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Posted to commits@hive.apache.org by se...@apache.org on 2017/10/03 22:55:14 UTC
[08/50] [abbrv] hive git commit: HIVE-17543: Enable PerfCliDriver for
HoS (Sahil Takiar, reviewed by Peter Vary) (addendum)
http://git-wip-us.apache.org/repos/asf/hive/blob/9244fdc7/ql/src/test/results/clientpositive/perf/tez/query65.q.out
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diff --git a/ql/src/test/results/clientpositive/perf/tez/query65.q.out b/ql/src/test/results/clientpositive/perf/tez/query65.q.out
new file mode 100644
index 0000000..0091ad0
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/query65.q.out
@@ -0,0 +1,169 @@
+PREHOOK: query: explain
+select
+ s_store_name,
+ i_item_desc,
+ sc.revenue,
+ i_current_price,
+ i_wholesale_cost,
+ i_brand
+ from store, item,
+ (select ss_store_sk, avg(revenue) as ave
+ from
+ (select ss_store_sk, ss_item_sk,
+ sum(ss_sales_price) as revenue
+ from store_sales, date_dim
+ where ss_sold_date_sk = d_date_sk and d_month_seq between 1212 and 1212+11
+ group by ss_store_sk, ss_item_sk) sa
+ group by ss_store_sk) sb,
+ (select ss_store_sk, ss_item_sk, sum(ss_sales_price) as revenue
+ from store_sales, date_dim
+ where ss_sold_date_sk = d_date_sk and d_month_seq between 1212 and 1212+11
+ group by ss_store_sk, ss_item_sk) sc
+ where sb.ss_store_sk = sc.ss_store_sk and
+ sc.revenue <= 0.1 * sb.ave and
+ s_store_sk = sc.ss_store_sk and
+ i_item_sk = sc.ss_item_sk
+ order by s_store_name, i_item_desc
+limit 100
+PREHOOK: type: QUERY
+POSTHOOK: query: explain
+select
+ s_store_name,
+ i_item_desc,
+ sc.revenue,
+ i_current_price,
+ i_wholesale_cost,
+ i_brand
+ from store, item,
+ (select ss_store_sk, avg(revenue) as ave
+ from
+ (select ss_store_sk, ss_item_sk,
+ sum(ss_sales_price) as revenue
+ from store_sales, date_dim
+ where ss_sold_date_sk = d_date_sk and d_month_seq between 1212 and 1212+11
+ group by ss_store_sk, ss_item_sk) sa
+ group by ss_store_sk) sb,
+ (select ss_store_sk, ss_item_sk, sum(ss_sales_price) as revenue
+ from store_sales, date_dim
+ where ss_sold_date_sk = d_date_sk and d_month_seq between 1212 and 1212+11
+ group by ss_store_sk, ss_item_sk) sc
+ where sb.ss_store_sk = sc.ss_store_sk and
+ sc.revenue <= 0.1 * sb.ave and
+ s_store_sk = sc.ss_store_sk and
+ i_item_sk = sc.ss_item_sk
+ order by s_store_name, i_item_desc
+limit 100
+POSTHOOK: type: QUERY
+Plan optimized by CBO.
+
+Vertex dependency in root stage
+Reducer 2 <- Map 1 (SIMPLE_EDGE), Map 9 (SIMPLE_EDGE)
+Reducer 3 <- Reducer 2 (SIMPLE_EDGE)
+Reducer 4 <- Map 10 (SIMPLE_EDGE), Reducer 3 (SIMPLE_EDGE), Reducer 8 (SIMPLE_EDGE)
+Reducer 5 <- Map 11 (SIMPLE_EDGE), Reducer 4 (SIMPLE_EDGE)
+Reducer 6 <- Reducer 5 (SIMPLE_EDGE)
+Reducer 7 <- Map 1 (SIMPLE_EDGE), Map 9 (SIMPLE_EDGE)
+Reducer 8 <- Reducer 7 (SIMPLE_EDGE)
+
+Stage-0
+ Fetch Operator
+ limit:100
+ Stage-1
+ Reducer 6
+ File Output Operator [FS_51]
+ Limit [LIM_50] (rows=100 width=88)
+ Number of rows:100
+ Select Operator [SEL_49] (rows=255550079 width=88)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5"]
+ <-Reducer 5 [SIMPLE_EDGE]
+ SHUFFLE [RS_48]
+ Select Operator [SEL_47] (rows=255550079 width=88)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5"]
+ Merge Join Operator [MERGEJOIN_81] (rows=255550079 width=88)
+ Conds:RS_44._col1=RS_45._col0(Inner),Output:["_col2","_col6","_col8","_col9","_col10","_col11"]
+ <-Map 11 [SIMPLE_EDGE]
+ SHUFFLE [RS_45]
+ PartitionCols:_col0
+ Select Operator [SEL_38] (rows=462000 width=1436)
+ Output:["_col0","_col1","_col2","_col3","_col4"]
+ Filter Operator [FIL_77] (rows=462000 width=1436)
+ predicate:i_item_sk is not null
+ TableScan [TS_36] (rows=462000 width=1436)
+ default@item,item,Tbl:COMPLETE,Col:NONE,Output:["i_item_sk","i_item_desc","i_current_price","i_wholesale_cost","i_brand"]
+ <-Reducer 4 [SIMPLE_EDGE]
+ SHUFFLE [RS_44]
+ PartitionCols:_col1
+ Filter Operator [FIL_43] (rows=232318249 width=88)
+ predicate:(_col2 <= (0.1 * _col4))
+ Merge Join Operator [MERGEJOIN_80] (rows=696954748 width=88)
+ Conds:RS_39._col0=RS_40._col0(Inner),RS_39._col0=RS_41._col0(Inner),Output:["_col1","_col2","_col4","_col6"]
+ <-Map 10 [SIMPLE_EDGE]
+ SHUFFLE [RS_41]
+ PartitionCols:_col0
+ Select Operator [SEL_35] (rows=1704 width=1910)
+ Output:["_col0","_col1"]
+ Filter Operator [FIL_76] (rows=1704 width=1910)
+ predicate:s_store_sk is not null
+ TableScan [TS_33] (rows=1704 width=1910)
+ default@store,store,Tbl:COMPLETE,Col:NONE,Output:["s_store_sk","s_store_name"]
+ <-Reducer 3 [SIMPLE_EDGE]
+ SHUFFLE [RS_39]
+ PartitionCols:_col0
+ Group By Operator [GBY_12] (rows=316797606 width=88)
+ Output:["_col0","_col1","_col2"],aggregations:["sum(VALUE._col0)"],keys:KEY._col0, KEY._col1
+ <-Reducer 2 [SIMPLE_EDGE]
+ SHUFFLE [RS_11]
+ PartitionCols:_col0, _col1
+ Group By Operator [GBY_10] (rows=633595212 width=88)
+ Output:["_col0","_col1","_col2"],aggregations:["sum(_col3)"],keys:_col2, _col1
+ Merge Join Operator [MERGEJOIN_78] (rows=633595212 width=88)
+ Conds:RS_6._col0=RS_7._col0(Inner),Output:["_col1","_col2","_col3"]
+ <-Map 1 [SIMPLE_EDGE]
+ SHUFFLE [RS_6]
+ PartitionCols:_col0
+ Select Operator [SEL_2] (rows=575995635 width=88)
+ Output:["_col0","_col1","_col2","_col3"]
+ Filter Operator [FIL_72] (rows=575995635 width=88)
+ predicate:(ss_item_sk is not null and ss_sold_date_sk is not null and ss_store_sk is not null)
+ TableScan [TS_0] (rows=575995635 width=88)
+ default@store_sales,store_sales,Tbl:COMPLETE,Col:NONE,Output:["ss_sold_date_sk","ss_item_sk","ss_store_sk","ss_sales_price"]
+ <-Map 9 [SIMPLE_EDGE]
+ SHUFFLE [RS_7]
+ PartitionCols:_col0
+ Select Operator [SEL_5] (rows=8116 width=1119)
+ Output:["_col0"]
+ Filter Operator [FIL_73] (rows=8116 width=1119)
+ predicate:(d_date_sk is not null and d_month_seq BETWEEN 1212 AND 1223)
+ TableScan [TS_3] (rows=73049 width=1119)
+ default@date_dim,date_dim,Tbl:COMPLETE,Col:NONE,Output:["d_date_sk","d_month_seq"]
+ <-Reducer 8 [SIMPLE_EDGE]
+ SHUFFLE [RS_40]
+ PartitionCols:_col0
+ Select Operator [SEL_32] (rows=158398803 width=88)
+ Output:["_col0","_col1"]
+ Group By Operator [GBY_31] (rows=158398803 width=88)
+ Output:["_col0","_col1"],aggregations:["avg(_col2)"],keys:_col1
+ Select Operator [SEL_27] (rows=316797606 width=88)
+ Output:["_col1","_col2"]
+ Group By Operator [GBY_26] (rows=316797606 width=88)
+ Output:["_col0","_col1","_col2"],aggregations:["sum(VALUE._col0)"],keys:KEY._col0, KEY._col1
+ <-Reducer 7 [SIMPLE_EDGE]
+ SHUFFLE [RS_25]
+ PartitionCols:_col0
+ Group By Operator [GBY_24] (rows=633595212 width=88)
+ Output:["_col0","_col1","_col2"],aggregations:["sum(_col3)"],keys:_col2, _col1
+ Merge Join Operator [MERGEJOIN_79] (rows=633595212 width=88)
+ Conds:RS_20._col0=RS_21._col0(Inner),Output:["_col1","_col2","_col3"]
+ <-Map 1 [SIMPLE_EDGE]
+ SHUFFLE [RS_20]
+ PartitionCols:_col0
+ Select Operator [SEL_16] (rows=575995635 width=88)
+ Output:["_col0","_col1","_col2","_col3"]
+ Filter Operator [FIL_74] (rows=575995635 width=88)
+ predicate:(ss_sold_date_sk is not null and ss_store_sk is not null)
+ Please refer to the previous TableScan [TS_0]
+ <-Map 9 [SIMPLE_EDGE]
+ SHUFFLE [RS_21]
+ PartitionCols:_col0
+ Please refer to the previous Select Operator [SEL_5]
+
http://git-wip-us.apache.org/repos/asf/hive/blob/9244fdc7/ql/src/test/results/clientpositive/perf/tez/query66.q.out
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diff --git a/ql/src/test/results/clientpositive/perf/tez/query66.q.out b/ql/src/test/results/clientpositive/perf/tez/query66.q.out
new file mode 100644
index 0000000..7c7d7a1
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/query66.q.out
@@ -0,0 +1,612 @@
+PREHOOK: query: explain
+select
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,ship_carriers
+ ,year
+ ,sum(jan_sales) as jan_sales
