http://git-wip-us.apache.org/repos/asf/hive/blob/bd371246/ql/src/test/results/clientpositive/perf/spark/query66.q.out ---------------------------------------------------------------------- diff --git a/ql/src/test/results/clientpositive/perf/spark/query66.q.out b/ql/src/test/results/clientpositive/perf/spark/query66.q.out new file mode 100644 index 0000000..1dc0fac --- /dev/null +++ b/ql/src/test/results/clientpositive/perf/spark/query66.q.out @@ -0,0 +1,873 @@ +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 +STAGE DEPENDENCIES: + Stage-2 is a root stage + Stage-3 depends on stages: Stage-2 + Stage-4 depends on stages: Stage-3 + Stage-5 depends on stages: Stage-4 + Stage-1 depends on stages: Stage-5 + Stage-0 depends on stages: Stage-1 + +STAGE PLANS: + Stage: Stage-2 + Spark +#### A masked pattern was here #### + Vertices: + Map 8 + Map Operator Tree: + TableScan + alias: ship_mode + Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE + Filter Operator + predicate: ((sm_carrier) IN ('DIAMOND', 'AIRBORNE') and sm_ship_mode_sk is not null) (type: boolean) + Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE + Select Operator + expressions: sm_ship_mode_sk (type: int) + outputColumnNames: _col0 + Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE + Spark HashTable Sink Operator + keys: + 0 _col2 (type: int) + 1 _col0 (type: int) + Local Work: + Map Reduce Local Work + Map 9 + Map Operator Tree: + TableScan + alias: warehouse + Statistics: Num rows: 27 Data size: 27802 Basic stats: COMPLETE Column stats: NONE + Filter Operator + predicate: w_warehouse_sk is not null (type: boolean) + Statistics: Num rows: 27 Data size: 27802 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: w_warehouse_sk (type: int), w_warehouse_name (type: string), w_warehouse_sq_ft (type: int), w_city (type: string), w_county (type: string), w_state (type: string), w_country (type: string) + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6 + Statistics: Num rows: 27 Data size: 27802 Basic stats: COMPLETE Column stats: NONE + Spark HashTable Sink Operator + keys: + 0 _col3 (type: int) + 1 _col0 (type: int) + Local Work: + Map Reduce Local Work + + Stage: Stage-3 + Spark +#### A masked pattern was here #### + Vertices: + Map 6 + Map Operator Tree: + TableScan + alias: time_dim + Statistics: Num rows: 86400 Data size: 40694400 Basic stats: COMPLETE Column stats: NONE + Filter Operator + predicate: (t_time BETWEEN 49530 AND 78330 and t_time_sk is not null) (type: boolean) + Statistics: Num rows: 9600 Data size: 4521600 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: t_time_sk (type: int) + outputColumnNames: _col0 + Statistics: Num rows: 9600 Data size: 4521600 Basic stats: COMPLETE Column stats: NONE + Spark HashTable Sink Operator + keys: + 0 _col1 (type: int) + 1 _col0 (type: int) + Local Work: + Map Reduce Local Work + + Stage: Stage-4 + Spark +#### A masked pattern was here #### + Vertices: + Map 15 + Map Operator Tree: + TableScan + alias: ship_mode + Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE + Filter Operator + predicate: ((sm_carrier) IN ('DIAMOND', 'AIRBORNE') and sm_ship_mode_sk is not null) (type: boolean) + Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE + Select Operator + expressions: sm_ship_mode_sk (type: int) + outputColumnNames: _col0 + Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE + Spark HashTable Sink Operator + keys: + 0 _col2 (type: int) + 1 _col0 (type: int) + Local Work: + Map Reduce Local Work + Map 16 + Map Operator Tree: + TableScan + alias: warehouse + Statistics: Num rows: 27 Data size: 27802 Basic stats: COMPLETE Column stats: NONE + Filter Operator + predicate: w_warehouse_sk is not null (type: boolean) + Statistics: Num rows: 27 Data size: 27802 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: w_warehouse_sk (type: int), w_warehouse_name (type: string), w_warehouse_sq_ft (type: int), w_city (type: string), w_county (type: string), w_state (type: string), w_country (type: string) + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6 + Statistics: Num rows: 27 Data size: 27802 Basic stats: COMPLETE Column stats: NONE + Spark HashTable Sink Operator + keys: + 0 _col3 (type: int) + 1 _col0 (type: int) + Local Work: + Map Reduce Local Work + + Stage: Stage-5 + Spark +#### A masked pattern was here #### + Vertices: + Map 13 + Map Operator Tree: + TableScan + alias: time_dim + Statistics: Num rows: 86400 Data size: 40694400 Basic stats: COMPLETE Column stats: NONE + Filter Operator + predicate: (t_time BETWEEN 49530 AND 78330 and t_time_sk is not null) (type: boolean) + Statistics: Num rows: 9600 Data size: 4521600 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: t_time_sk (type: int) + outputColumnNames: _col0 + Statistics: Num rows: 9600 Data size: 4521600 Basic stats: COMPLETE Column stats: NONE + Spark HashTable Sink Operator + keys: + 0 _col1 (type: int) + 1 _col0 (type: int) + Local Work: + Map Reduce Local Work + + Stage: Stage-1 + Spark + Edges: + Reducer 11 <- Map 10 (PARTITION-LEVEL SORT, 336), Map 14 (PARTITION-LEVEL SORT, 336) + Reducer 12 <- Reducer 11 (GROUP, 447) + Reducer 2 <- Map 1 (PARTITION-LEVEL SORT, 169), Map 7 (PARTITION-LEVEL SORT, 169) + Reducer 3 <- Reducer 2 (GROUP, 