sql/core/src/test/resources/sql-tests/analyzer-results/postgreSQL/window_part3.sql.out

-- Automatically generated by SQLQueryTestSuite
-- !query
CREATE TEMPORARY VIEW tenk2 AS SELECT * FROM tenk1
-- !query analysis
CreateViewCommand `tenk2`, SELECT * FROM tenk1, false, false, LocalTempView, true
   +- Project [unique1#x, unique2#x, two#x, four#x, ten#x, twenty#x, hundred#x, thousand#x, twothousand#x, fivethous#x, tenthous#x, odd#x, even#x, stringu1#x, stringu2#x, string4#x]
      +- SubqueryAlias spark_catalog.default.tenk1
         +- Relation spark_catalog.default.tenk1[unique1#x,unique2#x,two#x,four#x,ten#x,twenty#x,hundred#x,thousand#x,twothousand#x,fivethous#x,tenthous#x,odd#x,even#x,stringu1#x,stringu2#x,string4#x] parquet


-- !query
CREATE TABLE empsalary (
    depname string,
    empno integer,
    salary int,
    enroll_date date
) USING parquet
-- !query analysis
CreateDataSourceTableCommand `spark_catalog`.`default`.`empsalary`, false


-- !query
INSERT INTO empsalary VALUES
  ('develop', 10, 5200, date '2007-08-01'),
  ('sales', 1, 5000, date '2006-10-01'),
  ('personnel', 5, 3500, date '2007-12-10'),
  ('sales', 4, 4800, date '2007-08-08'),
  ('personnel', 2, 3900, date '2006-12-23'),
  ('develop', 7, 4200, date '2008-01-01'),
  ('develop', 9, 4500, date '2008-01-01'),
  ('sales', 3, 4800, date '2007-08-01'),
  ('develop', 8, 6000, date '2006-10-01'),
  ('develop', 11, 5200, date '2007-08-15')
-- !query analysis
InsertIntoHadoopFsRelationCommand file:[not included in comparison]/{warehouse_dir}/empsalary, false, Parquet, [path=file:[not included in comparison]/{warehouse_dir}/empsalary], Append, `spark_catalog`.`default`.`empsalary`, org.apache.spark.sql.execution.datasources.InMemoryFileIndex(file:[not included in comparison]/{warehouse_dir}/empsalary), [depname, empno, salary, enroll_date]
+- Project [cast(col1#x as string) AS depname#x, cast(col2#x as int) AS empno#x, cast(col3#x as int) AS salary#x, cast(col4#x as date) AS enroll_date#x]
   +- LocalRelation [col1#x, col2#x, col3#x, col4#x]


-- !query
create table datetimes (
    id int,
    f_time timestamp,
    f_timetz timestamp,
    f_interval timestamp,
    f_timestamptz timestamp,
    f_timestamp timestamp
) using parquet
-- !query analysis
CreateDataSourceTableCommand `spark_catalog`.`default`.`datetimes`, false


