You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@hive.apache.org by jc...@apache.org on 2018/10/22 02:10:37 UTC
[32/51] [partial] hive git commit: HIVE-20718: Add perf cli driver
with constraints (Jesus Camacho Rodriguez, reviewed by Ashutosh Chauhan)
http://git-wip-us.apache.org/repos/asf/hive/blob/b8299551/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query51.q.out
----------------------------------------------------------------------
diff --git a/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query51.q.out b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query51.q.out
new file mode 100644
index 0000000..3d81b6b
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query51.q.out
@@ -0,0 +1,125 @@
+PREHOOK: query: explain cbo
+WITH web_v1 as (
+select
+ 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 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(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 1212 and 1212+11
+ and ss_item_sk is not NULL
+group by ss_item_sk, d_date)
+ select *
+from (select item_sk
+ ,d_date
+ ,web_sales
+ ,store_sales
+ ,max(web_sales)
+ over (partition by item_sk order by d_date rows between unbounded preceding and current row) web_cumulative
+ ,max(store_sales)
+ over (partition by item_sk order by d_date rows between unbounded preceding and current row) store_cumulative
+ from (select case when web.item_sk is not null then web.item_sk else store.item_sk end item_sk
+ ,case when web.d_date is not null then web.d_date else store.d_date end d_date
+ ,web.cume_sales web_sales
+ ,store.cume_sales store_sales
+ from web_v1 web full outer join store_v1 store on (web.item_sk = store.item_sk
+ and web.d_date = store.d_date)
+ )x )y
+where web_cumulative > store_cumulative
+order by item_sk
+ ,d_date
+limit 100
+PREHOOK: type: QUERY
+PREHOOK: Input: default@date_dim
+PREHOOK: Input: default@store_sales
+PREHOOK: Input: default@web_sales
+PREHOOK: Output: hdfs://### HDFS PATH ###
+POSTHOOK: query: explain cbo
+WITH web_v1 as (
+select
+ 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 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(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 1212 and 1212+11
+ and ss_item_sk is not NULL
+group by ss_item_sk, d_date)
+ select *
+from (select item_sk
+ ,d_date
+ ,web_sales
+ ,store_sales
+ ,max(web_sales)
+ over (partition by item_sk order by d_date rows between unbounded preceding and current row) web_cumulative
+ ,max(store_sales)
+ over (partition by item_sk order by d_date rows between unbounded preceding and current row) store_cumulative
+ from (select case when web.item_sk is not null then web.item_sk else store.item_sk end item_sk
+ ,case when web.d_date is not null then web.d_date else store.d_date end d_date
+ ,web.cume_sales web_sales
+ ,store.cume_sales store_sales
+ from web_v1 web full outer join store_v1 store on (web.item_sk = store.item_sk
+ and web.d_date = store.d_date)
+ )x )y
+where web_cumulative > store_cumulative
+order by item_sk
+ ,d_date
+limit 100
+POSTHOOK: type: QUERY
+POSTHOOK: Input: default@date_dim
+POSTHOOK: Input: default@store_sales
+POSTHOOK: Input: default@web_sales
+POSTHOOK: Output: hdfs://### HDFS PATH ###
+CBO PLAN:
+HiveSortLimit(sort0=[$0], sort1=[$1], dir0=[ASC], dir1=[ASC], fetch=[100])
+ HiveProject(item_sk=[$0], d_date=[$1], web_sales=[$2], store_sales=[$3], max_window_0=[$4], max_window_1=[$5])
+ HiveFilter(condition=[>($4, $5)])
+ HiveProject(item_sk=[CASE(IS NOT NULL($3), $3, $0)], d_date=[CASE(IS NOT NULL($4), $4, $1)], web_sales=[$5], store_sales=[$2], max_window_0=[max($5) OVER (PARTITION BY CASE(IS NOT NULL($3), $3, $0) ORDER BY CASE(IS NOT NULL($4), $4, $1) NULLS LAST ROWS BETWEEN CURRENT ROW AND 2147483647 PRECEDING)], max_window_1=[max($2) OVER (PARTITION BY CASE(IS NOT NULL($3), $3, $0) ORDER BY CASE(IS NOT NULL($4), $4, $1) NULLS LAST ROWS BETWEEN CURRENT ROW AND 2147483647 PRECEDING)])
+ HiveJoin(condition=[AND(=($3, $0), =($4, $1))], joinType=[full], algorithm=[none], cost=[not available])
+ HiveProject((tok_table_or_col ss_item_sk)=[$0], (tok_table_or_col d_date)=[$1], sum_window_0=[$2])
+ HiveProject((tok_table_or_col ss_item_sk)=[$0], (tok_table_or_col d_date)=[$1], sum_window_0=[sum($2) OVER (PARTITION BY $0 ORDER BY $1 NULLS LAST ROWS BETWEEN CURRENT ROW AND 2147483647 PRECEDING)], window_col_0=[$2])
+ HiveProject(ss_item_sk=[$0], d_date=[$1], $f2=[$2])
+ HiveAggregate(group=[{1, 4}], agg#0=[sum($2)])
+ HiveJoin(condition=[=($0, $3)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$2], ss_sales_price=[$13])
+ HiveFilter(condition=[IS NOT NULL($0)])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject(d_date_sk=[$0], d_date=[$2])
+ HiveFilter(condition=[BETWEEN(false, $3, 1212, 1223)])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject((tok_table_or_col ws_item_sk)=[$0], (tok_table_or_col d_date)=[$1], sum_window_0=[$2])
+ HiveProject((tok_table_or_col ws_item_sk)=[$0], (tok_table_or_col d_date)=[$1], sum_window_0=[sum($2) OVER (PARTITION BY $0 ORDER BY $1 NULLS LAST ROWS BETWEEN CURRENT ROW AND 2147483647 PRECEDING)], window_col_0=[$2])
+ HiveProject(ws_item_sk=[$0], d_date=[$1], $f2=[$2])
+ HiveAggregate(group=[{1, 4}], agg#0=[sum($2)])
+ HiveJoin(condition=[=($0, $3)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ws_sold_date_sk=[$0], ws_item_sk=[$3], ws_sales_price=[$21])
+ HiveFilter(condition=[IS NOT NULL($0)])
+ HiveTableScan(table=[[default, web_sales]], table:alias=[web_sales])
+ HiveProject(d_date_sk=[$0], d_date=[$2])
+ HiveFilter(condition=[BETWEEN(false, $3, 1212, 1223)])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+
http://git-wip-us.apache.org/repos/asf/hive/blob/b8299551/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query52.q.out
----------------------------------------------------------------------
diff --git a/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query52.q.out b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query52.q.out
new file mode 100644
index 0000000..ab2db4b
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query52.q.out
@@ -0,0 +1,67 @@
+PREHOOK: query: explain cbo
+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
+PREHOOK: Input: default@date_dim
+PREHOOK: Input: default@item
+PREHOOK: Input: default@store_sales
+PREHOOK: Output: hdfs://### HDFS PATH ###
+POSTHOOK: query: explain cbo
+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
+POSTHOOK: Input: default@date_dim
+POSTHOOK: Input: default@item
+POSTHOOK: Input: default@store_sales
+POSTHOOK: Output: hdfs://### HDFS PATH ###
+CBO PLAN:
+HiveProject(d_year=[CAST(1998):INTEGER], brand_id=[$0], brand=[$1], ext_price=[$2])
+ HiveSortLimit(sort0=[$2], sort1=[$0], dir0=[DESC-nulls-last], dir1=[ASC], fetch=[100])
+ HiveProject(i_brand_id=[$0], i_brand=[$1], $f2=[$2])
+ HiveAggregate(group=[{5, 6}], agg#0=[sum($2)])
+ HiveJoin(condition=[=($1, $4)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($3, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$2], ss_ext_sales_price=[$15])
+ HiveFilter(condition=[IS NOT NULL($0)])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject(d_date_sk=[$0])
+ HiveFilter(condition=[AND(=($8, 12), =($6, 1998))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[dt])
+ HiveProject(i_item_sk=[$0], i_brand_id=[$7], i_brand=[$8])
+ HiveFilter(condition=[=($20, 1)])
+ HiveTableScan(table=[[default, item]], table:alias=[item])
+
http://git-wip-us.apache.org/repos/asf/hive/blob/b8299551/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query53.q.out
----------------------------------------------------------------------
diff --git a/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query53.q.out b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query53.q.out
new file mode 100644
index 0000000..bac3f77
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query53.q.out
