http://git-wip-us.apache.org/repos/asf/hive/blob/9244fdc7/ql/src/test/results/clientpositive/perf/tez/query45.q.out ---------------------------------------------------------------------- diff --git a/ql/src/test/results/clientpositive/perf/tez/query45.q.out b/ql/src/test/results/clientpositive/perf/tez/query45.q.out new file mode 100644 index 0000000..3efed2e --- /dev/null +++ b/ql/src/test/results/clientpositive/perf/tez/query45.q.out @@ -0,0 +1,180 @@ +Warning: Shuffle Join MERGEJOIN[87][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3]] in Stage 'Reducer 4' is a cross product +PREHOOK: query: explain +select ca_zip, ca_county, sum(ws_sales_price) + from web_sales, customer, customer_address, date_dim, item + where ws_bill_customer_sk = c_customer_sk + and c_current_addr_sk = ca_address_sk + and ws_item_sk = i_item_sk + and ( substr(ca_zip,1,5) in ('85669', '86197','88274','83405','86475', '85392', '85460', '80348', '81792') + or + i_item_id in (select i_item_id + from item + where i_item_sk in (2, 3, 5, 7, 11, 13, 17, 19, 23, 29) + ) + ) + and ws_sold_date_sk = d_date_sk + and d_qoy = 2 and d_year = 2000 + group by ca_zip, ca_county + order by ca_zip, ca_county + limit 100 +PREHOOK: type: QUERY +POSTHOOK: query: explain +select ca_zip, ca_county, sum(ws_sales_price) + from web_sales, customer, customer_address, date_dim, item + where ws_bill_customer_sk = c_customer_sk + and c_current_addr_sk = ca_address_sk + and ws_item_sk = i_item_sk + and ( substr(ca_zip,1,5) in ('85669', '86197','88274','83405','86475', '85392', '85460', '80348', '81792') + or + i_item_id in (select i_item_id + from item + where i_item_sk in (2, 3, 5, 7, 11, 13, 17, 19, 23, 29) + ) + ) + and ws_sold_date_sk = d_date_sk + and d_qoy = 2 and d_year = 2000 + group by ca_zip, ca_county + order by ca_zip, ca_county + limit 100 +POSTHOOK: type: QUERY +Plan optimized by CBO. + +Vertex dependency in root stage +Reducer 10 <- Reducer 14 (SIMPLE_EDGE), Reducer 9 (SIMPLE_EDGE) +Reducer 11 <- Map 8 (SIMPLE_EDGE) +Reducer 12 <- Map 8 (CUSTOM_SIMPLE_EDGE) +Reducer 14 <- Map 13 (SIMPLE_EDGE), Map 15 (SIMPLE_EDGE) +Reducer 2 <- Map 1 (SIMPLE_EDGE), Map 7 (SIMPLE_EDGE) +Reducer 3 <- Reducer 10 (SIMPLE_EDGE), Reducer 2 (SIMPLE_EDGE) +Reducer 4 <- Reducer 12 (CUSTOM_SIMPLE_EDGE), Reducer 3 (CUSTOM_SIMPLE_EDGE) +Reducer 5 <- Reducer 4 (SIMPLE_EDGE) +Reducer 6 <- Reducer 5 (SIMPLE_EDGE) +Reducer 9 <- Map 8 (SIMPLE_EDGE), Reducer 11 (ONE_TO_ONE_EDGE) + +Stage-0 + Fetch Operator + limit:100 + Stage-1 + Reducer 6 + File Output Operator [FS_59] + Limit [LIM_58] (rows=100 width=152) + Number of rows:100 + Select Operator [SEL_57] (rows=95833781 width=152) + Output:["_col0","_col1","_col2"] + <-Reducer 5 [SIMPLE_EDGE] + SHUFFLE [RS_56] + Group By Operator [GBY_54] (rows=95833781 width=152) + Output:["_col0","_col1","_col2"],aggregations:["sum(VALUE._col0)"],keys:KEY._col0, KEY._col1 + <-Reducer 4 [SIMPLE_EDGE] + SHUFFLE [RS_53] + PartitionCols:_col0, _col1 + Group By Operator [GBY_52] (rows=191667562 width=152) + Output:["_col0","_col1","_col2"],aggregations:["sum(_col3)"],keys:_col8, _col7 + Select Operator [SEL_51] (rows=191667562 width=152) + Output:["_col3","_col7","_col8"] + Filter Operator [FIL_50] (rows=191667562 width=152) + predicate:((substr(_col8, 1, 5)) IN ('85669', '86197', '88274', '83405', '86475', '85392', '85460', '80348', '81792') or CASE WHEN ((_col14 = 0)) THEN (false) WHEN (_col17 is not null) THEN (true) WHEN (_col13 is null) THEN (null) WHEN ((_col15 < _col14)) THEN (null) ELSE (false) END) + Select Operator [SEL_49] (rows=191667562 width=152) + Output:["_col3","_col7","_col8","_col13","_col14","_col15","_col17"] + Merge Join Operator [MERGEJOIN_87] (rows=191667562 width=152) + Conds:(Inner),Output:["_col3","_col4","_col6","_col8","_col12","_col16","_col17"] + <-Reducer 12 [CUSTOM_SIMPLE_EDGE] + PARTITION_ONLY_SHUFFLE [RS_47] + Group By Operator [GBY_38] (rows=1 width=16) + Output:["_col0","_col1"],aggregations:["count(VALUE._col0)","count(VALUE._col1)"] + <-Map 8 [CUSTOM_SIMPLE_EDGE] + SHUFFLE [RS_37] + Group By Operator [GBY_36] (rows=1 width=16) + Output:["_col0","_col1"],aggregations:["count()","count(i_item_id)"] + Select Operator [SEL_35] (rows=231000 width=1436) + Output:["i_item_id"] + Filter Operator [FIL_81] (rows=231000 width=1436) + predicate:(i_item_sk) IN (2, 3, 5, 7, 11, 13, 17, 19, 23, 29) + TableScan [TS_6] (rows=462000 width=1436) + default@item,item,Tbl:COMPLETE,Col:NONE,Output:["i_item_sk","i_item_id"] + <-Reducer 3 [CUSTOM_SIMPLE_EDGE] + PARTITION_ONLY_SHUFFLE [RS_46] + Merge Join Operator [MERGEJOIN_86] (rows=191667562 width=135) + Conds:RS_43._col0=RS_44._col6(Inner),Output:["_col3","_col4","_col6","_col8","_col12"] + <-Reducer 10 [SIMPLE_EDGE] + SHUFFLE [RS_44] + PartitionCols:_col6 + Merge Join Operator [MERGEJOIN_85] (rows=174243235 width=135) + Conds:RS_29._col0=RS_30._col1(Inner),Output:["_col1","_col3","_col6","_col7"] + <-Reducer 14 [SIMPLE_EDGE] + SHUFFLE [RS_30] + PartitionCols:_col1 + Merge Join Operator [MERGEJOIN_84] (rows=158402938 width=135) + Conds:RS_22._col0=RS_23._col0(Inner),Output:["_col1","_col2","_col3"] + <-Map 13 [SIMPLE_EDGE] + SHUFFLE [RS_22] + PartitionCols:_col0 + Select Operator [SEL_18] (rows=144002668 width=135) + Output:["_col0","_col1","_col2","_col3"] + Filter Operator [FIL_79] (rows=144002668 width=135) + predicate:(ws_bill_customer_sk is not null and ws_item_sk is not null and ws_sold_date_sk is not null) + TableScan [TS_16] (rows=144002668 width=135) + default@web_sales,web_sales,Tbl:COMPLETE,Col:NONE,Output:["ws_sold_date_sk","ws_item_sk","ws_bill_customer_sk","ws_sales_price"] + <-Map 15 [SIMPLE_EDGE] + SHUFFLE [RS_23] + PartitionCols:_col0 + Select Operator [SEL_21] (rows=18262 width=1119) + Output:["_col0"] + Filter Operator [FIL_80] (rows=18262 width=1119) + predicate:((d_qoy = 2) and (d_year = 2000) and d_date_sk is not null) + TableScan [TS_19] (rows=73049 width=1119) + default@date_dim,date_dim,Tbl:COMPLETE,Col:NONE,Output:["d_date_sk","d_year","d_qoy"] + <-Reducer 9 [SIMPLE_EDGE] + SHUFFLE [RS_29] + PartitionCols:_col0 + Merge Join Operator [MERGEJOIN_83] (rows=508200 width=1436) + Conds:RS_26._col1=RS_27._col0(Left Outer),Output:["_col0","_col1","_col3"] + <-Map 8 [SIMPLE_EDGE] + SHUFFLE [RS_26] + PartitionCols:_col1 + Select Operator [SEL_8] (rows=462000 width=1436) + Output:["_col0","_col1"] + Filter Operator [FIL_77] (rows=462000 width=1436) + predicate:i_item_sk is not null + Please refer to the previous TableScan [TS_6] + <-Reducer 11 [ONE_TO_ONE_EDGE] + FORWARD [RS_27] + PartitionCols:_col0 + Select