-- !query
insert into datetimes values
(1, timestamp '11:00', cast ('11:00 BST' as timestamp), cast ('1 year' as timestamp), cast ('2000-10-19 10:23:54+01' as timestamp), timestamp '2000-10-19 10:23:54'),
(2, timestamp '12:00', cast ('12:00 BST' as timestamp), cast ('2 years' as timestamp), cast ('2001-10-19 10:23:54+01' as timestamp), timestamp '2001-10-19 10:23:54'),
(3, timestamp '13:00', cast ('13:00 BST' as timestamp), cast ('3 years' as timestamp), cast ('2001-10-19 10:23:54+01' as timestamp), timestamp '2001-10-19 10:23:54'),
(4, timestamp '14:00', cast ('14:00 BST' as timestamp), cast ('4 years' as timestamp), cast ('2002-10-19 10:23:54+01' as timestamp), timestamp '2002-10-19 10:23:54'),
(5, timestamp '15:00', cast ('15:00 BST' as timestamp), cast ('5 years' as timestamp), cast ('2003-10-19 10:23:54+01' as timestamp), timestamp '2003-10-19 10:23:54'),
(6, timestamp '15:00', cast ('15:00 BST' as timestamp), cast ('5 years' as timestamp), cast ('2004-10-19 10:23:54+01' as timestamp), timestamp '2004-10-19 10:23:54'),
(7, timestamp '17:00', cast ('17:00 BST' as timestamp), cast ('7 years' as timestamp), cast ('2005-10-19 10:23:54+01' as timestamp), timestamp '2005-10-19 10:23:54'),
(8, timestamp '18:00', cast ('18:00 BST' as timestamp), cast ('8 years' as timestamp), cast ('2006-10-19 10:23:54+01' as timestamp), timestamp '2006-10-19 10:23:54'),
(9, timestamp '19:00', cast ('19:00 BST' as timestamp), cast ('9 years' as timestamp), cast ('2007-10-19 10:23:54+01' as timestamp), timestamp '2007-10-19 10:23:54'),
(10, timestamp '20:00', cast ('20:00 BST' as timestamp), cast ('10 years' as timestamp), cast ('2008-10-19 10:23:54+01' as timestamp), timestamp '2008-10-19 10:23:54')
-- !query analysis
org.apache.spark.sql.AnalysisException
{
  "errorClass" : "INVALID_INLINE_TABLE.FAILED_SQL_EXPRESSION_EVALUATION",
  "sqlState" : "42000",
  "messageParameters" : {
    "sqlExpr" : "\"CAST(11:00 BST AS TIMESTAMP)\""
  },
  "queryContext" : [ {
    "objectType" : "",
    "objectName" : "",
    "startIndex" : 23,
    "stopIndex" : 1698,
    "fragment" : "values\n(1, timestamp '11:00', cast ('11:00 BST' as timestamp), cast ('1 year' as timestamp), cast ('2000-10-19 10:23:54+01' as timestamp), timestamp '2000-10-19 10:23:54'),\n(2, timestamp '12:00', cast ('12:00 BST' as timestamp), cast ('2 years' as timestamp), cast ('2001-10-19 10:23:54+01' as timestamp), timestamp '2001-10-19 10:23:54'),\n(3, timestamp '13:00', cast ('13:00 BST' as timestamp), cast ('3 years' as timestamp), cast ('2001-10-19 10:23:54+01' as timestamp), timestamp '2001-10-19 10:23:54'),\n(4, timestamp '14:00', cast ('14:00 BST' as timestamp), cast ('4 years' as timestamp), cast ('2002-10-19 10:23:54+01' as timestamp), timestamp '2002-10-19 10:23:54'),\n(5, timestamp '15:00', cast ('15:00 BST' as timestamp), cast ('5 years' as timestamp), cast ('2003-10-19 10:23:54+01' as timestamp), timestamp '2003-10-19 10:23:54'),\n(6, timestamp '15:00', cast ('15:00 BST' as timestamp), cast ('5 years' as timestamp), cast ('2004-10-19 10:23:54+01' as timestamp), timestamp '2004-10-19 10:23:54'),\n(7, timestamp '17:00', cast ('17:00 BST' as timestamp), cast ('7 years' as timestamp), cast ('2005-10-19 10:23:54+01' as timestamp), timestamp '2005-10-19 10:23:54'),\n(8, timestamp '18:00', cast ('18:00 BST' as timestamp), cast ('8 years' as timestamp), cast ('2006-10-19 10:23:54+01' as timestamp), timestamp '2006-10-19 10:23:54'),\n(9, timestamp '19:00', cast ('19:00 BST' as timestamp), cast ('9 years' as timestamp), cast ('2007-10-19 10:23:54+01' as timestamp), timestamp '2007-10-19 10:23:54'),\n(10, timestamp '20:00', cast ('20:00 BST' as timestamp), cast ('10 years' as timestamp), cast ('2008-10-19 10:23:54+01' as timestamp), timestamp '2008-10-19 10:23:54')"
  } ]
}


