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Posted to commits@hive.apache.org by jc...@apache.org on 2018/10/22 02:10:33 UTC
[28/51] [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_query83.q.out
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diff --git a/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query83.q.out b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query83.q.out
new file mode 100644
index 0000000..ee94ea3
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query83.q.out
@@ -0,0 +1,219 @@
+PREHOOK: query: explain cbo
+with sr_items as
+ (select i_item_id item_id,
+ sum(sr_return_quantity) sr_item_qty
+ from store_returns,
+ item,
+ date_dim
+ where sr_item_sk = i_item_sk
+ and d_date in
+ (select d_date
+ from date_dim
+ where d_week_seq in
+ (select d_week_seq
+ from date_dim
+ where d_date in ('1998-01-02','1998-10-15','1998-11-10')))
+ and sr_returned_date_sk = d_date_sk
+ group by i_item_id),
+ cr_items as
+ (select i_item_id item_id,
+ sum(cr_return_quantity) cr_item_qty
+ from catalog_returns,
+ item,
+ date_dim
+ where cr_item_sk = i_item_sk
+ and d_date in
+ (select d_date
+ from date_dim
+ where d_week_seq in
+ (select d_week_seq
+ from date_dim
+ where d_date in ('1998-01-02','1998-10-15','1998-11-10')))
+ and cr_returned_date_sk = d_date_sk
+ group by i_item_id),
+ wr_items as
+ (select i_item_id item_id,
+ sum(wr_return_quantity) wr_item_qty
+ from web_returns,
+ item,
+ date_dim
+ where wr_item_sk = i_item_sk
+ and d_date in
+ (select d_date
+ from date_dim
+ where d_week_seq in
+ (select d_week_seq
+ from date_dim
+ where d_date in ('1998-01-02','1998-10-15','1998-11-10')))
+ and wr_returned_date_sk = d_date_sk
+ group by i_item_id)
+ select sr_items.item_id
+ ,sr_item_qty
+ ,sr_item_qty/(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 * 100 sr_dev
+ ,cr_item_qty
+ ,cr_item_qty/(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 * 100 cr_dev
+ ,wr_item_qty
+ ,wr_item_qty/(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 * 100 wr_dev
+ ,(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 average
+ from sr_items
+ ,cr_items
+ ,wr_items
+ where sr_items.item_id=cr_items.item_id
+ and sr_items.item_id=wr_items.item_id
+ order by sr_items.item_id
+ ,sr_item_qty
+ limit 100
+PREHOOK: type: QUERY
+PREHOOK: Input: default@catalog_returns
+PREHOOK: Input: default@date_dim
+PREHOOK: Input: default@item
+PREHOOK: Input: default@store_returns
+PREHOOK: Input: default@web_returns
+PREHOOK: Output: hdfs://### HDFS PATH ###
+POSTHOOK: query: explain cbo
+with sr_items as
+ (select i_item_id item_id,
+ sum(sr_return_quantity) sr_item_qty
+ from store_returns,
+ item,
+ date_dim
+ where sr_item_sk = i_item_sk
+ and d_date in
+ (select d_date
+ from date_dim
+ where d_week_seq in
+ (select d_week_seq
+ from date_dim
+ where d_date in ('1998-01-02','1998-10-15','1998-11-10')))
+ and sr_returned_date_sk = d_date_sk
+ group by i_item_id),
+ cr_items as
+ (select i_item_id item_id,
+ sum(cr_return_quantity) cr_item_qty
+ from catalog_returns,
+ item,
+ date_dim
+ where cr_item_sk = i_item_sk
+ and d_date in
+ (select d_date
+ from date_dim
+ where d_week_seq in
+ (select d_week_seq
+ from date_dim
+ where d_date in ('1998-01-02','1998-10-15','1998-11-10')))
+ and cr_returned_date_sk = d_date_sk
+ group by i_item_id),
+ wr_items as
+ (select i_item_id item_id,
+ sum(wr_return_quantity) wr_item_qty
+ from web_returns,
+ item,
+ date_dim
+ where wr_item_sk = i_item_sk
+ and d_date in
+ (select d_date
+ from date_dim
+ where d_week_seq in
