http://git-wip-us.apache.org/repos/asf/hive/blob/86b18772/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 index 8c6e914..6806703 100644 --- a/ql/src/test/results/clientpositive/perf/query46.q.out +++ b/ql/src/test/results/clientpositive/perf/query46.q.out @@ -1,6 +1,70 @@ -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 = 4 or household_demographics.hd_vehicle_count= 2) and date_dim.d_dow in (6,0) and date_dim.d_year in (1998,1998+1,1998+2) and store.s_city in ('Rosedale','Bethlehem','Clinton','Clifton','Springfield') group by ss_ticket_number,ss_customer_sk,ss_addr_sk,ca_city) dn,customer,customer_address current_addr where dn.ss_customer_sk = customer.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: 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 = 4 or household_demographics.hd_vehicle_count= 2) and date_dim.d_dow in (6,0) and date_dim.d_year in (1998,1998+1,1998+2) and store.s_city in ('Rosedale','Bethlehem','Clinton','Clifton','Springfield') group by ss_ticket_number,ss_customer_sk,ss_addr_sk,ca_city) dn,customer,customer_address current_addr where dn.ss_customer_sk = customer.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: 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. @@ -88,7 +152,7 @@ Stage-0 Select Operator [SEL_17] (rows=7200 width=107) Output:["_col0"] Filter Operator [FIL_79] (rows=7200 width=107) - predicate:(((hd_dep_count = 4) or (hd_vehicle_count = 2)) and hd_demo_sk is not null) + 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] @@ -102,7 +166,7 @@ Stage-0 Select Operator [SEL_14] (rows=852 width=1910) Output:["_col0"] Filter Operator [FIL_78] (rows=852 width=1910) - predicate:((s_city) IN ('Rosedale', 'Bethlehem', 'Clinton', 'Clifton', 'Springfield') and s_store_sk is not null) + 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]
http://git-wip-us.apache.org/repos/asf/hive/blob/86b18772/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 index e377e3f..ffe80b4 100644 --- a/ql/src/test/results/clientpositive/perf/query48.q.out +++ b/ql/src/test/results/clientpositive/perf/query48.q.out @@ -1,6 +1,132 @@ -PREHOOK: query: explain select sum (ss_quantity) from store_sales, store, customer_demographics, customer_address, date_dim where store.s_store_sk = store_sales.ss_store_sk and store_sales.ss_sold_date_sk = date_dim.d_date_sk and d_year = 1998 and ( ( customer_demographics.cd_demo_sk = store_sales.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 ( customer_demographics.cd_demo_sk = store_sales.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 ( customer_demographics.cd_demo_sk = store_sales.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 ( ( store_sales.ss_addr_sk = customer_address.ca_address_sk and ca_country = 'United States' and ca_state in ('KY', 'GA', 'NM') and ss_net_profit between 0 and 2000 ) or (store_sales.ss_addr_sk = customer_add ress.ca_address_sk and ca_country = 'United States' and ca_state in ('MT', 'OR', 'IN') and ss_net_profit between 150 and 3000 ) or (store_sales.ss_addr_sk = customer_address.ca_address_sk and ca_country = 'United States' and ca_state in ('WI', 'MO', 'WV') and ss_net_profit between 50 and 25000 ) ) +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 store.s_store_sk = store_sales.ss_store_sk and store_sales.ss_sold_date_sk = date_dim.d_date_sk and d_year = 1998 and ( ( customer_demographics.cd_demo_sk = store_sales.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 ( customer_demographics.cd_demo_sk = store_sales.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 ( customer_demographics.cd_demo_sk = store_sales.