224) + Reducer 4 <- Reducer 12 (GROUP, 336), Reducer 3 (GROUP, 336) + Reducer 5 <- Reducer 4 (SORT, 1) +#### A masked pattern was here #### + Vertices: + Map 1 + Map Operator Tree: + TableScan + alias: web_sales + Statistics: Num rows: 144002668 Data size: 19580198212 Basic stats: COMPLETE Column stats: NONE + Filter Operator + 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) (type: boolean) + Statistics: Num rows: 144002668 Data size: 19580198212 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: ws_sold_date_sk (type: int), ws_sold_time_sk (type: int), ws_ship_mode_sk (type: int), ws_warehouse_sk (type: int), ws_quantity (type: int), ws_sales_price (type: decimal(7,2)), ws_net_paid_inc_tax (type: decimal(7,2)) + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6 + Statistics: Num rows: 144002668 Data size: 19580198212 Basic stats: COMPLETE Column stats: NONE + Map Join Operator + condition map: + Inner Join 0 to 1 + keys: + 0 _col1 (type: int) + 1 _col0 (type: int) + outputColumnNames: _col0, _col2, _col3, _col4, _col5, _col6 + input vertices: + 1 Map 6 + Statistics: Num rows: 158402938 Data size: 21538218500 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: int) + sort order: + + Map-reduce partition columns: _col0 (type: int) + Statistics: Num rows: 158402938 Data size: 21538218500 Basic stats: COMPLETE Column stats: NONE + value expressions: _col2 (type: int), _col3 (type: int), _col4 (type: int), _col5 (type: decimal(7,2)), _col6 (type: decimal(7,2)) + Local Work: + Map Reduce Local Work + Map 10 + Map Operator Tree: + TableScan + alias: catalog_sales + Statistics: Num rows: 287989836 Data size: 38999608952 Basic stats: COMPLETE Column stats: NONE + Filter Operator + 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) (type: boolean) + Statistics: Num rows: 287989836 Data size: 38999608952 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: cs_sold_date_sk (type: int), cs_sold_time_sk (type: int), cs_ship_mode_sk (type: int), cs_warehouse_sk (type: int), cs_quantity (type: int), cs_ext_sales_price (type: decimal(7,2)), cs_net_paid_inc_ship_tax (type: decimal(7,2)) + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6 + Statistics: Num rows: 287989836 Data size: 38999608952 Basic stats: COMPLETE Column stats: NONE + Map Join Operator + condition map: + Inner Join 0 to 1 + keys: + 0 _col1 (type: int) + 1 _col0 (type: int) + outputColumnNames: _col0, _col2, _col3, _col4, _col5, _col6 + input vertices: + 1 Map 13 + Statistics: Num rows: 316788826 Data size: 42899570777 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: int) + sort order: + + Map-reduce partition columns: _col0 (type: int) + Statistics: Num rows: 316788826 Data size: 42899570777 Basic stats: COMPLETE Column stats: NONE + value expressions: _col2 (type: int), _col3 (type: int), _col4 (type: int), _col5 (type: decimal(7,2)), _col6 (type: decimal(7,2)) + Local Work: + Map Reduce Local Work + Map 14 + Map Operator Tree: + TableScan + alias: date_dim + Statistics: Num rows: 73049 Data size: 81741831 Basic stats: COMPLETE Column stats: NONE + Filter Operator + predicate: ((d_year = 2002) and d_date_sk is not null) (type: boolean) + Statistics: Num rows: 36524 Data size: 40870356 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: d_date_sk (type: int), d_moy (type: int) + outputColumnNames: _col0, _col2 + Statistics: Num rows: 36524 Data size: 40870356 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: int) + sort order: + + Map-reduce partition columns: _col0 (type: int) + Statistics: Num rows: 36524 Data size: 40870356 Basic stats: COMPLETE Column stats: NONE + value expressions: _col2 (type: int) + Map 7 + Map Operator Tree: + TableScan + alias: date_dim + Statistics: Num rows: 73049 Data size: 81741831 Basic stats: COMPLETE Column stats: NONE + Filter Operator + predicate: ((d_year = 2002) and d_date_sk is not null) (type: boolean) + Statistics: Num rows: 36524 Data size: 40870356 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: d_date_sk (type: int), d_moy (type: int) + outputColumnNames: _col0, _col2 + Statistics: Num rows: 36524 Data size: 40870356 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: int) + sort order: + + Map-reduce partition columns: _col0 (type: int) + Statistics: Num rows: 36524 Data size: 40870356 Basic stats: COMPLETE Column stats: NONE + value expressions: _col2 (type: int) + Reducer 11 + Local Work: + Map Reduce Local Work + Reduce Operator Tree: + Join Operator + condition map: + Inner Join 0 to 1 + keys: + 0 _col0 (type: int) + 1 _col0 (type: int) + outputColumnNames: _col2, _col3, _col4, _col5, _col6, _col11 + Statistics: Num rows: 348467716 Data size: 47189528877 Basic stats: COMPLETE Column stats: NONE + Map Join Operator + condition map: + Inner Join 0 to 1 + keys: + 0 _col2 (type: int) + 1 _col0 (type: int) + outputColumnNames: _col3, _col4, _col5, _col6, _col11 + input vertices: + 1 Map 15 + Statistics: Num rows: 383314495 Data size: 51908482889 Basic stats: COMPLETE Column stats: NONE + Map Join Operator + condition map: + Inner Join 0 to 1 + keys: + 0 _col3 (type: int) + 1 _col0 (type: int) + outputColumnNames: _col4, _col5, _col6, _col11, _col15, _col16, _col17, _col18, _col19, _col20 + input vertices: + 1 