+ (select d_week_seq
+ from date_dim
+ where d_date in ('1998-01-02','1998-10-15','1998-11-10')))
+ and wr_returned_date_sk = d_date_sk
+ group by i_item_id)
+ select sr_items.item_id
+ ,sr_item_qty
+ ,sr_item_qty/(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 * 100 sr_dev
+ ,cr_item_qty
+ ,cr_item_qty/(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 * 100 cr_dev
+ ,wr_item_qty
+ ,wr_item_qty/(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 * 100 wr_dev
+ ,(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 average
+ from sr_items
+ ,cr_items
+ ,wr_items
+ where sr_items.item_id=cr_items.item_id
+ and sr_items.item_id=wr_items.item_id
+ order by sr_items.item_id
+ ,sr_item_qty
+ limit 100
+POSTHOOK: type: QUERY
+POSTHOOK: Input: default@catalog_returns
+POSTHOOK: Input: default@date_dim
+POSTHOOK: Input: default@item
+POSTHOOK: Input: default@store_returns
+POSTHOOK: Input: default@web_returns
+POSTHOOK: Output: hdfs://### HDFS PATH ###
+CBO PLAN:
+HiveSortLimit(sort0=[$0], sort1=[$1], dir0=[ASC], dir1=[ASC], fetch=[100])
+ HiveProject(item_id=[$0], sr_item_qty=[$4], sr_dev=[*(/(/($5, CAST(+(+($4, $1), $7)):DOUBLE), CAST(3):DOUBLE), CAST(100):DOUBLE)], cr_item_qty=[$1], cr_dev=[*(/(/($2, CAST(+(+($4, $1), $7)):DOUBLE), CAST(3):DOUBLE), CAST(100):DOUBLE)], wr_item_qty=[$7], wr_dev=[*(/(/($8, CAST(+(+($4, $1), $7)):DOUBLE), CAST(3):DOUBLE), CAST(100):DOUBLE)], average=[/(CAST(+(+($4, $1), $7)):DECIMAL(19, 0), 3)])
+ HiveJoin(condition=[=($0, $6)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($3, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(item_id=[$0], cr_item_qty=[$1], CAST=[CAST($1):DOUBLE])
+ 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(cr_returned_date_sk=[$0], cr_item_sk=[$2], cr_return_quantity=[$17])
+ HiveFilter(condition=[IS NOT NULL($0)])
+ HiveTableScan(table=[[default, catalog_returns]], table:alias=[catalog_returns])
+ 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}])
+ HiveSemiJoin(condition=[=($1, $6)], joinType=[inner])
+ 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])
+ HiveProject(d_date_sk=[$0], d_date_id=[$1], d_date=[$2], d_month_seq=[$3], d_week_seq=[$4], d_quarter_seq=[$5], d_year=[$6], d_dow=[$7], d_moy=[$8], d_dom=[$9], d_qoy=[$10], d_fy_year=[$11], d_fy_quarter_seq=[$12], d_fy_week_seq=[$13], d_day_name=[$14], d_quarter_name=[$15], d_holiday=[$16], d_weekend=[$17], d_following_holiday=[$18], d_first_dom=[$19], d_last_dom=[$20], d_same_day_ly=[$21], d_same_day_lq=[$22], d_current_day=[$23], d_current_week=[$24], d_current_month=[$25], d_current_quarter=[$26], d_current_year=[$27], BLOCK__OFFSET__INSIDE__FILE=[$28], INPUT__FILE__NAME=[$29], ROW__ID=[$30])
+ HiveFilter(condition=[AND(IN($2, _UTF-16LE'1998-01-02', _UTF-16LE'1998-10-15', _UTF-16LE'1998-11-10'), IS NOT NULL($4))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(item_id=[$0], sr_item_qty=[$1], CAST=[CAST($1):DOUBLE])
+ 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(sr_returned_date_sk=[$0], sr_item_sk=[$2], sr_return_quantity=[$10])
+ HiveFilter(condition=[IS NOT NULL($0)])
+ HiveTableScan(table=[[default, store_returns]], table:alias=[store_returns])
+ 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}])
+ HiveSemiJoin(condition=[=($1, $6)], joinType=[inner])
+ 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])
