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[fix](nereids) fix UnknownValue's reference in simplify range rule #44637

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merged 11 commits into from
Nov 28, 2024
Merged

[fix](nereids) fix UnknownValue's reference in simplify range rule #44637

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23001d9
fix simple range unknown value reference
yujun777 Nov 26, 2024
9c0cf87
add test
yujun777 Nov 26, 2024
1c610b9
update
yujun777 Nov 26, 2024
416885f
fix test
yujun777 Nov 26, 2024
dc2809e
add test
yujun777 Nov 27, 2024
9664463
fix fe ut
yujun777 Nov 27, 2024
8352e5a
add annotation
yujun777 Nov 27, 2024
d53bddc
fix test
yujun777 Nov 27, 2024
3e487c4
fix test
yujun777 Nov 27, 2024
aecfaa3
run gen
yujun777 Nov 27, 2024
314ec04
run gen
yujun777 Nov 27, 2024
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235 changes: 129 additions & 106 deletions fe/fe-core/src/main/java/org/apache/doris/nereids/rules/expression/rules/SimplifyRange.java
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4 changes: 4 additions & 0 deletions fe/fe-core/src/test/java/org/apache/doris/nereids/rules/expression/SimplifyRangeTest.java
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Expand Up @@ -101,6 +101,7 @@ public void testSimplify() {
assertRewrite("TA > 5 + 1 and TA > 10", "cast(TA as smallint) > 6 and TA > 10");
assertRewrite("(TA > 1 and TA > 10) or TA > 20", "TA > 10");
assertRewrite("(TA > 1 or TA > 10) and TA > 20", "TA > 20");
assertRewrite("(TA < 1 and TA > 10) or TA = 20 and TB > 10", "(TA is null and null) or TA = 20 and TB > 10");
assertRewrite("(TA + TB > 1 or TA + TB > 10) and TA + TB > 20", "TA + TB > 20");
assertRewrite("TA > 10 or TA > 10", "TA > 10");
assertRewrite("(TA > 10 or TA > 20) and (TB > 10 and TB < 20)", "TA > 10 and (TB > 10 and TB < 20) ");
Expand Down Expand Up @@ -131,7 +132,10 @@ public void testSimplify() {
assertRewrite("TA in (1) and TA in (3)", "TA is null and null");
assertRewrite("TA in (1) and TA in (1)", "TA = 1");
assertRewriteNotNull("(TA > 3 and TA < 1) and TB < 5", "FALSE");
assertRewrite("(TA > 3 and TA < 1) and (TA > 5 and TA = 4)", "TA is null and null");
assertRewrite("(TA > 3 and TA < 1) or (TA > 5 and TA = 4)", "TA is null and null");
assertRewrite("(TA > 3 and TA < 1) and TB < 5", "TA is null and null and TB < 5");
assertRewrite("(TA > 3 and TA < 1) and (TB < 5 and TB = 6)", "TA is null and null and TB is null");
assertRewrite("TA > 3 and TB < 5 and TA < 1", "TA is null and null and TB < 5");
assertRewrite("(TA > 3 and TA < 1) or TB < 5", "(TA is null and null) or TB < 5");
assertRewrite("((IA = 1 AND SC ='1') OR SC = '1212') AND IA =1", "((IA = 1 AND SC ='1') OR SC = '1212') AND IA =1");
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2 changes: 1 addition & 1 deletion fe/fe-core/src/test/java/org/apache/doris/nereids/rules/rewrite/OrToInTest.java
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Expand Up @@ -193,7 +193,7 @@ void test15() {
String expr = "x=1 or (a=1 and b=2) or (a=2 and c=3)";
Expression expression = PARSER.parseExpression(expr);
Expression rewritten = OrToIn.INSTANCE.rewriteTree(expression, context);
Assertions.assertEquals("((x = 1) OR (((a = 1) AND (b = 2)) OR ((a = 2) AND (c = 3))))",
Assertions.assertEquals("(((x = 1) OR ((a = 1) AND (b = 2))) OR ((a = 2) AND (c = 3)))",
rewritten.toSql());
}

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2 changes: 1 addition & 1 deletion regression-test/data/nereids_hint_tpcds_p0/shape/query41.out
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Expand Up @@ -18,6 +18,6 @@ PhysicalResultSink
------------------------PhysicalDistribute[DistributionSpecHash]
--------------------------hashAgg[LOCAL]
----------------------------PhysicalProject