Map 16 + Statistics: Num rows: 421645953 Data size: 57099332415 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: _col15 (type: string), _col16 (type: int), _col17 (type: string), _col18 (type: string), _col19 (type: string), _col20 (type: string), CASE WHEN ((_col11 = 1)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 2)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 3)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 4)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 5)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 6)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 7)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 8)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 9)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 10)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 11)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 12)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 1)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 2)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 3)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 4)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 5)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: d ecimal(18,2)), CASE WHEN ((_col11 = 6)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 7)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 8)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 9)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 10)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 11)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 12)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)) + outputColumnNames: _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 + Statistics: Num rows: 421645953 Data size: 57099332415 Basic stats: COMPLETE Column stats: NONE + Group By Operator + 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 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string) + mode: hash + outputColumnNames: _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 + Statistics: Num rows: 421645953 Data size: 57099332415 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string) + sort order: ++++++ + Map-reduce partition columns: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string) + Statistics: Num rows: 421645953 Data size: 57099332415 Basic stats: COMPLETE Column stats: NONE + value expressions: _col6 (type: decimal(28,2)), _col7 (type: decimal(28,2)), _col8 (type: decimal(28,2)), _col9 (type: decimal(28,2)), _col10 (type: decimal(28,2)), _col11 (type: decimal(28,2)), _col12 (type: decimal(28,2)), _col13 (type: decimal(28,2)), _col14 (type: decimal(28,2)), _col15 (type: decimal(28,2)), _col16 (type: decimal(28,2)), _col17 (type: decimal(28,2)), _col18 (type: decimal(28,2)), _col19 (type: decimal(28,2)), _col20 (type: decimal(28,2)), _col21 (type: decimal(28,2)), _col22 (type: decimal(28,2)), _col23 (type: decimal(28,2)), _col24 (type: decimal(28,2)), _col25 (type: decimal(28,2)), _col26 (type: decimal(28,2)), _col27 (type: decimal(28,2)), _col28 (type: decimal(28,2)), _col29 (type: decimal(28,2)) + Reducer 12 + Reduce Operator Tree: + Group By Operator + 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 (type: string), KEY._col1 (type: int), KEY._col2 (type: string), KEY._col3 (type: string), KEY._col4 (type: string), KEY._col5 (type: string) + mode: mergepartial + outputColumnNames: _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 + Statistics: Num rows: 210822976 Data size: 28549666139 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string), _col6 (type: decimal(28,2)), _col7 (type: decimal(28,2)), _col8 (type: decimal(28,2)), _col9 (type: decimal(28,2)), _col10 (type: decimal(28,2)), _col11 (type: decimal(28,2)), _col12 (type: decimal(28,2)), _col13 (type: decimal(28,2)), _col14 (type: decimal(28,2)), _col15 (type: decimal(28,2)), _col16 (type: decimal(28,2)), _col17 (type: decimal(28,2)), (_col6 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col7 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col8 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col9 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col10 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col11 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col12 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col13 / CAST( _col1 AS decim al(10,0))) (type: decimal(38,12)), (_col14 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col15 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col16 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col17 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), _col18 (type: decimal(28,2)), _col19 (type: decimal(28,2)), _col20 (type: decimal(28,2)), _col21 (type: decimal(28,2)), _col22 (type: decimal(28,2)), _col23 (type: decimal(28,2)), _col24 (type: decimal(28,2)), _col25 (type: decimal(28,2)), _col26 (type: decimal(28,2)), _col27 (type: decimal(28,2)), _col28 (type: decimal(28,2)), _col29 (type: decimal(28,2)) + outputColumnNames: _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 + Statistics: Num rows: 316240137 Data size: 42883351482 Basic stats: COMPLETE Column stats: NONE + Group By Operator + 