+ ,sum(feb_sales) as feb_sales
+ ,sum(mar_sales) as mar_sales
+ ,sum(apr_sales) as apr_sales
+ ,sum(may_sales) as may_sales
+ ,sum(jun_sales) as jun_sales
+ ,sum(jul_sales) as jul_sales
+ ,sum(aug_sales) as aug_sales
+ ,sum(sep_sales) as sep_sales
+ ,sum(oct_sales) as oct_sales
+ ,sum(nov_sales) as nov_sales
+ ,sum(dec_sales) as dec_sales
+ ,sum(jan_sales/w_warehouse_sq_ft) as jan_sales_per_sq_foot
+ ,sum(feb_sales/w_warehouse_sq_ft) as feb_sales_per_sq_foot
+ ,sum(mar_sales/w_warehouse_sq_ft) as mar_sales_per_sq_foot
+ ,sum(apr_sales/w_warehouse_sq_ft) as apr_sales_per_sq_foot
+ ,sum(may_sales/w_warehouse_sq_ft) as may_sales_per_sq_foot
+ ,sum(jun_sales/w_warehouse_sq_ft) as jun_sales_per_sq_foot
+ ,sum(jul_sales/w_warehouse_sq_ft) as jul_sales_per_sq_foot
+ ,sum(aug_sales/w_warehouse_sq_ft) as aug_sales_per_sq_foot
+ ,sum(sep_sales/w_warehouse_sq_ft) as sep_sales_per_sq_foot
+ ,sum(oct_sales/w_warehouse_sq_ft) as oct_sales_per_sq_foot
+ ,sum(nov_sales/w_warehouse_sq_ft) as nov_sales_per_sq_foot
+ ,sum(dec_sales/w_warehouse_sq_ft) as dec_sales_per_sq_foot
+ ,sum(jan_net) as jan_net
+ ,sum(feb_net) as feb_net
+ ,sum(mar_net) as mar_net
+ ,sum(apr_net) as apr_net
+ ,sum(may_net) as may_net
+ ,sum(jun_net) as jun_net
+ ,sum(jul_net) as jul_net
+ ,sum(aug_net) as aug_net
+ ,sum(sep_net) as sep_net
+ ,sum(oct_net) as oct_net
+ ,sum(nov_net) as nov_net
+ ,sum(dec_net) as dec_net
+ from (
+ (select
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,'DIAMOND' || ',' || 'AIRBORNE' as ship_carriers
+ ,d_year as year
+ ,sum(case when d_moy = 1
+ then ws_sales_price* ws_quantity else 0 end) as jan_sales
+ ,sum(case when d_moy = 2
+ then ws_sales_price* ws_quantity else 0 end) as feb_sales
+ ,sum(case when d_moy = 3
+ then ws_sales_price* ws_quantity else 0 end) as mar_sales
+ ,sum(case when d_moy = 4
+ then ws_sales_price* ws_quantity else 0 end) as apr_sales
+ ,sum(case when d_moy = 5
+ then ws_sales_price* ws_quantity else 0 end) as may_sales
+ ,sum(case when d_moy = 6
+ then ws_sales_price* ws_quantity else 0 end) as jun_sales
+ ,sum(case when d_moy = 7
+ then ws_sales_price* ws_quantity else 0 end) as jul_sales
+ ,sum(case when d_moy = 8
+ then ws_sales_price* ws_quantity else 0 end) as aug_sales
+ ,sum(case when d_moy = 9
+ then ws_sales_price* ws_quantity else 0 end) as sep_sales
+ ,sum(case when d_moy = 10
+ then ws_sales_price* ws_quantity else 0 end) as oct_sales
+ ,sum(case when d_moy = 11
+ then ws_sales_price* ws_quantity else 0 end) as nov_sales
+ ,sum(case when d_moy = 12
+ then ws_sales_price* ws_quantity else 0 end) as dec_sales
+ ,sum(case when d_moy = 1
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as jan_net
+ ,sum(case when d_moy = 2
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as feb_net
+ ,sum(case when d_moy = 3
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as mar_net
+ ,sum(case when d_moy = 4
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as apr_net
+ ,sum(case when d_moy = 5
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as may_net
+ ,sum(case when d_moy = 6
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as jun_net
+ ,sum(case when d_moy = 7
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as jul_net
+ ,sum(case when d_moy = 8
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as aug_net
+ ,sum(case when d_moy = 9
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as sep_net
+ ,sum(case when d_moy = 10
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as oct_net
+ ,sum(case when d_moy = 11
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as nov_net
+ ,sum(case when d_moy = 12
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as dec_net
+ from
+ web_sales
+ ,warehouse
+ ,date_dim
+ ,time_dim
+ ,ship_mode
+ where
+ ws_warehouse_sk = w_warehouse_sk
+ and ws_sold_date_sk = d_date_sk
+ and ws_sold_time_sk = t_time_sk
+ and ws_ship_mode_sk = sm_ship_mode_sk
+ and d_year = 2002
+ and t_time between 49530 and 49530+28800
+ and sm_carrier in ('DIAMOND','AIRBORNE')
+ group by
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,d_year
+ )
+ union all
+ (select
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,'DIAMOND' || ',' || 'AIRBORNE' as ship_carriers
+ ,d_year as year
+ ,sum(case when d_moy = 1
+ then cs_ext_sales_price* cs_quantity else 0 end) as jan_sales
+ ,sum(case when d_moy = 2
+ then cs_ext_sales_price* cs_quantity else 0 end) as feb_sales
+ ,sum(case when d_moy = 3
+ then cs_ext_sales_price* cs_quantity else 0 end) as mar_sales
+ ,sum(case when d_moy = 4
+ then cs_ext_sales_price* cs_quantity else 0 end) as apr_sales
+ ,sum(case when d_moy = 5
+ then cs_ext_sales_price* cs_quantity else 0 end) as may_sales
+ ,sum(case when d_moy = 6
+ then cs_ext_sales_price* cs_quantity else 0 end) as jun_sales
+ ,sum(case when d_moy = 7
+ then cs_ext_sales_price* cs_quantity else 0 end) as jul_sales
+ ,sum(case when d_moy = 8
+ then cs_ext_sales_price* cs_quantity else 0 end) as aug_sales
+ ,sum(case when d_moy = 9
+ then cs_ext_sales_price* cs_quantity else 0 end) as sep_sales
+ ,sum(case when d_moy = 10
+ then cs_ext_sales_price* cs_quantity else 0 end) as oct_sales
+ ,sum(case when d_moy = 11
+ then cs_ext_sales_price* cs_quantity else 0 end) as nov_sales
+ ,sum(case when d_moy = 12
+ then cs_ext_sales_price* cs_quantity else 0 end) as dec_sales
+ ,sum(case when d_moy = 1
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as jan_net
+ ,sum(case when d_moy = 2
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as feb_net
+ ,sum(case when d_moy = 3
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as mar_net
+ ,sum(case when d_moy = 4
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as apr_net
+ ,sum(case when d_moy = 5
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as may_net
+ ,sum(case when d_moy = 6
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as jun_net
+ ,sum(case when d_moy = 7
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as jul_net
+ ,sum(case when d_moy = 8
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as aug_net
+ ,sum(case when d_moy = 9
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as sep_net
+ ,sum(case when d_moy = 10
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as oct_net
+ ,sum(case when d_moy = 11
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as nov_net
+ ,sum(case when d_moy = 12
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as dec_net
+ from
+ catalog_sales
+ ,warehouse
+ ,date_dim
+ ,time_dim
+ ,ship_mode
+ where
+ cs_warehouse_sk = w_warehouse_sk
+ and cs_sold_date_sk = d_date_sk
+ and cs_sold_time_sk = t_time_sk
+ and cs_ship_mode_sk = sm_ship_mode_sk
+ and d_year = 2002
+ and t_time between 49530 AND 49530+28800
+ and sm_carrier in ('DIAMOND','AIRBORNE')
+ group by
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,d_year
+ )
+ ) x
+ group by
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,ship_carriers
+ ,year
+ order by w_warehouse_name
+ limit 100
+PREHOOK: type: QUERY
+POSTHOOK: query: explain
+select
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,ship_carriers
+ ,year
+ ,sum(jan_sales) as jan_sales
+ ,sum(feb_sales) as feb_sales
+ ,sum(mar_sales) as mar_sales
+ ,sum(apr_sales) as apr_sales
+ ,sum(may_sales) as may_sales
+ ,sum(jun_sales) as jun_sales
+ ,sum(jul_sales) as jul_sales
+ ,sum(aug_sales) as aug_sales
+ ,sum(sep_sales) as sep_sales
+ ,sum(oct_sales) as oct_sales
+ ,sum(nov_sales) as nov_sales
+ ,sum(dec_sales) as dec_sales
+ ,sum(jan_sales/w_warehouse_sq_ft) as jan_sales_per_sq_foot
+ ,sum(feb_sales/w_warehouse_sq_ft) as feb_sales_per_sq_foot
+ ,sum(mar_sales/w_warehouse_sq_ft) as mar_sales_per_sq_foot
+ ,sum(apr_sales/w_warehouse_sq_ft) as apr_sales_per_sq_foot
+ ,sum(may_sales/w_warehouse_sq_ft) as may_sales_per_sq_foot
+ ,sum(jun_sales/w_warehouse_sq_ft) as jun_sales_per_sq_foot
