/
explain.txt
142 lines (115 loc) · 6.44 KB
/
explain.txt
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
== Physical Plan ==
TakeOrderedAndProject (25)
+- * HashAggregate (24)
+- Exchange (23)
+- * HashAggregate (22)
+- * Expand (21)
+- BroadcastNestedLoopJoin Inner BuildRight (20)
:- * Project (16)
: +- * BroadcastHashJoin Inner BuildRight (15)
: :- * Project (10)
: : +- * BroadcastHashJoin Inner BuildRight (9)
: : :- * Filter (3)
: : : +- * ColumnarToRow (2)
: : : +- Scan parquet default.inventory (1)
: : +- BroadcastExchange (8)
: : +- * Project (7)
: : +- * Filter (6)
: : +- * ColumnarToRow (5)
: : +- Scan parquet default.date_dim (4)
: +- BroadcastExchange (14)
: +- * Filter (13)
: +- * ColumnarToRow (12)
: +- Scan parquet default.item (11)
+- BroadcastExchange (19)
+- * ColumnarToRow (18)
+- Scan parquet default.warehouse (17)
(1) Scan parquet default.inventory
Output [3]: [inv_date_sk#1, inv_item_sk#2, inv_quantity_on_hand#3]
Batched: true
Location [not included in comparison]/{warehouse_dir}/inventory]
PushedFilters: [IsNotNull(inv_date_sk), IsNotNull(inv_item_sk)]
ReadSchema: struct<inv_date_sk:int,inv_item_sk:int,inv_quantity_on_hand:int>
(2) ColumnarToRow [codegen id : 3]
Input [3]: [inv_date_sk#1, inv_item_sk#2, inv_quantity_on_hand#3]
(3) Filter [codegen id : 3]
Input [3]: [inv_date_sk#1, inv_item_sk#2, inv_quantity_on_hand#3]
Condition : (isnotnull(inv_date_sk#1) AND isnotnull(inv_item_sk#2))
(4) Scan parquet default.date_dim
Output [2]: [d_date_sk#4, d_month_seq#5]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_month_seq:int>
(5) ColumnarToRow [codegen id : 1]
Input [2]: [d_date_sk#4, d_month_seq#5]
(6) Filter [codegen id : 1]
Input [2]: [d_date_sk#4, d_month_seq#5]
Condition : (((isnotnull(d_month_seq#5) AND (d_month_seq#5 >= 1200)) AND (d_month_seq#5 <= 1211)) AND isnotnull(d_date_sk#4))
(7) Project [codegen id : 1]
Output [1]: [d_date_sk#4]
Input [2]: [d_date_sk#4, d_month_seq#5]
(8) BroadcastExchange
Input [1]: [d_date_sk#4]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [id=#6]
(9) BroadcastHashJoin [codegen id : 3]
Left keys [1]: [inv_date_sk#1]
Right keys [1]: [d_date_sk#4]
Join condition: None
(10) Project [codegen id : 3]
Output [2]: [inv_item_sk#2, inv_quantity_on_hand#3]
Input [4]: [inv_date_sk#1, inv_item_sk#2, inv_quantity_on_hand#3, d_date_sk#4]
(11) Scan parquet default.item
Output [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11]
Batched: true
Location [not included in comparison]/{warehouse_dir}/item]
PushedFilters: [IsNotNull(i_item_sk)]
ReadSchema: struct<i_item_sk:int,i_brand:string,i_class:string,i_category:string,i_product_name:string>
(12) ColumnarToRow [codegen id : 2]
Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11]
(13) Filter [codegen id : 2]
Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11]
Condition : isnotnull(i_item_sk#7)
(14) BroadcastExchange
Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [id=#12]
(15) BroadcastHashJoin [codegen id : 3]
Left keys [1]: [inv_item_sk#2]
Right keys [1]: [i_item_sk#7]
Join condition: None
(16) Project [codegen id : 3]
Output [5]: [inv_quantity_on_hand#3, i_brand#8, i_class#9, i_category#10, i_product_name#11]
Input [7]: [inv_item_sk#2, inv_quantity_on_hand#3, i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11]
(17) Scan parquet default.warehouse
Output: []
Batched: true
Location [not included in comparison]/{warehouse_dir}/warehouse]
ReadSchema: struct<>
(18) ColumnarToRow [codegen id : 4]
Input: []
(19) BroadcastExchange
Input: []
Arguments: IdentityBroadcastMode, [id=#13]
(20) BroadcastNestedLoopJoin
Join condition: None
(21) Expand [codegen id : 5]
Input [5]: [inv_quantity_on_hand#3, i_brand#8, i_class#9, i_category#10, i_product_name#11]
Arguments: [List(inv_quantity_on_hand#3, i_product_name#11, i_brand#8, i_class#9, i_category#10, 0), List(inv_quantity_on_hand#3, i_product_name#11, i_brand#8, i_class#9, null, 1), List(inv_quantity_on_hand#3, i_product_name#11, i_brand#8, null, null, 3), List(inv_quantity_on_hand#3, i_product_name#11, null, null, null, 7), List(inv_quantity_on_hand#3, null, null, null, null, 15)], [inv_quantity_on_hand#3, i_product_name#14, i_brand#15, i_class#16, i_category#17, spark_grouping_id#18]
(22) HashAggregate [codegen id : 5]
Input [6]: [inv_quantity_on_hand#3, i_product_name#14, i_brand#15, i_class#16, i_category#17, spark_grouping_id#18]
Keys [5]: [i_product_name#14, i_brand#15, i_class#16, i_category#17, spark_grouping_id#18]
Functions [1]: [partial_avg(cast(inv_quantity_on_hand#3 as bigint))]
Aggregate Attributes [2]: [sum#19, count#20]
Results [7]: [i_product_name#14, i_brand#15, i_class#16, i_category#17, spark_grouping_id#18, sum#21, count#22]
(23) Exchange
Input [7]: [i_product_name#14, i_brand#15, i_class#16, i_category#17, spark_grouping_id#18, sum#21, count#22]
Arguments: hashpartitioning(i_product_name#14, i_brand#15, i_class#16, i_category#17, spark_grouping_id#18, 5), true, [id=#23]
(24) HashAggregate [codegen id : 6]
Input [7]: [i_product_name#14, i_brand#15, i_class#16, i_category#17, spark_grouping_id#18, sum#21, count#22]
Keys [5]: [i_product_name#14, i_brand#15, i_class#16, i_category#17, spark_grouping_id#18]
Functions [1]: [avg(cast(inv_quantity_on_hand#3 as bigint))]
Aggregate Attributes [1]: [avg(cast(inv_quantity_on_hand#3 as bigint))#24]
Results [5]: [i_product_name#14, i_brand#15, i_class#16, i_category#17, avg(cast(inv_quantity_on_hand#3 as bigint))#24 AS qoh#25]
(25) TakeOrderedAndProject
Input [5]: [i_product_name#14, i_brand#15, i_class#16, i_category#17, qoh#25]
Arguments: 100, [qoh#25 ASC NULLS FIRST, i_product_name#14 ASC NULLS FIRST, i_brand#15 ASC NULLS FIRST, i_class#16 ASC NULLS FIRST, i_category#17 ASC NULLS FIRST], [i_product_name#14, i_brand#15, i_class#16, i_category#17, qoh#25]