@@ -0,0 +1,83 @@
+PREHOOK: query: explain cbo
+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
+PREHOOK: Input: default@date_dim
+PREHOOK: Input: default@item
+PREHOOK: Input: default@store
+PREHOOK: Input: default@store_sales
+PREHOOK: Output: hdfs://### HDFS PATH ###
+POSTHOOK: query: explain cbo
+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
+POSTHOOK: Input: default@date_dim
+POSTHOOK: Input: default@item
+POSTHOOK: Input: default@store
+POSTHOOK: Input: default@store_sales
+POSTHOOK: Output: hdfs://### HDFS PATH ###
+CBO PLAN:
+HiveSortLimit(sort0=[$2], sort1=[$1], sort2=[$0], dir0=[ASC], dir1=[ASC], dir2=[ASC], fetch=[100])
+ HiveProject((tok_table_or_col i_manufact_id)=[$0], (tok_function sum (tok_table_or_col ss_sales_price))=[$1], avg_window_0=[$2])
+ HiveFilter(condition=[CASE(>($2, 0), >(/(ABS(-($1, $2)), $2), 0.1), null)])
+ HiveProject((tok_table_or_col i_manufact_id)=[$0], (tok_function sum (tok_table_or_col ss_sales_price))=[$2], avg_window_0=[avg($2) OVER (PARTITION BY $0 ORDER BY $0 NULLS FIRST ROWS BETWEEN 2147483647 FOLLOWING AND 2147483647 PRECEDING)])
+ HiveProject(i_manufact_id=[$0], d_qoy=[$1], $f2=[$2])
+ HiveAggregate(group=[{4, 6}], agg#0=[sum($2)])
+ HiveJoin(condition=[=($0, $5)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($1, $3)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$2], ss_sales_price=[$13])
+ HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($7))])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject(i_item_sk=[$0], i_manufact_id=[$13])
+ HiveFilter(condition=[AND(IN($10, _UTF-16LE'personal', _UTF-16LE'portable', _UTF-16LE'reference', _UTF-16LE'self-help', _UTF-16LE'accessories', _UTF-16LE'classical', _UTF-16LE'fragrances', _UTF-16LE'pants'), IN($8, _UTF-16LE'scholaramalgamalg #14', _UTF-16LE'scholaramalgamalg #7', _UTF-16LE'exportiunivamalg #9', _UTF-16LE'scholaramalgamalg #9', _UTF-16LE'amalgimporto #1', _UTF-16LE'edu packscholar #1', _UTF-16LE'exportiimporto #1', _UTF-16LE'importoamalg #1'), IN($12, _UTF-16LE'Books', _UTF-16LE'Children', _UTF-16LE'Electronics', _UTF-16LE'Women', _UTF-16LE'Music', _UTF-16LE'Men'), OR(AND(IN($12, _UTF-16LE'Books', _UTF-16LE'Children', _UTF-16LE'Electronics'), IN($10, _UTF-16LE'personal', _UTF-16LE'portable', _UTF-16LE'reference', _UTF-16LE'self-help'), IN($8, _UTF-16LE'scholaramalgamalg #14', _UTF-16LE'scholaramalgamalg #7', _UTF-16LE'exportiunivamalg #9', _UTF-16LE'scholaramalgamalg #9')), AND(IN($12, _UTF-16LE'Women', _UTF-16LE'Music', _UTF-16LE'Men'), IN($10, _U
TF-16LE'accessories', _UTF-16LE'classical', _UTF-16LE'fragrances', _UTF-16LE'pants'), IN($8, _UTF-16LE'amalgimporto #1', _UTF-16LE'edu packscholar #1', _UTF-16LE'exportiimporto #1', _UTF-16LE'importoamalg #1'))))])
+ HiveTableScan(table=[[default, item]], table:alias=[item])
+ HiveProject(d_date_sk=[$0], d_qoy=[$10])
+ HiveFilter(condition=[IN($3, 1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219, 1220, 1221, 1222, 1223)])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+
http://git-wip-us.apache.org/repos/asf/hive/blob/b8299551/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query54.q.out
----------------------------------------------------------------------
diff --git a/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query54.q.out b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query54.q.out
new file mode 100644
index 0000000..1cf3ce4
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query54.q.out
@@ -0,0 +1,212 @@
+Warning: Shuffle Join MERGEJOIN[270][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3]] in Stage 'Reducer 4' is a cross product
+Warning: Shuffle Join MERGEJOIN[271][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3, $hdt$_4]] in Stage 'Reducer 5' is a cross product
+Warning: Shuffle Join MERGEJOIN[269][tables = [$hdt$_1, $hdt$_2]] in Stage 'Reducer 32' is a cross product
+Warning: Shuffle Join MERGEJOIN[272][tables = [$hdt$_1, $hdt$_2, $hdt$_0]] in Stage 'Reducer 6' is a cross product
+PREHOOK: query: explain cbo
+with my_customers as (
+ select distinct c_customer_sk
+ , c_current_addr_sk
+ from
+ ( select cs_sold_date_sk sold_date_sk,
+ cs_bill_customer_sk customer_sk,
+ cs_item_sk item_sk
+ from catalog_sales
+ union all
+ select ws_sold_date_sk sold_date_sk,
+ ws_bill_customer_sk customer_sk,
+ ws_item_sk item_sk
+ from web_sales
+ ) cs_or_ws_sales,
+ item,
+ date_dim,
+ customer
+ where sold_date_sk = d_date_sk
+ and item_sk = i_item_sk
+ and i_category = 'Jewelry'
+ and i_class = 'consignment'
+ and c_customer_sk = cs_or_ws_sales.customer_sk
+ and d_moy = 3
+ and d_year = 1999
+ )
+ , my_revenue as (
+ select c_customer_sk,
+ sum(ss_ext_sales_price) as revenue
+ from my_customers,
+ store_sales,
+ customer_address,
+ store,
+ date_dim
+ where c_current_addr_sk = ca_address_sk
+ and ca_county = s_county
+ and ca_state = s_state
+ and ss_sold_date_sk = d_date_sk
+ and c_customer_sk = ss_customer_sk
+ and d_month_seq between (select distinct d_month_seq+1
+ from date_dim where d_year = 1999 and d_moy = 3)
+ and (select distinct d_month_seq+3
+ from date_dim where d_year = 1999 and d_moy = 3)
+ group by c_customer_sk
+ )
+ , segments as
+ (select cast((revenue/50) as int) as segment
+ from my_revenue
+ )
+ select segment, count(*) as num_customers, segment*50 as segment_base
+ from segments
+ group by segment
+ order by segment, num_customers
+ limit 100
+PREHOOK: type: QUERY
+PREHOOK: Input: default@catalog_sales
+PREHOOK: Input: default@customer
+PREHOOK: Input: default@customer_address
+PREHOOK: Input: default@date_dim
+PREHOOK: Input: default@item
+PREHOOK: Input: default@store
+PREHOOK: Input: default@store_sales
+PREHOOK: Input: default@web_sales
+PREHOOK: Output: hdfs://### HDFS PATH ###
+POSTHOOK: query: explain cbo
+with my_customers as (
+ select distinct c_customer_sk
+ , c_current_addr_sk
+ from
+ ( select cs_sold_date_sk sold_date_sk,
+ cs_bill_customer_sk customer_sk,
+ cs_item_sk item_sk
+ from catalog_sales
+ union all
+ select ws_sold_date_sk sold_date_sk,
+ ws_bill_customer_sk customer_sk,
+ ws_item_sk item_sk
+ from web_sales
+ ) cs_or_ws_sales,
+ item,
+ date_dim,
+ customer
+ where sold_date_sk = d_date_sk
+ and item_sk = i_item_sk
+ and i_category = 'Jewelry'
+ and i_class = 'consignment'
+ and c_customer_sk = cs_or_ws_sales.customer_sk
+ and d_moy = 3
+ and d_year = 1999
+ )
+ , my_revenue as (
+ select c_customer_sk,
+ sum(ss_ext_sales_price) as revenue
+ from my_customers,
+ store_sales,
+ customer_address,
+ store,
+ date_dim
+ where c_current_addr_sk = ca_address_sk
+ and ca_county = s_county
+ and ca_state = s_state
+ and ss_sold_date_sk = d_date_sk
+ and c_customer_sk = ss_customer_sk
+ and d_month_seq between (select distinct d_month_seq+1
+ from date_dim where d_year = 1999 and d_moy = 3)
+ and (select distinct d_month_seq+3
+ from date_dim where d_year = 1999 and d_moy = 3)
+ group by c_customer_sk
+ )
+ , segments as
+ (select cast((revenue/50) as int) as segment
+ from my_revenue
+ )
+ select segment, count(*) as num_customers, segment*50 as segment_base
+ from segments
+ group by segment
+ order by segment, num_customers
+ limit 100
+POSTHOOK: type: QUERY
+POSTHOOK: Input: default@catalog_sales
+POSTHOOK: Input: default@customer
+POSTHOOK: Input: default@customer_address
+POSTHOOK: Input: default@date_dim
+POSTHOOK: Input: default@item
+POSTHOOK: Input: default@store
+POSTHOOK: Input: default@store_sales
+POSTHOOK: Input: default@web_sales
+POSTHOOK: Output: hdfs://### HDFS PATH ###
+CBO PLAN:
+HiveSortLimit(sort0=[$0], sort1=[$1], dir0=[ASC], dir1=[ASC], fetch=[100])
+ HiveProject(segment=[$0], num_customers=[$1], segment_base=[*($0, 50)])
+ HiveAggregate(group=[{0}], agg#0=[count()])
+ HiveProject(segment=[CAST(/($1, CAST(50):DECIMAL(10, 0))):INTEGER])
+ HiveAggregate(group=[{0}], agg#0=[sum($1)])
+ HiveFilter(condition=[BETWEEN(false, $2, $3, $4)])