+ ,sum(jul_sales/w_warehouse_sq_ft) as jul_sales_per_sq_foot
+ ,sum(aug_sales/w_warehouse_sq_ft) as aug_sales_per_sq_foot
+ ,sum(sep_sales/w_warehouse_sq_ft) as sep_sales_per_sq_foot
+ ,sum(oct_sales/w_warehouse_sq_ft) as oct_sales_per_sq_foot
+ ,sum(nov_sales/w_warehouse_sq_ft) as nov_sales_per_sq_foot
+ ,sum(dec_sales/w_warehouse_sq_ft) as dec_sales_per_sq_foot
+ ,sum(jan_net) as jan_net
+ ,sum(feb_net) as feb_net
+ ,sum(mar_net) as mar_net
+ ,sum(apr_net) as apr_net
+ ,sum(may_net) as may_net
+ ,sum(jun_net) as jun_net
+ ,sum(jul_net) as jul_net
+ ,sum(aug_net) as aug_net
+ ,sum(sep_net) as sep_net
+ ,sum(oct_net) as oct_net
+ ,sum(nov_net) as nov_net
+ ,sum(dec_net) as dec_net
+ from (
+ (select
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,'DIAMOND' || ',' || 'AIRBORNE' as ship_carriers
+ ,d_year as year
+ ,sum(case when d_moy = 1
+ then ws_sales_price* ws_quantity else 0 end) as jan_sales
+ ,sum(case when d_moy = 2
+ then ws_sales_price* ws_quantity else 0 end) as feb_sales
+ ,sum(case when d_moy = 3
+ then ws_sales_price* ws_quantity else 0 end) as mar_sales
+ ,sum(case when d_moy = 4
+ then ws_sales_price* ws_quantity else 0 end) as apr_sales
+ ,sum(case when d_moy = 5
+ then ws_sales_price* ws_quantity else 0 end) as may_sales
+ ,sum(case when d_moy = 6
+ then ws_sales_price* ws_quantity else 0 end) as jun_sales
+ ,sum(case when d_moy = 7
+ then ws_sales_price* ws_quantity else 0 end) as jul_sales
+ ,sum(case when d_moy = 8
+ then ws_sales_price* ws_quantity else 0 end) as aug_sales
+ ,sum(case when d_moy = 9
+ then ws_sales_price* ws_quantity else 0 end) as sep_sales
+ ,sum(case when d_moy = 10
+ then ws_sales_price* ws_quantity else 0 end) as oct_sales
+ ,sum(case when d_moy = 11
+ then ws_sales_price* ws_quantity else 0 end) as nov_sales
+ ,sum(case when d_moy = 12
+ then ws_sales_price* ws_quantity else 0 end) as dec_sales
+ ,sum(case when d_moy = 1
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as jan_net
+ ,sum(case when d_moy = 2
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as feb_net
+ ,sum(case when d_moy = 3
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as mar_net
+ ,sum(case when d_moy = 4
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as apr_net
+ ,sum(case when d_moy = 5
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as may_net
+ ,sum(case when d_moy = 6
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as jun_net
+ ,sum(case when d_moy = 7
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as jul_net
+ ,sum(case when d_moy = 8
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as aug_net
+ ,sum(case when d_moy = 9
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as sep_net
+ ,sum(case when d_moy = 10
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as oct_net
+ ,sum(case when d_moy = 11
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as nov_net
+ ,sum(case when d_moy = 12
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as dec_net
+ from
+ web_sales
+ ,warehouse
+ ,date_dim
+ ,time_dim
+ ,ship_mode
+ where
+ ws_warehouse_sk = w_warehouse_sk
+ and ws_sold_date_sk = d_date_sk
+ and ws_sold_time_sk = t_time_sk
+ and ws_ship_mode_sk = sm_ship_mode_sk
+ and d_year = 2002
+ and t_time between 49530 and 49530+28800
+ and sm_carrier in ('DIAMOND','AIRBORNE')
+ group by
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,d_year
+ )
+ union all
+ (select
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,'DIAMOND' || ',' || 'AIRBORNE' as ship_carriers
+ ,d_year as year
+ ,sum(case when d_moy = 1
+ then cs_ext_sales_price* cs_quantity else 0 end) as jan_sales
+ ,sum(case when d_moy = 2
+ then cs_ext_sales_price* cs_quantity else 0 end) as feb_sales
+ ,sum(case when d_moy = 3
+ then cs_ext_sales_price* cs_quantity else 0 end) as mar_sales
+ ,sum(case when d_moy = 4
+ then cs_ext_sales_price* cs_quantity else 0 end) as apr_sales
+ ,sum(case when d_moy = 5
+ then cs_ext_sales_price* cs_quantity else 0 end) as may_sales
+ ,sum(case when d_moy = 6
+ then cs_ext_sales_price* cs_quantity else 0 end) as jun_sales
+ ,sum(case when d_moy = 7
+ then cs_ext_sales_price* cs_quantity else 0 end) as jul_sales
+ ,sum(case when d_moy = 8
+ then cs_ext_sales_price* cs_quantity else 0 end) as aug_sales
+ ,sum(case when d_moy = 9
+ then cs_ext_sales_price* cs_quantity else 0 end) as sep_sales
+ ,sum(case when d_moy = 10
+ then cs_ext_sales_price* cs_quantity else 0 end) as oct_sales
+ ,sum(case when d_moy = 11
+ then cs_ext_sales_price* cs_quantity else 0 end) as nov_sales
+ ,sum(case when d_moy = 12
+ then cs_ext_sales_price* cs_quantity else 0 end) as dec_sales
+ ,sum(case when d_moy = 1
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as jan_net
+ ,sum(case when d_moy = 2
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as feb_net
+ ,sum(case when d_moy = 3
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as mar_net
+ ,sum(case when d_moy = 4
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as apr_net
+ ,sum(case when d_moy = 5
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as may_net
+ ,sum(case when d_moy = 6
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as jun_net
+ ,sum(case when d_moy = 7
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as jul_net
+ ,sum(case when d_moy = 8
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as aug_net
+ ,sum(case when d_moy = 9
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as sep_net
+ ,sum(case when d_moy = 10
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as oct_net
+ ,sum(case when d_moy = 11
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as nov_net
+ ,sum(case when d_moy = 12
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as dec_net
+ from
+ catalog_sales
+ ,warehouse
+ ,date_dim
+ ,time_dim
+ ,ship_mode
+ where
+ cs_warehouse_sk = w_warehouse_sk
+ and cs_sold_date_sk = d_date_sk
+ and cs_sold_time_sk = t_time_sk
+ and cs_ship_mode_sk = sm_ship_mode_sk
+ and d_year = 2002
+ and t_time between 49530 AND 49530+28800
+ and sm_carrier in ('DIAMOND','AIRBORNE')
+ group by
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,d_year
+ )
+ ) x
+ group by
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,ship_carriers
+ ,year
+ order by w_warehouse_name
+ limit 100
+POSTHOOK: type: QUERY
+Plan optimized by CBO.
+
+Vertex dependency in root stage
+Reducer 11 <- Map 10 (SIMPLE_EDGE), Map 19 (SIMPLE_EDGE)
+Reducer 12 <- Map 16 (SIMPLE_EDGE), Reducer 11 (SIMPLE_EDGE)
+Reducer 13 <- Map 17 (SIMPLE_EDGE), Reducer 12 (SIMPLE_EDGE)
+Reducer 14 <- Map 18 (SIMPLE_EDGE), Reducer 13 (SIMPLE_EDGE)
+Reducer 15 <- Reducer 14 (SIMPLE_EDGE), Union 7 (CONTAINS)
+Reducer 2 <- Map 1 (SIMPLE_EDGE), Map 10 (SIMPLE_EDGE)
+Reducer 3 <- Map 16 (SIMPLE_EDGE), Reducer 2 (SIMPLE_EDGE)
+Reducer 4 <- Map 17 (SIMPLE_EDGE), Reducer 3 (SIMPLE_EDGE)
+Reducer 5 <- Map 18 (SIMPLE_EDGE), Reducer 4 (SIMPLE_EDGE)
+Reducer 6 <- Reducer 5 (SIMPLE_EDGE), Union 7 (CONTAINS)
+Reducer 8 <- Union 7 (SIMPLE_EDGE)
+Reducer 9 <- Reducer 8 (SIMPLE_EDGE)
+
+Stage-0
+ Fetch Operator
+ limit:-1
+ Stage-1
+ Reducer 9
+ File Output Operator [FS_77]
+ Select Operator [SEL_76] (rows=100 width=135)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8","_col9","_col10","_col11","_col12","_col13","_col14","_col15","_col16","_col17","_col18","_col19","_col20","_col21","_col22","_col23","_col24","_col25","_col26","_col27","_col28","_col29","_col30","_col31","_col32","_col33","_col34","_col35","_col36","_col37","_col38","_col39","_col40","_col41","_col42","_col43"]
+ Limit [LIM_75] (rows=100 width=135)
+ Number of rows:100