-- !query
WITH cte (x) AS (
        SELECT * FROM range(1, 36, 2)
)
SELECT x, (sum(x) over w)
FROM cte
WINDOW w AS (ORDER BY x rows between 1 preceding and 1 following)
-- !query analysis
WithCTE
:- CTERelationDef xxxx, false
:  +- SubqueryAlias cte
:     +- Project [id#xL AS x#xL]
:        +- Project [id#xL]
:           +- Range (1, 36, step=2)
+- Project [x#xL, sum(x) OVER (ORDER BY x ASC NULLS FIRST ROWS BETWEEN 1 PRECEDING AND 1 FOLLOWING)#xL]
   +- Project [x#xL, sum(x) OVER (ORDER BY x ASC NULLS FIRST ROWS BETWEEN 1 PRECEDING AND 1 FOLLOWING)#xL, sum(x) OVER (ORDER BY x ASC NULLS FIRST ROWS BETWEEN 1 PRECEDING AND 1 FOLLOWING)#xL]
      +- Window [sum(x#xL) windowspecdefinition(x#xL ASC NULLS FIRST, specifiedwindowframe(RowFrame, -1, 1)) AS sum(x) OVER (ORDER BY x ASC NULLS FIRST ROWS BETWEEN 1 PRECEDING AND 1 FOLLOWING)#xL], [x#xL ASC NULLS FIRST]
         +- Project [x#xL]
            +- SubqueryAlias cte
               +- CTERelationRef xxxx, true, [x#xL], false


-- !query
WITH cte (x) AS (
        SELECT * FROM range(1, 36, 2)
)
SELECT x, (sum(x) over w)
FROM cte
WINDOW w AS (ORDER BY x range between 1 preceding and 1 following)
-- !query analysis
WithCTE
:- CTERelationDef xxxx, false
:  +- SubqueryAlias cte
:     +- Project [id#xL AS x#xL]
:        +- Project [id#xL]
:           +- Range (1, 36, step=2)
+- Project [x#xL, sum(x) OVER (ORDER BY x ASC NULLS FIRST RANGE BETWEEN (- 1) FOLLOWING AND 1 FOLLOWING)#xL]
   +- Project [x#xL, sum(x) OVER (ORDER BY x ASC NULLS FIRST RANGE BETWEEN (- 1) FOLLOWING AND 1 FOLLOWING)#xL, sum(x) OVER (ORDER BY x ASC NULLS FIRST RANGE BETWEEN (- 1) FOLLOWING AND 1 FOLLOWING)#xL]
      +- Window [sum(x#xL) windowspecdefinition(x#xL ASC NULLS FIRST, specifiedwindowframe(RangeFrame, cast(-1 as bigint), cast(1 as bigint))) AS sum(x) OVER (ORDER BY x ASC NULLS FIRST RANGE BETWEEN (- 1) FOLLOWING AND 1 FOLLOWING)#xL], [x#xL ASC NULLS FIRST]
         +- Project [x#xL]
            +- SubqueryAlias cte
               +- CTERelationRef xxxx, true, [x#xL], false