+ HiveProject(c_customer_sk=[$0], ss_ext_sales_price=[$4], d_month_seq=[$11], _o__c0=[$13], $f0=[$14])
+ HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject($f0=[$10], $f1=[$11], ss_sold_date_sk=[$0], ss_customer_sk=[$1], ss_ext_sales_price=[$2], ca_address_sk=[$5], ca_county=[$6], ca_state=[$7], s_county=[$8], s_state=[$9], d_date_sk=[$3], d_month_seq=[$4], cnt=[$12], $f00=[$13])
+ HiveJoin(condition=[true], joinType=[left], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($10, $1)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($0, $3)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ss_sold_date_sk=[$0], ss_customer_sk=[$3], ss_ext_sales_price=[$15])
+ HiveFilter(condition=[AND(IS NOT NULL($3), IS NOT NULL($0))])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject(d_date_sk=[$0], d_month_seq=[$3])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(ca_address_sk=[$0], ca_county=[$1], ca_state=[$2], s_county=[$3], s_state=[$4], c_customer_sk=[$5], c_current_addr_sk=[$6])
+ HiveJoin(condition=[=($6, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[AND(=($1, $3), =($2, $4))], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ca_address_sk=[$0], ca_county=[$7], ca_state=[$8])
+ HiveFilter(condition=[AND(IS NOT NULL($7), IS NOT NULL($8))])
+ HiveTableScan(table=[[default, customer_address]], table:alias=[customer_address])
+ HiveProject(s_county=[$23], s_state=[$24])
+ HiveFilter(condition=[AND(IS NOT NULL($23), IS NOT NULL($24))])
+ HiveTableScan(table=[[default, store]], table:alias=[store])
+ HiveProject(c_customer_sk=[$0], c_current_addr_sk=[$1])
+ HiveAggregate(group=[{0, 1}])
+ HiveJoin(condition=[=($0, $3)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(c_customer_sk=[$0], c_current_addr_sk=[$4])
+ HiveFilter(condition=[IS NOT NULL($4)])
+ HiveTableScan(table=[[default, customer]], table:alias=[customer])
+ HiveJoin(condition=[=($2, $4)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($0, $3)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(cs_sold_date_sk=[$0], cs_bill_customer_sk=[$1], cs_item_sk=[$2])
+ HiveUnion(all=[true])
+ HiveProject(cs_sold_date_sk=[$0], cs_bill_customer_sk=[$3], cs_item_sk=[$15])
+ HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($3))])
+ HiveTableScan(table=[[default, catalog_sales]], table:alias=[catalog_sales])
+ HiveProject(sold_date_sk=[$0], customer_sk=[$4], item_sk=[$3])
+ HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($4))])
+ HiveTableScan(table=[[default, web_sales]], table:alias=[web_sales])
+ HiveProject(d_date_sk=[$0])
+ HiveFilter(condition=[AND(=($8, 3), =($6, 1999))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(i_item_sk=[$0])
+ HiveFilter(condition=[AND(=($12, _UTF-16LE'Jewelry'), =($10, _UTF-16LE'consignment'))])
+ HiveTableScan(table=[[default, item]], table:alias=[item])
+ HiveProject(cnt=[$0])
+ HiveFilter(condition=[<=(sq_count_check($0), 1)])
+ HiveProject(cnt=[$0])
+ HiveAggregate(group=[{}], cnt=[COUNT()])
+ HiveProject($f0=[$0])
+ HiveAggregate(group=[{0}])
+ HiveProject($f0=[+($3, 1)])
+ HiveFilter(condition=[AND(=($6, 1999), =($8, 3))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject($f0=[$0])
+ HiveAggregate(group=[{0}])
+ HiveProject($f0=[+($3, 1)])
+ HiveFilter(condition=[AND(=($6, 1999), =($8, 3))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveJoin(condition=[true], joinType=[right], algorithm=[none], cost=[not available])
+ HiveProject($f0=[$0])
+ HiveAggregate(group=[{0}])
+ HiveProject($f0=[+($3, 3)])
+ HiveFilter(condition=[AND(=($6, 1999), =($8, 3))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(cnt=[$0])
+ HiveFilter(condition=[<=(sq_count_check($0), 1)])
+ HiveProject(cnt=[$0])
+ HiveAggregate(group=[{}], cnt=[COUNT()])
+ HiveProject($f0=[$0])
+ HiveAggregate(group=[{0}])
+ HiveProject($f0=[+($3, 3)])
+ HiveFilter(condition=[AND(=($6, 1999), =($8, 3))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+
http://git-wip-us.apache.org/repos/asf/hive/blob/b8299551/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query55.q.out
----------------------------------------------------------------------
diff --git a/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query55.q.out b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query55.q.out
new file mode 100644
index 0000000..6af451c
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query55.q.out
@@ -0,0 +1,51 @@
+PREHOOK: query: explain cbo
+select i_brand_id brand_id, i_brand brand,
+ sum(ss_ext_sales_price) ext_price
+ from date_dim, store_sales, item
+ where d_date_sk = ss_sold_date_sk
+ and ss_item_sk = i_item_sk
+ and i_manager_id=36
+ and d_moy=12
+ and d_year=2001
+ group by i_brand, i_brand_id
+ order by ext_price desc, i_brand_id
+limit 100
+PREHOOK: type: QUERY
+PREHOOK: Input: default@date_dim
+PREHOOK: Input: default@item
+PREHOOK: Input: default@store_sales
+PREHOOK: Output: hdfs://### HDFS PATH ###
+POSTHOOK: query: explain cbo
+select i_brand_id brand_id, i_brand brand,
+ sum(ss_ext_sales_price) ext_price
+ from date_dim, store_sales, item
+ where d_date_sk = ss_sold_date_sk
+ and ss_item_sk = i_item_sk
+ and i_manager_id=36
+ and d_moy=12
+ and d_year=2001
+ group by i_brand, i_brand_id
+ order by ext_price desc, i_brand_id
+limit 100
+POSTHOOK: type: QUERY
+POSTHOOK: Input: default@date_dim
+POSTHOOK: Input: default@item
+POSTHOOK: Input: default@store_sales
+POSTHOOK: Output: hdfs://### HDFS PATH ###
+CBO PLAN:
+HiveProject(brand_id=[$0], brand=[$1], ext_price=[$2])
+ HiveSortLimit(sort0=[$2], sort1=[$3], dir0=[DESC-nulls-last], dir1=[ASC], fetch=[100])
+ HiveProject(brand_id=[$0], brand=[$1], ext_price=[$2], (tok_table_or_col i_brand_id)=[$0])
+ HiveAggregate(group=[{5, 6}], agg#0=[sum($2)])
+ HiveJoin(condition=[=($1, $4)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($3, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$2], ss_ext_sales_price=[$15])
+ HiveFilter(condition=[IS NOT NULL($0)])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject(d_date_sk=[$0])
+ HiveFilter(condition=[AND(=($8, 12), =($6, 2001))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(i_item_sk=[$0], i_brand_id=[$7], i_brand=[$8])
+ HiveFilter(condition=[=($20, 36)])
+ HiveTableScan(table=[[default, item]], table:alias=[item])
+
http://git-wip-us.apache.org/repos/asf/hive/blob/b8299551/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query56.q.out
----------------------------------------------------------------------
diff --git a/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query56.q.out b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query56.q.out
new file mode 100644
index 0000000..a13e599
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query56.q.out
@@ -0,0 +1,221 @@
+PREHOOK: query: explain cbo
+with ss as (
+ select i_item_id,sum(ss_ext_sales_price) total_sales
+ from
+ store_sales,
+ date_dim,
+ customer_address,
+ item
+ where i_item_id in (select
+ i_item_id
+from item
+where i_color in ('orchid','chiffon','lace'))
+ and ss_item_sk = i_item_sk
+ and ss_sold_date_sk = d_date_sk
+ and d_year = 2000
+ and d_moy = 1
+ and ss_addr_sk = ca_address_sk
+ and ca_gmt_offset = -8
+ group by i_item_id),
+ cs as (
+ select i_item_id,sum(cs_ext_sales_price) total_sales
+ from
+ catalog_sales,
+ date_dim,
+ customer_address,
+ item
+ where
+ i_item_id in (select
+ i_item_id
+from item
+where i_color in ('orchid','chiffon','lace'))
+ and cs_item_sk = i_item_sk
+ and cs_sold_date_sk = d_date_sk
+ and d_year = 2000
+ and d_moy = 1
+ and cs_bill_addr_sk = ca_address_sk
+ and ca_gmt_offset = -8
+ group by i_item_id),
+ ws as (
+ select i_item_id,sum(ws_ext_sales_price) total_sales
+ from
+ web_sales,
+ date_dim,
+ customer_address,
+ item
+ where
+ i_item_id in (select
+ i_item_id
+from item
+where i_color in ('orchid','chiffon','lace'))
+ and ws_item_sk = i_item_sk