+ Select Operator [SEL_74] (rows=158120068 width=135)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8","_col9","_col10","_col11","_col12","_col13","_col14","_col15","_col16","_col17","_col18","_col19","_col20","_col21","_col22","_col23","_col24","_col25","_col26","_col27","_col28","_col29","_col30","_col31","_col32","_col33","_col34","_col35","_col36","_col37","_col38","_col39","_col40","_col41"]
+ <-Reducer 8 [SIMPLE_EDGE]
+ SHUFFLE [RS_73]
+ Group By Operator [GBY_71] (rows=158120068 width=135)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8","_col9","_col10","_col11","_col12","_col13","_col14","_col15","_col16","_col17","_col18","_col19","_col20","_col21","_col22","_col23","_col24","_col25","_col26","_col27","_col28","_col29","_col30","_col31","_col32","_col33","_col34","_col35","_col36","_col37","_col38","_col39","_col40","_col41"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)","sum(VALUE._col2)","sum(VALUE._col3)","sum(VALUE._col4)","sum(VALUE._col5)","sum(VALUE._col6)","sum(VALUE._col7)","sum(VALUE._col8)","sum(VALUE._col9)","sum(VALUE._col10)","sum(VALUE._col11)","sum(VALUE._col12)","sum(VALUE._col13)","sum(VALUE._col14)","sum(VALUE._col15)","sum(VALUE._col16)","sum(VALUE._col17)","sum(VALUE._col18)","sum(VALUE._col19)","sum(VALUE._col20)","sum(VALUE._col21)","sum(VALUE._col22)","sum(VALUE._col23)","sum(VALUE._col24)","sum(VALUE._col25)","sum(VALUE._col26)","sum(VALUE._col27)","sum(VALUE._col28)","sum(VALUE._col29)
","sum(VALUE._col30)","sum(VALUE._col31)","sum(VALUE._col32)","sum(VALUE._col33)","sum(VALUE._col34)","sum(VALUE._col35)"],keys:KEY._col0, KEY._col1, KEY._col2, KEY._col3, KEY._col4, KEY._col5
+ <-Union 7 [SIMPLE_EDGE]
+ <-Reducer 15 [CONTAINS]
+ Reduce Output Operator [RS_70]
+ PartitionCols:_col0, _col1, _col2, _col3, _col4, _col5
+ Group By Operator [GBY_69] (rows=316240137 width=135)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8","_col9","_col10","_col11","_col12","_col13","_col14","_col15","_col16","_col17","_col18","_col19","_col20","_col21","_col22","_col23","_col24","_col25","_col26","_col27","_col28","_col29","_col30","_col31","_col32","_col33","_col34","_col35","_col36","_col37","_col38","_col39","_col40","_col41"],aggregations:["sum(_col6)","sum(_col7)","sum(_col8)","sum(_col9)","sum(_col10)","sum(_col11)","sum(_col12)","sum(_col13)","sum(_col14)","sum(_col15)","sum(_col16)","sum(_col17)","sum(_col18)","sum(_col19)","sum(_col20)","sum(_col21)","sum(_col22)","sum(_col23)","sum(_col24)","sum(_col25)","sum(_col26)","sum(_col27)","sum(_col28)","sum(_col29)","sum(_col30)","sum(_col31)","sum(_col32)","sum(_col33)","sum(_col34)","sum(_col35)","sum(_col36)","sum(_col37)","sum(_col38)","sum(_col39)","sum(_col40)","sum(_col41)"],keys:_col0, _col1, _col2, _col3, _col4, _col5
+ Select Operator [SEL_67] (rows=316240137 width=135)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8","_col9","_col10","_col11","_col12","_col13","_col14","_col15","_col16","_col17","_col18","_col19","_col20","_col21","_col22","_col23","_col24","_col25","_col26","_col27","_col28","_col29","_col30","_col31","_col32","_col33","_col34","_col35","_col36","_col37","_col38","_col39","_col40","_col41"]
+ Group By Operator [GBY_64] (rows=210822976 width=135)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8","_col9","_col10","_col11","_col12","_col13","_col14","_col15","_col16","_col17","_col18","_col19","_col20","_col21","_col22","_col23","_col24","_col25","_col26","_col27","_col28","_col29"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)","sum(VALUE._col2)","sum(VALUE._col3)","sum(VALUE._col4)","sum(VALUE._col5)","sum(VALUE._col6)","sum(VALUE._col7)","sum(VALUE._col8)","sum(VALUE._col9)","sum(VALUE._col10)","sum(VALUE._col11)","sum(VALUE._col12)","sum(VALUE._col13)","sum(VALUE._col14)","sum(VALUE._col15)","sum(VALUE._col16)","sum(VALUE._col17)","sum(VALUE._col18)","sum(VALUE._col19)","sum(VALUE._col20)","sum(VALUE._col21)","sum(VALUE._col22)","sum(VALUE._col23)"],keys:KEY._col0, KEY._col1, KEY._col2, KEY._col3, KEY._col4, KEY._col5
+ <-Reducer 14 [SIMPLE_EDGE]
+ SHUFFLE [RS_63]
+ PartitionCols:_col0, _col1, _col2, _col3, _col4, _col5
+ Group By Operator [GBY_62] (rows=421645953 width=135)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8","_col9","_col10","_col11","_col12","_col13","_col14","_col15","_col16","_col17","_col18","_col19","_col20","_col21","_col22","_col23","_col24","_col25","_col26","_col27","_col28","_col29"],aggregations:["sum(_col6)","sum(_col7)","sum(_col8)","sum(_col9)","sum(_col10)","sum(_col11)","sum(_col12)","sum(_col13)","sum(_col14)","sum(_col15)","sum(_col16)","sum(_col17)","sum(_col18)","sum(_col19)","sum(_col20)","sum(_col21)","sum(_col22)","sum(_col23)","sum(_col24)","sum(_col25)","sum(_col26)","sum(_col27)","sum(_col28)","sum(_col29)"],keys:_col0, _col1, _col2, _col3, _col4, _col5
+ Select Operator [SEL_60] (rows=421645953 width=135)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8","_col9","_col10","_col11","_col12","_col13","_col14","_col15","_col16","_col17","_col18","_col19","_col20","_col21","_col22","_col23","_col24","_col25","_col26","_col27","_col28","_col29"]
+ Merge Join Operator [MERGEJOIN_123] (rows=421645953 width=135)
+ Conds:RS_57._col3=RS_58._col0(Inner),Output:["_col4","_col5","_col6","_col11","_col15","_col16","_col17","_col18","_col19","_col20"]
+ <-Map 18 [SIMPLE_EDGE]
+ SHUFFLE [RS_58]
+ PartitionCols:_col0
+ Select Operator [SEL_14] (rows=27 width=1029)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"]
+ Filter Operator [FIL_110] (rows=27 width=1029)
+ predicate:w_warehouse_sk is not null
+ TableScan [TS_12] (rows=27 width=1029)
+ default@warehouse,warehouse,Tbl:COMPLETE,Col:NONE,Output:["w_warehouse_sk","w_warehouse_name","w_warehouse_sq_ft","w_city","w_county","w_state","w_country"]
+ <-Reducer 13 [SIMPLE_EDGE]
+ SHUFFLE [RS_57]
+ PartitionCols:_col3
+ Merge Join Operator [MERGEJOIN_122] (rows=383314495 width=135)
+ Conds:RS_54._col2=RS_55._col0(Inner),Output:["_col3","_col4","_col5","_col6","_col11"]
+ <-Map 17 [SIMPLE_EDGE]
+ SHUFFLE [RS_55]
+ PartitionCols:_col0
+ Select Operator [SEL_11] (rows=1 width=0)
+ Output:["_col0"]
+ Filter Operator [FIL_109] (rows=1 width=0)
+ predicate:((sm_carrier) IN ('DIAMOND', 'AIRBORNE') and sm_ship_mode_sk is not null)
+ TableScan [TS_9] (rows=1 width=0)
+ default@ship_mode,ship_mode,Tbl:PARTIAL,Col:NONE,Output:["sm_ship_mode_sk","sm_carrier"]
+ <-Reducer 12 [SIMPLE_EDGE]
+ SHUFFLE [RS_54]
+ PartitionCols:_col2
+ Merge Join Operator [MERGEJOIN_121] (rows=348467716 width=135)
+ Conds:RS_51._col0=RS_52._col0(Inner),Output:["_col2","_col3","_col4","_col5","_col6","_col11"]
+ <-Map 16 [SIMPLE_EDGE]
+ SHUFFLE [RS_52]
+ PartitionCols:_col0
+ Select Operator [SEL_8] (rows=36524 width=1119)
+ Output:["_col0","_col2"]
+ Filter Operator [FIL_108] (rows=36524 width=1119)
+ predicate:((d_year = 2002) and d_date_sk is not null)
+ TableScan [TS_6] (rows=73049 width=1119)
+ default@date_dim,date_dim,Tbl:COMPLETE,Col:NONE,Output:["d_date_sk","d_year","d_moy"]
+ <-Reducer 11 [SIMPLE_EDGE]
+ SHUFFLE [RS_51]
+ PartitionCols:_col0
+ Merge Join Operator [MERGEJOIN_120] (rows=316788826 width=135)
+ Conds:RS_48._col1=RS_49._col0(Inner),Output:["_col0","_col2","_col3","_col4","_col5","_col6"]
+ <-Map 10 [SIMPLE_EDGE]
+ SHUFFLE [RS_49]
+ PartitionCols:_col0
+ Select Operator [SEL_5] (rows=9600 width=471)
+ Output:["_col0"]
+ Filter Operator [FIL_107] (rows=9600 width=471)
+ predicate:(t_time BETWEEN 49530 AND 78330 and t_time_sk is not null)
+ TableScan [TS_3] (rows=86400 width=471)
+ default@time_dim,time_dim,Tbl:COMPLETE,Col:NONE,Output:["t_time_sk","t_time"]
+ <-Map 19 [SIMPLE_EDGE]
+ SHUFFLE [RS_48]
+ PartitionCols:_col1
+ Select Operator [SEL_35] (rows=287989836 width=135)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"]
+ Filter Operator [FIL_111] (rows=287989836 width=135)
+ predicate:(cs_ship_mode_sk is not null and cs_sold_date_sk is not null and cs_sold_time_sk is not null and cs_warehouse_sk is not null)
