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Posted to commits@hive.apache.org by we...@apache.org on 2017/05/31 00:11:48 UTC
[10/17] hive git commit: HIVE-16764: Support numeric as same as
decimal (Pengcheng Xiong, reviewed by Ashutosh Chauhan)
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"]
+