+ and ws_sold_date_sk = d_date_sk
+ and d_year = 2000
+ and d_moy = 1
+ and ws_bill_addr_sk = ca_address_sk
+ and ca_gmt_offset = -8
+ group by i_item_id)
+ select i_item_id ,sum(total_sales) total_sales
+ from (select * from ss
+ union all
+ select * from cs
+ union all
+ select * from ws) tmp1
+ group by i_item_id
+ order by total_sales
+ limit 100
+PREHOOK: type: QUERY
+PREHOOK: Input: default@catalog_sales
+PREHOOK: Input: default@customer_address
+PREHOOK: Input: default@date_dim
+PREHOOK: Input: default@item
+PREHOOK: Input: default@store_sales
+PREHOOK: Input: default@web_sales
+PREHOOK: Output: hdfs://### HDFS PATH ###
+POSTHOOK: query: explain cbo
+with ss as (
+ select i_item_id,sum(ss_ext_sales_price) total_sales
+ from
+ store_sales,
+ date_dim,
+ customer_address,
+ item
+ where i_item_id in (select
+ i_item_id
+from item
+where i_color in ('orchid','chiffon','lace'))
+ and ss_item_sk = i_item_sk
+ and ss_sold_date_sk = d_date_sk
+ and d_year = 2000
+ and d_moy = 1
+ and ss_addr_sk = ca_address_sk
+ and ca_gmt_offset = -8
+ group by i_item_id),
+ cs as (
+ select i_item_id,sum(cs_ext_sales_price) total_sales
+ from
+ catalog_sales,
+ date_dim,
+ customer_address,
+ item
+ where
+ i_item_id in (select
+ i_item_id
+from item
+where i_color in ('orchid','chiffon','lace'))
+ and cs_item_sk = i_item_sk
+ and cs_sold_date_sk = d_date_sk
+ and d_year = 2000
+ and d_moy = 1
+ and cs_bill_addr_sk = ca_address_sk
+ and ca_gmt_offset = -8
+ group by i_item_id),
+ ws as (
+ select i_item_id,sum(ws_ext_sales_price) total_sales
+ from
+ web_sales,
+ date_dim,
+ customer_address,
+ item
+ where
+ i_item_id in (select
+ i_item_id
+from item
+where i_color in ('orchid','chiffon','lace'))
+ and ws_item_sk = i_item_sk
+ and ws_sold_date_sk = d_date_sk
+ and d_year = 2000
+ and d_moy = 1
+ and ws_bill_addr_sk = ca_address_sk
+ and ca_gmt_offset = -8
+ group by i_item_id)
+ select i_item_id ,sum(total_sales) total_sales
+ from (select * from ss
+ union all
+ select * from cs
+ union all
+ select * from ws) tmp1
+ group by i_item_id
+ order by total_sales
+ limit 100
+POSTHOOK: type: QUERY
+POSTHOOK: Input: default@catalog_sales
+POSTHOOK: Input: default@customer_address
+POSTHOOK: Input: default@date_dim
+POSTHOOK: Input: default@item
+POSTHOOK: Input: default@store_sales
+POSTHOOK: Input: default@web_sales
+POSTHOOK: Output: hdfs://### HDFS PATH ###
+CBO PLAN:
+HiveSortLimit(sort0=[$1], dir0=[ASC], fetch=[100])
+ HiveProject(i_item_id=[$0], $f1=[$1])
+ HiveAggregate(group=[{0}], agg#0=[sum($1)])
+ HiveProject(i_item_id=[$0], $f1=[$1])
+ HiveUnion(all=[true])
+ HiveProject(i_item_id=[$0], $f1=[$1])
+ HiveAggregate(group=[{1}], agg#0=[sum($7)])
+ HiveJoin(condition=[=($5, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($1, $2)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(i_item_sk=[$0], i_item_id=[$1])
+ HiveTableScan(table=[[default, item]], table:alias=[item])
+ HiveProject(i_item_id=[$0])
+ HiveAggregate(group=[{1}])
+ HiveFilter(condition=[IN($17, _UTF-16LE'orchid', _UTF-16LE'chiffon', _UTF-16LE'lace')])
+ HiveTableScan(table=[[default, item]], table:alias=[item])
+ HiveProject(ca_address_sk=[$0], ss_sold_date_sk=[$1], ss_item_sk=[$2], ss_addr_sk=[$3], ss_ext_sales_price=[$4], d_date_sk=[$5])
+ HiveJoin(condition=[=($3, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ca_address_sk=[$0])
+ HiveFilter(condition=[=($11, -8)])
+ HiveTableScan(table=[[default, customer_address]], table:alias=[customer_address])
+ HiveJoin(condition=[=($0, $4)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$2], ss_addr_sk=[$6], ss_ext_sales_price=[$15])
+ HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($6))])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject(d_date_sk=[$0])
+ HiveFilter(condition=[AND(=($6, 2000), =($8, 1))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(i_item_id=[$0], $f1=[$1])
+ HiveAggregate(group=[{1}], agg#0=[sum($7)])
+ HiveJoin(condition=[=($6, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($1, $2)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(i_item_sk=[$0], i_item_id=[$1])
+ HiveTableScan(table=[[default, item]], table:alias=[item])
+ HiveProject(i_item_id=[$0])
+ HiveAggregate(group=[{1}])
+ HiveFilter(condition=[IN($17, _UTF-16LE'orchid', _UTF-16LE'chiffon', _UTF-16LE'lace')])
+ HiveTableScan(table=[[default, item]], table:alias=[item])
+ HiveProject(ca_address_sk=[$0], cs_sold_date_sk=[$1], cs_bill_addr_sk=[$2], cs_item_sk=[$3], cs_ext_sales_price=[$4], d_date_sk=[$5])
+ HiveJoin(condition=[=($2, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ca_address_sk=[$0])
+ HiveFilter(condition=[=($11, -8)])
+ HiveTableScan(table=[[default, customer_address]], table:alias=[customer_address])
+ HiveJoin(condition=[=($0, $4)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(cs_sold_date_sk=[$0], cs_bill_addr_sk=[$6], cs_item_sk=[$15], cs_ext_sales_price=[$23])
+ HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($6))])
+ HiveTableScan(table=[[default, catalog_sales]], table:alias=[catalog_sales])
+ HiveProject(d_date_sk=[$0])
+ HiveFilter(condition=[AND(=($6, 2000), =($8, 1))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(i_item_id=[$0], $f1=[$1])
+ HiveAggregate(group=[{1}], agg#0=[sum($7)])
+ HiveJoin(condition=[=($5, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($1, $2)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(i_item_sk=[$0], i_item_id=[$1])
+ HiveTableScan(table=[[default, item]], table:alias=[item])
+ HiveProject(i_item_id=[$0])
+ HiveAggregate(group=[{1}])
+ HiveFilter(condition=[IN($17, _UTF-16LE'orchid', _UTF-16LE'chiffon', _UTF-16LE'lace')])
+ HiveTableScan(table=[[default, item]], table:alias=[item])
+ HiveProject(ca_address_sk=[$0], ws_sold_date_sk=[$1], ws_item_sk=[$2], ws_bill_addr_sk=[$3], ws_ext_sales_price=[$4], d_date_sk=[$5])
+ HiveJoin(condition=[=($3, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ca_address_sk=[$0])
+ HiveFilter(condition=[=($11, -8)])
+ HiveTableScan(table=[[default, customer_address]], table:alias=[customer_address])
+ HiveJoin(condition=[=($0, $4)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ws_sold_date_sk=[$0], ws_item_sk=[$3], ws_bill_addr_sk=[$7], ws_ext_sales_price=[$23])
+ HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($7))])
+ HiveTableScan(table=[[default, web_sales]], table:alias=[web_sales])
+ HiveProject(d_date_sk=[$0])
+ HiveFilter(condition=[AND(=($6, 2000), =($8, 1))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+
http://git-wip-us.apache.org/repos/asf/hive/blob/b8299551/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query57.q.out
----------------------------------------------------------------------
diff --git a/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query57.q.out b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query57.q.out
new file mode 100644
index 0000000..440a4e9
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query57.q.out
@@ -0,0 +1,171 @@
+PREHOOK: query: explain cbo
+with v1 as(
+ select i_category, i_brand,
+ cc_name,
+ d_year, d_moy,
+ sum(cs_sales_price) sum_sales,
+ avg(sum(cs_sales_price)) over
+ (partition by i_category, i_brand,
+ cc_name, d_year)
+ avg_monthly_sales,
+ rank() over
+ (partition by i_category, i_brand,
+ cc_name
+ order by d_year, d_moy) rn
+ from item, catalog_sales, date_dim, call_center
+ where cs_item_sk = i_item_sk and
+ cs_sold_date_sk = d_date_sk and
+ cc_call_center_sk= cs_call_center_sk and
+ (
+ d_year = 2000 or
+ ( d_year = 2000-1 and d_moy =12) or
+ ( d_year = 2000+1 and d_moy =1)
+ )
+ group by i_category, i_brand,
+ cc_name , d_year, d_moy),
+ v2 as(
+ select v1.i_category, v1.i_brand
+ ,v1.d_year, v1.d_moy
+ ,v1.avg_monthly_sales
+ ,v1.sum_sales, v1_lag.sum_sales psum, v1_lead.sum_sales nsum
+ from v1, v1 v1_lag, v1 v1_lead
+ where v1.i_category = v1_lag.i_category and