+ TableScan [TS_33] (rows=287989836 width=135)
+ default@catalog_sales,catalog_sales,Tbl:COMPLETE,Col:NONE,Output:["cs_sold_date_sk","cs_sold_time_sk","cs_ship_mode_sk","cs_warehouse_sk","cs_quantity","cs_ext_sales_price","cs_net_paid_inc_ship_tax"]
+ <-Reducer 6 [CONTAINS]
+ Reduce Output Operator [RS_70]
+ PartitionCols:_col0, _col1, _col2, _col3, _col4, _col5
+ Group By Operator [GBY_69] (rows=316240137 width=135)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8","_col9","_col10","_col11","_col12","_col13","_col14","_col15","_col16","_col17","_col18","_col19","_col20","_col21","_col22","_col23","_col24","_col25","_col26","_col27","_col28","_col29","_col30","_col31","_col32","_col33","_col34","_col35","_col36","_col37","_col38","_col39","_col40","_col41"],aggregations:["sum(_col6)","sum(_col7)","sum(_col8)","sum(_col9)","sum(_col10)","sum(_col11)","sum(_col12)","sum(_col13)","sum(_col14)","sum(_col15)","sum(_col16)","sum(_col17)","sum(_col18)","sum(_col19)","sum(_col20)","sum(_col21)","sum(_col22)","sum(_col23)","sum(_col24)","sum(_col25)","sum(_col26)","sum(_col27)","sum(_col28)","sum(_col29)","sum(_col30)","sum(_col31)","sum(_col32)","sum(_col33)","sum(_col34)","sum(_col35)","sum(_col36)","sum(_col37)","sum(_col38)","sum(_col39)","sum(_col40)","sum(_col41)"],keys:_col0, _col1, _col2, _col3, _col4, _col5
+ Select Operator [SEL_67] (rows=316240137 width=135)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8","_col9","_col10","_col11","_col12","_col13","_col14","_col15","_col16","_col17","_col18","_col19","_col20","_col21","_col22","_col23","_col24","_col25","_col26","_col27","_col28","_col29","_col30","_col31","_col32","_col33","_col34","_col35","_col36","_col37","_col38","_col39","_col40","_col41"]
+ Group By Operator [GBY_31] (rows=105417161 width=135)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8","_col9","_col10","_col11","_col12","_col13","_col14","_col15","_col16","_col17","_col18","_col19","_col20","_col21","_col22","_col23","_col24","_col25","_col26","_col27","_col28","_col29"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)","sum(VALUE._col2)","sum(VALUE._col3)","sum(VALUE._col4)","sum(VALUE._col5)","sum(VALUE._col6)","sum(VALUE._col7)","sum(VALUE._col8)","sum(VALUE._col9)","sum(VALUE._col10)","sum(VALUE._col11)","sum(VALUE._col12)","sum(VALUE._col13)","sum(VALUE._col14)","sum(VALUE._col15)","sum(VALUE._col16)","sum(VALUE._col17)","sum(VALUE._col18)","sum(VALUE._col19)","sum(VALUE._col20)","sum(VALUE._col21)","sum(VALUE._col22)","sum(VALUE._col23)"],keys:KEY._col0, KEY._col1, KEY._col2, KEY._col3, KEY._col4, KEY._col5
+ <-Reducer 5 [SIMPLE_EDGE]
+ SHUFFLE [RS_30]
+ PartitionCols:_col0, _col1, _col2, _col3, _col4, _col5
+ Group By Operator [GBY_29] (rows=210834322 width=135)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8","_col9","_col10","_col11","_col12","_col13","_col14","_col15","_col16","_col17","_col18","_col19","_col20","_col21","_col22","_col23","_col24","_col25","_col26","_col27","_col28","_col29"],aggregations:["sum(_col6)","sum(_col7)","sum(_col8)","sum(_col9)","sum(_col10)","sum(_col11)","sum(_col12)","sum(_col13)","sum(_col14)","sum(_col15)","sum(_col16)","sum(_col17)","sum(_col18)","sum(_col19)","sum(_col20)","sum(_col21)","sum(_col22)","sum(_col23)","sum(_col24)","sum(_col25)","sum(_col26)","sum(_col27)","sum(_col28)","sum(_col29)"],keys:_col0, _col1, _col2, _col3, _col4, _col5
+ Select Operator [SEL_27] (rows=210834322 width=135)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8","_col9","_col10","_col11","_col12","_col13","_col14","_col15","_col16","_col17","_col18","_col19","_col20","_col21","_col22","_col23","_col24","_col25","_col26","_col27","_col28","_col29"]
+ Merge Join Operator [MERGEJOIN_119] (rows=210834322 width=135)
+ Conds:RS_24._col3=RS_25._col0(Inner),Output:["_col4","_col5","_col6","_col11","_col15","_col16","_col17","_col18","_col19","_col20"]
+ <-Map 18 [SIMPLE_EDGE]
+ SHUFFLE [RS_25]
+ PartitionCols:_col0
+ Please refer to the previous Select Operator [SEL_14]
+ <-Reducer 4 [SIMPLE_EDGE]
+ SHUFFLE [RS_24]
+ PartitionCols:_col3
+ Merge Join Operator [MERGEJOIN_118] (rows=191667562 width=135)
+ Conds:RS_21._col2=RS_22._col0(Inner),Output:["_col3","_col4","_col5","_col6","_col11"]
+ <-Map 17 [SIMPLE_EDGE]
+ SHUFFLE [RS_22]
+ PartitionCols:_col0
+ Please refer to the previous Select Operator [SEL_11]
+ <-Reducer 3 [SIMPLE_EDGE]
+ SHUFFLE [RS_21]
+ PartitionCols:_col2
+ Merge Join Operator [MERGEJOIN_117] (rows=174243235 width=135)
+ Conds:RS_18._col0=RS_19._col0(Inner),Output:["_col2","_col3","_col4","_col5","_col6","_col11"]
+ <-Map 16 [SIMPLE_EDGE]
+ SHUFFLE [RS_19]
+ PartitionCols:_col0
+ Please refer to the previous Select Operator [SEL_8]
+ <-Reducer 2 [SIMPLE_EDGE]
+ SHUFFLE [RS_18]
+ PartitionCols:_col0
+ Merge Join Operator [MERGEJOIN_116] (rows=158402938 width=135)
+ Conds:RS_15._col1=RS_16._col0(Inner),Output:["_col0","_col2","_col3","_col4","_col5","_col6"]
+ <-Map 10 [SIMPLE_EDGE]
+ SHUFFLE [RS_16]
+ PartitionCols:_col0
+ Please refer to the previous Select Operator [SEL_5]
+ <-Map 1 [SIMPLE_EDGE]
+ SHUFFLE [RS_15]
+ PartitionCols:_col1
+ Select Operator [SEL_2] (rows=144002668 width=135)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"]
+ Filter Operator [FIL_106] (rows=144002668 width=135)
+ predicate:(ws_ship_mode_sk is not null and ws_sold_date_sk is not null and ws_sold_time_sk is not null and ws_warehouse_sk is not null)
+ TableScan [TS_0] (rows=144002668 width=135)
+ default@web_sales,web_sales,Tbl:COMPLETE,Col:NONE,Output:["ws_sold_date_sk","ws_sold_time_sk","ws_ship_mode_sk","ws_warehouse_sk","ws_quantity","ws_sales_price","ws_net_paid_inc_tax"]
+
http://git-wip-us.apache.org/repos/asf/hive/blob/9244fdc7/ql/src/test/results/clientpositive/perf/tez/query67.q.out
----------------------------------------------------------------------
diff --git a/ql/src/test/results/clientpositive/perf/tez/query67.q.out b/ql/src/test/results/clientpositive/perf/tez/query67.q.out
new file mode 100644
index 0000000..803af6f
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/query67.q.out
@@ -0,0 +1,179 @@
+PREHOOK: query: explain
+select *
+from (select i_category
+ ,i_class
+ ,i_brand
+ ,i_product_name
+ ,d_year
+ ,d_qoy
+ ,d_moy
+ ,s_store_id
+ ,sumsales
+ ,rank() over (partition by i_category order by sumsales desc) rk
+ from (select i_category
+ ,i_class
+ ,i_brand
+ ,i_product_name
+ ,d_year
+ ,d_qoy
+ ,d_moy
+ ,s_store_id
+ ,sum(coalesce(ss_sales_price*ss_quantity,0)) sumsales
+ from store_sales
+ ,date_dim
+ ,store
+ ,item
+ where ss_sold_date_sk=d_date_sk
+ and ss_item_sk=i_item_sk
+ and ss_store_sk = s_store_sk
+ and d_month_seq between 1212 and 1212+11
+ group by rollup(i_category, i_class, i_brand, i_product_name, d_year, d_qoy, d_moy,s_store_id))dw1) dw2
+where rk <= 100
+order by i_category
+ ,i_class
+ ,i_brand
+ ,i_product_name
+ ,d_year
+ ,d_qoy
+ ,d_moy
+ ,s_store_id
+ ,sumsales
+ ,rk
+limit 100
+PREHOOK: type: QUERY
+POSTHOOK: query: explain
+select *
+from (select i_category
+ ,i_class
+ ,i_brand
+ ,i_product_name
+ ,d_year
+ ,d_qoy
+ ,d_moy
+ ,s_store_id
+ ,sumsales
+ ,rank() over (partition by i_category order by sumsales desc) rk
+ from (select i_category
+ ,i_class
+ ,i_brand
+ ,i_product_name
+ ,d_year
+ ,d_qoy
+ ,d_moy
+ ,s_store_id
+ ,sum(coalesce(ss_sales_price*ss_quantity,0)) sumsales
+ from store_sales
+ ,date_dim
+ ,store
+ ,item
+ where ss_sold_date_sk=d_date_sk
+ and ss_item_sk=i_item_sk
+ and ss_store_sk = s_store_sk
+ and d_month_seq between 1212 and 1212+11
+ group by rollup(i_category, i_class, i_brand, i_product_name, d_year, d_qoy, d_moy,s_store_id))dw1) dw2
+where rk <= 100
+order by i_category
+ ,i_class
+ ,i_brand
+ ,i_product_name
+ ,d_year
+ ,d_qoy
+ ,d_moy
+ ,s_store_id
+ ,sumsales
+ ,rk
+limit 100
+POSTHOOK: type: QUERY
+Plan optimized by CBO.