-- !query
WITH cte (x) AS (
        select 1 union all select 1 union all select 1 union all
        SELECT * FROM range(5, 50, 2)
)
SELECT x, (sum(x) over w)
FROM cte
WINDOW w AS (ORDER BY x rows between 1 preceding and 1 following)
-- !query analysis
WithCTE
:- CTERelationDef xxxx, false
:  +- SubqueryAlias cte
:     +- Project [1#xL AS x#xL]
:        +- Union false, false
:           :- Project [cast(1#x as bigint) AS 1#xL]
:           :  +- Union false, false
:           :     :- Union false, false
:           :     :  :- Project [1 AS 1#x]
:           :     :  :  +- OneRowRelation
:           :     :  +- Project [1 AS 1#x]
:           :     :     +- OneRowRelation
:           :     +- Project [1 AS 1#x]
:           :        +- OneRowRelation
:           +- Project [id#xL]
:              +- Range (5, 50, step=2)
+- Project [x#xL, sum(x) OVER (ORDER BY x ASC NULLS FIRST ROWS BETWEEN 1 PRECEDING AND 1 FOLLOWING)#xL]
   +- Project [x#xL, sum(x) OVER (ORDER BY x ASC NULLS FIRST ROWS BETWEEN 1 PRECEDING AND 1 FOLLOWING)#xL, sum(x) OVER (ORDER BY x ASC NULLS FIRST ROWS BETWEEN 1 PRECEDING AND 1 FOLLOWING)#xL]
      +- Window [sum(x#xL) windowspecdefinition(x#xL ASC NULLS FIRST, specifiedwindowframe(RowFrame, -1, 1)) AS sum(x) OVER (ORDER BY x ASC NULLS FIRST ROWS BETWEEN 1 PRECEDING AND 1 FOLLOWING)#xL], [x#xL ASC NULLS FIRST]
         +- Project [x#xL]
            +- SubqueryAlias cte
               +- CTERelationRef xxxx, true, [x#xL], false


-- !query
WITH cte (x) AS (
        select 1 union all select 1 union all select 1 union all
        SELECT * FROM range(5, 50, 2)
)
SELECT x, (sum(x) over w)
FROM cte
WINDOW w AS (ORDER BY x range between 1 preceding and 1 following)
-- !query analysis
WithCTE
:- CTERelationDef xxxx, false
:  +- SubqueryAlias cte
:     +- Project [1#xL AS x#xL]
:        +- Union false, false
:           :- Project [cast(1#x as bigint) AS 1#xL]
:           :  +- Union false, false
:           :     :- Union false, false
:           :     :  :- Project [1 AS 1#x]
:           :     :  :  +- OneRowRelation
:           :     :  +- Project [1 AS 1#x]
:           :     :     +- OneRowRelation
:           :     +- Project [1 AS 1#x]
:           :        +- OneRowRelation
:           +- Project [id#xL]
:              +- Range (5, 50, step=2)
+- Project [x#xL, sum(x) OVER (ORDER BY x ASC NULLS FIRST RANGE BETWEEN (- 1) FOLLOWING AND 1 FOLLOWING)#xL]
   +- Project [x#xL, sum(x) OVER (ORDER BY x ASC NULLS FIRST RANGE BETWEEN (- 1) FOLLOWING AND 1 FOLLOWING)#xL, sum(x) OVER (ORDER BY x ASC NULLS FIRST RANGE BETWEEN (- 1) FOLLOWING AND 1 FOLLOWING)#xL]
      +- Window [sum(x#xL) windowspecdefinition(x#xL ASC NULLS FIRST, specifiedwindowframe(RangeFrame, cast(-1 as bigint), cast(1 as bigint))) AS sum(x) OVER (ORDER BY x ASC NULLS FIRST RANGE BETWEEN (- 1) FOLLOWING AND 1 FOLLOWING)#xL], [x#xL ASC NULLS FIRST]
         +- Project [x#xL]
            +- SubqueryAlias cte
               +- CTERelationRef xxxx, true, [x#xL], false