Operator [SEL_15] (rows=115500 width=1436) + Output:["_col0","_col1"] + Group By Operator [GBY_14] (rows=115500 width=1436) + Output:["_col0"],keys:KEY._col0 + <-Map 8 [SIMPLE_EDGE] + SHUFFLE [RS_13] + PartitionCols:_col0 + Group By Operator [GBY_12] (rows=231000 width=1436) + Output:["_col0"],keys:i_item_id + Select Operator [SEL_11] (rows=231000 width=1436) + Output:["i_item_id"] + Filter Operator [FIL_78] (rows=231000 width=1436) + predicate:(i_item_sk) IN (2, 3, 5, 7, 11, 13, 17, 19, 23, 29) + Please refer to the previous TableScan [TS_6] + <-Reducer 2 [SIMPLE_EDGE] + SHUFFLE [RS_43] + PartitionCols:_col0 + Merge Join Operator [MERGEJOIN_82] (rows=88000001 width=860) + Conds:RS_40._col1=RS_41._col0(Inner),Output:["_col0","_col3","_col4"] + <-Map 1 [SIMPLE_EDGE] + SHUFFLE [RS_40] + PartitionCols:_col1 + Select Operator [SEL_2] (rows=80000000 width=860) + Output:["_col0","_col1"] + Filter Operator [FIL_75] (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"] + <-Map 7 [SIMPLE_EDGE] + SHUFFLE [RS_41] + PartitionCols:_col0 + Select Operator [SEL_5] (rows=40000000 width=1014) + Output:["_col0","_col1","_col2"] + Filter Operator [FIL_76] (rows=40000000 width=1014) + predicate:ca_address_sk is not null + TableScan [TS_3] (rows=40000000 width=1014) + default@customer_address,customer_address,Tbl:COMPLETE,Col:NONE,Output:["ca_address_sk","ca_county","ca_zip"] +
http://git-wip-us.apache.org/repos/asf/hive/blob/9244fdc7/ql/src/test/results/clientpositive/perf/tez/query46.q.out ---------------------------------------------------------------------- diff --git a/ql/src/test/results/clientpositive/perf/tez/query46.q.out b/ql/src/test/results/clientpositive/perf/tez/query46.q.out new file mode 100644 index 0000000..1a193ed --- /dev/null +++ b/ql/src/test/results/clientpositive/perf/tez/query46.q.out @@ -0,0 +1,191 @@ +PREHOOK: query: explain +select c_last_name + ,c_first_name + ,ca_city + ,bought_city + ,ss_ticket_number + ,amt,profit + from + (select ss_ticket_number + ,ss_customer_sk + ,ca_city bought_city + ,sum(ss_coupon_amt) amt + ,sum(ss_net_profit) profit + 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 (household_demographics.hd_dep_count = 2 or + household_demographics.hd_vehicle_count= 1) + and date_dim.d_dow in (6,0) + and date_dim.d_year in (1998,1998+1,1998+2) + and store.s_city in ('Cedar Grove','Wildwood','Union','Salem','Highland Park') + 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 + ,c_first_name + ,ca_city + ,bought_city + ,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 + ,amt,profit + from + (select ss_ticket_number + ,ss_customer_sk + ,ca_city bought_city + ,sum(ss_coupon_amt) amt + ,sum(ss_net_profit) profit + 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 (household_demographics.hd_dep_count = 2 or + household_demographics.hd_vehicle_count= 1) + and date_dim.d_dow in (6,0) + and date_dim.d_year in (1998,1998+1,1998+2) + and store.s_city in ('Cedar Grove','Wildwood','Union','Salem','Highland Park') + 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 + ,c_first_name + ,ca_city + ,bought_city + ,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"] + <-Reducer 3 [SIMPLE_EDGE] + SHUFFLE [RS_47] + Select Operator [SEL_46] (rows=463823414 width=88) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"] + 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"] + <-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"] + Group By Operator [GBY_36] (rows=421657640 width=88) + Output:["_col0","_col1","_col2","_col3","_col4","_col5"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)"],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"],aggregations:["sum(_col6)","sum(_col7)"],keys:_col1, _col17, _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","_col17"] + <-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"] + <-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"] + <-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', 'Union', 'Salem', 'Highland Park') 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"] + <-Map 12 [SIMPLE_EDGE] + SHUFFLE [RS_22] + PartitionCols:_col0 + Select Operator [SEL_11] (rows=18263 width=1119) + Output:["_col0"] + Filter Operator [FIL_77] (rows=18263 width=1119) + predicate:((d_dow) IN (6, 0) and (d_year) IN (1998, 1999, 2000) and d_date_sk is not null) + TableScan [TS_9] (rows=73049 width=1119) + default@date_dim,date_dim,Tbl:COMPLETE,Col:NONE,Output:["d_date_sk","d_year","d_dow"] + <-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"] + 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_coupon_amt","ss_net_profit"] + http://git-wip-us.apache.org/repos/asf/hive/blob/9244fdc7/ql/src/test/results/clientpositive/perf/tez/query47.q.out ---------------------------------------------------------------------- diff --git a/ql/src/test/results/clientpositive/perf/tez/query47.q.out b/ql/src/test/results/clientpositive/perf/tez/query47.q.out new file mode 100644 index 0000000..1288408 --- /dev/null +++ b/ql/src/test/results/clientpositive/perf/tez/query47.q.out @@ -0,0 +1,325 @@ +PREHOOK: query: explain +with v1 as( + select i_category, i_brand, + s_store_name, s_company_name, + d_year, d_moy, + sum(ss_sales_price) sum_sales, + avg(sum(ss_sales_price)) over + (partition by i_category, i_brand, + s_store_name, s_company_name, d_year) + avg_monthly_sales, + rank() over + (partition by i_category, i_brand, + s_store_name, s_company_name + order by d_year, d_moy) rn + from item, store_sales, date_dim, store + where ss_item_sk = i_item_sk and + ss_sold_date_sk = d_date_sk and + ss_store_sk = s_store_sk and + ( + d_year = 2000 or + ( d_year = 2000-1 and d_moy =12) or + ( d_year = 2000+1 and d_moy =1) + ) + group by i_category, i_brand, + s_store_name, s_company_name, + d_year, d_moy), + v2 as( + select v1.i_category + ,v1.d_year, v1.d_moy + ,v1.avg_monthly_sales + ,v1.sum_sales, v1_lag.sum_sales psum, v1_lead.sum_sales nsum + from v1, v1 v1_lag, v1 v1_lead + where v1.i_category = v1_lag.i_category and + v1.i_category = v1_lead.i_category and + v1.i_brand = v1_lag.i_brand and + v1.i_brand = v1_lead.i_brand and + v1.s_store_name = v1_lag.s_store_name and + v1.s_store_name = v1_lead.s_store_name and + v1.s_company_name = v1_lag.s_company_name and + v1.s_company_name = v1_lead.s_company_name and + v1.rn = v1_lag.rn + 1 and + v1.rn = v1_lead.rn - 1) + select * + from v2 + where d_year = 2000 and + avg_monthly_sales > 0 and + case when avg_monthly_sales > 0 then abs(sum_sales - avg_monthly_sales) / avg_monthly_sales else null end > 0.1 + order by sum_sales - avg_monthly_sales, 3 + limit 100 +PREHOOK: type: QUERY +POSTHOOK: query: explain +with v1 as( + select i_category, i_brand, + s_store_name, s_company_name, + d_year, d_moy, + sum(ss_sales_price) sum_sales, + avg(sum(ss_sales_price)) over + (partition by i_category, i_brand, + s_store_name, s_company_name, d_year) + avg_monthly_sales, + rank() over + (partition by i_category, i_brand, + s_store_name, s_company_name + order by d_year, d_moy) rn + from item, store_sales, date_dim, store + where ss_item_sk = i_item_sk and + ss_sold_date_sk = d_date_sk and + ss_store_sk = s_store_sk and + ( + d_year = 2000 or + ( d_year = 2000-1 and d_moy =12) or + ( d_year = 2000+1 and d_moy =1) + ) + group by i_category, i_brand, + s_store_name, s_company_name, + d_year, d_moy), + v2 as( + select v1.i_category + ,v1.d_year, v1.d_moy + ,v1.avg_monthly_sales + ,v1.sum_sales, v1_lag.sum_sales psum, v1_lead.sum_sales nsum + from v1, v1 v1_lag, v1 v1_lead + where v1.i_category = v1_lag.i_category and + v1.i_category = v1_lead.i_category and + v1.i_brand = v1_lag.i_brand and + v1.i_brand = v1_lead.i_brand and + v1.s_store_name = v1_lag.s_store_name and + v1.s_store_name = v1_lead.s_store_name and + v1.s_company_name = v1_lag.s_company_name and + v1.s_company_name = v1_lead.s_company_name and + v1.rn = v1_lag.rn + 1 and + v1.rn = v1_lead.rn - 1) + select * + from v2 + where d_year = 2000 and + avg_monthly_sales > 0 and + case when avg_monthly_sales > 0 then abs(sum_sales - avg_monthly_sales) / avg_monthly_sales else null end > 0.1 + order by sum_sales - avg_monthly_sales, 3 + limit 100 +POSTHOOK: type: QUERY +Plan optimized by CBO. + +Vertex dependency in root stage +Reducer 10 <- Map 21 (SIMPLE_EDGE), Reducer 9 (SIMPLE_EDGE) +Reducer 11 <- Map 22 (SIMPLE_EDGE), Reducer 10 (SIMPLE_EDGE) +Reducer 12 <- Reducer 11 (SIMPLE_EDGE) +Reducer 13 <- Reducer 12 (SIMPLE_EDGE) +Reducer 14 <- Map 1 (SIMPLE_EDGE), Map 20 (SIMPLE_EDGE) +Reducer 15 <- Map 21 (SIMPLE_EDGE), Reducer 14 (SIMPLE_EDGE) +Reducer 16 <- Map 22 (SIMPLE_EDGE), Reducer 15 (SIMPLE_EDGE) +Reducer 17 <- Reducer 16 (SIMPLE_EDGE) +Reducer 18 <- Reducer 17 (SIMPLE_EDGE) +Reducer 19 <- Reducer 18 (SIMPLE_EDGE) +Reducer 2 <- Map 1 (SIMPLE_EDGE), Map 20 (SIMPLE_EDGE) +Reducer 3 <- Map 21 (SIMPLE_EDGE), Reducer 2 (SIMPLE_EDGE) +Reducer 4 <- Map 22 (SIMPLE_EDGE), Reducer 3 (SIMPLE_EDGE) +Reducer 5 <- Reducer 4 (SIMPLE_EDGE) +Reducer 6 <- Reducer 5 (SIMPLE_EDGE) +Reducer 7 <- Reducer 13 (SIMPLE_EDGE), Reducer 19 (SIMPLE_EDGE), Reducer 6 (SIMPLE_EDGE) +Reducer 8 <- Reducer 7 (SIMPLE_EDGE) +Reducer 9 <- Map 1 (SIMPLE_EDGE), Map 20 (SIMPLE_EDGE) + +Stage-0 + Fetch Operator + limit:-1 + Stage-1 + Reducer 8 + File Output Operator [FS_112] + Limit [LIM_110] (rows=100 width=88) + Number of rows:100 + Select Operator [SEL_109] (rows=843315280 width=88) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"] + <-Reducer 7 [SIMPLE_EDGE] + SHUFFLE [RS_108] + Select Operator [SEL_107] (rows=843315280 width=88) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7"] + Merge Join Operator [MERGEJOIN_189] (rows=843315280 width=88) + Conds:RS_103._col0, _col1, _col2, _col3, (_col7 + 1)=RS_104._col0, _col1, _col2, _col3, _col8(Inner),RS_104._col0, _col1, _col2, _col3, _col8=RS_105._col0, _col1, _col2, _col3, (_col7 - 1)(Inner),Output:["_col6","_col8","_col12","_col13","_col14","_col15","_col23"] + <-Reducer 13 [SIMPLE_EDGE] + SHUFFLE [RS_103] + PartitionCols:_col0, _col1, _col2, _col3, (_col7 + 1) + Select Operator [SEL_29] (rows=383325119 width=88) + Output:["_col0","_col1","_col2","_col3","_col6","_col7"] + Filter Operator [FIL_164] (rows=383325119 width=88) + predicate:rank_window_0 is not null + PTF Operator [PTF_28] (rows=383325119 width=88) + Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col4 ASC NULLS FIRST, _col5 ASC NULLS FIRST","partition by:":"_col0, _col1, _col2, _col3"}] + Select Operator [SEL_27] (rows=383325119 width=88) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"] + <-Reducer 12 [SIMPLE_EDGE] + SHUFFLE [RS_26] + PartitionCols:_col0, _col1, _col2, _col3 + Select Operator [SEL_25] (rows=383325119 width=88) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"] + Group By Operator [GBY_24] (rows=383325119 width=88) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"],aggregations:["sum(VALUE._col0)"],keys:KEY._col0, KEY._col1, KEY._col2, KEY._col3, KEY._col4, KEY._col5 + <-Reducer 11 [SIMPLE_EDGE] + SHUFFLE [RS_23] + PartitionCols:_col0, _col1, _col2, _col3, _col4, _col5 + Group By Operator [GBY_22] (rows=766650239 width=88) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"],aggregations:["sum(_col3)"],keys:_col5, _col6, _col8, _col9, _col11, _col12 + Merge Join Operator [MERGEJOIN_182] (rows=766650239 width=88) + Conds:RS_18._col2=RS_19._col0(Inner),Output:["_col3","_col5","_col6","_col8","_col9","_col11","_col12"] + <-Map 22 [SIMPLE_EDGE] + SHUFFLE [RS_19] + PartitionCols:_col0 + Select Operator [SEL_81] (rows=1704 width=1910) + Output:["_col0","_col1","_col2"] + Filter Operator [FIL_179] (rows=1704 width=1910) + predicate:(s_company_name is not null and s_store_name is not null and s_store_sk is not null) + TableScan [TS_79] (rows=1704 width=1910) + default@store,store,Tbl:COMPLETE,Col:NONE,Output:["s_store_sk","s_store_name","s_company_name"] + <-Reducer 10 [SIMPLE_EDGE] + SHUFFLE [RS_18] + PartitionCols:_col2 + Merge Join Operator [MERGEJOIN_181] (rows=696954748 width=88) + Conds:RS_15._col1=RS_16._col0(Inner),Output:["_col2","_col3","_col5","_col6","_col8","_col9"] + <-Map 21 [SIMPLE_EDGE] + SHUFFLE [RS_16] + PartitionCols:_col0 + Select Operator [SEL_78] (rows=462000 width=1436) + Output:["_col0","_col1","_col2"] + Filter Operator [FIL_178] (rows=462000 width=1436) + predicate:(i_brand is not null and i_category is not null and i_item_sk is not null) + TableScan [TS_76] (rows=462000 width=1436) + default@item,item,Tbl:COMPLETE,Col:NONE,Output:["i_item_sk","i_brand","i_category"] + <-Reducer 9 [SIMPLE_EDGE] + SHUFFLE [RS_15] + PartitionCols:_col1 + Merge Join Operator [MERGEJOIN_180] (rows=633595212 width=88) + Conds:RS_12._col0=RS_13._col0(Inner),Output:["_col1","_col2","_col3","_col5","_col6"] + <-Map 1 [SIMPLE_EDGE] + SHUFFLE [RS_12] + PartitionCols:_col0 + Select Operator [SEL_72] (rows=575995635 width=88) + Output:["_col0","_col1","_col2","_col3"] + Filter Operator [FIL_176] (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_70] (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 20 [SIMPLE_EDGE] + SHUFFLE [RS_13] + PartitionCols:_col0 + Select Operator [SEL_75] (rows=73048 