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 ( ( store_sales.ss_addr_sk = customer_address.ca_address_sk and ca_country = 'United States' and ca_state in ('KY', 'GA', 'NM') and ss_net_profit between 0 and 2000 ) or (store_sales.ss_addr_sk = customer_ad dress.ca_address_sk and ca_country = 'United States' and ca_state in ('MT', 'OR', 'IN') and ss_net_profit between 150 and 3000 ) or (store_sales.ss_addr_sk = customer_address.ca_address_sk and ca_country = 'United States' and ca_state in ('WI', 'MO', 'WV') and ss_net_profit between 50 and 25000 ) ) +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. http://git-wip-us.apache.org/repos/asf/hive/blob/86b18772/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 new file mode 100644 index 0000000..8b8ad8b --- /dev/null +++ b/ql/src/test/results/clientpositive/perf/query49.q.out @@ -0,0 +1,504 @@ +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_76] (rows=18262 width=1119) + Output:["_col0"] + Filter Operator [FIL_139] (rows=18262 width=1119) + predicate:((d_year = 2000) and (d_moy = 12) 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_profit > 1) and (ss_net_paid > 0) and (ss_quantity > 0) and ss_item_sk is not null and ss_ticket_number is not null and ss_sold_date_sk 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_order_number is not null and cr_item_sk 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 + Select Operator [SEL_37] (rows=18262 width=1119) + Output:["_col0"] + Filter Operator [FIL_135] (rows=18262 width=1119) + predicate:((d_year = 2000) and (d_moy = 12) and d_date_sk is not null) + Please refer to the previous TableScan [TS_3] + <-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_profit > 1) and (cs_net_paid > 0) and (cs_quantity > 0) and cs_order_number is not null and cs_item_sk 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 + Select Operator [SEL_5] (rows=18262 width=1119) + Output:["_col0"] + Filter Operator [FIL_131] (rows=18262 width=1119) + predicate:((d_year = 2000) and (d_moy = 12) and d_date_sk is not null) + Please refer to the previous TableScan [TS_3] + <-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_profit > 1) and (ws_net_paid > 0) and (ws_quantity > 0) and ws_order_number is not null and ws_item_sk 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"] + http://git-wip-us.apache.org/repos/asf/hive/blob/86b18772/ql/src/test/results/clientpositive/perf/query50.q.out ---------------------------------------------------------------------- diff --git a/ql/src/test/results/clientpositive/perf/query50.q.out b/ql/src/test/results/clientpositive/perf/query50.q.out index 47a00b0..149dc98 100644 --- a/ql/src/test/results/clientpositive/perf/query50.q.out +++ b/ql/src/test/results/clientpositive/perf/query50.q.out @@ -1,4 +1,4 @@ -PREHOOK: query: explain +PREHOOK: query: explain select s_store_name ,s_company_id @@ -10,14 +10,14 @@ select ,s_county ,s_state ,s_zip - ,sum(case when (sr_returned_date_sk - ss_sold_date_sk <= 30 ) then 1 else 0 end) as 30days + ,sum(case when (sr_returned_date_sk - ss_sold_date_sk <= 30 ) then 1 else 0 end) as `30 days` ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 30) and - (sr_returned_date_sk - ss_sold_date_sk <= 60) then 1 else 0 end ) as 3160days + (sr_returned_date_sk - ss_sold_date_sk <= 60) then 1 else 0 end ) as `31-60 days` ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 60) and - (sr_returned_date_sk - ss_sold_date_sk <= 90) then 1 else 0 end) as 6190days + (sr_returned_date_sk - ss_sold_date_sk <= 90) then 1 else 0 end) as `61-90 days` ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 90) and - (sr_returned_date_sk - ss_sold_date_sk <= 120) then 1 else 0 end) as 91120days - ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 120) then 1 else 0 end) as 120days + (sr_returned_date_sk - ss_sold_date_sk <= 120) then 1 