+ v1.i_category = v1_lead.i_category and
+ v1.i_brand = v1_lag.i_brand and
+ v1.i_brand = v1_lead.i_brand and
+ v1. cc_name = v1_lag. cc_name and
+ v1. cc_name = v1_lead. cc_name and
+ v1.rn = v1_lag.rn + 1 and
+ v1.rn = v1_lead.rn - 1)
+ select *
+ from v2
+ where d_year = 2000 and
+ avg_monthly_sales > 0 and
+ case when avg_monthly_sales > 0 then abs(sum_sales - avg_monthly_sales) / avg_monthly_sales else null end > 0.1
+ order by sum_sales - avg_monthly_sales, 3
+ limit 100
+PREHOOK: type: QUERY
+PREHOOK: Input: default@call_center
+PREHOOK: Input: default@catalog_sales
+PREHOOK: Input: default@date_dim
+PREHOOK: Input: default@item
+PREHOOK: Output: hdfs://### HDFS PATH ###
+POSTHOOK: query: explain cbo
+with v1 as(
+ select i_category, i_brand,
+ cc_name,
+ d_year, d_moy,
+ sum(cs_sales_price) sum_sales,
+ avg(sum(cs_sales_price)) over
+ (partition by i_category, i_brand,
+ cc_name, d_year)
+ avg_monthly_sales,
+ rank() over
+ (partition by i_category, i_brand,
+ cc_name
+ order by d_year, d_moy) rn
+ from item, catalog_sales, date_dim, call_center
+ where cs_item_sk = i_item_sk and
+ cs_sold_date_sk = d_date_sk and
+ cc_call_center_sk= cs_call_center_sk and
+ (
+ d_year = 2000 or
+ ( d_year = 2000-1 and d_moy =12) or
+ ( d_year = 2000+1 and d_moy =1)
+ )
+ group by i_category, i_brand,
+ cc_name , d_year, d_moy),
+ v2 as(
+ select v1.i_category, v1.i_brand
+ ,v1.d_year, v1.d_moy
+ ,v1.avg_monthly_sales
+ ,v1.sum_sales, v1_lag.sum_sales psum, v1_lead.sum_sales nsum
+ from v1, v1 v1_lag, v1 v1_lead
+ where v1.i_category = v1_lag.i_category and
+ v1.i_category = v1_lead.i_category and
+ v1.i_brand = v1_lag.i_brand and
+ v1.i_brand = v1_lead.i_brand and
+ v1. cc_name = v1_lag. cc_name and
+ v1. cc_name = v1_lead. cc_name and
+ v1.rn = v1_lag.rn + 1 and
+ v1.rn = v1_lead.rn - 1)
+ select *
+ from v2
+ where d_year = 2000 and
+ avg_monthly_sales > 0 and
+ case when avg_monthly_sales > 0 then abs(sum_sales - avg_monthly_sales) / avg_monthly_sales else null end > 0.1
+ order by sum_sales - avg_monthly_sales, 3
+ limit 100
+POSTHOOK: type: QUERY
+POSTHOOK: Input: default@call_center
+POSTHOOK: Input: default@catalog_sales
+POSTHOOK: Input: default@date_dim
+POSTHOOK: Input: default@item
+POSTHOOK: Output: hdfs://### HDFS PATH ###
+CBO PLAN:
+HiveProject(i_category=[$0], i_brand=[$1], d_year=[$2], d_moy=[$3], avg_monthly_sales=[$4], sum_sales=[$5], psum=[$6], nsum=[$7])
+ HiveSortLimit(sort0=[$8], sort1=[$2], dir0=[ASC], dir1=[ASC], fetch=[100])
+ HiveProject(i_category=[$10], i_brand=[$11], d_year=[$13], d_moy=[$14], avg_monthly_sales=[$16], sum_sales=[$15], psum=[$8], nsum=[$3], (- (tok_table_or_col sum_sales) (tok_table_or_col avg_monthly_sales))=[-($15, $16)])
+ HiveJoin(condition=[AND(AND(AND(=($10, $0), =($11, $1)), =($12, $2)), =($17, $4))], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject((tok_table_or_col i_category)=[$0], (tok_table_or_col i_brand)=[$1], (tok_table_or_col cc_name)=[$2], (tok_function sum (tok_table_or_col cs_sales_price))=[$3], -=[-($4, 1)])
+ HiveFilter(condition=[IS NOT NULL($4)])
+ HiveProject((tok_table_or_col i_category)=[$1], (tok_table_or_col i_brand)=[$0], (tok_table_or_col cc_name)=[$4], (tok_function sum (tok_table_or_col cs_sales_price))=[$5], rank_window_1=[rank() OVER (PARTITION BY $1, $0, $4 ORDER BY $2 NULLS LAST, $3 NULLS LAST ROWS BETWEEN 2147483647 FOLLOWING AND 2147483647 PRECEDING)])
+ HiveProject(i_brand=[$0], i_category=[$1], d_year=[$2], d_moy=[$3], cc_name=[$4], $f5=[$5])
+ HiveAggregate(group=[{1, 2, 8, 9, 11}], agg#0=[sum($6)])
+ HiveJoin(condition=[=($5, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(i_item_sk=[$0], i_brand=[$8], i_category=[$12])
+ HiveFilter(condition=[AND(IS NOT NULL($12), IS NOT NULL($8))])
+ HiveTableScan(table=[[default, item]], table:alias=[item])
+ HiveJoin(condition=[=($7, $1)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($0, $4)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(cs_sold_date_sk=[$0], cs_call_center_sk=[$11], cs_item_sk=[$15], cs_sales_price=[$21])
+ HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($11))])
+ HiveTableScan(table=[[default, catalog_sales]], table:alias=[catalog_sales])
+ HiveProject(d_date_sk=[$0], d_year=[$6], d_moy=[$8])
+ HiveFilter(condition=[AND(IN($6, 2000, 1999, 2001), OR(=($6, 2000), IN(ROW($6, $8), ROW(1999, 12), ROW(2001, 1))))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(cc_call_center_sk=[$0], cc_name=[$6])
+ HiveFilter(condition=[IS NOT NULL($6)])
+ HiveTableScan(table=[[default, call_center]], table:alias=[call_center])
+ HiveJoin(condition=[AND(AND(AND(=($5, $0), =($6, $1)), =($7, $2)), =($12, $4))], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject((tok_table_or_col i_category)=[$0], (tok_table_or_col i_brand)=[$1], (tok_table_or_col cc_name)=[$2], (tok_function sum (tok_table_or_col cs_sales_price))=[$3], +=[+($4, 1)])
+ HiveFilter(condition=[IS NOT NULL($4)])
+ HiveProject((tok_table_or_col i_category)=[$1], (tok_table_or_col i_brand)=[$0], (tok_table_or_col cc_name)=[$4], (tok_function sum (tok_table_or_col cs_sales_price))=[$5], rank_window_1=[rank() OVER (PARTITION BY $1, $0, $4 ORDER BY $2 NULLS LAST, $3 NULLS LAST ROWS BETWEEN 2147483647 FOLLOWING AND 2147483647 PRECEDING)])
+ HiveProject(i_brand=[$0], i_category=[$1], d_year=[$2], d_moy=[$3], cc_name=[$4], $f5=[$5])
+ HiveAggregate(group=[{1, 2, 8, 9, 11}], agg#0=[sum($6)])
+ HiveJoin(condition=[=($5, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(i_item_sk=[$0], i_brand=[$8], i_category=[$12])
+ HiveFilter(condition=[AND(IS NOT NULL($12), IS NOT NULL($8))])
+ HiveTableScan(table=[[default, item]], table:alias=[item])
+ HiveJoin(condition=[=($7, $1)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($0, $4)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(cs_sold_date_sk=[$0], cs_call_center_sk=[$11], cs_item_sk=[$15], cs_sales_price=[$21])
+ HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($11))])
+ HiveTableScan(table=[[default, catalog_sales]], table:alias=[catalog_sales])
+ HiveProject(d_date_sk=[$0], d_year=[$6], d_moy=[$8])
+ HiveFilter(condition=[AND(IN($6, 2000, 1999, 2001), OR(=($6, 2000), IN(ROW($6, $8), ROW(1999, 12), ROW(2001, 1))))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(cc_call_center_sk=[$0], cc_name=[$6])
+ HiveFilter(condition=[IS NOT NULL($6)])
+ HiveTableScan(table=[[default, call_center]], table:alias=[call_center])
+ HiveProject((tok_table_or_col i_category)=[$0], (tok_table_or_col i_brand)=[$1], (tok_table_or_col cc_name)=[$2], (tok_table_or_col d_year)=[$3], (tok_table_or_col d_moy)=[$4], (tok_function sum (tok_table_or_col cs_sales_price))=[$5], avg_window_0=[$6], rank_window_1=[$7])
+ HiveFilter(condition=[AND(=($3, 2000), >($6, 0), CASE(>($6, 0), >(/(ABS(-($5, $6)), $6), 0.1), null), IS NOT NULL($7))])
+ HiveProject((tok_table_or_col i_category)=[$1], (tok_table_or_col i_brand)=[$0], (tok_table_or_col cc_name)=[$4], (tok_table_or_col d_year)=[$2], (tok_table_or_col d_moy)=[$3], (tok_function sum (tok_table_or_col cs_sales_price))=[$5], avg_window_0=[avg($5) OVER (PARTITION BY $1, $0, $4, $2 ORDER BY $1 NULLS FIRST, $0 NULLS FIRST, $4 NULLS FIRST, $2 NULLS FIRST ROWS BETWEEN 2147483647 FOLLOWING AND 2147483647 PRECEDING)], rank_window_1=[rank() OVER (PARTITION BY $1, $0, $4 ORDER BY $2 NULLS LAST, $3 NULLS LAST ROWS BETWEEN 2147483647 FOLLOWING AND 2147483647 PRECEDING)])
+ HiveProject(i_brand=[$0], i_category=[$1], d_year=[$2], d_moy=[$3], cc_name=[$4], $f5=[$5])
+ HiveAggregate(group=[{1, 2, 8, 9, 11}], agg#0=[sum($6)])
+ HiveJoin(condition=[=($5, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(i_item_sk=[$0], i_brand=[$8], i_category=[$12])
+ HiveFilter(condition=[AND(IS NOT NULL($12), IS NOT NULL($8))])
+ HiveTableScan(table=[[default, item]], table:alias=[item])