width=1119) + Output:["_col0","_col1","_col2"] + Filter Operator [FIL_177] (rows=73048 width=1119) + predicate:(((d_year = 2000) or ((d_year = 1999) and (d_moy = 12)) or ((d_year = 2001) and (d_moy = 1))) and d_date_sk is not null) + TableScan [TS_73] (rows=73049 width=1119) + default@date_dim,date_dim,Tbl:COMPLETE,Col:NONE,Output:["d_date_sk","d_year","d_moy"] + <-Reducer 19 [SIMPLE_EDGE] + SHUFFLE [RS_104] + PartitionCols:_col0, _col1, _col2, _col3, _col8 + Select Operator [SEL_67] (rows=31943759 width=88) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8"] + Filter Operator [FIL_169] (rows=31943759 width=88) + predicate:CASE WHEN ((_col0 > 0)) THEN (((abs((_col7 - _col0)) / _col0) > 0.1)) ELSE (null) END + Select Operator [SEL_66] (rows=63887519 width=88) + Output:["rank_window_1","_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7"] + Filter Operator [FIL_170] (rows=63887519 width=88) + predicate:((_col0 > 0) and (_col5 = 2000) and rank_window_1 is not null) + PTF Operator [PTF_65] (rows=383325119 width=88) + Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col5 ASC NULLS FIRST, _col6 ASC NULLS FIRST","partition by:":"_col1, _col2, _col3, _col4"}] + Select Operator [SEL_64] (rows=383325119 width=88) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7"] + <-Reducer 18 [SIMPLE_EDGE] + SHUFFLE [RS_63] + PartitionCols:_col0, _col1, _col2, _col3 + Select Operator [SEL_62] (rows=383325119 width=88) + Output:["avg_window_0","_col0","_col1","_col2","_col3","_col4","_col5","_col6"] + PTF Operator [PTF_61] (rows=383325119 width=88) + Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col0 ASC NULLS FIRST, _col1 ASC NULLS FIRST, _col2 ASC NULLS FIRST, _col3 ASC NULLS FIRST, _col4 ASC NULLS FIRST","partition by:":"_col0, _col1, _col2, _col3, _col4"}] + Select Operator [SEL_60] (rows=383325119 width=88) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"] + <-Reducer 17 [SIMPLE_EDGE] + SHUFFLE [RS_59] + PartitionCols:_col0, _col1, _col2, _col3, _col4 + Select Operator [SEL_58] (rows=383325119 width=88) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"] + Group By Operator [GBY_57] (rows=383325119 width=88) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"],aggregations:["sum(VALUE._col0)"],keys:KEY._col0, KEY._col1, KEY._col2, KEY._col3, KEY._col4, KEY._col5 + <-Reducer 16 [SIMPLE_EDGE] + SHUFFLE [RS_56] + PartitionCols:_col0, _col1, _col2, _col3, _col4, _col5 + Group By Operator [GBY_55] (rows=766650239 width=88) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"],aggregations:["sum(_col3)"],keys:_col5, _col6, _col8, _col9, _col11, _col12 + Merge Join Operator [MERGEJOIN_185] (rows=766650239 width=88) + Conds:RS_51._col2=RS_52._col0(Inner),Output:["_col3","_col5","_col6","_col8","_col9","_col11","_col12"] + <-Map 22 [SIMPLE_EDGE] + SHUFFLE [RS_52] + PartitionCols:_col0 + Please refer to the previous Select Operator [SEL_81] + <-Reducer 15 [SIMPLE_EDGE] + SHUFFLE [RS_51] + PartitionCols:_col2 + Merge Join Operator [MERGEJOIN_184] (rows=696954748 width=88) + Conds:RS_48._col1=RS_49._col0(Inner),Output:["_col2","_col3","_col5","_col6","_col8","_col9"] + <-Map 21 [SIMPLE_EDGE] + SHUFFLE [RS_49] + PartitionCols:_col0 + Please refer to the previous Select Operator [SEL_78] + <-Reducer 14 [SIMPLE_EDGE] + SHUFFLE [RS_48] + PartitionCols:_col1 + Merge Join Operator [MERGEJOIN_183] (rows=633595212 width=88) + Conds:RS_45._col0=RS_46._col0(Inner),Output:["_col1","_col2","_col3","_col5","_col6"] + <-Map 1 [SIMPLE_EDGE] + SHUFFLE [RS_45] + PartitionCols:_col0 + Please refer to the previous Select Operator [SEL_72] + <-Map 20 [SIMPLE_EDGE] + SHUFFLE [RS_46] + PartitionCols:_col0 + Please refer to the previous Select Operator [SEL_75] + <-Reducer 6 [SIMPLE_EDGE] + SHUFFLE [RS_105] + PartitionCols:_col0, _col1, _col2, _col3, (_col7 - 1) + Select Operator [SEL_99] (rows=383325119 width=88) + Output:["_col0","_col1","_col2","_col3","_col6","_col7"] + Filter Operator [FIL_175] (rows=383325119 width=88) + predicate:rank_window_0 is not null + PTF Operator [PTF_98] (rows=383325119 width=88) + Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col4 ASC NULLS FIRST, _col5 ASC NULLS FIRST","partition by:":"_col0, _col1, _col2, _col3"}] + Select Operator [SEL_97] (rows=383325119 width=88) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"] + <-Reducer 5 [SIMPLE_EDGE] + SHUFFLE [RS_96] + PartitionCols:_col0, _col1, _col2, _col3 + Select Operator [SEL_95] (rows=383325119 width=88) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"] + Group By Operator [GBY_94] (rows=383325119 width=88) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"],aggregations:["sum(VALUE._col0)"],keys:KEY._col0, KEY._col1, KEY._col2, KEY._col3, KEY._col4, KEY._col5 + <-Reducer 4 [SIMPLE_EDGE] + SHUFFLE [RS_93] + PartitionCols:_col0, _col1, _col2, _col3, _col4, _col5 + Group By Operator [GBY_92] (rows=766650239 width=88) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"],aggregations:["sum(_col3)"],keys:_col5, _col6, _col8, _col9, _col11, _col12 + Merge Join Operator [MERGEJOIN_188] (rows=766650239 width=88) + Conds:RS_88._col2=RS_89._col0(Inner),Output:["_col3","_col5","_col6","_col8","_col9","_col11","_col12"] + <-Map 22 [SIMPLE_EDGE] + SHUFFLE [RS_89] + PartitionCols:_col0 + Please refer to the previous Select Operator [SEL_81] + <-Reducer 3 [SIMPLE_EDGE] + SHUFFLE [RS_88] + PartitionCols:_col2 + Merge Join Operator [MERGEJOIN_187] (rows=696954748 width=88) + Conds:RS_85._col1=RS_86._col0(Inner),Output:["_col2","_col3","_col5","_col6","_col8","_col9"] + <-Map 21 [SIMPLE_EDGE] + SHUFFLE [RS_86] + PartitionCols:_col0 + Please refer to the previous Select Operator [SEL_78] + <-Reducer 2 [SIMPLE_EDGE] + SHUFFLE [RS_85] + PartitionCols:_col1 + Merge Join Operator [MERGEJOIN_186] (rows=633595212 width=88) + Conds:RS_82._col0=RS_83._col0(Inner),Output:["_col1","_col2","_col3","_col5","_col6"] + <-Map 1 [SIMPLE_EDGE] + SHUFFLE [RS_82] + PartitionCols:_col0 + Please refer to the previous Select Operator [SEL_72] + <-Map 20 [SIMPLE_EDGE] + SHUFFLE [RS_83] + PartitionCols:_col0 + Please refer to the previous Select Operator [SEL_75] + http://git-wip-us.apache.org/repos/asf/hive/blob/9244fdc7/ql/src/test/results/clientpositive/perf/tez/query48.q.out ---------------------------------------------------------------------- diff --git a/ql/src/test/results/clientpositive/perf/tez/query48.q.out b/ql/src/test/results/clientpositive/perf/tez/query48.q.out new file mode 100644 index 0000000..8db0c1e --- /dev/null +++ b/ql/src/test/results/clientpositive/perf/tez/query48.q.out @@ -0,0 +1,218 @@ +PREHOOK: query: explain +select sum (ss_quantity) + from store_sales, store, customer_demographics, customer_address, date_dim + where s_store_sk = ss_store_sk + and ss_sold_date_sk = d_date_sk and d_year = 1998 + and + ( + ( + cd_demo_sk = ss_cdemo_sk + and + cd_marital_status = 'M' + and + cd_education_status = '4 yr Degree' + and + ss_sales_price between 100.00 and 150.00 + ) + or + ( + cd_demo_sk = ss_cdemo_sk + and + cd_marital_status = 'M' + and + cd_education_status = '4 yr Degree' + and + ss_sales_price between 50.00 and 100.00 + ) + or + ( + cd_demo_sk = ss_cdemo_sk + and + cd_marital_status = 'M' + and + cd_education_status = '4 yr Degree' + and + ss_sales_price between 150.00 and 200.00 + ) + ) + and + ( + ( + ss_addr_sk = ca_address_sk + and + ca_country = 'United States' + and + ca_state in ('KY', 'GA', 'NM') + and ss_net_profit between 0 and 2000 + ) + or + (ss_addr_sk = ca_address_sk + and + ca_country = 'United States' + and + ca_state in ('MT', 'OR', 'IN') + and ss_net_profit between 150 and 3000 + ) + or + (ss_addr_sk = ca_address_sk + and + ca_country = 'United States' + and + ca_state in ('WI', 'MO', 'WV') + and ss_net_profit between 50 and 25000 + ) + ) +PREHOOK: type: QUERY +POSTHOOK: query: explain +select sum (ss_quantity) + from store_sales, store, customer_demographics, customer_address, date_dim + where s_store_sk = ss_store_sk + and ss_sold_date_sk = d_date_sk and d_year = 1998 + and + ( + ( + cd_demo_sk = ss_cdemo_sk + and + cd_marital_status = 'M' + and + cd_education_status = '4 yr Degree' + and + ss_sales_price between 100.00 and 150.00 + ) + or + ( + cd_demo_sk = ss_cdemo_sk + and + cd_marital_status = 'M' + and + cd_education_status = '4 yr Degree' + and + ss_sales_price between 50.00 and 100.00 + ) + or + ( + cd_demo_sk = ss_cdemo_sk + and + cd_marital_status = 'M' + and + cd_education_status = '4 yr Degree' + and + ss_sales_price between 150.00 and 200.00 + ) + ) + and + ( + ( + ss_addr_sk = ca_address_sk + and + ca_country = 'United States' + and + ca_state in ('KY', 'GA', 'NM') + and ss_net_profit between 0 and 2000 + ) + or + (ss_addr_sk = ca_address_sk + and + ca_country = 'United States' + and + ca_state in ('MT', 'OR', 'IN') + and ss_net_profit between 150 and 3000 + ) + or + (ss_addr_sk = ca_address_sk + and + ca_country = 'United States' + and + ca_state in ('WI', 'MO', 'WV') + and ss_net_profit between 50 and 25000 + ) + ) +POSTHOOK: type: QUERY +Plan optimized by CBO. + +Vertex dependency in root stage +Reducer 2 <- Map 1 (SIMPLE_EDGE), Map 7 (SIMPLE_EDGE) +Reducer 3 <- Map 8 (SIMPLE_EDGE), Reducer 2 (SIMPLE_EDGE) +Reducer 4 <- Map 9 (SIMPLE_EDGE), Reducer 3 (SIMPLE_EDGE) +Reducer 5 <- Map 10 (SIMPLE_EDGE), Reducer 4 (SIMPLE_EDGE) +Reducer 6 <- Reducer 5 (CUSTOM_SIMPLE_EDGE) + +Stage-0 + Fetch Operator + limit:-1 + Stage-1 + Reducer 6 + File Output Operator [FS_33] + Group By Operator [GBY_31] (rows=1 width=8) + Output:["_col0"],aggregations:["sum(VALUE._col0)"] + <-Reducer 5 [CUSTOM_SIMPLE_EDGE] + PARTITION_ONLY_SHUFFLE [RS_30] + Group By Operator [GBY_29] (rows=1 width=8) + Output:["_col0"],aggregations:["sum(_col5)"] + Select Operator [SEL_28] (rows=15616947 width=88) + Output:["_col5"] + Filter Operator [FIL_27] (rows=15616947 width=88) + predicate:(((_col14) IN ('KY', 'GA', 'NM') and _col7 BETWEEN 0 AND 2000) or ((_col14) IN ('MT', 'OR', 'IN') and _col7 BETWEEN 150 AND 3000) or ((_col14) IN ('WI', 'MO', 'WV') and _col7 BETWEEN 50 AND 25000)) + Merge Join Operator [MERGEJOIN_56] (rows=93701693 width=88) + Conds:RS_24._col3=RS_25._col0(Inner),Output:["_col5","_col7","_col14"] + <-Map 10 [SIMPLE_EDGE] + SHUFFLE [RS_25] + PartitionCols:_col0 + Select Operator [SEL_14] (rows=10000000 width=1014) + Output:["_col0","_col1"] + Filter Operator [FIL_52] (rows=10000000 width=1014) + predicate:((ca_country = 'United States') and (ca_state) IN ('KY', 'GA', 'NM', 'MT', 'OR', 'IN', 'WI', 'MO', 'WV') and ca_address_sk is not null) + TableScan [TS_12] (rows=40000000 width=1014) + default@customer_address,customer_address,Tbl:COMPLETE,Col:NONE,Output:["ca_address_sk","ca_state","ca_country"] + <-Reducer 4 [SIMPLE_EDGE] + SHUFFLE [RS_24] + PartitionCols:_col3 + Merge Join Operator [MERGEJOIN_55] (rows=85183356 width=88) + Conds:RS_21._col2=RS_22._col0(Inner),Output:["_col3","_col5","_col7"] + <-Map 9 [SIMPLE_EDGE] + SHUFFLE [RS_22] + PartitionCols:_col0 + Select Operator [SEL_11] (rows=465450 width=385) + Output:["_col0"] + Filter Operator [FIL_51] (rows=465450 width=385) + predicate:((cd_education_status = '4 yr Degree') and (cd_marital_status = 'M') and cd_demo_sk is not null) + TableScan [TS_9] (rows=1861800 width=385) + default@customer_demographics,customer_demographics,Tbl:COMPLETE,Col:NONE,Output:["cd_demo_sk","cd_marital_status","cd_education_status"] + <-Reducer 3 [SIMPLE_EDGE] + SHUFFLE [RS_21] + PartitionCols:_col2 + Merge Join Operator [MERGEJOIN_54] (rows=77439413 width=88) + Conds:RS_18._col1=RS_19._col0(Inner),Output:["_col2","_col3","_col5","_col7"] + <-Map 8 [SIMPLE_EDGE] + SHUFFLE [RS_19] + PartitionCols:_col0 + Select Operator [SEL_8] (rows=36524 width=1119) + Output:["_col0"] + Filter Operator [FIL_50] (rows=36524 width=1119) + predicate:((d_year = 1998) 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"] + <-Reducer 2 [SIMPLE_EDGE] + SHUFFLE [RS_18] + PartitionCols:_col1 + Merge Join Operator [MERGEJOIN_53] (rows=70399465 width=88) + Conds:RS_15._col0=RS_16._col3(Inner),Output:["_col1","_col2","_col3","_col5","_col7"] + <-Map 1 [SIMPLE_EDGE] + SHUFFLE [RS_15] + PartitionCols:_col0 + Select Operator [SEL_2] (rows=1704 width=1910) + Output:["_col0"] + Filter Operator [FIL_48] (rows=1704 width=1910) + predicate:s_store_sk is not null + TableScan [TS_0] (rows=1704 width=1910) + default@store,store,Tbl:COMPLETE,Col:NONE,Output:["s_store_sk"] + <-Map 7 [SIMPLE_EDGE] + SHUFFLE [RS_16] + PartitionCols:_col3 + Select Operator [SEL_5] (rows=63999513 width=88) + Output:["_col0","_col1","_col2","_col3","_col4","_col6"] + Filter Operator [FIL_49] (rows=63999513 width=88) + predicate:((ss_net_profit BETWEEN 0 AND 2000 or ss_net_profit BETWEEN 150 AND 3000 or ss_net_profit BETWEEN 50 AND 25000) and (ss_sales_price BETWEEN 100 AND 150 or ss_sales_price BETWEEN 50 AND 100 or ss_sales_price BETWEEN 150 AND 200) and ss_addr_sk is not null and ss_cdemo_sk is not null and ss_sold_date_sk is not null and ss_store_sk is not null) + TableScan [TS_3] (rows=575995635 width=88) + default@store_sales,store_sales,Tbl:COMPLETE,Col:NONE,Output:["ss_sold_date_sk","ss_cdemo_sk","ss_addr_sk","ss_store_sk","ss_quantity","ss_sales_price","ss_net_profit"] + http://git-wip-us.apache.org/repos/asf/hive/blob/9244fdc7/ql/src/test/results/clientpositive/perf/tez/query49.q.out ---------------------------------------------------------------------- diff --git a/ql/src/test/results/clientpositive/perf/tez/query49.q.out b/ql/src/test/results/clientpositive/perf/tez/query49.q.out new file mode 100644 index 0000000..be4027d --- /dev/null +++ b/ql/src/test/results/clientpositive/perf/tez/query49.q.out @@ -0,0 +1,496 @@ +PREHOOK: query: explain +select + 'web' as channel + ,web.item + ,web.return_ratio + ,web.return_rank + ,web.currency_rank + from ( + select + item + ,return_ratio + ,currency_ratio + ,rank() over (order by return_ratio) as return_rank + ,rank() over (order by currency_ratio) as currency_rank + from + ( select ws.ws_item_sk as item + ,(cast(sum(coalesce(wr.wr_return_quantity,0)) as dec(15,4))/ + cast(sum(coalesce(ws.ws_quantity,0)) as dec(15,4) )) as return_ratio + ,(cast(sum(coalesce(wr.wr_return_amt,0)) as dec(15,4))/ + cast(sum(coalesce(ws.ws_net_paid,0)) as dec(15,4) )) as currency_ratio + from + web_sales ws left outer join web_returns wr + on (ws.ws_order_number = wr.wr_order_number and + ws.ws_item_sk = wr.wr_item_sk) + ,date_dim + where + wr.wr_return_amt > 10000 + and ws.ws_net_profit > 1 + and ws.ws_net_paid > 0 + and ws.ws_quantity > 0 + and ws_sold_date_sk = d_date_sk + and d_year = 2000 + and d_moy = 12 + group by ws.ws_item_sk + ) in_web + ) web + where + ( + web.return_rank <= 10 + or + web.currency_rank <= 10 + ) + union + select + 'catalog' as channel + ,catalog.item + ,catalog.return_ratio + ,catalog.return_rank + ,catalog.currency_rank + from ( + select + item + ,return_ratio + ,currency_ratio + ,rank() over (order by return_ratio) as return_rank + ,rank() over (order by currency_ratio) as currency_rank + from + ( select + cs.cs_item_sk as item + ,(cast(sum(coalesce(cr.cr_return_quantity,0)) as dec(15,4))/ + cast(sum(coalesce(cs.cs_quantity,0)) as dec(15,4) )) as return_ratio + ,(cast(sum(coalesce(cr.cr_return_amount,0)) as dec(15,4))/ + cast(sum(coalesce(cs.cs_net_paid,0)) as dec(15,4) )) as currency_ratio + from + catalog_sales cs left outer join catalog_returns cr + on (cs.cs_order_number = cr.cr_order_number and + cs.cs_item_sk = cr.cr_item_sk) + ,date_dim + where + cr.cr_return_amount > 10000 + and cs.cs_net_profit > 1 + and cs.cs_net_paid > 0 + and cs.cs_quantity > 0 + and cs_sold_date_sk = d_date_sk + and d_year = 2000 + and d_moy = 12 + group by cs.cs_item_sk + ) in_cat + ) catalog + where + ( + catalog.return_rank <= 10 + or + catalog.currency_rank <=10 + ) + union + select + 'store' as channel + ,store.item + ,store.return_ratio + ,store.return_rank + ,store.currency_rank + from ( + select + item + ,return_ratio + ,currency_ratio + ,rank() over (order by return_ratio) as return_rank + ,rank() over (order by currency_ratio) as currency_rank + from + ( select sts.ss_item_sk as item + ,(cast(sum(coalesce(sr.sr_return_quantity,0)) as dec(15,4))/cast(sum(coalesce(sts.ss_quantity,0)) as dec(15,4) )) as return_ratio + ,(cast(sum(coalesce(sr.sr_return_amt,0)) as dec(15,4))/cast(sum(coalesce(sts.ss_net_paid,0)) as dec(15,4) )) as currency_ratio + from + store_sales sts left outer join store_returns sr + on (sts.ss_ticket_number = sr.sr_ticket_number and sts.ss_item_sk = sr.sr_item_sk) + ,date_dim + where + sr.sr_return_amt > 10000 + and sts.ss_net_profit > 1 + and sts.ss_net_paid > 0 + and sts.ss_quantity > 0 + and ss_sold_date_sk = d_date_sk + and d_year = 2000 + and d_moy = 12 + group by sts.ss_item_sk + ) in_store + ) store + where ( + store.return_rank <= 10 + or + store.currency_rank <= 10 + ) + order by 1,4,5 + limit 100 +PREHOOK: type: QUERY +POSTHOOK: query: explain +select + 'web' as channel + ,web.item + ,web.return_ratio + ,web.return_rank + ,web.currency_rank + from ( + select + item + ,return_ratio + ,currency_ratio + ,rank() over (order by return_ratio) as return_rank + ,rank() over (order by currency_ratio) as currency_rank + from + ( select ws.ws_item_sk as item + ,(cast(sum(coalesce(wr.wr_return_quantity,0)) as dec(15,4))/ + cast(sum(coalesce(ws.ws_quantity,0)) as dec(15,4) )) as return_ratio + ,(cast(sum(coalesce(wr.wr_return_amt,0)) as dec(15,4))/ + cast(sum(coalesce(ws.ws_net_paid,0)) as dec(15,4) )) as currency_ratio + from + web_sales ws left outer join web_returns wr + on (ws.ws_order_number = wr.wr_order_number and + ws.ws_item_sk = wr.wr_item_sk) + ,date_dim + where + wr.wr_return_amt > 10000 + and ws.ws_net_profit > 1 + and ws.ws_net_paid > 0 + and ws.ws_quantity > 0 + and ws_sold_date_sk = d_date_sk + and d_year = 2000 + and d_moy = 12 + group by ws.ws_item_sk + ) in_web + ) web + where + ( + web.return_rank <= 10 + or + web.currency_rank <= 10 + ) + union + select + 'catalog' as channel + ,catalog.item + ,catalog.return_ratio + ,catalog.return_rank + ,catalog.currency_rank + from ( + select + item + ,return_ratio + ,currency_ratio + ,rank() over (order by return_ratio) as return_rank + ,rank() over (order by currency_ratio) as currency_rank + from + ( select + cs.cs_item_sk as item + ,(cast(sum(coalesce(cr.cr_return_quantity,0)) as dec(15,4))/ + cast(sum(coalesce(cs.cs_quantity,0)) as dec(15,4) )) as return_ratio + ,(cast(sum(coalesce(cr.cr_return_amount,0)) as dec(15,4))/ + cast(sum(coalesce(cs.cs_net_paid,0)) as dec(15,4) )) as currency_ratio + from + catalog_sales cs left outer join catalog_returns cr + on (cs.cs_order_number = cr.cr_order_number and + cs.cs_item_sk = cr.cr_item_sk) + ,date_dim + where + cr.cr_return_amount > 10000 + and cs.cs_net_profit > 1 + and cs.cs_net_paid > 0 + and cs.cs_quantity > 0 + and cs_sold_date_sk = d_date_sk + and d_year = 2000 + and d_moy = 12 + group by cs.cs_item_sk + ) in_cat + ) catalog + where + ( + catalog.return_rank <= 10 + or + catalog.currency_rank <=10 + ) + union + select + 'store' as channel + ,store.item + ,store.return_ratio + ,store.return_rank + ,store.currency_rank + from ( + select + item + ,return_ratio + ,currency_ratio + ,rank() over (order by return_ratio) as return_rank + ,rank() over (order by currency_ratio) as currency_rank + from + ( select sts.ss_item_sk as item + ,(cast(sum(coalesce(sr.sr_return_quantity,0)) as dec(15,4))/cast(sum(coalesce(sts.ss_quantity,0)) as dec(15,4) )) as return_ratio + ,(cast(sum(coalesce(sr.sr_return_amt,0)) as dec(15,4))/cast(sum(coalesce(sts.ss_net_paid,0)) as dec(15,4) )) as currency_ratio + from + store_sales sts left outer join store_returns sr + on (sts.ss_ticket_number = sr.sr_ticket_number and sts.ss_item_sk = sr.sr_item_sk) + ,date_dim + where + sr.sr_return_amt > 10000 + and sts.ss_net_profit > 1 + and sts.ss_net_paid > 0 + and sts.ss_quantity > 0 + and ss_sold_date_sk = d_date_sk + and d_year = 2000 + and d_moy = 12 + group by sts.ss_item_sk + ) in_store + ) store + where ( + store.return_rank <= 10 + or + store.currency_rank <= 10 + ) + order by 1,4,5 + limit 100 +POSTHOOK: type: QUERY +Plan optimized by CBO. + +Vertex dependency in root stage +Reducer 10 <- Union 9 (SIMPLE_EDGE) +Reducer 11 <- Reducer 10 (SIMPLE_EDGE) +Reducer 13 <- Map 12 (SIMPLE_EDGE), Map 24 (SIMPLE_EDGE) +Reducer 14 <- Map 25 (SIMPLE_EDGE), Reducer 13 (SIMPLE_EDGE) +Reducer 15 <- Reducer 14 (SIMPLE_EDGE) +Reducer 16 <- Reducer 15 (SIMPLE_EDGE) +Reducer 17 <- Reducer 16 (SIMPLE_EDGE), Union 7 (CONTAINS) +Reducer 18 <- Map 12 (SIMPLE_EDGE), Map 26 (SIMPLE_EDGE) +Reducer 19 <- Map 27 (SIMPLE_EDGE), Reducer 18 (SIMPLE_EDGE) +Reducer 2 <- Map 1 (SIMPLE_EDGE), Map 12 (SIMPLE_EDGE) +Reducer 20 <- Reducer 19 (SIMPLE_EDGE) +Reducer 21 <- Reducer 20 (SIMPLE_EDGE) +Reducer 22 <- Reducer 21 (SIMPLE_EDGE), Union 9 (CONTAINS) +Reducer 3 <- Map 23 (SIMPLE_EDGE), Reducer 2 (SIMPLE_EDGE) +Reducer 4 <- Reducer 3 (SIMPLE_EDGE) +Reducer 5 <- Reducer 4 (SIMPLE_EDGE) +Reducer 6 <- Reducer 5 (SIMPLE_EDGE), Union 7 (CONTAINS) +Reducer 8 <- Union 7 (SIMPLE_EDGE), Union 9 (CONTAINS) + +Stage-0 + Fetch Operator + limit:100 + Stage-1 + Reducer 11 + File Output Operator [FS_113] + Limit [LIM_112] (rows=100 width=101) + Number of rows:100 + Select Operator [SEL_111] (rows=5915494 width=101) + Output:["_col0","_col1","_col2","_col3","_col4"] + <-Reducer 10 [SIMPLE_EDGE] + SHUFFLE [RS_110] + Select Operator [SEL_109] (rows=5915494 width=101) + Output:["_col0","_col1","_col2","_col3","_col4"] + Group By Operator [GBY_108] (rows=5915494 width=101) + Output:["_col0","_col1","_col2","_col3","_col4"],keys:KEY._col0, KEY._col1, KEY._col2, KEY._col3, KEY._col4 + <-Union 9 [SIMPLE_EDGE] + <-Reducer 22 [CONTAINS] + Reduce Output Operator [RS_107] + PartitionCols:_col0, _col1, _col2, _col3, _col4 + Group By Operator [GBY_106] (rows=11830988 width=101) + Output:["_col0","_col1","_col2","_col3","_col4"],keys:_col0, _col3, _col4, _col1, _col2 + Select Operator [SEL_99] (rows=8604378 width=88) + Output:["_col0","_col1","_col2","_col3","_col4"] + Filter Operator [FIL_137] (rows=8604378 width=88) + predicate:((_col0 <= 10) or (rank_window_1 <= 10)) + PTF Operator [PTF_98] (rows=12906568 width=88) + Function definitions:[{},{"name:":"windowingtablefunction","order by:":"(CAST( _col4 AS decimal(15,4)) / CAST( _col5 AS decimal(15,4))) ASC NULLS FIRST","partition by:":"0"}] + Select Operator [SEL_97] (rows=12906568 width=88) + Output:["_col0","_col1","_col2","_col3","_col4","_col5"] + <-Reducer 21 [SIMPLE_EDGE] + SHUFFLE [RS_96] + PartitionCols:0 + Select Operator [SEL_95] (rows=12906568 width=88) + Output:["rank_window_0","_col0","_col1","_col2","_col3","_col4"] + PTF Operator [PTF_94] (rows=12906568 width=88) + Function definitions:[{},{"name:":"windowingtablefunction","order by:":"(CAST( _col1 AS decimal(15,4)) / CAST( _col2 AS decimal(15,4))) ASC NULLS FIRST","partition by:":"0"}] + Select Operator [SEL_93] (rows=12906568 width=88) + Output:["_col0","_col1","_col2","_col3","_col4"] + <-Reducer 20 [SIMPLE_EDGE] + SHUFFLE [RS_92] + PartitionCols:0 + Group By Operator [GBY_90] (rows=12906568 width=88) + Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)","sum(VALUE._col2)","sum(VALUE._col3)"],keys:KEY._col0 + <-Reducer 19 [SIMPLE_EDGE] + SHUFFLE [RS_89] + PartitionCols:_col0 + Group By Operator [GBY_88] (rows=25813137 width=88) + Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(_col1)","sum(_col2)","sum(_col3)","sum(_col4)"],keys:_col0 + Select Operator [SEL_86] (rows=25813137 width=88) + Output:["_col0","_col1","_col2","_col3","_col4"] + Merge Join Operator [MERGEJOIN_146] (rows=25813137 width=88) + Conds:RS_83._col1, _col2=RS_84._col0, _col1(Inner),Output:["_col1","_col3","_col4","_col11","_col12"] + <-Map 27 [SIMPLE_EDGE] + SHUFFLE [RS_84] + PartitionCols:_col0, _col1 + Select Operator [SEL_79] (rows=19197050 width=77) + Output:["_col0","_col1","_col2","_col3"] + Filter Operator [FIL_140] (rows=19197050 width=77) + predicate:((sr_return_amt > 10000) and sr_item_sk is not null and sr_ticket_number is not null) + TableScan [TS_77] (rows=57591150 width=77) + default@store_returns,sr,Tbl:COMPLETE,Col:NONE,Output:["sr_item_sk","sr_ticket_number","sr_return_quantity","sr_return_amt"] + <-Reducer 18 [SIMPLE_EDGE] + SHUFFLE [RS_83] + PartitionCols:_col1, _col2 + Merge Join Operator [MERGEJOIN_145] (rows=23466488 width=88) + Conds:RS_80._col0=RS_81._col0(Inner),Output:["_col1","_col2","_col3","_col4"] + <-Map 12 [SIMPLE_EDGE] + SHUFFLE [RS_81] + PartitionCols:_col0 + Select Operator [SEL_5] (rows=18262 width=1119) + Output:["_col0"] + Filter Operator [FIL_131] (rows=18262 width=1119) + predicate:((d_moy = 12) and (d_year = 2000) and d_date_sk is not null) + TableScan [TS_3] (rows=73049 width=1119) + default@date_dim,date_dim,Tbl:COMPLETE,Col:NONE,Output:["d_date_sk","d_year","d_moy"] + <-Map 26 [SIMPLE_EDGE] + SHUFFLE [RS_80] + PartitionCols:_col0 + Select Operator [SEL_73] (rows=21333171 width=88) + Output:["_col0","_col1","_col2","_col3","_col4"] + Filter Operator [FIL_138] (rows=21333171 width=88) + predicate:((ss_net_paid > 0) and (ss_net_profit > 1) and (ss_quantity > 0) and ss_item_sk is not null and ss_sold_date_sk is not null and ss_ticket_number is not null) + TableScan [TS_71] (rows=575995635 width=88) + default@store_sales,sts,Tbl:COMPLETE,Col:NONE,Output:["ss_sold_date_sk","ss_item_sk","ss_ticket_number","ss_quantity","ss_net_paid","ss_net_profit"] + <-Reducer 8 [CONTAINS] + Reduce Output Operator [RS_107] + PartitionCols:_col0, _col1, _col2, _col3, _col4 + Group By Operator [GBY_106] (rows=11830988 width=101) + Output:["_col0","_col1","_col2","_col3","_col4"],keys:_col0, _col3, _col4, _col1, _col2 + Select Operator [SEL_70] (rows=3226610 width=135) + Output:["_col0","_col1","_col2","_col3","_col4"] + Group By Operator [GBY_69] (rows=3226610 width=135) + Output:["_col0","_col1","_col2","_col3","_col4"],keys:KEY._col0, KEY._col1, KEY._col2, KEY._col3, KEY._col4 + <-Union 7 [SIMPLE_EDGE] + <-Reducer 17 [CONTAINS] + Reduce Output Operator [RS_68] + PartitionCols:_col0, _col1, _col2, _col3, _col4 + Group By Operator [GBY_67] (rows=6453220 width=135) + Output:["_col0","_col1","_col2","_col3","_col4"],keys:_col0, _col3, _col4, _col1, _col2 + Select Operator [SEL_60] (rows=4302070 width=135) + Output:["_col0","_col1","_col2","_col3","_col4"] + Filter