else 0 end) as `91-120 days` + ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 120) then 1 else 0 end) as `>120 days` from store_sales ,store_returns @@ -27,12 +27,12 @@ from where d2.d_year = 2000 and d2.d_moy = 9 -and store_sales.ss_ticket_number = store_returns.sr_ticket_number -and store_sales.ss_item_sk = store_returns.sr_item_sk -and store_sales.ss_sold_date_sk = d1.d_date_sk +and ss_ticket_number = sr_ticket_number +and ss_item_sk = sr_item_sk +and ss_sold_date_sk = d1.d_date_sk and sr_returned_date_sk = d2.d_date_sk -and store_sales.ss_customer_sk = store_returns.sr_customer_sk -and store_sales.ss_store_sk = store.s_store_sk +and ss_customer_sk = sr_customer_sk +and ss_store_sk = s_store_sk group by s_store_name ,s_company_id @@ -56,7 +56,7 @@ order by s_store_name ,s_zip limit 100 PREHOOK: type: QUERY -POSTHOOK: query: explain +POSTHOOK: query: explain select s_store_name ,s_company_id @@ -68,14 +68,14 @@ select ,s_county ,s_state ,s_zip - ,sum(case when (sr_returned_date_sk - ss_sold_date_sk <= 30 ) then 1 else 0 end) as 30days + ,sum(case when (sr_returned_date_sk - ss_sold_date_sk <= 30 ) then 1 else 0 end) as `30 days` ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 30) and - (sr_returned_date_sk - ss_sold_date_sk <= 60) then 1 else 0 end ) as 3160days + (sr_returned_date_sk - ss_sold_date_sk <= 60) then 1 else 0 end ) as `31-60 days` ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 60) and - (sr_returned_date_sk - ss_sold_date_sk <= 90) then 1 else 0 end) as 6190days + (sr_returned_date_sk - ss_sold_date_sk <= 90) then 1 else 0 end) as `61-90 days` ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 90) and - (sr_returned_date_sk - ss_sold_date_sk <= 120) then 1 else 0 end) as 91120days - ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 120) then 1 else 0 end) as 120days + (sr_returned_date_sk - ss_sold_date_sk <= 120) then 1 else 0 end) as `91-120 days` + ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 120) then 1 else 0 end) as `>120 days` from store_sales ,store_returns @@ -85,12 +85,12 @@ from where d2.d_year = 2000 and d2.d_moy = 9 -and store_sales.ss_ticket_number = store_returns.sr_ticket_number -and store_sales.ss_item_sk = store_returns.sr_item_sk -and store_sales.ss_sold_date_sk = d1.d_date_sk +and ss_ticket_number = sr_ticket_number +and ss_item_sk = sr_item_sk +and ss_sold_date_sk = d1.d_date_sk and sr_returned_date_sk = d2.d_date_sk -and store_sales.ss_customer_sk = store_returns.sr_customer_sk -and store_sales.ss_store_sk = store.s_store_sk +and ss_customer_sk = sr_customer_sk +and ss_store_sk = s_store_sk group by s_store_name ,s_company_id http://git-wip-us.apache.org/repos/asf/hive/blob/86b18772/ql/src/test/results/clientpositive/perf/query51.q.out ---------------------------------------------------------------------- diff --git a/ql/src/test/results/clientpositive/perf/query51.q.out b/ql/src/test/results/clientpositive/perf/query51.q.out index 2468c77..0ce3e9f 100644 --- a/ql/src/test/results/clientpositive/perf/query51.q.out +++ b/ql/src/test/results/clientpositive/perf/query51.q.out @@ -1,23 +1,24 @@ -PREHOOK: query: explain WITH web_v1 as ( +PREHOOK: query: explain +WITH web_v1 as ( select - ws_item_sk item_sk, d_date, sum(ws_sales_price), + ws_item_sk item_sk, d_date, sum(sum(ws_sales_price)) over (partition by ws_item_sk order by d_date rows between unbounded preceding and current row) cume_sales from web_sales ,date_dim where ws_sold_date_sk=d_date_sk - and d_month_seq between 1193 and 1193+11 + and d_month_seq between 1212 and 1212+11 and ws_item_sk is not NULL group by ws_item_sk, d_date), store_v1 as ( select - ss_item_sk item_sk, d_date, sum(ss_sales_price), + ss_item_sk item_sk, d_date, sum(sum(ss_sales_price)) over (partition by ss_item_sk order by d_date rows between unbounded preceding and current row) cume_sales from store_sales ,date_dim where ss_sold_date_sk=d_date_sk - and d_month_seq between 1193 and 1193+11 + and d_month_seq between 1212 and 1212+11 and ss_item_sk is not NULL group by ss_item_sk, d_date) select * @@ -41,26 +42,27 @@ order by item_sk ,d_date limit 100 PREHOOK: type: QUERY -POSTHOOK: query: explain WITH web_v1 as ( +POSTHOOK: query: explain +WITH web_v1 as ( select - ws_item_sk item_sk, d_date, sum(ws_sales_price), + ws_item_sk item_sk, d_date, sum(sum(ws_sales_price)) over (partition by ws_item_sk order by d_date rows between unbounded preceding and current row) cume_sales from web_sales ,date_dim where ws_sold_date_sk=d_date_sk - and d_month_seq between 1193 and 1193+11 + and d_month_seq between 1212 and 1212+11 and ws_item_sk is not NULL group by ws_item_sk, d_date), store_v1 as ( select - ss_item_sk item_sk, d_date, sum(ss_sales_price), + ss_item_sk item_sk, d_date, sum(sum(ss_sales_price)) over (partition by ss_item_sk order by d_date rows between unbounded preceding and current row) cume_sales from store_sales ,date_dim where ss_sold_date_sk=d_date_sk - and d_month_seq between 1193 and 1193+11 + and d_month_seq between 1212 and 1212+11 and ss_item_sk is not NULL group by ss_item_sk, d_date) select * @@ -142,7 +144,7 @@ Stage-0 Select Operator [SEL_5] (rows=8116 width=1119) Output:["_col0","_col1"] Filter Operator [FIL_60] (rows=8116 width=1119) - predicate:(d_month_seq BETWEEN 1193 AND 1204 and d_date_sk is not null) + predicate:(d_month_seq BETWEEN 1212 AND 1223 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_date","d_month_seq"] <-Map 1 [SIMPLE_EDGE] @@ -176,7 +178,7 @@ Stage-0 Select Operator [SEL_25] (rows=8116 width=1119) Output:["_col0","_col1"] Filter Operator [FIL_62] (rows=8116 width=1119) - predicate:(d_month_seq BETWEEN 1193 AND 1204 and d_date_sk is not null) + predicate:(d_month_seq BETWEEN 1212 AND 1223 and d_date_sk is not null) Please refer to the previous TableScan [TS_3] <-Map 10 [SIMPLE_EDGE] SHUFFLE [RS_26] http://git-wip-us.apache.org/repos/asf/hive/blob/86b18772/ql/src/test/results/clientpositive/perf/query52.q.out ---------------------------------------------------------------------- diff --git a/ql/src/test/results/clientpositive/perf/query52.q.out b/ql/src/test/results/clientpositive/perf/query52.q.out index 3d4b9e5..9631f59 100644 --- a/ql/src/test/results/clientpositive/perf/query52.q.out +++ b/ql/src/test/results/clientpositive/perf/query52.q.out @@ -1,6 +1,44 @@ -PREHOOK: query: explain select dt.d_year ,item.i_brand_id brand_id ,item.i_brand brand ,sum(ss_ext_sales_price) ext_price from date_dim dt ,store_sales ,item where dt.d_date_sk = store_sales.ss_sold_date_sk and store_sales.ss_item_sk = item.i_item_sk and item.i_manager_id = 1 and dt.d_moy=12 and dt.d_year=1998 group by dt.d_year ,item.i_brand ,item.i_brand_id order by dt.d_year ,ext_price desc ,brand_id limit 100 +PREHOOK: query: explain +select dt.d_year + ,item.i_brand_id brand_id + ,item.i_brand brand + ,sum(ss_ext_sales_price) ext_price + from date_dim dt + ,store_sales + ,item + where dt.d_date_sk = store_sales.ss_sold_date_sk + and store_sales.ss_item_sk = item.i_item_sk + and item.i_manager_id = 1 + and dt.d_moy=12 + and dt.d_year=1998 + group by dt.d_year + ,item.i_brand + ,item.i_brand_id + order by dt.d_year + ,ext_price desc + ,brand_id +limit 100 PREHOOK: type: QUERY -POSTHOOK: query: explain select dt.d_year ,item.i_brand_id brand_id ,item.i_brand brand ,sum(ss_ext_sales_price) ext_price from date_dim dt ,store_sales ,item where dt.d_date_sk = store_sales.ss_sold_date_sk and store_sales.ss_item_sk = item.i_item_sk and