http://git-wip-us.apache.org/repos/asf/hive/blob/9244fdc7/ql/src/test/results/clientpositive/perf/query45.q.out ---------------------------------------------------------------------- diff --git a/ql/src/test/results/clientpositive/perf/query45.q.out b/ql/src/test/results/clientpositive/perf/query45.q.out deleted file mode 100644 index 3efed2e..0000000 --- a/ql/src/test/results/clientpositive/perf/query45.q.out +++ /dev/null @@ -1,180 +0,0 @@ -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/query46.q.out ---------------------------------------------------------------------- diff --git a/ql/src/test/results/clientpositive/perf/query46.q.out b/ql/src/test/results/clientpositive/perf/query46.q.out deleted file mode 100644 index 1a193ed..0000000 --- a/ql/src/test/results/clientpositive/perf/query46.q.out +++ /dev/null @@ -1,191 +0,0 @@ -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/query47.q.out ---------------------------------------------------------------------- diff --git a/ql/src/test/results/clientpositive/perf/query47.q.out b/ql/src/test/results/clientpositive/perf/query47.q.out deleted file mode 100644 index 1288408..0000000 --- a/ql/src/test/results/clientpositive/perf/query47.q.out +++ /dev/null @@ -1,325 +0,0 @@ -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/query48.q.out ---------------------------------------------------------------------- diff --git a/ql/src/test/results/clientpositive/perf/query48.q.out b/ql/src/test/results/clientpositive/perf/query48.q.out deleted file mode 100644 index 8db0c1e..0000000 --- a/ql/src/test/results/clientpositive/perf/query48.q.out +++ /dev/null @@ -1,218 +0,0 @@ -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/query49.q.out ---------------------------------------------------------------------- diff --git a/ql/src/test/results/clientpositive/perf/query49.q.out b/ql/src/test/results/clientpositive/perf/query49.q.out deleted file mode 100644 index be4027d..0000000 --- a/ql/src/test/results/clientpositive/perf/query49.q.out +++ /dev/null @@ -1,496 +0,0 @@ -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"] -