------------------------------filter((((i_color IN ('forest', 'lime', 'maroon', 'navy', 'powder', 'sky', 'slate', 'smoke') AND i_units IN ('Bunch', 'Case', 'Dozen', 'Gross', 'Lb', 'Ounce', 'Pallet', 'Pound')) AND ((((((item.i_category = 'Women') AND i_color IN ('forest', 'lime')) AND i_units IN ('Pallet', 'Pound')) AND i_size IN ('economy', 'small')) OR ((((item.i_category = 'Women') AND i_color IN ('navy', 'slate')) AND i_units IN ('Bunch', 'Gross')) AND i_size IN ('extra large', 'petite'))) OR (((((item.i_category = 'Men') AND i_color IN ('powder', 'sky')) AND i_units IN ('Dozen', 'Lb')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('maroon', 'smoke')) AND i_units IN ('Case', 'Ounce')) AND i_size IN ('economy', 'small'))))) OR ((i_color IN ('aquamarine', 'dark', 'firebrick', 'frosted', 'papaya', 'peach', 'plum', 'sienna') AND i_units IN ('Box', 'Bundle', 'Carton', 'Cup', 'Dram', 'Each', 'Tbl', 'Ton')) AND ((((((item.i_category = 'Women') AND i_color IN ('aquamarine', 'dark')) AND i_units IN ('Tbl', 'Ton')) AND i_size IN ('economy', 'small')) OR ((((item.i_category = 'Women') AND i_color IN ('frosted', 'plum')) AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'petite'))) OR (((((item.i_category = 'Men') AND i_color IN ('papaya', 'peach')) AND i_units IN ('Bundle', 'Carton')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('firebrick', 'sienna')) AND i_units IN ('Cup', 'Each')) AND i_size IN ('economy', 'small')))))) and i_category IN ('Men', 'Women') and i_size IN ('N/A', 'economy', 'extra large', 'large', 'petite', 'small'))
------------------------------filter((((i_color IN ('forest', 'lime', 'maroon', 'navy', 'powder', 'sky', 'slate', 'smoke') AND i_units IN ('Bunch', 'Case', 'Dozen', 'Gross', 'Lb', 'Ounce', 'Pallet', 'Pound')) AND (((((((item.i_category = 'Women') AND i_color IN ('forest', 'lime')) AND i_units IN ('Pallet', 'Pound')) AND i_size IN ('economy', 'small')) OR ((((item.i_category = 'Women') AND i_color IN ('navy', 'slate')) AND i_units IN ('Bunch', 'Gross')) AND i_size IN ('extra large', 'petite'))) OR ((((item.i_category = 'Men') AND i_color IN ('powder', 'sky')) AND i_units IN ('Dozen', 'Lb')) AND i_size IN ('N/A', 'large'))) OR ((((item.i_category = 'Men') AND i_color IN ('maroon', 'smoke')) AND i_units IN ('Case', 'Ounce')) AND i_size IN ('economy', 'small')))) OR ((i_color IN ('aquamarine', 'dark', 'firebrick', 'frosted', 'papaya', 'peach', 'plum', 'sienna') AND i_units IN ('Box', 'Bundle', 'Carton', 'Cup', 'Dram', 'Each', 'Tbl', 'Ton')) AND (((((((item.i_category = 'Women') AND i_color IN ('aquamarine', 'dark')) AND i_units IN ('Tbl', 'Ton')) AND i_size IN ('economy', 'small')) OR ((((item.i_category = 'Women') AND i_color IN ('frosted', 'plum')) AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'petite'))) OR ((((item.i_category = 'Men') AND i_color IN ('papaya', 'peach')) AND i_units IN ('Bundle', 'Carton')) AND i_size IN ('N/A', 'large'))) OR ((((item.i_category = 'Men') AND i_color IN ('firebrick', 'sienna')) AND i_units IN ('Cup', 'Each')) AND i_size IN ('economy', 'small'))))) and i_category IN ('Men', 'Women') and i_size IN ('N/A', 'economy', 'extra large', 'large', 'petite', 'small'))
--------------------------------PhysicalOlapScan[item]

2 changes: 1 addition & 1 deletion regression-test/data/nereids_hint_tpcds_p0/shape/query47.out
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Expand Up @@ -21,7 +21,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
------------------------------------PhysicalProject
--------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
------------------------------------PhysicalProject
--------------------------------------filter((((date_dim.d_year = 2000) OR ((date_dim.d_year = 1999) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2001) AND (date_dim.d_moy = 1))) and d_year IN (1999, 2000, 2001) and d_year IN (1999, 2000, 2001))
--------------------------------------filter((((date_dim.d_year = 2000) OR ((date_dim.d_year = 1999) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2001) AND (date_dim.d_moy = 1))) and d_year IN (1999, 2000, 2001))
----------------------------------------PhysicalOlapScan[date_dim]
--------------------------------PhysicalProject
----------------------------------PhysicalOlapScan[store]
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16 changes: 8 additions & 8 deletions regression-test/data/nereids_hint_tpcds_p0/shape/query88.out
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Expand Up @@ -24,7 +24,7 @@ PhysicalResultSink
--------------------------------------filter((time_dim.t_hour = 8) and (time_dim.t_minute >= 30))
----------------------------------------PhysicalOlapScan[time_dim]
--------------------------------PhysicalProject
----------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