-- !query
SELECT count(*) OVER (PARTITION BY four) FROM (SELECT * FROM tenk1 UNION ALL SELECT * FROM tenk2)s LIMIT 0
-- !query analysis
GlobalLimit 0
+- LocalLimit 0
   +- Project [count(1) OVER (PARTITION BY four ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING)#xL]
      +- Project [four#x, count(1) OVER (PARTITION BY four ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING)#xL, count(1) OVER (PARTITION BY four ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING)#xL]
         +- Window [count(1) windowspecdefinition(four#x, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS count(1) OVER (PARTITION BY four ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING)#xL], [four#x]
            +- Project [four#x]
               +- SubqueryAlias s
                  +- Union false, false
                     :- Project [unique1#x, unique2#x, two#x, four#x, ten#x, twenty#x, hundred#x, thousand#x, twothousand#x, fivethous#x, tenthous#x, odd#x, even#x, stringu1#x, stringu2#x, string4#x]
                     :  +- SubqueryAlias spark_catalog.default.tenk1
                     :     +- Relation spark_catalog.default.tenk1[unique1#x,unique2#x,two#x,four#x,ten#x,twenty#x,hundred#x,thousand#x,twothousand#x,fivethous#x,tenthous#x,odd#x,even#x,stringu1#x,stringu2#x,string4#x] parquet
                     +- Project [unique1#x, unique2#x, two#x, four#x, ten#x, twenty#x, hundred#x, thousand#x, twothousand#x, fivethous#x, tenthous#x, odd#x, even#x, stringu1#x, stringu2#x, string4#x]
                        +- SubqueryAlias tenk2
                           +- View (`tenk2`, [unique1#x, unique2#x, two#x, four#x, ten#x, twenty#x, hundred#x, thousand#x, twothousand#x, fivethous#x, tenthous#x, odd#x, even#x, stringu1#x, stringu2#x, string4#x])
                              +- Project [cast(unique1#x as int) AS unique1#x, cast(unique2#x as int) AS unique2#x, cast(two#x as int) AS two#x, cast(four#x as int) AS four#x, cast(ten#x as int) AS ten#x, cast(twenty#x as int) AS twenty#x, cast(hundred#x as int) AS hundred#x, cast(thousand#x as int) AS thousand#x, cast(twothousand#x as int) AS twothousand#x, cast(fivethous#x as int) AS fivethous#x, cast(tenthous#x as int) AS tenthous#x, cast(odd#x as int) AS odd#x, cast(even#x as int) AS even#x, cast(stringu1#x as string) AS stringu1#x, cast(stringu2#x as string) AS stringu2#x, cast(string4#x as string) AS string4#x]
                                 +- Project [unique1#x, unique2#x, two#x, four#x, ten#x, twenty#x, hundred#x, thousand#x, twothousand#x, fivethous#x, tenthous#x, odd#x, even#x, stringu1#x, stringu2#x, string4#x]
                                    +- SubqueryAlias spark_catalog.default.tenk1
                                       +- Relation spark_catalog.default.tenk1[unique1#x,unique2#x,two#x,four#x,ten#x,twenty#x,hundred#x,thousand#x,twothousand#x,fivethous#x,tenthous#x,odd#x,even#x,stringu1#x,stringu2#x,string4#x] parquet


-- !query
create table t1 (f1 int, f2 int) using parquet
-- !query analysis
CreateDataSourceTableCommand `spark_catalog`.`default`.`t1`, false


-- !query
insert into t1 values (1,1),(1,2),(2,2)
-- !query analysis
InsertIntoHadoopFsRelationCommand file:[not included in comparison]/{warehouse_dir}/t1, false, Parquet, [path=file:[not included in comparison]/{warehouse_dir}/t1], Append, `spark_catalog`.`default`.`t1`, org.apache.spark.sql.execution.datasources.InMemoryFileIndex(file:[not included in comparison]/{warehouse_dir}/t1), [f1, f2]
+- Project [cast(col1#x as int) AS f1#x, cast(col2#x as int) AS f2#x]
   +- LocalRelation [col1#x, col2#x]