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 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string) + mode: hash + outputColumnNames: _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 + Statistics: Num rows: 316240137 Data size: 42883351482 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string) + sort order: ++++++ + Map-reduce partition columns: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string) + Statistics: Num rows: 316240137 Data size: 42883351482 Basic stats: COMPLETE Column stats: NONE + TopN Hash Memory Usage: 0.1 + value expressions: _col6 (type: decimal(38,2)), _col7 (type: decimal(38,2)), _col8 (type: decimal(38,2)), _col9 (type: decimal(38,2)), _col10 (type: decimal(38,2)), _col11 (type: decimal(38,2)), _col12 (type: decimal(38,2)), _col13 (type: decimal(38,2)), _col14 (type: decimal(38,2)), _col15 (type: decimal(38,2)), _col16 (type: decimal(38,2)), _col17 (type: decimal(38,2)), _col18 (type: decimal(38,12)), _col19 (type: decimal(38,12)), _col20 (type: decimal(38,12)), _col21 (type: decimal(38,12)), _col22 (type: decimal(38,12)), _col23 (type: decimal(38,12)), _col24 (type: decimal(38,12)), _col25 (type: decimal(38,12)), _col26 (type: decimal(38,12)), _col27 (type: decimal(38,12)), _col28 (type: decimal(38,12)), _col29 (type: decimal(38,12)), _col30 (type: decimal(38,2)), _col31 (type: decimal(38,2)), _col32 (type: decimal(38,2)), _col33 (type: decimal(38,2)), _col34 (type: decimal(38,2)), _col35 (type: decimal(38,2)), _col36 (type: decimal(38,2)), _col37 (type: deci mal(38,2)), _col38 (type: decimal(38,2)), _col39 (type: decimal(38,2)), _col40 (type: decimal(38,2)), _col41 (type: decimal(38,2)) + Reducer 2 + Local Work: + Map Reduce Local Work + Reduce Operator Tree: + Join Operator + condition map: + Inner Join 0 to 1 + keys: + 0 _col0 (type: int) + 1 _col0 (type: int) + outputColumnNames: _col2, _col3, _col4, _col5, _col6, _col11 + Statistics: Num rows: 174243235 Data size: 23692040863 Basic stats: COMPLETE Column stats: NONE + Map Join Operator + condition map: + Inner Join 0 to 1 + keys: + 0 _col2 (type: int) + 1 _col0 (type: int) + outputColumnNames: _col3, _col4, _col5, _col6, _col11 + input vertices: + 1 Map 8 + Statistics: Num rows: 191667562 Data size: 26061245514 Basic stats: COMPLETE Column stats: NONE + Map Join Operator + condition map: + Inner Join 0 to 1 + keys: + 0 _col3 (type: int) + 1 _col0 (type: int) + outputColumnNames: _col4, _col5, _col6, _col11, _col15, _col16, _col17, _col18, _col19, _col20 + input vertices: + 1 Map 9 + Statistics: Num rows: 210834322 Data size: 28667370686 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: _col15 (type: string), _col16 (type: int), _col17 (type: string), _col18 (type: string), _col19 (type: string), _col20 (type: string), CASE WHEN ((_col11 = 1)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 2)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 3)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 4)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 5)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 6)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 7)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 8)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 9)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 10)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 11)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 12)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 1)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 2)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 3)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 4)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 5)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: d ecimal(18,2)), CASE WHEN ((_col11 = 6)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 7)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 8)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 9)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 10)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 11)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 12)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)) + outputColumnNames: _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 + Statistics: Num rows: 210834322 Data size: 28667370686 Basic stats: COMPLETE Column stats: NONE + Group By Operator + 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 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string) + mode: hash + outputColumnNames: _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 + Statistics: Num rows: 210834322 Data size: 28667370686 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string) + sort order: ++++++ + Map-reduce partition columns: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string) + Statistics: Num rows: 210834322 Data size: 28667370686 Basic stats: COMPLETE Column stats: NONE + value expressions: _col6 (type: decimal(28,2)), _col7 (type: decimal(28,2)), _col8 (type: decimal(28,2)), _col9 (type: decimal(28,2)), _col10 (type: decimal(28,2)), _col11 (type: decimal(28,2)), _col12 (type: decimal(28,2)), _col13 (type: decimal(28,2)), _col14 (type: decimal(28,2)), _col15 (type: decimal(28,2)), _col16 (type: decimal(28,2)), _col17 (type: decimal(28,2)), _col18 (type: decimal(28,2)), _col19 (type: decimal(28,2)), _col20 (type: decimal(28,2)), _col21 (type: decimal(28,2)), _col22 (type: decimal(28,2)), _col23 (type: decimal(28,2)), _col24 (type: decimal(28,2)), _col25 (type: decimal(28,2)), _col26 (type: decimal(28,2)), _col27 (type: decimal(28,2)), _col28 (type: decimal(28,2)), _col29 (type: decimal(28,2)) + Reducer 3 + Reduce Operator Tree: + Group By Operator + 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 (type: string), KEY._col1 (type: int), KEY._col2 (type: string), KEY._col3 (type: string), KEY._col4 (type: string), KEY._col5 (type: string) + mode: mergepartial + outputColumnNames: _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 + Statistics: Num rows: 105417161 Data size: 14333685343 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string), _col6 (type: decimal(28,2)), _col7 (type: decimal(28,2)), _col8 (type: decimal(28,2)), _col9 (type: decimal(28,2)), _col10 (type: decimal(28,2)), _col11 (type: decimal(28,2)), _col12 (type: decimal(28,2)), _col13 (type: decimal(28,2)), _col14 (type: decimal(28,2)), _col15 (type: decimal(28,2)), _col16 (type: decimal(28,2)), _col17 (type: decimal(28,2)), (_col6 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col7 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col8 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col9 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col10 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col11 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col12 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col13 / CAST( _col1 AS decim al(10,0))) (type: decimal(38,12)), (_col14 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col15 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col16 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col17 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), _col18 (type: decimal(28,2)), _col19 (type: decimal(28,2)), _col20 (type: decimal(28,2)), _col21 (type: decimal(28,2)), _col22 (type: decimal(28,2)), _col23 (type: decimal(28,2)), _col24 (type: decimal(28,2)), _col25 (type: decimal(28,2)), _col26 (type: decimal(28,2)), _col27 (type: decimal(28,2)), _col28 (type: decimal(28,2)), _col29 (type: decimal(28,2)) + outputColumnNames: _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 + Statistics: Num rows: 316240137 Data size: 42883351482 Basic stats: COMPLETE Column stats: NONE + Group By Operator + 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 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string) + mode: hash + outputColumnNames: _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 + Statistics: Num rows: 316240137 Data size: 42883351482 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string) + sort order: ++++++ + Map-reduce partition columns: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string) + Statistics: Num rows: 316240137 Data size: 42883351482 Basic stats: COMPLETE Column stats: NONE + TopN Hash Memory Usage: 0.1 + value expressions: _col6 (type: decimal(38,2)), _col7 (type: decimal(38,2)), _col8 (type: decimal(38,2)), _col9 (type: decimal(38,2)), _col10 (type: decimal(38,2)), _col11 (type: decimal(38,2)), _col12 (type: decimal(38,2)), _col13 (type: decimal(38,2)), _col14 (type: decimal(38,2)), _col15 (type: decimal(38,2)), _col16 (type: decimal(38,2)), _col17 (type: decimal(38,2)), _col18 (type: decimal(38,12)), _col19 (type: decimal(38,12)), _col20 (type: decimal(38,12)), _col21 (type: decimal(38,12)), _col22 (type: decimal(38,12)), _col23 (type: decimal(38,12)), _col24 (type: decimal(38,12)), _col25 (type: decimal(38,12)), _col26 (type: decimal(38,12)), _col27 (type: decimal(38,12)), _col28 (type: decimal(38,12)), _col29 (type: decimal(38,12)), _col30 (type: decimal(38,2)), _col31 (type: decimal(38,2)), _col32 (type: decimal(38,2)), _col33 (type: decimal(38,2)), _col34 (type: decimal(38,2)), _col35 (type: decimal(38,2)), _col36 (type: decimal(38,2)), _col37 (type: deci mal(38,2)), _col38 (type: decimal(38,2)), _col39 (type: decimal(38,2)), _col40 (type: decimal(38,2)), _col41 (type: decimal(38,2)) + Reducer 4 + Reduce Operator Tree: + Group By Operator + 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 (type: string), KEY._col1 (type: int), KEY._col2 (type: string), KEY._col3 (type: string), KEY._col4 (type: string), KEY._col5 (type: string) + mode: mergepartial + outputColumnNames: _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 + Statistics: Num rows: 158120068 Data size: 21441675673 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: string) + sort order: + + Statistics: Num rows: 158120068 Data size: 21441675673 Basic stats: COMPLETE Column stats: NONE + TopN Hash Memory Usage: 0.1 + value expressions: _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string), _col6 (type: decimal(38,2)), _col7 (type: decimal(38,2)), _col8 (type: decimal(38,2)), _col9 (type: decimal(38,2)), _col10 (type: decimal(38,2)), _col11 (type: decimal(38,2)), _col12 (type: decimal(38,2)), _col13 (type: decimal(38,2)), _col14 (type: decimal(38,2)), _col15 (type: decimal(38,2)), _col16 (type: decimal(38,2)), _col17 (type: decimal(38,2)), _col18 (type: decimal(38,12)), _col19 (type: decimal(38,12)), _col20 (type: decimal(38,12)), _col21 (type: decimal(38,12)), _col22 (type: decimal(38,12)), _col23 (type: decimal(38,12)), _col24 (type: decimal(38,12)), _col25 (type: decimal(38,12)), _col26 (type: decimal(38,12)), _col27 (type: decimal(38,12)), _col28 (type: decimal(38,12)), _col29 (type: decimal(38,12)), _col30 (type: decimal(38,2)), _col31 (type: decimal(38,2)), _col32 (type: decimal(38,2)), _col33 (type: decimal(38,2)), _col3 4 (type: decimal(38,2)), _col35 (type: decimal(38,2)), _col36 (type: decimal(38,2)), _col37 (type: decimal(38,2)), _col38 (type: decimal(38,2)), _col39 (type: decimal(38,2)), _col40 (type: decimal(38,2)), _col41 (type: decimal(38,2)) + Reducer 5 + Reduce Operator Tree: + Select Operator + expressions: KEY.reducesinkkey0 (type: string), VALUE._col0 (type: int), VALUE._col1 (type: string), VALUE._col2 (type: string), VALUE._col3 (type: string), VALUE._col4 (type: string), VALUE._col5 (type: decimal(38,2)), VALUE._col6 (type: decimal(38,2)), VALUE._col7 (type: decimal(38,2)), VALUE._col8 (type: decimal(38,2)), VALUE._col9 (type: decimal(38,2)), VALUE._col10 (type: decimal(38,2)), VALUE._col11 (type: decimal(38,2)), VALUE._col12 (type: decimal(38,2)), VALUE._col13 (type: decimal(38,2)), VALUE._col14 (type: decimal(38,2)), VALUE._col15 (type: decimal(38,2)), VALUE._col16 (type: decimal(38,2)), VALUE._col17 (type: decimal(38,12)), VALUE._col18 (type: decimal(38,12)), VALUE._col19 (type: decimal(38,12)), VALUE._col20 (type: decimal(38,12)), VALUE._col21 (type: decimal(38,12)), VALUE._col22 (type: decimal(38,12)), VALUE._col23 (type: decimal(38,12)), VALUE._col24 (type: decimal(38,12)), VALUE._col25 (type: decimal(38,12)), VALUE._col26 (type: decimal(38,12)), VALUE._col27 (type: decimal(38,12)), VALUE._col28 (type: decimal(38,12)), VALUE._col29 (type: decimal(38,2)), VALUE._col30 (type: decimal(38,2)), VALUE._col31 (type: decimal(38,2)), VALUE._col32 (type: decimal(38,2)), VALUE._col33 (type: decimal(38,2)), VALUE._col34 (type: decimal(38,2)), VALUE._col35 (type: decimal(38,2)), VALUE._col36 (type: decimal(38,2)), VALUE._col37 (type: decimal(38,2)), VALUE._col38 (type: decimal(38,2)), VALUE._col39 (type: decimal(38,2)), VALUE._col40 (type: decimal(38,2)) + outputColumnNames: _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 + Statistics: Num rows: 158120068 Data size: 21441675673 Basic stats: COMPLETE Column stats: NONE + Limit + Number of rows: 100 + Statistics: Num rows: 100 Data size: 13500 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string), 'DIAMOND,AIRBORNE' (type: string), 2002 (type: int), _col6 (type: decimal(38,2)), _col7 (type: decimal(38,2)), _col8 (type: decimal(38,2)), _col9 (type: decimal(38,2)), _col10 (type: decimal(38,2)), _col11 (type: decimal(38,2)), _col12 (type: decimal(38,2)), _col13 (type: decimal(38,2)), _col14 (type: decimal(38,2)), _col15 (type: decimal(38,2)), _col16 (type: decimal(38,2)), _col17 (type: decimal(38,2)), _col18 (type: decimal(38,12)), _col19 (type: decimal(38,12)), _col20 (type: decimal(38,12)), _col21 (type: decimal(38,12)), _col22 (type: decimal(38,12)), _col23 (type: decimal(38,12)), _col24 (type: decimal(38,12)), _col25 (type: decimal(38,12)), _col26 (type: decimal(38,12)), _col27 (type: decimal(38,12)), _col28 (type: decimal(38,12)), _col29 (type: decimal(38,12)), _col30 (type: decimal(38,2)), _col31 (type: decimal(38 ,2)), _col32 (type: decimal(38,2)), _col33 (type: decimal(38,2)), _col34 (type: decimal(38,2)), _col35 (type: decimal(38,2)), _col36 (type: decimal(38,2)), _col37 (type: decimal(38,2)), _col38 (type: decimal(38,2)), _col39 (type: decimal(38,2)), _col40 (type: decimal(38,2)), _col41 (type: decimal(38,2)) + outputColumnNames: _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 + Statistics: Num rows: 100 Data size: 13500 Basic stats: COMPLETE Column stats: NONE + File Output Operator + compressed: false + Statistics: Num rows: 100 Data size: 13500 Basic stats: COMPLETE Column stats: NONE + table: + input format: org.apache.hadoop.mapred.SequenceFileInputFormat + output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat + serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe + + Stage: Stage-0 + Fetch Operator + limit: -1 + Processor Tree: + ListSink +
http://git-wip-us.apache.org/repos/asf/hive/blob/bd371246/ql/src/test/results/clientpositive/perf/spark/query67.q.out ---------------------------------------------------------------------- diff --git a/ql/src/test/results/clientpositive/perf/spark/query67.q.out b/ql/src/test/results/clientpositive/perf/spark/query67.q.out new file mode 100644 index 0000000..9affd8f --- /dev/null +++ b/ql/src/test/results/clientpositive/perf/spark/query67.q.out @@ -0,0 +1,315 @@ +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 +STAGE DEPENDENCIES: + Stage-2 is a root stage + Stage-1 depends on stages: Stage-2 + Stage-0 depends on stages: Stage-1 + +STAGE PLANS: + Stage: Stage-2 + Spark +#### A masked pattern was here #### + Vertices: + Map 8 + Map Operator Tree: + TableScan + alias: store + Statistics: Num rows: 1704 Data size: 3256276 Basic stats: COMPLETE Column stats: NONE + Filter Operator + predicate: s_store_sk is not null (type: boolean) + Statistics: Num rows: 1704 Data size: 3256276 