HIVE-18797 : ExprConstNodeDesc's getExprString should put appropriate qualifier with...
[hive.git] / ql / src / test / results / clientpositive / perf / tez / query12.q.out
1 PREHOOK: query: explain
2 select  i_item_desc 
3       ,i_category 
4       ,i_class 
5       ,i_current_price
6       ,sum(ws_ext_sales_price) as itemrevenue 
7       ,sum(ws_ext_sales_price)*100/sum(sum(ws_ext_sales_price)) over
8           (partition by i_class) as revenueratio
9 from    
10         web_sales
11         ,item 
12         ,date_dim
13 where 
14         ws_item_sk = i_item_sk 
15         and i_category in ('Jewelry', 'Sports', 'Books')
16         and ws_sold_date_sk = d_date_sk
17         and d_date between cast('2001-01-12' as date) 
18                                 and (cast('2001-01-12' as date) + 30 days)
19 group by 
20         i_item_id
21         ,i_item_desc 
22         ,i_category
23         ,i_class
24         ,i_current_price
25 order by 
26         i_category
27         ,i_class
28         ,i_item_id
29         ,i_item_desc
30         ,revenueratio
31 limit 100
32 PREHOOK: type: QUERY
33 POSTHOOK: query: explain
34 select  i_item_desc 
35       ,i_category 
36       ,i_class 
37       ,i_current_price
38       ,sum(ws_ext_sales_price) as itemrevenue 
39       ,sum(ws_ext_sales_price)*100/sum(sum(ws_ext_sales_price)) over
40           (partition by i_class) as revenueratio
41 from    
42         web_sales
43         ,item 
44         ,date_dim
45 where 
46         ws_item_sk = i_item_sk 
47         and i_category in ('Jewelry', 'Sports', 'Books')
48         and ws_sold_date_sk = d_date_sk
49         and d_date between cast('2001-01-12' as date) 
50                                 and (cast('2001-01-12' as date) + 30 days)
51 group by 
52         i_item_id
53         ,i_item_desc 
54         ,i_category
55         ,i_class
56         ,i_current_price
57 order by 
58         i_category
59         ,i_class
60         ,i_item_id
61         ,i_item_desc
62         ,revenueratio
63 limit 100
64 POSTHOOK: type: QUERY
65 Plan optimized by CBO.
66
67 Vertex dependency in root stage
68 Reducer 2 <- Map 1 (SIMPLE_EDGE), Map 7 (SIMPLE_EDGE)
69 Reducer 3 <- Map 8 (SIMPLE_EDGE), Reducer 2 (SIMPLE_EDGE)
70 Reducer 4 <- Reducer 3 (SIMPLE_EDGE)
71 Reducer 5 <- Reducer 4 (SIMPLE_EDGE)
72 Reducer 6 <- Reducer 5 (SIMPLE_EDGE)
73
74 Stage-0
75   Fetch Operator
76     limit:-1
77     Stage-1
78       Reducer 6
79       File Output Operator [FS_29]
80         Limit [LIM_27] (rows=100 width=135)
81           Number of rows:100
82           Select Operator [SEL_26] (rows=87121617 width=135)
83             Output:["_col0","_col1","_col2","_col3","_col4","_col5"]
84           <-Reducer 5 [SIMPLE_EDGE]
85             SHUFFLE [RS_25]
86               Select Operator [SEL_23] (rows=87121617 width=135)
87                 Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"]
88                 PTF Operator [PTF_22] (rows=87121617 width=135)
89                   Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col3 ASC NULLS FIRST","partition by:":"_col3"}]
90                   Select Operator [SEL_21] (rows=87121617 width=135)
91                     Output:["_col0","_col1","_col2","_col3","_col4","_col5"]
92                   <-Reducer 4 [SIMPLE_EDGE]
93                     SHUFFLE [RS_20]
94                       PartitionCols:_col3
95                       Select Operator [SEL_19] (rows=87121617 width=135)
96                         Output:["_col0","_col1","_col2","_col3","_col4","_col5"]
97                         Group By Operator [GBY_18] (rows=87121617 width=135)
98                           Output:["_col0","_col1","_col2","_col3","_col4","_col5"],aggregations:["sum(VALUE._col0)"],keys:KEY._col0, KEY._col1, KEY._col2, KEY._col3, KEY._col4
99                         <-Reducer 3 [SIMPLE_EDGE]
100                           SHUFFLE [RS_17]
101                             PartitionCols:_col0, _col1, _col2, _col3, _col4
102                             Group By Operator [GBY_16] (rows=174243235 width=135)
103                               Output:["_col0","_col1","_col2","_col3","_col4","_col5"],aggregations:["sum(_col2)"],keys:_col10, _col9, _col6, _col7, _col8
104                               Merge Join Operator [MERGEJOIN_39] (rows=174243235 width=135)
105                                 Conds:RS_12._col1=RS_13._col0(Inner),Output:["_col2","_col6","_col7","_col8","_col9","_col10"]
106                               <-Map 8 [SIMPLE_EDGE]
107                                 SHUFFLE [RS_13]
108                                   PartitionCols:_col0
109                                   Select Operator [SEL_8] (rows=231000 width=1436)
110                                     Output:["_col0","_col1","_col2","_col3","_col4","_col5"]
111                                     Filter Operator [FIL_37] (rows=231000 width=1436)
112                                       predicate:((i_category) IN ('Jewelry', 'Sports', 'Books') and i_item_sk is not null)
113                                       TableScan [TS_6] (rows=462000 width=1436)
114                                         default@item,item,Tbl:COMPLETE,Col:NONE,Output:["i_item_sk","i_item_id","i_item_desc","i_current_price","i_class","i_category"]
115                               <-Reducer 2 [SIMPLE_EDGE]
116                                 SHUFFLE [RS_12]
117                                   PartitionCols:_col1
118                                   Merge Join Operator [MERGEJOIN_38] (rows=158402938 width=135)
119                                     Conds:RS_9._col0=RS_10._col0(Inner),Output:["_col1","_col2"]
120                                   <-Map 1 [SIMPLE_EDGE]
121                                     SHUFFLE [RS_9]
122                                       PartitionCols:_col0
123                                       Select Operator [SEL_2] (rows=144002668 width=135)
124                                         Output:["_col0","_col1","_col2"]
125                                         Filter Operator [FIL_35] (rows=144002668 width=135)
126                                           predicate:(ws_item_sk is not null and ws_sold_date_sk is not null)
127                                           TableScan [TS_0] (rows=144002668 width=135)
128                                             default@web_sales,web_sales,Tbl:COMPLETE,Col:NONE,Output:["ws_sold_date_sk","ws_item_sk","ws_ext_sales_price"]
129                                   <-Map 7 [SIMPLE_EDGE]
130                                     SHUFFLE [RS_10]
131                                       PartitionCols:_col0
132                                       Select Operator [SEL_5] (rows=8116 width=1119)
133                                         Output:["_col0"]
134                                         Filter Operator [FIL_36] (rows=8116 width=1119)
135                                           predicate:(CAST( d_date AS TIMESTAMP) BETWEEN TIMESTAMP'2001-01-12 00:00:00.0' AND TIMESTAMP'2001-02-11 00:00:00.0' and d_date_sk is not null)
136                                           TableScan [TS_3] (rows=73049 width=1119)
137                                             default@date_dim,date_dim,Tbl:COMPLETE,Col:NONE,Output:["d_date_sk","d_date"]
138