+
+Vertex dependency in root stage
+Reducer 2 <- Map 1 (SIMPLE_EDGE), Map 8 (SIMPLE_EDGE)
+Reducer 3 <- Map 9 (SIMPLE_EDGE), Reducer 2 (SIMPLE_EDGE)
+Reducer 4 <- Map 10 (SIMPLE_EDGE), Reducer 3 (SIMPLE_EDGE)
+Reducer 5 <- Reducer 4 (SIMPLE_EDGE)
+Reducer 6 <- Reducer 5 (SIMPLE_EDGE)
+Reducer 7 <- Reducer 6 (SIMPLE_EDGE)
+
+Stage-0
+ Fetch Operator
+ limit:100
+ Stage-1
+ Reducer 7
+ File Output Operator [FS_37]
+ Limit [LIM_36] (rows=100 width=88)
+ Number of rows:100
+ Select Operator [SEL_35] (rows=1149975358 width=88)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8","_col9"]
+ <-Reducer 6 [SIMPLE_EDGE]
+ SHUFFLE [RS_34]
+ Select Operator [SEL_30] (rows=1149975358 width=88)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8","_col9"]
+ Filter Operator [FIL_47] (rows=1149975358 width=88)
+ predicate:(rank_window_0 <= 100)
+ PTF Operator [PTF_29] (rows=3449926075 width=88)
+ Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col16 DESC NULLS LAST","partition by:":"_col0"}]
+ Select Operator [SEL_28] (rows=3449926075 width=88)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col16"]
+ <-Reducer 5 [SIMPLE_EDGE]
+ SHUFFLE [RS_27]
+ PartitionCols:_col0
+ Select Operator [SEL_26] (rows=3449926075 width=88)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col16"]
+ Group By Operator [GBY_25] (rows=3449926075 width=88)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col9"],aggregations:["sum(VALUE._col0)"],keys:KEY._col0, KEY._col1, KEY._col2, KEY._col3, KEY._col4, KEY._col5, KEY._col6, KEY._col7, KEY._col8
+ <-Reducer 4 [SIMPLE_EDGE]
+ SHUFFLE [RS_24]
+ PartitionCols:_col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8
+ Group By Operator [GBY_23] (rows=6899852151 width=88)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8","_col9"],aggregations:["sum(_col8)"],keys:_col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, 0
+ Select Operator [SEL_21] (rows=766650239 width=88)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8"]
+ Merge Join Operator [MERGEJOIN_54] (rows=766650239 width=88)
+ Conds:RS_18._col1=RS_19._col0(Inner),Output:["_col3","_col4","_col7","_col8","_col9","_col11","_col13","_col14","_col15","_col16"]
+ <-Map 10 [SIMPLE_EDGE]
+ SHUFFLE [RS_19]
+ PartitionCols:_col0
+ Select Operator [SEL_11] (rows=462000 width=1436)
+ Output:["_col0","_col1","_col2","_col3","_col4"]
+ Filter Operator [FIL_51] (rows=462000 width=1436)
+ predicate:i_item_sk is not null
+ TableScan [TS_9] (rows=462000 width=1436)
+ default@item,item,Tbl:COMPLETE,Col:NONE,Output:["i_item_sk","i_brand","i_class","i_category","i_product_name"]
+ <-Reducer 3 [SIMPLE_EDGE]
+ SHUFFLE [RS_18]
+ PartitionCols:_col1
+ Merge Join Operator [MERGEJOIN_53] (rows=696954748 width=88)
+ Conds:RS_15._col2=RS_16._col0(Inner),Output:["_col1","_col3","_col4","_col7","_col8","_col9","_col11"]
+ <-Map 9 [SIMPLE_EDGE]
+ SHUFFLE [RS_16]
+ PartitionCols:_col0
+ Select Operator [SEL_8] (rows=1704 width=1910)
+ Output:["_col0","_col1"]
+ Filter Operator [FIL_50] (rows=1704 width=1910)
+ predicate:s_store_sk is not null
+ TableScan [TS_6] (rows=1704 width=1910)
+ default@store,store,Tbl:COMPLETE,Col:NONE,Output:["s_store_sk","s_store_id"]
+ <-Reducer 2 [SIMPLE_EDGE]
+ SHUFFLE [RS_15]
+ PartitionCols:_col2
+ Merge Join Operator [MERGEJOIN_52] (rows=633595212 width=88)
+ Conds:RS_12._col0=RS_13._col0(Inner),Output:["_col1","_col2","_col3","_col4","_col7","_col8","_col9"]
+ <-Map 1 [SIMPLE_EDGE]
+ SHUFFLE [RS_12]
+ PartitionCols:_col0
+ Select Operator [SEL_2] (rows=575995635 width=88)
+ Output:["_col0","_col1","_col2","_col3","_col4"]
+ Filter Operator [FIL_48] (rows=575995635 width=88)
+ predicate:(ss_item_sk is not null and ss_sold_date_sk is not null and ss_store_sk is not null)
+ TableScan [TS_0] (rows=575995635 width=88)
+ default@store_sales,store_sales,Tbl:COMPLETE,Col:NONE,Output:["ss_sold_date_sk","ss_item_sk","ss_store_sk","ss_quantity","ss_sales_price"]
+ <-Map 8 [SIMPLE_EDGE]
+ SHUFFLE [RS_13]
+ PartitionCols:_col0
+ Select Operator [SEL_5] (rows=8116 width=1119)
+ Output:["_col0","_col2","_col3","_col4"]
+ Filter Operator [FIL_49] (rows=8116 width=1119)
+ predicate:(d_date_sk is not null and d_month_seq BETWEEN 1212 AND 1223)
+ TableScan [TS_3] (rows=73049 width=1119)
+ default@date_dim,date_dim,Tbl:COMPLETE,Col:NONE,Output:["d_date_sk","d_month_seq","d_year","d_moy","d_qoy"]
+
http://git-wip-us.apache.org/repos/asf/hive/blob/9244fdc7/ql/src/test/results/clientpositive/perf/tez/query68.q.out
----------------------------------------------------------------------
diff --git a/ql/src/test/results/clientpositive/perf/tez/query68.q.out b/ql/src/test/results/clientpositive/perf/tez/query68.q.out
new file mode 100644
index 0000000..e8f00ff
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/query68.q.out
@@ -0,0 +1,205 @@
+PREHOOK: query: explain
+select c_last_name
+ ,c_first_name
+ ,ca_city
+ ,bought_city
+ ,ss_ticket_number
+ ,extended_price
+ ,extended_tax
+ ,list_price
+ from (select ss_ticket_number
+ ,ss_customer_sk
+ ,ca_city bought_city
+ ,sum(ss_ext_sales_price) extended_price
+ ,sum(ss_ext_list_price) list_price
+ ,sum(ss_ext_tax) extended_tax
+ from store_sales
+ ,date_dim
+ ,store
+ ,household_demographics
+ ,customer_address
+ where store_sales.ss_sold_date_sk = date_dim.d_date_sk
+ and store_sales.ss_store_sk = store.s_store_sk
+ and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
+ and store_sales.ss_addr_sk = customer_address.ca_address_sk
+ and date_dim.d_dom between 1 and 2
+ and (household_demographics.hd_dep_count = 2 or
+ household_demographics.hd_vehicle_count= 1)
+ and date_dim.d_year in (1998,1998+1,1998+2)
+ and store.s_city in ('Cedar Grove','Wildwood')
+ group by ss_ticket_number
+ ,ss_customer_sk
+ ,ss_addr_sk,ca_city) dn
+ ,customer
+ ,customer_address current_addr
+ where ss_customer_sk = c_customer_sk
+ and customer.c_current_addr_sk = current_addr.ca_address_sk
+ and current_addr.ca_city <> bought_city
+ order by c_last_name
+ ,ss_ticket_number
+ limit 100
+PREHOOK: type: QUERY
+POSTHOOK: query: explain
+select c_last_name
+ ,c_first_name
+ ,ca_city
+ ,bought_city
+ ,ss_ticket_number
+ ,extended_price
+ ,extended_tax
+ ,list_price
+ from (select ss_ticket_number
+ ,ss_customer_sk
+ ,ca_city bought_city
+ ,sum(ss_ext_sales_price) extended_price
+ ,sum(ss_ext_list_price) list_price
+ ,sum(ss_ext_tax) extended_tax
+ from store_sales
+ ,date_dim
+ ,store
+ ,household_demographics
+ ,customer_address
+ where store_sales.ss_sold_date_sk = date_dim.d_date_sk
+ and store_sales.ss_store_sk = store.s_store_sk
+ and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
+ and store_sales.ss_addr_sk = customer_address.ca_address_sk
+ and date_dim.d_dom between 1 and 2
+ and (household_demographics.hd_dep_count = 2 or
+ household_demographics.hd_vehicle_count= 1)
+ and date_dim.d_year in (1998,1998+1,1998+2)
+ and store.s_city in ('Cedar Grove','Wildwood')
+ group by ss_ticket_number
+ ,ss_customer_sk
+ ,ss_addr_sk,ca_city) dn
+ ,customer
+ ,customer_address current_addr
+ where ss_customer_sk = c_customer_sk
+ and customer.c_current_addr_sk = current_addr.ca_address_sk
+ and current_addr.ca_city <> bought_city
+ order by c_last_name
+ ,ss_ticket_number
+ limit 100
+POSTHOOK: type: QUERY
+Plan optimized by CBO.