+ HiveJoin(condition=[=($7, $1)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($0, $4)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(cs_sold_date_sk=[$0], cs_call_center_sk=[$11], cs_item_sk=[$15], cs_sales_price=[$21])
+ HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($11))])
+ HiveTableScan(table=[[default, catalog_sales]], table:alias=[catalog_sales])
+ HiveProject(d_date_sk=[$0], d_year=[$6], d_moy=[$8])
+ HiveFilter(condition=[AND(IN($6, 2000, 1999, 2001), OR(=($6, 2000), IN(ROW($6, $8), ROW(1999, 12), ROW(2001, 1))))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(cc_call_center_sk=[$0], cc_name=[$6])
+ HiveFilter(condition=[IS NOT NULL($6)])
+ HiveTableScan(table=[[default, call_center]], table:alias=[call_center])
+
http://git-wip-us.apache.org/repos/asf/hive/blob/b8299551/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query58.q.out
----------------------------------------------------------------------
diff --git a/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query58.q.out b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query58.q.out
new file mode 100644
index 0000000..df67f6f
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query58.q.out
@@ -0,0 +1,237 @@
+Warning: Shuffle Join MERGEJOIN[401][tables = [$hdt$_4, $hdt$_5]] in Stage 'Reducer 22' is a cross product
+PREHOOK: query: explain cbo
+with ss_items as
+ (select i_item_id item_id
+ ,sum(ss_ext_sales_price) ss_item_rev
+ from store_sales
+ ,item
+ ,date_dim
+ where ss_item_sk = i_item_sk
+ and d_date in (select d_date
+ from date_dim
+ where d_week_seq = (select d_week_seq
+ from date_dim
+ where d_date = '1998-02-19'))
+ and ss_sold_date_sk = d_date_sk
+ group by i_item_id),
+ cs_items as
+ (select i_item_id item_id
+ ,sum(cs_ext_sales_price) cs_item_rev
+ from catalog_sales
+ ,item
+ ,date_dim
+ where cs_item_sk = i_item_sk
+ and d_date in (select d_date
+ from date_dim
+ where d_week_seq = (select d_week_seq
+ from date_dim
+ where d_date = '1998-02-19'))
+ and cs_sold_date_sk = d_date_sk
+ group by i_item_id),
+ ws_items as
+ (select i_item_id item_id
+ ,sum(ws_ext_sales_price) ws_item_rev
+ from web_sales
+ ,item
+ ,date_dim
+ where ws_item_sk = i_item_sk
+ and d_date in (select d_date
+ from date_dim
+ where d_week_seq =(select d_week_seq
+ from date_dim
+ where d_date = '1998-02-19'))
+ and ws_sold_date_sk = d_date_sk
+ group by i_item_id)
+ select ss_items.item_id
+ ,ss_item_rev
+ ,ss_item_rev/(ss_item_rev+cs_item_rev+ws_item_rev)/3 * 100 ss_dev
+ ,cs_item_rev
+ ,cs_item_rev/(ss_item_rev+cs_item_rev+ws_item_rev)/3 * 100 cs_dev
+ ,ws_item_rev
+ ,ws_item_rev/(ss_item_rev+cs_item_rev+ws_item_rev)/3 * 100 ws_dev
+ ,(ss_item_rev+cs_item_rev+ws_item_rev)/3 average
+ from ss_items,cs_items,ws_items
+ where ss_items.item_id=cs_items.item_id
+ and ss_items.item_id=ws_items.item_id
+ and ss_item_rev between 0.9 * cs_item_rev and 1.1 * cs_item_rev
+ and ss_item_rev between 0.9 * ws_item_rev and 1.1 * ws_item_rev
+ and cs_item_rev between 0.9 * ss_item_rev and 1.1 * ss_item_rev
+ and cs_item_rev between 0.9 * ws_item_rev and 1.1 * ws_item_rev
+ and ws_item_rev between 0.9 * ss_item_rev and 1.1 * ss_item_rev
+ and ws_item_rev between 0.9 * cs_item_rev and 1.1 * cs_item_rev
+ order by item_id
+ ,ss_item_rev
+ limit 100
+PREHOOK: type: QUERY
+PREHOOK: Input: default@catalog_sales
+PREHOOK: Input: default@date_dim
+PREHOOK: Input: default@item
+PREHOOK: Input: default@store_sales
+PREHOOK: Input: default@web_sales
+PREHOOK: Output: hdfs://### HDFS PATH ###
+POSTHOOK: query: explain cbo
+with ss_items as
+ (select i_item_id item_id
+ ,sum(ss_ext_sales_price) ss_item_rev
+ from store_sales
+ ,item
+ ,date_dim
+ where ss_item_sk = i_item_sk
+ and d_date in (select d_date
+ from date_dim
+ where d_week_seq = (select d_week_seq
+ from date_dim
+ where d_date = '1998-02-19'))
+ and ss_sold_date_sk = d_date_sk
+ group by i_item_id),
+ cs_items as
+ (select i_item_id item_id
+ ,sum(cs_ext_sales_price) cs_item_rev
+ from catalog_sales
+ ,item
+ ,date_dim
+ where cs_item_sk = i_item_sk
+ and d_date in (select d_date
+ from date_dim
+ where d_week_seq = (select d_week_seq
+ from date_dim
+ where d_date = '1998-02-19'))
+ and cs_sold_date_sk = d_date_sk
+ group by i_item_id),
+ ws_items as
+ (select i_item_id item_id
+ ,sum(ws_ext_sales_price) ws_item_rev
+ from web_sales
+ ,item
+ ,date_dim
+ where ws_item_sk = i_item_sk
+ and d_date in (select d_date
+ from date_dim
+ where d_week_seq =(select d_week_seq
+ from date_dim
+ where d_date = '1998-02-19'))
+ and ws_sold_date_sk = d_date_sk
+ group by i_item_id)
+ select ss_items.item_id
+ ,ss_item_rev
+ ,ss_item_rev/(ss_item_rev+cs_item_rev+ws_item_rev)/3 * 100 ss_dev
+ ,cs_item_rev
+ ,cs_item_rev/(ss_item_rev+cs_item_rev+ws_item_rev)/3 * 100 cs_dev
+ ,ws_item_rev
+ ,ws_item_rev/(ss_item_rev+cs_item_rev+ws_item_rev)/3 * 100 ws_dev
+ ,(ss_item_rev+cs_item_rev+ws_item_rev)/3 average
+ from ss_items,cs_items,ws_items
+ where ss_items.item_id=cs_items.item_id
+ and ss_items.item_id=ws_items.item_id
+ and ss_item_rev between 0.9 * cs_item_rev and 1.1 * cs_item_rev
+ and ss_item_rev between 0.9 * ws_item_rev and 1.1 * ws_item_rev
+ and cs_item_rev between 0.9 * ss_item_rev and 1.1 * ss_item_rev
+ and cs_item_rev between 0.9 * ws_item_rev and 1.1 * ws_item_rev
+ and ws_item_rev between 0.9 * ss_item_rev and 1.1 * ss_item_rev
+ and ws_item_rev between 0.9 * cs_item_rev and 1.1 * cs_item_rev
+ order by item_id
+ ,ss_item_rev
+ limit 100
+POSTHOOK: type: QUERY
+POSTHOOK: Input: default@catalog_sales
+POSTHOOK: Input: default@date_dim
+POSTHOOK: Input: default@item
+POSTHOOK: Input: default@store_sales
+POSTHOOK: Input: default@web_sales
+POSTHOOK: Output: hdfs://### HDFS PATH ###
+CBO PLAN:
+HiveSortLimit(sort0=[$0], sort1=[$1], dir0=[ASC], dir1=[ASC], fetch=[100])
+ HiveProject(item_id=[$0], ss_item_rev=[$5], ss_dev=[*(/(/($5, +(+($5, $1), $9)), CAST(3):DECIMAL(10, 0)), CAST(100):DECIMAL(10, 0))], cs_item_rev=[$1], cs_dev=[*(/(/($1, +(+($5, $1), $9)), CAST(3):DECIMAL(10, 0)), CAST(100):DECIMAL(10, 0))], ws_item_rev=[$9], ws_dev=[*(/(/($9, +(+($5, $1), $9)), CAST(3):DECIMAL(10, 0)), CAST(100):DECIMAL(10, 0))], average=[/(+(+($5, $1), $9), CAST(3):DECIMAL(10, 0))])
+ HiveJoin(condition=[AND(AND(AND(AND(=($0, $8), BETWEEN(false, $5, $10, $11)), BETWEEN(false, $1, $10, $11)), BETWEEN(false, $9, $6, $7)), BETWEEN(false, $9, $2, $3))], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[AND(AND(=($4, $0), BETWEEN(false, $5, $2, $3)), BETWEEN(false, $1, $6, $7))], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(item_id=[$0], cs_item_rev=[$1], *=[*(0.9, $1)], *3=[*(1.1, $1)])
+ HiveAggregate(group=[{4}], agg#0=[sum($2)])
+ HiveJoin(condition=[=($0, $5)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($1, $3)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(cs_sold_date_sk=[$0], cs_item_sk=[$15], cs_ext_sales_price=[$23])
+ HiveFilter(condition=[IS NOT NULL($0)])
+ HiveTableScan(table=[[default, catalog_sales]], table:alias=[catalog_sales])
+ HiveProject(i_item_sk=[$0], i_item_id=[$1])
+ HiveTableScan(table=[[default, item]], table:alias=[item])
+ HiveProject(d_date_sk=[$0], d_date=[$1], d_date0=[$2])
+ HiveJoin(condition=[=($1, $2)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(d_date_sk=[$0], d_date=[$2])
+ HiveFilter(condition=[IS NOT NULL($2)])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(d_date=[$0])
+ HiveAggregate(group=[{0}])
+ HiveJoin(condition=[=($1, $3)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(d_date=[$2], d_week_seq=[$4])
+ HiveFilter(condition=[AND(IS NOT NULL($4), IS NOT NULL($2))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(cnt=[$0])
+ HiveFilter(condition=[<=(sq_count_check($0), 1)])
+ HiveProject(cnt=[$0])
+ HiveAggregate(group=[{}], cnt=[COUNT()])
+ HiveFilter(condition=[=($2, _UTF-16LE'1998-02-19')])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(d_week_seq=[$4])
