ON "a"."num" = "b"."num"
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JOIN "stops" AS "c"("id", "name")
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ON "b"."stop" = "c"."id"
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JOIN "stops" AS "d"("id", "name")
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ON "c"."id" = "d"."id"
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AND (
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"c"."name" = 'Craiglockhart' OR "d"."name" = 'Tollcross'
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);
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