+
+Vertex dependency in root stage
+Reducer 10 <- Map 13 (SIMPLE_EDGE), Reducer 9 (SIMPLE_EDGE)
+Reducer 11 <- Map 14 (SIMPLE_EDGE), Reducer 10 (SIMPLE_EDGE)
+Reducer 2 <- Map 1 (SIMPLE_EDGE), Map 5 (SIMPLE_EDGE)
+Reducer 3 <- Reducer 2 (SIMPLE_EDGE), Reducer 7 (SIMPLE_EDGE)
+Reducer 4 <- Reducer 3 (SIMPLE_EDGE)
+Reducer 6 <- Map 5 (SIMPLE_EDGE), Reducer 11 (SIMPLE_EDGE)
+Reducer 7 <- Reducer 6 (SIMPLE_EDGE)
+Reducer 9 <- Map 12 (SIMPLE_EDGE), Map 8 (SIMPLE_EDGE)
+
+Stage-0
+ Fetch Operator
+ limit:100
+ Stage-1
+ Reducer 4
+ File Output Operator [FS_50]
+ Limit [LIM_49] (rows=100 width=88)
+ Number of rows:100
+ Select Operator [SEL_48] (rows=463823414 width=88)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7"]
+ <-Reducer 3 [SIMPLE_EDGE]
+ SHUFFLE [RS_47]
+ Select Operator [SEL_46] (rows=463823414 width=88)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7"]
+ Filter Operator [FIL_45] (rows=463823414 width=88)
+ predicate:(_col5 <> _col8)
+ Merge Join Operator [MERGEJOIN_86] (rows=463823414 width=88)
+ Conds:RS_42._col0=RS_43._col1(Inner),Output:["_col2","_col3","_col5","_col6","_col8","_col9","_col10","_col11"]
+ <-Reducer 2 [SIMPLE_EDGE]
+ SHUFFLE [RS_42]
+ PartitionCols:_col0
+ Merge Join Operator [MERGEJOIN_81] (rows=88000001 width=860)
+ Conds:RS_39._col1=RS_40._col0(Inner),Output:["_col0","_col2","_col3","_col5"]
+ <-Map 5 [SIMPLE_EDGE]
+ SHUFFLE [RS_40]
+ PartitionCols:_col0
+ Select Operator [SEL_5] (rows=40000000 width=1014)
+ Output:["_col0","_col1"]
+ Filter Operator [FIL_75] (rows=40000000 width=1014)
+ predicate:ca_address_sk is not null
+ TableScan [TS_3] (rows=40000000 width=1014)
+ default@customer_address,current_addr,Tbl:COMPLETE,Col:NONE,Output:["ca_address_sk","ca_city"]
+ <-Map 1 [SIMPLE_EDGE]
+ SHUFFLE [RS_39]
+ PartitionCols:_col1
+ Select Operator [SEL_2] (rows=80000000 width=860)
+ Output:["_col0","_col1","_col2","_col3"]
+ Filter Operator [FIL_74] (rows=80000000 width=860)
+ predicate:(c_current_addr_sk is not null and c_customer_sk is not null)
+ TableScan [TS_0] (rows=80000000 width=860)
+ default@customer,customer,Tbl:COMPLETE,Col:NONE,Output:["c_customer_sk","c_current_addr_sk","c_first_name","c_last_name"]
+ <-Reducer 7 [SIMPLE_EDGE]
+ SHUFFLE [RS_43]
+ PartitionCols:_col1
+ Select Operator [SEL_37] (rows=421657640 width=88)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5"]
+ Group By Operator [GBY_36] (rows=421657640 width=88)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)","sum(VALUE._col2)"],keys:KEY._col0, KEY._col1, KEY._col2, KEY._col3
+ <-Reducer 6 [SIMPLE_EDGE]
+ SHUFFLE [RS_35]
+ PartitionCols:_col0, _col1, _col2, _col3
+ Group By Operator [GBY_34] (rows=843315281 width=88)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"],aggregations:["sum(_col6)","sum(_col7)","sum(_col8)"],keys:_col1, _col18, _col3, _col5
+ Merge Join Operator [MERGEJOIN_85] (rows=843315281 width=88)
+ Conds:RS_30._col3=RS_31._col0(Inner),Output:["_col1","_col3","_col5","_col6","_col7","_col8","_col18"]
+ <-Map 5 [SIMPLE_EDGE]
+ SHUFFLE [RS_31]
+ PartitionCols:_col0
+ Please refer to the previous Select Operator [SEL_5]
+ <-Reducer 11 [SIMPLE_EDGE]
+ SHUFFLE [RS_30]
+ PartitionCols:_col3
+ Merge Join Operator [MERGEJOIN_84] (rows=766650239 width=88)
+ Conds:RS_27._col2=RS_28._col0(Inner),Output:["_col1","_col3","_col5","_col6","_col7","_col8"]
+ <-Map 14 [SIMPLE_EDGE]
+ SHUFFLE [RS_28]
+ PartitionCols:_col0
+ Select Operator [SEL_17] (rows=7200 width=107)
+ Output:["_col0"]
+ Filter Operator [FIL_79] (rows=7200 width=107)
+ predicate:(((hd_dep_count = 2) or (hd_vehicle_count = 1)) and hd_demo_sk is not null)
+ TableScan [TS_15] (rows=7200 width=107)
+ default@household_demographics,household_demographics,Tbl:COMPLETE,Col:NONE,Output:["hd_demo_sk","hd_dep_count","hd_vehicle_count"]
+ <-Reducer 10 [SIMPLE_EDGE]
+ SHUFFLE [RS_27]
+ PartitionCols:_col2
+ Merge Join Operator [MERGEJOIN_83] (rows=696954748 width=88)
+ Conds:RS_24._col4=RS_25._col0(Inner),Output:["_col1","_col2","_col3","_col5","_col6","_col7","_col8"]
+ <-Map 13 [SIMPLE_EDGE]
+ SHUFFLE [RS_25]
+ PartitionCols:_col0
+ Select Operator [SEL_14] (rows=852 width=1910)
+ Output:["_col0"]
+ Filter Operator [FIL_78] (rows=852 width=1910)
+ predicate:((s_city) IN ('Cedar Grove', 'Wildwood') and s_store_sk is not null)
+ TableScan [TS_12] (rows=1704 width=1910)
+ default@store,store,Tbl:COMPLETE,Col:NONE,Output:["s_store_sk","s_city"]
+ <-Reducer 9 [SIMPLE_EDGE]
+ SHUFFLE [RS_24]
+ PartitionCols:_col4
+ Merge Join Operator [MERGEJOIN_82] (rows=633595212 width=88)
+ Conds:RS_21._col0=RS_22._col0(Inner),Output:["_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8"]
+ <-Map 12 [SIMPLE_EDGE]
+ SHUFFLE [RS_22]
+ PartitionCols:_col0
+ Select Operator [SEL_11] (rows=4058 width=1119)
+ Output:["_col0"]
+ Filter Operator [FIL_77] (rows=4058 width=1119)
+ predicate:((d_year) IN (1998, 1999, 2000) and d_date_sk is not null and d_dom BETWEEN 1 AND 2)
+ TableScan [TS_9] (rows=73049 width=1119)
+ default@date_dim,date_dim,Tbl:COMPLETE,Col:NONE,Output:["d_date_sk","d_year","d_dom"]
+ <-Map 8 [SIMPLE_EDGE]
+ SHUFFLE [RS_21]
+ PartitionCols:_col0
+ Select Operator [SEL_8] (rows=575995635 width=88)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8"]
+ Filter Operator [FIL_76] (rows=575995635 width=88)
+ predicate:(ss_addr_sk is not null and ss_customer_sk is not null and ss_hdemo_sk is not null and ss_sold_date_sk is not null and ss_store_sk is not null)
+ TableScan [TS_6] (rows=575995635 width=88)
+ default@store_sales,store_sales,Tbl:COMPLETE,Col:NONE,Output:["ss_sold_date_sk","ss_customer_sk","ss_hdemo_sk","ss_addr_sk","ss_store_sk","ss_ticket_number","ss_ext_sales_price","ss_ext_list_price","ss_ext_tax"]
+
http://git-wip-us.apache.org/repos/asf/hive/blob/9244fdc7/ql/src/test/results/clientpositive/perf/tez/query69.q.out
----------------------------------------------------------------------
diff --git a/ql/src/test/results/clientpositive/perf/tez/query69.q.out b/ql/src/test/results/clientpositive/perf/tez/query69.q.out
new file mode 100644
index 0000000..591f3fc
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/query69.q.out
@@ -0,0 +1,268 @@
+PREHOOK: query: explain
+select
+ cd_gender,
+ cd_marital_status,
+ cd_education_status,
+ count(*) cnt1,
+ cd_purchase_estimate,
+ count(*) cnt2,
+ cd_credit_rating,
+ count(*) cnt3
+ from
+ customer c,customer_address ca,customer_demographics
+ where
+ c.c_current_addr_sk = ca.ca_address_sk and
+ ca_state in ('CO','IL','MN') and
+ cd_demo_sk = c.c_current_cdemo_sk and
+ exists (select *
+ from store_sales,date_dim
+ where c.c_customer_sk = ss_customer_sk and
+ ss_sold_date_sk = d_date_sk and
+ d_year = 1999 and
+ d_moy between 1 and 1+2) and
+ (not exists (select *
+ from web_sales,date_dim
+ where c.c_customer_sk = ws_bill_customer_sk and
+ ws_sold_date_sk = d_date_sk and
+ d_year = 1999 and
+ d_moy between 1 and 1+2) and
+ not exists (select *
+ from catalog_sales,date_dim
+ where c.c_customer_sk = cs_ship_customer_sk and
+ cs_sold_date_sk = d_date_sk and
+ d_year = 1999 and
+ d_moy between 1 and 1+2))
+ group by cd_gender,
+ cd_marital_status,
+ cd_education_status,
+ cd_purchase_estimate,
+ cd_credit_rating
+ order by cd_gender,
+ cd_marital_status,
+ cd_education_status,
+ cd_purchase_estimate,
+ cd_credit_rating
+ limit 100
+PREHOOK: type: QUERY
+POSTHOOK: query: explain
+select
+ cd_gender,
+ cd_marital_status,
+ cd_education_status,
+ count(*) cnt1,
+ cd_purchase_estimate,
+ count(*) cnt2,
+ cd_credit_rating,
+ count(*) cnt3
+ from
+ customer c,customer_address ca,customer_demographics
+ where
+ c.c_current_addr_sk = ca.ca_address_sk and
+ ca_state in ('CO','IL','MN') and
+ cd_demo_sk = c.c_current_cdemo_sk and
+ exists (select *
+ from store_sales,date_dim
+ where c.c_customer_sk = ss_customer_sk and
+ ss_sold_date_sk = d_date_sk and
+ d_year = 1999 and
+ d_moy between 1 and 1+2) and
+ (not exists (select *
+ from web_sales,date_dim
+ where c.c_customer_sk = ws_bill_customer_sk and
+ ws_sold_date_sk = d_date_sk and
+ d_year = 1999 and
+ d_moy between 1 and 1+2) and
+ not exists (select *
+ from catalog_sales,date_dim
+ where c.c_customer_sk = cs_ship_customer_sk and
+ cs_sold_date_sk = d_date_sk and
+ d_year = 1999 and
+ d_moy between 1 and 1+2))
+ group by cd_gender,
+ cd_marital_status,
+ cd_education_status,
+ cd_purchase_estimate,
+ cd_credit_rating
+ order by cd_gender,
+ cd_marital_status,
+ cd_education_status,
+ cd_purchase_estimate,
+ cd_credit_rating
+ limit 100
+POSTHOOK: type: QUERY
+Plan optimized by CBO.