+ HiveFilter(condition=[AND(=($2, _UTF-16LE'1998-02-19'), IS NOT NULL($4))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(item_id=[$0], ss_item_rev=[$1], *=[*(0.9, $1)], *3=[*(1.1, $1)])
+ HiveAggregate(group=[{4}], agg#0=[sum($2)])
+ HiveJoin(condition=[=($0, $5)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($1, $3)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$2], ss_ext_sales_price=[$15])
+ HiveFilter(condition=[IS NOT NULL($0)])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject(i_item_sk=[$0], i_item_id=[$1])
+ HiveTableScan(table=[[default, item]], table:alias=[item])
+ HiveProject(d_date_sk=[$0], d_date=[$1], d_date0=[$2])
+ HiveJoin(condition=[=($1, $2)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(d_date_sk=[$0], d_date=[$2])
+ HiveFilter(condition=[IS NOT NULL($2)])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(d_date=[$0])
+ HiveAggregate(group=[{0}])
+ HiveJoin(condition=[=($1, $3)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(d_date=[$2], d_week_seq=[$4])
+ HiveFilter(condition=[AND(IS NOT NULL($4), IS NOT NULL($2))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(cnt=[$0])
+ HiveFilter(condition=[<=(sq_count_check($0), 1)])
+ HiveProject(cnt=[$0])
+ HiveAggregate(group=[{}], cnt=[COUNT()])
+ HiveFilter(condition=[=($2, _UTF-16LE'1998-02-19')])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(d_week_seq=[$4])
+ HiveFilter(condition=[AND(=($2, _UTF-16LE'1998-02-19'), IS NOT NULL($4))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(item_id=[$0], ws_item_rev=[$1], *=[*(0.9, $1)], *3=[*(1.1, $1)])
+ HiveAggregate(group=[{4}], agg#0=[sum($2)])
+ HiveJoin(condition=[=($0, $5)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($1, $3)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ws_sold_date_sk=[$0], ws_item_sk=[$3], ws_ext_sales_price=[$23])
+ HiveFilter(condition=[IS NOT NULL($0)])
+ HiveTableScan(table=[[default, web_sales]], table:alias=[web_sales])
+ HiveProject(i_item_sk=[$0], i_item_id=[$1])
+ HiveTableScan(table=[[default, item]], table:alias=[item])
+ HiveProject(d_date_sk=[$0], d_date=[$1], d_date0=[$2])
+ HiveJoin(condition=[=($1, $2)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(d_date_sk=[$0], d_date=[$2])
+ HiveFilter(condition=[IS NOT NULL($2)])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(d_date=[$0])
+ HiveAggregate(group=[{0}])
+ HiveJoin(condition=[=($1, $3)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(d_date=[$2], d_week_seq=[$4])
+ HiveFilter(condition=[AND(IS NOT NULL($4), IS NOT NULL($2))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(cnt=[$0])
+ HiveFilter(condition=[<=(sq_count_check($0), 1)])
+ HiveProject(cnt=[$0])
+ HiveAggregate(group=[{}], cnt=[COUNT()])
+ HiveFilter(condition=[=($2, _UTF-16LE'1998-02-19')])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(d_week_seq=[$4])
+ HiveFilter(condition=[AND(=($2, _UTF-16LE'1998-02-19'), IS NOT NULL($4))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+
http://git-wip-us.apache.org/repos/asf/hive/blob/b8299551/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query59.q.out
----------------------------------------------------------------------
diff --git a/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query59.q.out b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query59.q.out
new file mode 100644
index 0000000..989bd78
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query59.q.out
@@ -0,0 +1,134 @@
+PREHOOK: query: explain cbo
+with wss as
+ (select d_week_seq,
+ ss_store_sk,
+ sum(case when (d_day_name='Sunday') then ss_sales_price else null end) sun_sales,
+ sum(case when (d_day_name='Monday') then ss_sales_price else null end) mon_sales,
+ sum(case when (d_day_name='Tuesday') then ss_sales_price else null end) tue_sales,
+ sum(case when (d_day_name='Wednesday') then ss_sales_price else null end) wed_sales,
+ sum(case when (d_day_name='Thursday') then ss_sales_price else null end) thu_sales,
+ sum(case when (d_day_name='Friday') then ss_sales_price else null end) fri_sales,
+ sum(case when (d_day_name='Saturday') then ss_sales_price else null end) sat_sales
+ from store_sales,date_dim
+ where d_date_sk = ss_sold_date_sk
+ group by d_week_seq,ss_store_sk
+ )
+ select s_store_name1,s_store_id1,d_week_seq1
+ ,sun_sales1/sun_sales2,mon_sales1/mon_sales2
+ ,tue_sales1/tue_sales1,wed_sales1/wed_sales2,thu_sales1/thu_sales2
+ ,fri_sales1/fri_sales2,sat_sales1/sat_sales2
+ from
+ (select s_store_name s_store_name1,wss.d_week_seq d_week_seq1
+ ,s_store_id s_store_id1,sun_sales sun_sales1
+ ,mon_sales mon_sales1,tue_sales tue_sales1
+ ,wed_sales wed_sales1,thu_sales thu_sales1
+ ,fri_sales fri_sales1,sat_sales sat_sales1
+ from wss,store,date_dim d
+ where d.d_week_seq = wss.d_week_seq and
+ ss_store_sk = s_store_sk and
+ d_month_seq between 1185 and 1185 + 11) y,
+ (select s_store_name s_store_name2,wss.d_week_seq d_week_seq2
+ ,s_store_id s_store_id2,sun_sales sun_sales2
+ ,mon_sales mon_sales2,tue_sales tue_sales2
+ ,wed_sales wed_sales2,thu_sales thu_sales2
+ ,fri_sales fri_sales2,sat_sales sat_sales2
+ from wss,store,date_dim d
+ where d.d_week_seq = wss.d_week_seq and
+ ss_store_sk = s_store_sk and
+ d_month_seq between 1185+ 12 and 1185 + 23) x
+ where s_store_id1=s_store_id2
+ and d_week_seq1=d_week_seq2-52
+ order by s_store_name1,s_store_id1,d_week_seq1
+limit 100
+PREHOOK: type: QUERY
+PREHOOK: Input: default@date_dim
+PREHOOK: Input: default@store
+PREHOOK: Input: default@store_sales
+PREHOOK: Output: hdfs://### HDFS PATH ###
+POSTHOOK: query: explain cbo
+with wss as
+ (select d_week_seq,
+ ss_store_sk,
+ sum(case when (d_day_name='Sunday') then ss_sales_price else null end) sun_sales,
+ sum(case when (d_day_name='Monday') then ss_sales_price else null end) mon_sales,
+ sum(case when (d_day_name='Tuesday') then ss_sales_price else null end) tue_sales,
+ sum(case when (d_day_name='Wednesday') then ss_sales_price else null end) wed_sales,
+ sum(case when (d_day_name='Thursday') then ss_sales_price else null end) thu_sales,
+ sum(case when (d_day_name='Friday') then ss_sales_price else null end) fri_sales,
+ sum(case when (d_day_name='Saturday') then ss_sales_price else null end) sat_sales
+ from store_sales,date_dim
+ where d_date_sk = ss_sold_date_sk
+ group by d_week_seq,ss_store_sk
+ )
+ select s_store_name1,s_store_id1,d_week_seq1
+ ,sun_sales1/sun_sales2,mon_sales1/mon_sales2
+ ,tue_sales1/tue_sales1,wed_sales1/wed_sales2,thu_sales1/thu_sales2
+ ,fri_sales1/fri_sales2,sat_sales1/sat_sales2
+ from
+ (select s_store_name s_store_name1,wss.d_week_seq d_week_seq1
+ ,s_store_id s_store_id1,sun_sales sun_sales1
+ ,mon_sales mon_sales1,tue_sales tue_sales1
+ ,wed_sales wed_sales1,thu_sales thu_sales1
+ ,fri_sales fri_sales1,sat_sales sat_sales1
+ from wss,store,date_dim d
+ where d.d_week_seq = wss.d_week_seq and
+ ss_store_sk = s_store_sk and
+ d_month_seq between 1185 and 1185 + 11) y,
+ (select s_store_name s_store_name2,wss.d_week_seq d_week_seq2
+ ,s_store_id s_store_id2,sun_sales sun_sales2
+ ,mon_sales mon_sales2,tue_sales tue_sales2
+ ,wed_sales wed_sales2,thu_sales thu_sales2
+ ,fri_sales fri_sales2,sat_sales sat_sales2
+ from wss,store,date_dim d
+ where d.d_week_seq = wss.d_week_seq and
+ ss_store_sk = s_store_sk and
+ d_month_seq between 1185+ 12 and 1185 + 23) x
+ where s_store_id1=s_store_id2
+ and d_week_seq1=d_week_seq2-52
+ order by s_store_name1,s_store_id1,d_week_seq1
+limit 100
+POSTHOOK: type: QUERY
+POSTHOOK: Input: default@date_dim
+POSTHOOK: Input: default@store
+POSTHOOK: Input: default@store_sales
+POSTHOOK: Output: hdfs://### HDFS PATH ###
+CBO PLAN:
+HiveSortLimit(sort0=[$0], sort1=[$1], sort2=[$2], dir0=[ASC], dir1=[ASC], dir2=[ASC], fetch=[100])
+ HiveProject(s_store_name1=[$2], s_store_id1=[$1], d_week_seq1=[$3], _o__c3=[/($5, $14)], _o__c4=[/($6, $15)], _o__c5=[/($7, $7)], _o__c6=[/($8, $16)], _o__c7=[/($9, $17)], _o__c8=[/($10, $18)], _o__c9=[/($11, $19)])