-- !query
select f1, sum(f1) over (partition by f1
                         range between 1 preceding and 1 following)
from t1 where f1 = f2
-- !query analysis
org.apache.spark.sql.catalyst.ExtendedAnalysisException
{
  "errorClass" : "DATATYPE_MISMATCH.RANGE_FRAME_WITHOUT_ORDER",
  "sqlState" : "42K09",
  "messageParameters" : {
    "sqlExpr" : "\"(PARTITION BY f1 RANGE BETWEEN 1 PRECEDING AND 1 FOLLOWING)\""
  },
  "queryContext" : [ {
    "objectType" : "",
    "objectName" : "",
    "startIndex" : 25,
    "stopIndex" : 108,
    "fragment" : "(partition by f1\n                         range between 1 preceding and 1 following)"
  } ]
}


-- !query
select f1, sum(f1) over (partition by f1 order by f2
range between 1 preceding and 1 following)
from t1 where f1 = f2
-- !query analysis
Project [f1#x, sum(f1) OVER (PARTITION BY f1 ORDER BY f2 ASC NULLS FIRST RANGE BETWEEN 1 PRECEDING AND 1 FOLLOWING)#xL]
+- Project [f1#x, f2#x, sum(f1) OVER (PARTITION BY f1 ORDER BY f2 ASC NULLS FIRST RANGE BETWEEN 1 PRECEDING AND 1 FOLLOWING)#xL, sum(f1) OVER (PARTITION BY f1 ORDER BY f2 ASC NULLS FIRST RANGE BETWEEN 1 PRECEDING AND 1 FOLLOWING)#xL]
   +- Window [sum(f1#x) windowspecdefinition(f1#x, f2#x ASC NULLS FIRST, specifiedwindowframe(RangeFrame, -1, 1)) AS sum(f1) OVER (PARTITION BY f1 ORDER BY f2 ASC NULLS FIRST RANGE BETWEEN 1 PRECEDING AND 1 FOLLOWING)#xL], [f1#x], [f2#x ASC NULLS FIRST]
      +- Project [f1#x, f2#x]
         +- Filter (f1#x = f2#x)
            +- SubqueryAlias spark_catalog.default.t1
               +- Relation spark_catalog.default.t1[f1#x,f2#x] parquet


-- !query
select f1, sum(f1) over (partition by f1, f1 order by f2
range between 2 preceding and 1 preceding)
from t1 where f1 = f2
-- !query analysis
Project [f1#x, sum(f1) OVER (PARTITION BY f1, f1 ORDER BY f2 ASC NULLS FIRST RANGE BETWEEN 2 PRECEDING AND 1 PRECEDING)#xL]
+- Project [f1#x, f2#x, sum(f1) OVER (PARTITION BY f1, f1 ORDER BY f2 ASC NULLS FIRST RANGE BETWEEN 2 PRECEDING AND 1 PRECEDING)#xL, sum(f1) OVER (PARTITION BY f1, f1 ORDER BY f2 ASC NULLS FIRST RANGE BETWEEN 2 PRECEDING AND 1 PRECEDING)#xL]
   +- Window [sum(f1#x) windowspecdefinition(f1#x, f1#x, f2#x ASC NULLS FIRST, specifiedwindowframe(RangeFrame, -2, -1)) AS sum(f1) OVER (PARTITION BY f1, f1 ORDER BY f2 ASC NULLS FIRST RANGE BETWEEN 2 PRECEDING AND 1 PRECEDING)#xL], [f1#x, f1#x], [f2#x ASC NULLS FIRST]
      +- Project [f1#x, f2#x]
         +- Filter (f1#x = f2#x)
            +- SubqueryAlias spark_catalog.default.t1
               +- Relation spark_catalog.default.t1[f1#x,f2#x] parquet