+
+Vertex dependency in root stage
+Reducer 11 <- Map 10 (SIMPLE_EDGE), Map 13 (SIMPLE_EDGE)
+Reducer 12 <- Reducer 11 (SIMPLE_EDGE)
+Reducer 14 <- Map 13 (SIMPLE_EDGE), Map 18 (SIMPLE_EDGE)
+Reducer 15 <- Reducer 14 (SIMPLE_EDGE)
+Reducer 16 <- Map 13 (SIMPLE_EDGE), Map 19 (SIMPLE_EDGE)
+Reducer 17 <- Reducer 16 (SIMPLE_EDGE)
+Reducer 2 <- Map 1 (SIMPLE_EDGE), Map 8 (SIMPLE_EDGE)
+Reducer 3 <- Map 9 (SIMPLE_EDGE), Reducer 2 (SIMPLE_EDGE)
+Reducer 4 <- Reducer 12 (ONE_TO_ONE_EDGE), Reducer 15 (ONE_TO_ONE_EDGE), Reducer 3 (SIMPLE_EDGE)
+Reducer 5 <- Reducer 17 (ONE_TO_ONE_EDGE), Reducer 4 (SIMPLE_EDGE)
+Reducer 6 <- Reducer 5 (SIMPLE_EDGE)
+Reducer 7 <- Reducer 6 (SIMPLE_EDGE)
+
+Stage-0
+ Fetch Operator
+ limit:100
+ Stage-1
+ Reducer 7
+ File Output Operator [FS_76]
+ Limit [LIM_75] (rows=100 width=88)
+ Number of rows:100
+ Select Operator [SEL_74] (rows=95831279 width=88)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7"]
+ <-Reducer 6 [SIMPLE_EDGE]
+ SHUFFLE [RS_73]
+ Select Operator [SEL_72] (rows=95831279 width=88)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col6"]
+ Group By Operator [GBY_71] (rows=95831279 width=88)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5"],aggregations:["count(VALUE._col0)"],keys:KEY._col0, KEY._col1, KEY._col2, KEY._col3, KEY._col4
+ <-Reducer 5 [SIMPLE_EDGE]
+ SHUFFLE [RS_70]
+ PartitionCols:_col0, _col1, _col2, _col3, _col4
+ Group By Operator [GBY_69] (rows=191662559 width=88)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5"],aggregations:["count()"],keys:_col6, _col7, _col8, _col9, _col10
+ Select Operator [SEL_68] (rows=191662559 width=88)
+ Output:["_col6","_col7","_col8","_col9","_col10"]
+ Filter Operator [FIL_67] (rows=191662559 width=88)
+ predicate:_col15 is null
+ Merge Join Operator [MERGEJOIN_114] (rows=383325119 width=88)
+ Conds:RS_64._col0=RS_65._col0(Left Outer),Output:["_col6","_col7","_col8","_col9","_col10","_col15"]
+ <-Reducer 17 [ONE_TO_ONE_EDGE]
+ FORWARD [RS_65]
+ PartitionCols:_col0
+ Select Operator [SEL_63] (rows=158394413 width=135)
+ Output:["_col0","_col1"]
+ Group By Operator [GBY_62] (rows=158394413 width=135)
+ Output:["_col0"],keys:KEY._col0
+ <-Reducer 16 [SIMPLE_EDGE]
+ SHUFFLE [RS_61]
+ PartitionCols:_col0
+ Group By Operator [GBY_60] (rows=316788826 width=135)
+ Output:["_col0"],keys:_col1
+ Merge Join Operator [MERGEJOIN_112] (rows=316788826 width=135)
+ Conds:RS_56._col0=RS_57._col0(Inner),Output:["_col1"]
+ <-Map 13 [SIMPLE_EDGE]
+ SHUFFLE [RS_57]
+ PartitionCols:_col0
+ Select Operator [SEL_14] (rows=4058 width=1119)
+ Output:["_col0"]
+ Filter Operator [FIL_103] (rows=4058 width=1119)
+ predicate:((d_year = 1999) and d_date_sk is not null and d_moy BETWEEN 1 AND 3)
+ TableScan [TS_12] (rows=73049 width=1119)
+ default@date_dim,date_dim,Tbl:COMPLETE,Col:NONE,Output:["d_date_sk","d_year","d_moy"]
+ <-Map 19 [SIMPLE_EDGE]
+ SHUFFLE [RS_56]
+ PartitionCols:_col0
+ Select Operator [SEL_52] (rows=287989836 width=135)
+ Output:["_col0","_col1"]
+ Filter Operator [FIL_106] (rows=287989836 width=135)
+ predicate:(cs_ship_customer_sk is not null and cs_sold_date_sk is not null)
+ TableScan [TS_50] (rows=287989836 width=135)
+ default@catalog_sales,catalog_sales,Tbl:COMPLETE,Col:NONE,Output:["cs_sold_date_sk","cs_ship_customer_sk"]
+ <-Reducer 4 [SIMPLE_EDGE]
+ SHUFFLE [RS_64]
+ PartitionCols:_col0
+ Select Operator [SEL_49] (rows=348477374 width=88)
+ Output:["_col0","_col6","_col7","_col8","_col9","_col10"]
+ Filter Operator [FIL_48] (rows=348477374 width=88)
+ predicate:_col13 is null
+ Select Operator [SEL_47] (rows=696954748 width=88)
+ Output:["_col0","_col6","_col7","_col8","_col9","_col10","_col13"]
+ Merge Join Operator [MERGEJOIN_113] (rows=696954748 width=88)
+ Conds:RS_43._col0=RS_44._col0(Left Outer),RS_43._col0=RS_45._col0(Inner),Output:["_col0","_col6","_col7","_col8","_col9","_col10","_col12"]
+ <-Reducer 12 [ONE_TO_ONE_EDGE]
+ FORWARD [RS_44]
+ PartitionCols:_col0
+ Select Operator [SEL_22] (rows=79201469 width=135)
+ Output:["_col0","_col1"]
+ Group By Operator [GBY_21] (rows=79201469 width=135)
+ Output:["_col0"],keys:KEY._col0
+ <-Reducer 11 [SIMPLE_EDGE]
+ SHUFFLE [RS_20]
+ PartitionCols:_col0
+ Group By Operator [GBY_19] (rows=158402938 width=135)
+ Output:["_col0"],keys:_col1
+ Merge Join Operator [MERGEJOIN_110] (rows=158402938 width=135)
+ Conds:RS_15._col0=RS_16._col0(Inner),Output:["_col1"]
+ <-Map 13 [SIMPLE_EDGE]
+ SHUFFLE [RS_16]
+ PartitionCols:_col0
+ Please refer to the previous Select Operator [SEL_14]
+ <-Map 10 [SIMPLE_EDGE]
+ SHUFFLE [RS_15]
+ PartitionCols:_col0
+ Select Operator [SEL_11] (rows=144002668 width=135)
+ Output:["_col0","_col1"]
+ Filter Operator [FIL_102] (rows=144002668 width=135)
+ predicate:(ws_bill_customer_sk is not null and ws_sold_date_sk is not null)
+ TableScan [TS_9] (rows=144002668 width=135)
+ default@web_sales,web_sales,Tbl:COMPLETE,Col:NONE,Output:["ws_sold_date_sk","ws_bill_customer_sk"]
+ <-Reducer 15 [ONE_TO_ONE_EDGE]
+ FORWARD [RS_45]
+ PartitionCols:_col0
+ Group By Operator [GBY_35] (rows=316797606 width=88)
+ Output:["_col0"],keys:KEY._col0
+ <-Reducer 14 [SIMPLE_EDGE]
+ SHUFFLE [RS_34]
+ PartitionCols:_col0
+ Group By Operator [GBY_33] (rows=633595212 width=88)
+ Output:["_col0"],keys:_col1
+ Merge Join Operator [MERGEJOIN_111] (rows=633595212 width=88)
+ Conds:RS_29._col0=RS_30._col0(Inner),Output:["_col1"]
+ <-Map 13 [SIMPLE_EDGE]
+ SHUFFLE [RS_30]
+ PartitionCols:_col0
+ Please refer to the previous Select Operator [SEL_14]
+ <-Map 18 [SIMPLE_EDGE]
+ SHUFFLE [RS_29]
+ PartitionCols:_col0
+ Select Operator [SEL_25] (rows=575995635 width=88)
+ Output:["_col0","_col1"]
+ Filter Operator [FIL_104] (rows=575995635 width=88)
+ predicate:(ss_customer_sk is not null and ss_sold_date_sk is not null)
+ TableScan [TS_23] (rows=575995635 width=88)
+ default@store_sales,store_sales,Tbl:COMPLETE,Col:NONE,Output:["ss_sold_date_sk","ss_customer_sk"]
+ <-Reducer 3 [SIMPLE_EDGE]
+ SHUFFLE [RS_43]
+ PartitionCols:_col0
+ Merge Join Operator [MERGEJOIN_109] (rows=96800003 width=860)
+ Conds:RS_40._col1=RS_41._col0(Inner),Output:["_col0","_col6","_col7","_col8","_col9","_col10"]
+ <-Map 9 [SIMPLE_EDGE]
+ SHUFFLE [RS_41]
+ PartitionCols:_col0
+ Select Operator [SEL_8] (rows=1861800 width=385)
+ Output:["_col0","_col1","_col2","_col3","_col4","_col5"]
+ Filter Operator [FIL_101] (rows=1861800 width=385)
+ predicate:cd_demo_sk is not null
+ TableScan [TS_6] (rows=1861800 width=385)
+ default@customer_demographics,customer_demographics,Tbl:COMPLETE,Col:NONE,Output:["cd_demo_sk","cd_gender","cd_marital_status","cd_education_status","cd_purchase_estimate","cd_credit_rating"]
+ <-Reducer 2 [SIMPLE_EDGE]
+ SHUFFLE [RS_40]
+ PartitionCols:_col1
+ Merge Join Operator [MERGEJOIN_108] (rows=88000001 width=860)
+ Conds:RS_37._col2=RS_38._col0(Inner),Output:["_col0","_col1"]
+ <-Map 1 [SIMPLE_EDGE]
+ SHUFFLE [RS_37]
+ PartitionCols:_col2
+ Select Operator [SEL_2] (rows=80000000 width=860)
+ Output:["_col0","_col1","_col2"]
+ Filter Operator [FIL_99] (rows=80000000 width=860)
+ predicate:(c_current_addr_sk is not null and c_current_cdemo_sk is not null)
+ TableScan [TS_0] (rows=80000000 width=860)
+ default@customer,c,Tbl:COMPLETE,Col:NONE,Output:["c_customer_sk","c_current_cdemo_sk","c_current_addr_sk"]
+ <-Map 8 [SIMPLE_EDGE]
+ SHUFFLE [RS_38]
+ PartitionCols:_col0
+ Select Operator [SEL_5] (rows=20000000 width=1014)
+ Output:["_col0"]
+ Filter Operator [FIL_100] (rows=20000000 width=1014)
+ predicate:((ca_state) IN ('CO', 'IL', 'MN') and ca_address_sk is not null)
+ TableScan [TS_3] (rows=40000000 width=1014)
+ default@customer_address,ca,Tbl:COMPLETE,Col:NONE,Output:["ca_address_sk","ca_state"]
+