+ HiveJoin(condition=[AND(=($1, $13), =($3, $20))], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($4, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(s_store_sk=[$0], s_store_id=[$1], s_store_name=[$5])
+ HiveTableScan(table=[[default, store]], table:alias=[store])
+ HiveJoin(condition=[=($9, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject($f0=[$0], $f1=[$1], $f2=[$2], $f3=[$3], $f4=[$4], $f5=[$5], $f6=[$6], $f7=[$7], $f8=[$8])
+ HiveAggregate(group=[{0, 1}], agg#0=[sum($2)], agg#1=[sum($3)], agg#2=[sum($4)], agg#3=[sum($5)], agg#4=[sum($6)], agg#5=[sum($7)], agg#6=[sum($8)])
+ HiveProject($f0=[$4], $f1=[$1], $f2=[CASE($5, $2, null)], $f3=[CASE($6, $2, null)], $f4=[CASE($7, $2, null)], $f5=[CASE($8, $2, null)], $f6=[CASE($9, $2, null)], $f7=[CASE($10, $2, null)], $f8=[CASE($11, $2, null)])
+ HiveJoin(condition=[=($3, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ss_sold_date_sk=[$0], ss_store_sk=[$7], ss_sales_price=[$13])
+ HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($7))])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject(d_date_sk=[$0], d_week_seq=[$4], ==[=($14, _UTF-16LE'Sunday')], =3=[=($14, _UTF-16LE'Monday')], =4=[=($14, _UTF-16LE'Tuesday')], =5=[=($14, _UTF-16LE'Wednesday')], =6=[=($14, _UTF-16LE'Thursday')], =7=[=($14, _UTF-16LE'Friday')], =8=[=($14, _UTF-16LE'Saturday')])
+ HiveFilter(condition=[IS NOT NULL($4)])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(d_week_seq=[$4])
+ HiveFilter(condition=[AND(BETWEEN(false, $3, 1185, 1196), IS NOT NULL($4))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[d])
+ HiveProject(s_store_id2=[$1], sun_sales2=[$4], mon_sales2=[$5], wed_sales2=[$6], thu_sales2=[$7], fri_sales2=[$8], sat_sales2=[$9], -=[-($2, 52)])
+ HiveJoin(condition=[=($3, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(s_store_sk=[$0], s_store_id=[$1])
+ HiveTableScan(table=[[default, store]], table:alias=[store])
+ HiveJoin(condition=[=($8, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject($f0=[$0], $f1=[$1], $f2=[$2], $f3=[$3], $f4=[$4], $f5=[$5], $f6=[$6], $f7=[$7])
+ HiveAggregate(group=[{0, 1}], agg#0=[sum($2)], agg#1=[sum($3)], agg#2=[sum($5)], agg#3=[sum($6)], agg#4=[sum($7)], agg#5=[sum($8)])
+ HiveProject($f0=[$4], $f1=[$1], $f2=[CASE($5, $2, null)], $f3=[CASE($6, $2, null)], $f4=[CASE($7, $2, null)], $f5=[CASE($8, $2, null)], $f6=[CASE($9, $2, null)], $f7=[CASE($10, $2, null)], $f8=[CASE($11, $2, null)])
+ HiveJoin(condition=[=($3, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ss_sold_date_sk=[$0], ss_store_sk=[$7], ss_sales_price=[$13])
+ HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($7))])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject(d_date_sk=[$0], d_week_seq=[$4], ==[=($14, _UTF-16LE'Sunday')], =3=[=($14, _UTF-16LE'Monday')], =4=[=($14, _UTF-16LE'Tuesday')], =5=[=($14, _UTF-16LE'Wednesday')], =6=[=($14, _UTF-16LE'Thursday')], =7=[=($14, _UTF-16LE'Friday')], =8=[=($14, _UTF-16LE'Saturday')])
+ HiveFilter(condition=[IS NOT NULL($4)])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(d_week_seq=[$4])
+ HiveFilter(condition=[AND(BETWEEN(false, $3, 1197, 1208), IS NOT NULL($4))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[d])
+
http://git-wip-us.apache.org/repos/asf/hive/blob/b8299551/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query6.q.out
----------------------------------------------------------------------
diff --git a/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query6.q.out b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query6.q.out
new file mode 100644
index 0000000..ef53060
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query6.q.out
@@ -0,0 +1,108 @@
+Warning: Map Join MAPJOIN[172][bigTable=?] in task 'Reducer 15' is a cross product
+PREHOOK: query: explain cbo
+select a.ca_state state, count(*) cnt
+ from customer_address a
+ ,customer c
+ ,store_sales s
+ ,date_dim d
+ ,item i
+ where a.ca_address_sk = c.c_current_addr_sk
+ and c.c_customer_sk = s.ss_customer_sk
+ and s.ss_sold_date_sk = d.d_date_sk
+ and s.ss_item_sk = i.i_item_sk
+ and d.d_month_seq =
+ (select distinct (d_month_seq)
+ from date_dim
+ where d_year = 2000
+ and d_moy = 2 )
+ and i.i_current_price > 1.2 *
+ (select avg(j.i_current_price)
+ from item j
+ where j.i_category = i.i_category)
+ group by a.ca_state
+ having count(*) >= 10
+ order by cnt
+ limit 100
+PREHOOK: type: QUERY
+PREHOOK: Input: default@customer
+PREHOOK: Input: default@customer_address
+PREHOOK: Input: default@date_dim
+PREHOOK: Input: default@item
+PREHOOK: Input: default@store_sales
+PREHOOK: Output: hdfs://### HDFS PATH ###
+POSTHOOK: query: explain cbo
+select a.ca_state state, count(*) cnt
+ from customer_address a
+ ,customer c
+ ,store_sales s
+ ,date_dim d
+ ,item i
+ where a.ca_address_sk = c.c_current_addr_sk
+ and c.c_customer_sk = s.ss_customer_sk
+ and s.ss_sold_date_sk = d.d_date_sk
+ and s.ss_item_sk = i.i_item_sk
+ and d.d_month_seq =
+ (select distinct (d_month_seq)
+ from date_dim
+ where d_year = 2000
+ and d_moy = 2 )
+ and i.i_current_price > 1.2 *
+ (select avg(j.i_current_price)
+ from item j
+ where j.i_category = i.i_category)
+ group by a.ca_state
+ having count(*) >= 10
+ order by cnt
+ limit 100
+POSTHOOK: type: QUERY
+POSTHOOK: Input: default@customer
+POSTHOOK: Input: default@customer_address
+POSTHOOK: Input: default@date_dim
+POSTHOOK: Input: default@item
+POSTHOOK: Input: default@store_sales
+POSTHOOK: Output: hdfs://### HDFS PATH ###
+CBO PLAN:
+HiveSortLimit(sort0=[$1], dir0=[ASC], fetch=[100])
+ HiveProject(ca_state=[$0], $f1=[$1])
+ HiveFilter(condition=[>=($1, 10)])
+ HiveAggregate(group=[{9}], agg#0=[count()])
+ HiveJoin(condition=[=($1, $10)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($6, $2)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($0, $3)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$2], ss_customer_sk=[$3])
+ HiveFilter(condition=[AND(IS NOT NULL($3), IS NOT NULL($0))])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[s])
+ HiveJoin(condition=[=($1, $2)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(d_date_sk=[$0], d_month_seq=[$3])
+ HiveFilter(condition=[IS NOT NULL($3)])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[d])
+ HiveProject(d_month_seq=[$0])
+ HiveAggregate(group=[{3}])
+ HiveFilter(condition=[AND(=($6, 2000), =($8, 2), IS NOT NULL($3))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(c_customer_sk=[$0], c_current_addr_sk=[$1], ca_address_sk=[$2], ca_state=[$3])
+ HiveJoin(condition=[=($2, $1)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(c_customer_sk=[$0], c_current_addr_sk=[$4])
+ HiveFilter(condition=[IS NOT NULL($4)])
+ HiveTableScan(table=[[default, customer]], table:alias=[c])
+ HiveProject(ca_address_sk=[$0], ca_state=[$8])
+ HiveTableScan(table=[[default, customer_address]], table:alias=[a])
+ HiveProject(i_item_sk=[$0], i_current_price=[$1], i_category=[$2], i_category0=[$3], *=[$4], cnt=[$5])
+ HiveJoin(condition=[AND(=($3, $2), >($1, $4))], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(i_item_sk=[$0], i_current_price=[$5], i_category=[$12])
+ HiveFilter(condition=[IS NOT NULL($12)])
+ HiveTableScan(table=[[default, item]], table:alias=[i])
+ HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(i_category=[$0], *=[*(1.2, CAST(/($1, $2)):DECIMAL(16, 6))])
+ HiveAggregate(group=[{12}], agg#0=[sum($5)], agg#1=[count($5)])
+ HiveFilter(condition=[IS NOT NULL($12)])
+ HiveTableScan(table=[[default, item]], table:alias=[j])
+ HiveProject(cnt=[$0])
+ HiveFilter(condition=[<=(sq_count_check($0), 1)])
+ HiveProject(cnt=[$0])
+ HiveAggregate(group=[{}], cnt=[COUNT()])
+ HiveProject(d_month_seq=[$0])
+ HiveAggregate(group=[{3}])
+ HiveFilter(condition=[AND(=($6, 2000), =($8, 2))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+