-- !query
select f1, sum(f1) over (partition by f1, f2 order by f2
range between 1 following and 2 following)
from t1 where f1 = f2
-- !query analysis
Project [f1#x, sum(f1) OVER (PARTITION BY f1, f2 ORDER BY f2 ASC NULLS FIRST RANGE BETWEEN 1 FOLLOWING AND 2 FOLLOWING)#xL]
+- Project [f1#x, f2#x, sum(f1) OVER (PARTITION BY f1, f2 ORDER BY f2 ASC NULLS FIRST RANGE BETWEEN 1 FOLLOWING AND 2 FOLLOWING)#xL, sum(f1) OVER (PARTITION BY f1, f2 ORDER BY f2 ASC NULLS FIRST RANGE BETWEEN 1 FOLLOWING AND 2 FOLLOWING)#xL]
   +- Window [sum(f1#x) windowspecdefinition(f1#x, f2#x, f2#x ASC NULLS FIRST, specifiedwindowframe(RangeFrame, 1, 2)) AS sum(f1) OVER (PARTITION BY f1, f2 ORDER BY f2 ASC NULLS FIRST RANGE BETWEEN 1 FOLLOWING AND 2 FOLLOWING)#xL], [f1#x, f2#x], [f2#x ASC NULLS FIRST]
      +- Project [f1#x, f2#x]
         +- Filter (f1#x = f2#x)
            +- SubqueryAlias spark_catalog.default.t1
               +- Relation spark_catalog.default.t1[f1#x,f2#x] parquet


-- !query
SELECT rank() OVER (ORDER BY length('abc'))
-- !query analysis
Project [RANK() OVER (ORDER BY length(abc) ASC NULLS FIRST ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)#x]
+- Project [RANK() OVER (ORDER BY length(abc) ASC NULLS FIRST ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)#x, RANK() OVER (ORDER BY length(abc) ASC NULLS FIRST ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)#x]
   +- Window [rank(length(abc)) windowspecdefinition(length(abc) ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS RANK() OVER (ORDER BY length(abc) ASC NULLS FIRST ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)#x], [length(abc) ASC NULLS FIRST]
      +- Project
         +- OneRowRelation


-- !query
SELECT * FROM empsalary WHERE row_number() OVER (ORDER BY salary) < 10
-- !query analysis
org.apache.spark.sql.AnalysisException
{
  "errorClass" : "_LEGACY_ERROR_TEMP_1034",
  "messageParameters" : {
    "clauseName" : "WHERE"
  }
}


-- !query
SELECT * FROM empsalary INNER JOIN tenk1 ON row_number() OVER (ORDER BY salary) < 10
-- !query analysis
org.apache.spark.sql.catalyst.ExtendedAnalysisException
{
  "errorClass" : "UNSUPPORTED_EXPR_FOR_OPERATOR",
  "sqlState" : "42K0E",
  "messageParameters" : {
    "invalidExprSqls" : "\"row_number() OVER (ORDER BY salary ASC NULLS FIRST ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)\""
  },
  "queryContext" : [ {
    "objectType" : "",
    "objectName" : "",
    "startIndex" : 25,
    "stopIndex" : 84,
    "fragment" : "INNER JOIN tenk1 ON row_number() OVER (ORDER BY salary) < 10"
  } ]
}


-- !query
SELECT rank() OVER (ORDER BY 1), count(*) FROM empsalary GROUP BY 1
-- !query analysis
org.apache.spark.sql.catalyst.ExtendedAnalysisException
{
  "errorClass" : "UNSUPPORTED_EXPR_FOR_OPERATOR",
  "sqlState" : "42K0E",
  "messageParameters" : {
    "invalidExprSqls" : "\"RANK() OVER (ORDER BY 1 ASC NULLS FIRST ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)\""
  },
  "queryContext" : [ {
    "objectType" : "",
    "objectName" : "",
    "startIndex" : 58,
    "stopIndex" : 67,
    "fragment" : "GROUP BY 1"
  } ]
}


-- !query
SELECT * FROM rank() OVER (ORDER BY random())
-- !query analysis
org.apache.spark.sql.catalyst.parser.ParseException
{
  "errorClass" : "PARSE_SYNTAX_ERROR",
  "sqlState" : "42601",
  "messageParameters" : {
    "error" : "'BY'",
    "hint" : ""
  }
}