----------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3))
------------------------------------PhysicalOlapScan[household_demographics]
----------------------------PhysicalProject
------------------------------filter((store.s_store_name = 'ese'))
Expand All @@ -45,7 +45,7 @@ PhysicalResultSink
--------------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute < 30))
----------------------------------------PhysicalOlapScan[time_dim]
--------------------------------PhysicalProject
----------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
----------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3))
------------------------------------PhysicalOlapScan[household_demographics]
----------------------------PhysicalProject
------------------------------filter((store.s_store_name = 'ese'))
Expand All @@ -66,7 +66,7 @@ PhysicalResultSink
------------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute >= 30))
--------------------------------------PhysicalOlapScan[time_dim]
------------------------------PhysicalProject
--------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
--------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3))
----------------------------------PhysicalOlapScan[household_demographics]
--------------------------PhysicalProject
----------------------------filter((store.s_store_name = 'ese'))
Expand All @@ -87,7 +87,7 @@ PhysicalResultSink
----------------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute < 30))
------------------------------------PhysicalOlapScan[time_dim]
----------------------------PhysicalProject
------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3))
--------------------------------PhysicalOlapScan[household_demographics]
------------------------PhysicalProject
--------------------------filter((store.s_store_name = 'ese'))
Expand All @@ -108,7 +108,7 @@ PhysicalResultSink
--------------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute >= 30))
----------------------------------PhysicalOlapScan[time_dim]
--------------------------PhysicalProject
----------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
----------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3))
------------------------------PhysicalOlapScan[household_demographics]
----------------------PhysicalProject
------------------------filter((store.s_store_name = 'ese'))
Expand All @@ -129,7 +129,7 @@ PhysicalResultSink
------------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute < 30))
--------------------------------PhysicalOlapScan[time_dim]
------------------------PhysicalProject
--------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
--------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3))
----------------------------PhysicalOlapScan[household_demographics]
--------------------PhysicalProject
----------------------filter((store.s_store_name = 'ese'))
Expand All @@ -150,7 +150,7 @@ PhysicalResultSink
----------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute >= 30))
------------------------------PhysicalOlapScan[time_dim]
----------------------PhysicalProject
------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3))
--------------------------PhysicalOlapScan[household_demographics]
------------------PhysicalProject
--------------------filter((store.s_store_name = 'ese'))
Expand All @@ -171,7 +171,7 @@ PhysicalResultSink
--------------------------filter((time_dim.t_hour = 12) and (time_dim.t_minute < 30))
----------------------------PhysicalOlapScan[time_dim]
--------------------PhysicalProject
----------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
----------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3))
------------------------PhysicalOlapScan[household_demographics]
----------------PhysicalProject
------------------filter((store.s_store_name = 'ese'))
Expand Down
2 changes: 1 addition & 1 deletion regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query41.out
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Expand Up @@ -18,6 +18,6 @@ PhysicalResultSink
------------------------PhysicalDistribute[DistributionSpecHash]
--------------------------hashAgg[LOCAL]
----------------------------PhysicalProject
