http://git-wip-us.apache.org/repos/asf/hive/blob/9244fdc7/ql/src/test/results/clientpositive/perf/query65.q.out ---------------------------------------------------------------------- diff --git a/ql/src/test/results/clientpositive/perf/query65.q.out b/ql/src/test/results/clientpositive/perf/query65.q.out deleted file mode 100644 index 0091ad0..0000000 --- a/ql/src/test/results/clientpositive/perf/query65.q.out +++ /dev/null @@ -1,169 +0,0 @@ -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/query66.q.out ---------------------------------------------------------------------- diff --git a/ql/src/test/results/clientpositive/perf/query66.q.out b/ql/src/test/results/clientpositive/perf/query66.q.out deleted file mode 100644 index 7c7d7a1..0000000 --- a/ql/src/test/results/clientpositive/perf/query66.q.out +++ /dev/null @@ -1,612 +0,0 @@ -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/query67.q.out ---------------------------------------------------------------------- diff --git a/ql/src/test/results/clientpositive/perf/query67.q.out b/ql/src/test/results/clientpositive/perf/query67.q.out deleted file mode 100644 index 803af6f..0000000 --- a/ql/src/test/results/clientpositive/perf/query67.q.out +++ /dev/null @@ -1,179 +0,0 @@ -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/query68.q.out ---------------------------------------------------------------------- diff --git a/ql/src/test/results/clientpositive/perf/query68.q.out b/ql/src/test/results/clientpositive/perf/query68.q.out deleted file mode 100644 index e8f00ff..0000000 --- a/ql/src/test/results/clientpositive/perf/query68.q.out +++ /dev/null @@ -1,205 +0,0 @@ -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/query69.q.out ---------------------------------------------------------------------- diff --git a/ql/src/test/results/clientpositive/perf/query69.q.out b/ql/src/test/results/clientpositive/perf/query69.q.out deleted file mode 100644 index 591f3fc..0000000 --- a/ql/src/test/results/clientpositive/perf/query69.q.out +++ /dev/null @@ -1,268 +0,0 @@ -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"] -