-- !query
SELECT * FROM empsalary WHERE (rank() OVER (ORDER BY random())) > 10
-- !query analysis
org.apache.spark.sql.AnalysisException
{
  "errorClass" : "_LEGACY_ERROR_TEMP_1034",
  "messageParameters" : {
    "clauseName" : "WHERE"
  }
}


-- !query
SELECT * FROM empsalary WHERE rank() OVER (ORDER BY random())
-- !query analysis
org.apache.spark.sql.AnalysisException
{
  "errorClass" : "_LEGACY_ERROR_TEMP_1034",
  "messageParameters" : {
    "clauseName" : "WHERE"
  }
}


-- !query
select rank() OVER (PARTITION BY four, ORDER BY ten) FROM tenk1
-- !query analysis
org.apache.spark.sql.catalyst.parser.ParseException
{
  "errorClass" : "PARSE_SYNTAX_ERROR",
  "sqlState" : "42601",
  "messageParameters" : {
    "error" : "'BY'",
    "hint" : ": extra input 'BY'"
  }
}


-- !query
SELECT range(1, 100) OVER () FROM empsalary
-- !query analysis
org.apache.spark.sql.AnalysisException
{
  "errorClass" : "UNRESOLVED_ROUTINE",
  "sqlState" : "42883",
  "messageParameters" : {
    "routineName" : "`range`",
    "searchPath" : "[`system`.`builtin`, `system`.`session`, `spark_catalog`.`default`]"
  },
  "queryContext" : [ {
    "objectType" : "",
    "objectName" : "",
    "startIndex" : 8,
    "stopIndex" : 28,
    "fragment" : "range(1, 100) OVER ()"
  } ]
}


-- !query
SELECT ntile(0) OVER (ORDER BY ten), ten, four FROM tenk1
-- !query analysis
org.apache.spark.sql.catalyst.ExtendedAnalysisException
{
  "errorClass" : "DATATYPE_MISMATCH.VALUE_OUT_OF_RANGE",
  "sqlState" : "42K09",
  "messageParameters" : {
    "currentValue" : "0",
    "exprName" : "buckets",
    "sqlExpr" : "\"ntile(0)\"",
    "valueRange" : "(0, 2147483647]"
  },
  "queryContext" : [ {
    "objectType" : "",
    "objectName" : "",
    "startIndex" : 8,
    "stopIndex" : 35,
    "fragment" : "ntile(0) OVER (ORDER BY ten)"
  } ]
}


-- !query
SELECT nth_value(four, 0) OVER (ORDER BY ten), ten, four FROM tenk1
-- !query analysis
org.apache.spark.sql.catalyst.ExtendedAnalysisException
{
  "errorClass" : "DATATYPE_MISMATCH.VALUE_OUT_OF_RANGE",
  "sqlState" : "42K09",
  "messageParameters" : {
    "currentValue" : "0L",
    "exprName" : "offset",
    "sqlExpr" : "\"nth_value(four, 0)\"",
    "valueRange" : "(0, 9223372036854775807]"
  },
  "queryContext" : [ {
    "objectType" : "",
    "objectName" : "",
    "startIndex" : 8,
    "stopIndex" : 45,
    "fragment" : "nth_value(four, 0) OVER (ORDER BY ten)"
  } ]
}


-- !query
DROP TABLE empsalary
-- !query analysis
DropTable false, false
+- ResolvedIdentifier V2SessionCatalog(spark_catalog), default.empsalary


-- !query
DROP TABLE datetimes
-- !query analysis
DropTable false, false
+- ResolvedIdentifier V2SessionCatalog(spark_catalog), default.datetimes


-- !query
DROP TABLE t1
-- !query analysis
DropTable false, false
+- ResolvedIdentifier V2SessionCatalog(spark_catalog), default.t1