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: s_store_sk (type: int), s_store_id (type: string) + outputColumnNames: _col0, _col1 + Statistics: Num rows: 1704 Data size: 3256276 Basic stats: COMPLETE Column stats: NONE + Spark HashTable Sink Operator + keys: + 0 _col2 (type: int) + 1 _col0 (type: int) + Local Work: + Map Reduce Local Work + + Stage: Stage-1 + Spark + Edges: + Reducer 2 <- Map 1 (PARTITION-LEVEL SORT, 398), Map 7 (PARTITION-LEVEL SORT, 398) + Reducer 3 <- Map 9 (PARTITION-LEVEL SORT, 486), Reducer 2 (PARTITION-LEVEL SORT, 486) + Reducer 4 <- Reducer 3 (GROUP, 1009) + Reducer 5 <- Reducer 4 (PARTITION-LEVEL SORT, 1009) + Reducer 6 <- Reducer 5 (SORT, 1) +#### A masked pattern was here #### + Vertices: + Map 1 + Map Operator Tree: + TableScan + alias: store_sales + Statistics: Num rows: 575995635 Data size: 50814502088 Basic stats: COMPLETE Column stats: NONE + Filter Operator + predicate: (ss_item_sk is not null and ss_sold_date_sk is not null and ss_store_sk is not null) (type: boolean) + Statistics: Num rows: 575995635 Data size: 50814502088 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: ss_sold_date_sk (type: int), ss_item_sk (type: int), ss_store_sk (type: int), ss_quantity (type: int), ss_sales_price (type: decimal(7,2)) + outputColumnNames: _col0, _col1, _col2, _col3, _col4 + Statistics: Num rows: 575995635 Data size: 50814502088 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: int) + sort order: + + Map-reduce partition columns: _col0 (type: int) + Statistics: Num rows: 575995635 Data size: 50814502088 Basic stats: COMPLETE Column stats: NONE + value expressions: _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: decimal(7,2)) + Map 7 + Map Operator Tree: + TableScan + alias: date_dim + Statistics: Num rows: 73049 Data size: 81741831 Basic stats: COMPLETE Column stats: NONE + Filter Operator + predicate: (d_date_sk is not null and d_month_seq BETWEEN 1212 AND 1223) (type: boolean) + Statistics: Num rows: 8116 Data size: 9081804 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: d_date_sk (type: int), d_year (type: int), d_moy (type: int), d_qoy (type: int) + outputColumnNames: _col0, _col2, _col3, _col4 + Statistics: Num rows: 8116 Data size: 9081804 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: int) + sort order: + + Map-reduce partition columns: _col0 (type: int) + Statistics: Num rows: 8116 Data size: 9081804 Basic stats: COMPLETE Column stats: NONE + value expressions: _col2 (type: int), _col3 (type: int), _col4 (type: int) + Map 9 + Map Operator Tree: + TableScan + alias: item + Statistics: Num rows: 462000 Data size: 663560457 Basic stats: COMPLETE Column stats: NONE + Filter Operator + predicate: i_item_sk is not null (type: boolean) + Statistics: Num rows: 462000 Data size: 663560457 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: i_item_sk (type: int), i_brand (type: string), i_class (type: string), i_category (type: string), i_product_name (type: string) + outputColumnNames: _col0, _col1, _col2, _col3, _col4 + Statistics: Num rows: 462000 Data size: 663560457 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: int) + sort order: + + Map-reduce partition columns: _col0 (type: int) + Statistics: Num rows: 462000 Data size: 663560457 Basic stats: COMPLETE Column stats: NONE + value expressions: _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string) + Reducer 2 + Local Work: + Map Reduce Local Work + Reduce Operator Tree: + Join Operator + condition map: + Inner Join 0 to 1 + keys: + 0 _col0 (type: int) + 1 _col0 (type: int) + outputColumnNames: _col1, _col2, _col3, _col4, _col7, _col8, _col9 + Statistics: Num rows: 633595212 Data size: 55895953508 Basic stats: COMPLETE Column stats: NONE + Map Join Operator + condition map: + Inner Join 0 to 1 + keys: + 0 _col2 (type: int) + 1 _col0 (type: int) + outputColumnNames: _col1, _col3, _col4, _col7, _col8, _col9, _col11 + input vertices: + 1 Map 8 + Statistics: Num rows: 696954748 Data size: 61485550191 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col1 (type: int) + sort order: + + Map-reduce partition columns: _col1 (type: int) + Statistics: Num rows: 696954748 Data size: 61485550191 Basic stats: COMPLETE Column stats: NONE + value expressions: _col3 (type: int), _col4 (type: decimal(7,2)), _col7 (type: int), _col8 (type: int), _col9 (type: int), _col11 (type: string) + Reducer 3 + Reduce Operator Tree: + Join Operator + condition map: + Inner Join 0 to 1 + keys: + 0 _col1 (type: int) + 1 _col0 (type: int) + outputColumnNames: _col3, _col4, _col7, _col8, _col9, _col11, _col13, _col14, _col15, _col16 + Statistics: Num rows: 766650239 Data size: 67634106676 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: _col15 (type: string), _col14 (type: string), _col13 (type: string), _col16 (type: string), _col7 (type: int), _col9 (type: int), _col8 (type: int), _col11 (type: string), COALESCE((_col4 * CAST( _col3 AS decimal(10,0))),0) (type: decimal(18,2)) + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 + Statistics: Num rows: 766650239 Data size: 67634106676 Basic stats: COMPLETE Column stats: NONE + Group By Operator + aggregations: sum(_col8) + keys: _col0 (type: string), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: int), _col5 (type: int), _col6 (type: int), _col7 (type: string), 0 (type: int) + mode: hash + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9 + Statistics: Num rows: 6899852151 Data size: 608706960084 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: string), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: int), _col5 (type: int), _col6 (type: int), _col7 (type: string), _col8 (type: int) + sort order: +++++++++ + Map-reduce partition columns: _col0 (type: string), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: int), _col5 (type: int), _col6 (type: int), _col7 (type: string), _col8 (type: int) + Statistics: Num rows: 6899852151 Data size: 608706960084 Basic stats: COMPLETE Column stats: NONE + value expressions: _col9 (type: decimal(28,2)) + Reducer 4 + Reduce Operator Tree: + Group By Operator + aggregations: sum(VALUE._col0) + keys: KEY._col0 (type: string), KEY._col1 (type: string), KEY._col2 (type: string), KEY._col3 (type: string), KEY._col4 (type: int), KEY._col5 (type: int), KEY._col6 (type: int), KEY._col7 (type: string), KEY._col8 (type: int) + mode: mergepartial + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col9 + Statistics: Num rows: 3449926075 Data size: 304353479997 Basic stats: COMPLETE Column stats: NONE + pruneGroupingSetId: true + Select Operator + expressions: _col0 (type: string), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: int), _col5 (type: int), _col6 (type: int), _col7 (type: string), _col9 (type: decimal(28,2)) + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col16 + Statistics: Num rows: 3449926075 Data size: 304353479997 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: string), _col16 (type: decimal(28,2)) + sort order: +- + Map-reduce partition columns: _col0 (type: string) + Statistics: Num rows: 3449926075 Data size: 304353479997 Basic stats: COMPLETE Column stats: NONE + TopN Hash Memory Usage: 0.1 + value expressions: _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: int), _col5 (type: int), _col6 (type: int), _col7 (type: string) + Reducer 5 + Reduce Operator Tree: + Select Operator + expressions: KEY.reducesinkkey0 (type: string), VALUE._col0 (type: string), VALUE._col1 (type: string), VALUE._col2 (type: string), VALUE._col3 (type: int), VALUE._col4 (type: int), VALUE._col5 (type: int), VALUE._col6 (type: string), KEY.reducesinkkey1 (type: decimal(28,2)) + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col16 + Statistics: Num rows: 3449926075 Data size: 304353479997 Basic stats: COMPLETE Column stats: NONE + PTF Operator + Function definitions: + Input definition + input alias: ptf_0 + output shape: _col0: string, _col1: string, _col2: string, _col3: string, _col4: int, _col5: int, _col6: int, _col7: string, _col16: decimal(28,2) + type: WINDOWING + Windowing table definition + input alias: ptf_1 + name: windowingtablefunction + order by: _col16 DESC NULLS LAST + partition by: _col0 + raw input shape: + window functions: + window function definition + alias: rank_window_0 + arguments: _col16 + name: rank + window function: GenericUDAFRankEvaluator + window frame: ROWS PRECEDING(MAX)~FOLLOWING(MAX) + isPivotResult: true + Statistics: Num rows: 3449926075 Data size: 304353479997 Basic stats: COMPLETE Column stats: NONE + Filter Operator + predicate: (rank_window_0 <= 100) (type: boolean) + Statistics: Num rows: 1149975358 Data size: 101451159969 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: _col0 (type: string), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: int), _col5 (type: int), _col6 (type: int), _col7 (type: string), _col16 (type: decimal(28,2)), rank_window_0 (type: int) + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9 + Statistics: Num rows: 1149975358 Data size: 101451159969 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: string), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: int), _col5 (type: int), _col6 (type: int), _col7 (type: string), _col8 (type: decimal(28,2)), _col9 (type: int) + sort order: ++++++++++ + Statistics: Num rows: 1149975358 Data size: 101451159969 Basic stats: COMPLETE Column stats: NONE + TopN Hash Memory Usage: 0.1 + Reducer 6 + Reduce Operator Tree: + Select Operator + expressions: KEY.reducesinkkey0 (type: string), KEY.reducesinkkey1 (type: string), KEY.reducesinkkey2 (type: string), KEY.reducesinkkey3 (type: string), KEY.reducesinkkey4 (type: int), KEY.reducesinkkey5 (type: int), KEY.reducesinkkey6 (type: int), KEY.reducesinkkey7 (type: string), KEY.reducesinkkey8 (type: decimal(28,2)), KEY.reducesinkkey9 (type: int) + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9 + Statistics: Num rows: 1149975358 Data size: 101451159969 Basic stats: COMPLETE Column stats: NONE + Limit + Number of rows: 100 + Statistics: Num rows: 100 Data size: 8800 Basic stats: COMPLETE Column stats: NONE + File Output Operator + compressed: false + Statistics: Num rows: 100 Data size: 8800 Basic stats: COMPLETE Column stats: NONE + table: + input format: org.apache.hadoop.mapred.SequenceFileInputFormat + output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat + serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe + + Stage: Stage-0 + Fetch Operator + limit: 100 + Processor Tree: + ListSink +