Operator [FIL_133] (rows=4302070 width=135) + predicate:((_col0 <= 10) or (rank_window_1 <= 10)) + PTF Operator [PTF_59] (rows=6453105 width=135) + Function definitions:[{},{"name:":"windowingtablefunction","order by:":"(CAST( _col4 AS decimal(15,4)) / CAST( _col5 AS decimal(15,4))) ASC NULLS FIRST","partition by:":"0"}] + Select Operator [SEL_58] (rows=6453105 width=135) + Output:["_col0","_col1","_col2","_col3","_col4","_col5"] + <-Reducer 16 [SIMPLE_EDGE] + SHUFFLE [RS_57] + PartitionCols:0 + Select Operator [SEL_56] (rows=6453105 width=135) + Output:["rank_window_0","_col0","_col1","_col2","_col3","_col4"] + PTF Operator [PTF_55] (rows=6453105 width=135) + Function definitions:[{},{"name:":"windowingtablefunction","order by:":"(CAST( _col1 AS decimal(15,4)) / CAST( _col2 AS decimal(15,4))) ASC NULLS FIRST","partition by:":"0"}] + Select Operator [SEL_54] (rows=6453105 width=135) + Output:["_col0","_col1","_col2","_col3","_col4"] + <-Reducer 15 [SIMPLE_EDGE] + SHUFFLE [RS_53] + PartitionCols:0 + Group By Operator [GBY_51] (rows=6453105 width=135) + Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)","sum(VALUE._col2)","sum(VALUE._col3)"],keys:KEY._col0 + <-Reducer 14 [SIMPLE_EDGE] + SHUFFLE [RS_50] + PartitionCols:_col0 + Group By Operator [GBY_49] (rows=12906211 width=135) + Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(_col1)","sum(_col2)","sum(_col3)","sum(_col4)"],keys:_col0 + Select Operator [SEL_47] (rows=12906211 width=135) + Output:["_col0","_col1","_col2","_col3","_col4"] + Merge Join Operator [MERGEJOIN_144] (rows=12906211 width=135) + Conds:RS_44._col1, _col2=RS_45._col0, _col1(Inner),Output:["_col1","_col3","_col4","_col11","_col12"] + <-Map 25 [SIMPLE_EDGE] + SHUFFLE [RS_45] + PartitionCols:_col0, _col1 + Select Operator [SEL_40] (rows=9599627 width=106) + Output:["_col0","_col1","_col2","_col3"] + Filter Operator [FIL_136] (rows=9599627 width=106) + predicate:((cr_return_amount > 10000) and cr_item_sk is not null and cr_order_number is not null) + TableScan [TS_38] (rows=28798881 width=106) + default@catalog_returns,cr,Tbl:COMPLETE,Col:NONE,Output:["cr_item_sk","cr_order_number","cr_return_quantity","cr_return_amount"] + <-Reducer 13 [SIMPLE_EDGE] + SHUFFLE [RS_44] + PartitionCols:_col1, _col2 + Merge Join Operator [MERGEJOIN_143] (rows=11732919 width=135) + Conds:RS_41._col0=RS_42._col0(Inner),Output:["_col1","_col2","_col3","_col4"] + <-Map 12 [SIMPLE_EDGE] + SHUFFLE [RS_42] + PartitionCols:_col0 + Please refer to the previous Select Operator [SEL_5] + <-Map 24 [SIMPLE_EDGE] + SHUFFLE [RS_41] + PartitionCols:_col0 + Select Operator [SEL_34] (rows=10666290 width=135) + Output:["_col0","_col1","_col2","_col3","_col4"] + Filter Operator [FIL_134] (rows=10666290 width=135) + predicate:((cs_net_paid > 0) and (cs_net_profit > 1) and (cs_quantity > 0) and cs_item_sk is not null and cs_order_number is not null and cs_sold_date_sk is not null) + TableScan [TS_32] (rows=287989836 width=135) + default@catalog_sales,cs,Tbl:COMPLETE,Col:NONE,Output:["cs_sold_date_sk","cs_item_sk","cs_order_number","cs_quantity","cs_net_paid","cs_net_profit"] + <-Reducer 6 [CONTAINS] + Reduce Output Operator [RS_68] + PartitionCols:_col0, _col1, _col2, _col3, _col4 + Group By Operator [GBY_67] (rows=6453220 width=135) + Output:["_col0","_col1","_col2","_col3","_col4"],keys:_col0, _col3, _col4, _col1, _col2 + Select Operator [SEL_28] (rows=2151150 width=135) + Output:["_col0","_col1","_col2","_col3","_col4"] + Filter Operator [FIL_129] (rows=2151150 width=135) + predicate:((_col0 <= 10) or (rank_window_1 <= 10)) + PTF Operator [PTF_27] (rows=3226726 width=135) + Function definitions:[{},{"name:":"windowingtablefunction","order by:":"(CAST( _col4 AS decimal(15,4)) / CAST( _col5 AS decimal(15,4))) ASC NULLS FIRST","partition by:":"0"}] + Select Operator [SEL_26] (rows=3226726 width=135) + Output:["_col0","_col1","_col2","_col3","_col4","_col5"] + <-Reducer 5 [SIMPLE_EDGE] + SHUFFLE [RS_25] + PartitionCols:0 + Select Operator [SEL_24] (rows=3226726 width=135) + Output:["rank_window_0","_col0","_col1","_col2","_col3","_col4"] + PTF Operator [PTF_23] (rows=3226726 width=135) + Function definitions:[{},{"name:":"windowingtablefunction","order by:":"(CAST( _col1 AS decimal(15,4)) / CAST( _col2 AS decimal(15,4))) ASC NULLS FIRST","partition by:":"0"}] + Select Operator [SEL_22] (rows=3226726 width=135) + Output:["_col0","_col1","_col2","_col3","_col4"] + <-Reducer 4 [SIMPLE_EDGE] + SHUFFLE [RS_21] + PartitionCols:0 + Group By Operator [GBY_19] (rows=3226726 width=135) + Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)","sum(VALUE._col2)","sum(VALUE._col3)"],keys:KEY._col0 + <-Reducer 3 [SIMPLE_EDGE] + SHUFFLE [RS_18] + PartitionCols:_col0 + Group By Operator [GBY_17] (rows=6453452 width=135) + Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(_col1)","sum(_col2)","sum(_col3)","sum(_col4)"],keys:_col0 + Select Operator [SEL_15] (rows=6453452 width=135) + Output:["_col0","_col1","_col2","_col3","_col4"] + Merge Join Operator [MERGEJOIN_142] (rows=6453452 width=135) + Conds:RS_12._col1, _col2=RS_13._col0, _col1(Inner),Output:["_col1","_col3","_col4","_col11","_col12"] + <-Map 23 [SIMPLE_EDGE] + SHUFFLE [RS_13] + PartitionCols:_col0, _col1 + Select Operator [SEL_8] (rows=4799489 width=92) + Output:["_col0","_col1","_col2","_col3"] + Filter Operator [FIL_132] (rows=4799489 width=92) + predicate:((wr_return_amt > 10000) and wr_item_sk is not null and wr_order_number is not null) + TableScan [TS_6] (rows=14398467 width=92) + default@web_returns,wr,Tbl:COMPLETE,Col:NONE,Output:["wr_item_sk","wr_order_number","wr_return_quantity","wr_return_amt"] + <-Reducer 2 [SIMPLE_EDGE] + SHUFFLE [RS_12] + PartitionCols:_col1, _col2 + Merge Join Operator [MERGEJOIN_141] (rows=5866775 width=135) + Conds:RS_9._col0=RS_10._col0(Inner),Output:["_col1","_col2","_col3","_col4"] + <-Map 12 [SIMPLE_EDGE] + SHUFFLE [RS_10] + PartitionCols:_col0 + Please refer to the previous Select Operator [SEL_5] + <-Map 1 [SIMPLE_EDGE] + SHUFFLE [RS_9] + PartitionCols:_col0 + Select Operator [SEL_2] (rows=5333432 width=135) + Output:["_col0","_col1","_col2","_col3","_col4"] + Filter Operator [FIL_130] (rows=5333432 width=135) + predicate:((ws_net_paid > 0) and (ws_net_profit > 1) and (ws_quantity > 0) and ws_item_sk is not null and ws_order_number is not null and ws_sold_date_sk is not null) + TableScan [TS_0] (rows=144002668 width=135) + default@web_sales,ws,Tbl:COMPLETE,Col:NONE,Output:["ws_sold_date_sk","ws_item_sk","ws_order_number","ws_quantity","ws_net_paid","ws_net_profit"] +