------------------------------filter((((i_color IN ('forest', 'lime', 'maroon', 'navy', 'powder', 'sky', 'slate', 'smoke') AND i_units IN ('Bunch', 'Case', 'Dozen', 'Gross', 'Lb', 'Ounce', 'Pallet', 'Pound')) AND ((((((item.i_category = 'Women') AND i_color IN ('forest', 'lime')) AND i_units IN ('Pallet', 'Pound')) AND i_size IN ('economy', 'small')) OR ((((item.i_category = 'Women') AND i_color IN ('navy', 'slate')) AND i_units IN ('Bunch', 'Gross')) AND i_size IN ('extra large', 'petite'))) OR (((((item.i_category = 'Men') AND i_color IN ('powder', 'sky')) AND i_units IN ('Dozen', 'Lb')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('maroon', 'smoke')) AND i_units IN ('Case', 'Ounce')) AND i_size IN ('economy', 'small'))))) OR ((i_color IN ('aquamarine', 'dark', 'firebrick', 'frosted', 'papaya', 'peach', 'plum', 'sienna') AND i_units IN ('Box', 'Bundle', 'Carton', 'Cup', 'Dram', 'Each', 'Tbl', 'Ton')) AND ((((((item.i_category = 'Women') AND i_color IN ('aquamarine', 'dark')) AND i_units IN ('Tbl', 'Ton')) AND i_size IN ('economy', 'small')) OR ((((item.i_category = 'Women') AND i_color IN ('frosted', 'plum')) AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'petite'))) OR (((((item.i_category = 'Men') AND i_color IN ('papaya', 'peach')) AND i_units IN ('Bundle', 'Carton')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('firebrick', 'sienna')) AND i_units IN ('Cup', 'Each')) AND i_size IN ('economy', 'small')))))) and i_category IN ('Men', 'Women') and i_size IN ('N/A', 'economy', 'extra large', 'large', 'petite', 'small'))
------------------------------filter((((i_color IN ('forest', 'lime', 'maroon', 'navy', 'powder', 'sky', 'slate', 'smoke') AND i_units IN ('Bunch', 'Case', 'Dozen', 'Gross', 'Lb', 'Ounce', 'Pallet', 'Pound')) AND (((((((item.i_category = 'Women') AND i_color IN ('forest', 'lime')) AND i_units IN ('Pallet', 'Pound')) AND i_size IN ('economy', 'small')) OR ((((item.i_category = 'Women') AND i_color IN ('navy', 'slate')) AND i_units IN ('Bunch', 'Gross')) AND i_size IN ('extra large', 'petite'))) OR ((((item.i_category = 'Men') AND i_color IN ('powder', 'sky')) AND i_units IN ('Dozen', 'Lb')) AND i_size IN ('N/A', 'large'))) OR ((((item.i_category = 'Men') AND i_color IN ('maroon', 'smoke')) AND i_units IN ('Case', 'Ounce')) AND i_size IN ('economy', 'small')))) OR ((i_color IN ('aquamarine', 'dark', 'firebrick', 'frosted', 'papaya', 'peach', 'plum', 'sienna') AND i_units IN ('Box', 'Bundle', 'Carton', 'Cup', 'Dram', 'Each', 'Tbl', 'Ton')) AND (((((((item.i_category = 'Women') AND i_color IN ('aquamarine', 'dark')) AND i_units IN ('Tbl', 'Ton')) AND i_size IN ('economy', 'small')) OR ((((item.i_category = 'Women') AND i_color IN ('frosted', 'plum')) AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'petite'))) OR ((((item.i_category = 'Men') AND i_color IN ('papaya', 'peach')) AND i_units IN ('Bundle', 'Carton')) AND i_size IN ('N/A', 'large'))) OR ((((item.i_category = 'Men') AND i_color IN ('firebrick', 'sienna')) AND i_units IN ('Cup', 'Each')) AND i_size IN ('economy', 'small'))))) and i_category IN ('Men', 'Women') and i_size IN ('N/A', 'economy', 'extra large', 'large', 'petite', 'small'))
--------------------------------PhysicalOlapScan[item]

2 changes: 1 addition & 1 deletion regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query47.out
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Expand Up @@ -21,7 +21,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
------------------------------------PhysicalProject
--------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
------------------------------------PhysicalProject
--------------------------------------filter((((date_dim.d_year = 2000) OR ((date_dim.d_year = 1999) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2001) AND (date_dim.d_moy = 1))) and d_year IN (1999, 2000, 2001) and d_year IN (1999, 2000, 2001))
--------------------------------------filter((((date_dim.d_year = 2000) OR ((date_dim.d_year = 1999) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2001) AND (date_dim.d_moy = 1))) and d_year IN (1999, 2000, 2001))
----------------------------------------PhysicalOlapScan[date_dim]
--------------------------------PhysicalProject
----------------------------------PhysicalOlapScan[store]
Expand Down
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