item.i_manager_id = 1 and dt.d_moy=12 and dt.d_year=1998 group by dt.d_year ,item.i_brand ,item.i_brand_id order by dt.d_year ,ext_price desc ,brand_id limit 100 +POSTHOOK: query: explain +select dt.d_year + ,item.i_brand_id brand_id + ,item.i_brand brand + ,sum(ss_ext_sales_price) ext_price + from date_dim dt + ,store_sales + ,item + where dt.d_date_sk = store_sales.ss_sold_date_sk + and store_sales.ss_item_sk = item.i_item_sk + and item.i_manager_id = 1 + and dt.d_moy=12 + and dt.d_year=1998 + group by dt.d_year + ,item.i_brand + ,item.i_brand_id + order by dt.d_year + ,ext_price desc + ,brand_id +limit 100 POSTHOOK: type: QUERY Plan optimized by CBO. http://git-wip-us.apache.org/repos/asf/hive/blob/86b18772/ql/src/test/results/clientpositive/perf/query53.q.out ---------------------------------------------------------------------- diff --git a/ql/src/test/results/clientpositive/perf/query53.q.out b/ql/src/test/results/clientpositive/perf/query53.q.out new file mode 100644 index 0000000..bc9e6c4 --- /dev/null +++ b/ql/src/test/results/clientpositive/perf/query53.q.out @@ -0,0 +1,141 @@ +PREHOOK: query: explain +select * from +(select i_manufact_id, +sum(ss_sales_price) sum_sales, +avg(sum(ss_sales_price)) over (partition by i_manufact_id) avg_quarterly_sales +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_month_seq in (1212,1212+1,1212+2,1212+3,1212+4,1212+5,1212+6,1212+7,1212+8,1212+9,1212+10,1212+11) and +((i_category in ('Books','Children','Electronics') and +i_class in ('personal','portable','reference','self-help') and +i_brand in ('scholaramalgamalg #14','scholaramalgamalg #7', + 'exportiunivamalg #9','scholaramalgamalg #9')) +or(i_category in ('Women','Music','Men') and +i_class in ('accessories','classical','fragrances','pants') and +i_brand in ('amalgimporto #1','edu packscholar #1','exportiimporto #1', + 'importoamalg #1'))) +group by i_manufact_id, d_qoy ) tmp1 +where case when avg_quarterly_sales > 0 + then abs (sum_sales - avg_quarterly_sales)/ avg_quarterly_sales + else null end > 0.1 +order by avg_quarterly_sales, + sum_sales, + i_manufact_id +limit 100 +PREHOOK: type: QUERY +POSTHOOK: query: explain +select * from +(select i_manufact_id, +sum(ss_sales_price) sum_sales, +avg(sum(ss_sales_price)) over (partition by i_manufact_id) avg_quarterly_sales +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_month_seq in (1212,1212+1,1212+2,1212+3,1212+4,1212+5,1212+6,1212+7,1212+8,1212+9,1212+10,1212+11) and +((i_category in ('Books','Children','Electronics') and +i_class in ('personal','portable','reference','self-help') and +i_brand in ('scholaramalgamalg #14','scholaramalgamalg #7', + 'exportiunivamalg #9','scholaramalgamalg #9')) +or(i_category in ('Women','Music','Men') and +i_class in ('accessories','classical','fragrances','pants') and +i_brand in ('amalgimporto #1','edu packscholar #1','exportiimporto #1', + 'importoamalg #1'))) +group by i_manufact_id, d_qoy ) tmp1 +where case when avg_quarterly_sales > 0 + then abs (sum_sales - avg_quarterly_sales)/ avg_quarterly_sales + else null end > 0.1 +order by avg_quarterly_sales, + sum_sales, + i_manufact_id +limit 100 +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 <- Reducer 4 (SIMPLE_EDGE) +Reducer 6 <- Reducer 5 (SIMPLE_EDGE) + +Stage-0 + Fetch Operator + limit:100 + Stage-1 + Reducer 6 + File Output Operator [FS_36] + Limit [LIM_35] (rows=100 width=88) + Number of rows:100 + Select Operator [SEL_34] (rows=191662559 width=88) + Output:["_col0","_col1","_col2"] + <-Reducer 5 [SIMPLE_EDGE] + SHUFFLE [RS_33] + Select Operator [SEL_30] (rows=191662559 width=88) + Output:["_col0","_col1","_col2"] + Filter Operator [FIL_46] (rows=191662559 width=88) + predicate:CASE WHEN ((avg_window_0 > 0)) THEN (((abs((_col2 - avg_window_0)) / avg_window_0) > 0.1)) ELSE (null) END + Select Operator [SEL_29] (rows=383325119 width=88) + Output:["avg_window_0","_col0","_col2"] + PTF Operator [PTF_28] (rows=383325119 width=88) + Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col0 ASC NULLS FIRST","partition by:":"_col0"}] + Select Operator [SEL_25] (rows=383325119 width=88) + Output:["_col0","_col2"] + Group By Operator [GBY_24] (rows=383325119 width=88) + Output:["_col0","_col1","_col2"],aggregations:["sum(VALUE._col0)"],keys:KEY._col0, KEY._col1 + <-Reducer 4 [SIMPLE_EDGE] + SHUFFLE [RS_23] + PartitionCols:_col0 + Group By Operator [GBY_22] (rows=766650239 width=88) + Output:["_col0","_col1","_col2"],aggregations:["sum(_col3)"],keys:_col8, _col11 + Merge Join Operator [MERGEJOIN_54] (rows=766650239 width=88) + Conds:RS_18._col2=RS_19._col0(Inner),Output:["_col3","_col8","_col11"] + <-Map 9 [SIMPLE_EDGE] + SHUFFLE [RS_19] + PartitionCols:_col0 + Select Operator [SEL_11] (rows=1704 width=1910) + Output:["_col0"] + Filter Operator [FIL_50] (rows=1704 width=1910) + predicate:s_store_sk is not null + TableScan [TS_9] (rows=1704 width=1910) + default@store,store,Tbl:COMPLETE,Col:NONE,Output:["s_store_sk"] + <-Reducer 3 [SIMPLE_EDGE] + SHUFFLE [RS_18] + PartitionCols:_col2 + Merge Join Operator [MERGEJOIN_53] (rows=696954748 width=88) + Conds:RS_15._col0=RS_16._col0(Inner),Output:["_col2","_col3","_col8","_col11"] + <-Map 8 [SIMPLE_EDGE] + SHUFFLE [RS_16] + PartitionCols:_col0 + Select Operator [SEL_8] (rows=36525 width=1119) + Output:["_col0","_col2"] + Filter Operator [FIL_49] (rows=36525 width=1119) + predicate:((d_month_seq) IN (1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219, 1220, 1221, 1222, 1223) 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_month_seq","d_qoy"] + <-Reducer 2 [SIMPLE_EDGE] + SHUFFLE [RS_15] + PartitionCols:_col0 + Merge Join Operator [MERGEJOIN_52] (rows=633595212 width=88) + Conds:RS_12._col1=RS_13._col0(Inner),Output:["_col0","_col2","_col3","_col8"] + <-Map 1 [SIMPLE_EDGE] + SHUFFLE [RS_12] + PartitionCols:_col1 + Select Operator [SEL_2] (rows=575995635 width=88) + Output:["_col0","_col1","_col2","_col3"] + Filter Operator [FIL_47] (rows=575995635 width=88) + predicate:(ss_item_sk is not null and ss_sold_date_sk is not null and ss_store_sk is not null) + TableScan [TS_0] (rows=575995635 width=88) + default@store_sales,store_sales,Tbl:COMPLETE,Col:NONE,Output:["ss_sold_date_sk","ss_item_sk","ss_store_sk","ss_sales_price"] + <-Map 7 [SIMPLE_EDGE] + SHUFFLE [RS_13] + PartitionCols:_col0 + Select Operator [SEL_5] (rows=115500 width=1436) + Output:["_col0","_col4"] + Filter Operator [FIL_48] (rows=115500 width=1436) + predicate:(((i_class) IN ('personal', 'portable', 'reference', 'self-help') or (i_class) IN ('accessories', 'classical', 'fragrances', 'pants')) and ((i_brand) IN ('scholaramalgamalg #14', 'scholaramalgamalg #7', 'exportiunivamalg #9', 'scholaramalgamalg #9') or (i_brand) IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1')) and ((i_category) IN ('Books', 'Children', 'Electronics') or (i_category) IN ('Women', 'Music', 'Men')) and (((i_category) IN ('Books', 'Children', 'Electronics') and (i_class) IN ('personal', 'portable', 'reference', 'self-help') and (i_brand) IN ('scholaramalgamalg #14', 'scholaramalgamalg #7', 'exportiunivamalg #9', 'scholaramalgamalg #9')) or ((i_category) IN ('Women', 'Music', 'Men') and (i_class) IN ('accessories', 'classical', 'fragrances', 'pants') and (i_brand) IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_item_sk is not null) + TableScan [TS_3] (rows=462000 width=1436) + default@item,item,Tbl:COMPLETE,Col:NONE,Output:["i_item_sk","i_brand","i_class","i_category","i_manufact_id"] +