+ HiveProject(d_date_sk=[$0], d_date_id=[$1], d_date=[$2], d_month_seq=[$3], d_week_seq=[$4], d_quarter_seq=[$5], d_year=[$6], d_dow=[$7], d_moy=[$8], d_dom=[$9], d_qoy=[$10], d_fy_year=[$11], d_fy_quarter_seq=[$12], d_fy_week_seq=[$13], d_day_name=[$14], d_quarter_name=[$15], d_holiday=[$16], d_weekend=[$17], d_following_holiday=[$18], d_first_dom=[$19], d_last_dom=[$20], d_same_day_ly=[$21], d_same_day_lq=[$22], d_current_day=[$23], d_current_week=[$24], d_current_month=[$25], d_current_quarter=[$26], d_current_year=[$27], BLOCK__OFFSET__INSIDE__FILE=[$28], INPUT__FILE__NAME=[$29], ROW__ID=[$30])
+ HiveFilter(condition=[AND(IN($2, _UTF-16LE'1998-01-02', _UTF-16LE'1998-10-15', _UTF-16LE'1998-11-10'), IS NOT NULL($4))])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(item_id=[$0], wr_item_qty=[$1], CAST=[CAST($1):DOUBLE])
+ 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(wr_returned_date_sk=[$0], wr_item_sk=[$2], wr_return_quantity=[$14])
+ HiveFilter(condition=[IS NOT NULL($0)])
+ HiveTableScan(table=[[default, web_returns]], table:alias=[web_returns])
+ 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}])
+ HiveSemiJoin(condition=[=($1, $6)], joinType=[inner])
+ 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])
+ HiveProject(d_date_sk=[$0], d_date_id=[$1], d_date=[$2], d_month_seq=[$3], d_week_seq=[$4], d_quarter_seq=[$5], d_year=[$6], d_dow=[$7], d_moy=[$8], d_dom=[$9], d_qoy=[$10], d_fy_year=[$11], d_fy_quarter_seq=[$12], d_fy_week_seq=[$13], d_day_name=[$14], d_quarter_name=[$15], d_holiday=[$16], d_weekend=[$17], d_following_holiday=[$18], d_first_dom=[$19], d_last_dom=[$20], d_same_day_ly=[$21], d_same_day_lq=[$22], d_current_day=[$23], d_current_week=[$24], d_current_month=[$25], d_current_quarter=[$26], d_current_year=[$27], BLOCK__OFFSET__INSIDE__FILE=[$28], INPUT__FILE__NAME=[$29], ROW__ID=[$30])
+ HiveFilter(condition=[AND(IN($2, _UTF-16LE'1998-01-02', _UTF-16LE'1998-10-15', _UTF-16LE'1998-11-10'), 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_query84.q.out
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diff --git a/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query84.q.out b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query84.q.out
new file mode 100644
index 0000000..43ea953
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query84.q.out
@@ -0,0 +1,83 @@
+PREHOOK: query: explain cbo
+select c_customer_id as customer_id
+ ,c_last_name || ', ' || c_first_name as customername
+ from customer
+ ,customer_address
+ ,customer_demographics
+ ,household_demographics
+ ,income_band
+ ,store_returns
+ where ca_city = 'Hopewell'
+ and c_current_addr_sk = ca_address_sk
+ and ib_lower_bound >= 32287
+ and ib_upper_bound <= 32287 + 50000
+ and ib_income_band_sk = hd_income_band_sk
+ and cd_demo_sk = c_current_cdemo_sk
+ and hd_demo_sk = c_current_hdemo_sk
+ and sr_cdemo_sk = cd_demo_sk
+ order by c_customer_id
+ limit 100
+PREHOOK: type: QUERY
+PREHOOK: Input: default@customer
+PREHOOK: Input: default@customer_address
+PREHOOK: Input: default@customer_demographics
+PREHOOK: Input: default@household_demographics
+PREHOOK: Input: default@income_band
+PREHOOK: Input: default@store_returns
+PREHOOK: Output: hdfs://### HDFS PATH ###
+POSTHOOK: query: explain cbo
+select c_customer_id as customer_id
+ ,c_last_name || ', ' || c_first_name as customername
+ from customer
+ ,customer_address
+ ,customer_demographics
+ ,household_demographics
+ ,income_band
+ ,store_returns
+ where ca_city = 'Hopewell'
+ and c_current_addr_sk = ca_address_sk
+ and ib_lower_bound >= 32287
+ and ib_upper_bound <= 32287 + 50000
+ and ib_income_band_sk = hd_income_band_sk
+ and cd_demo_sk = c_current_cdemo_sk
+ and hd_demo_sk = c_current_hdemo_sk
+ and sr_cdemo_sk = cd_demo_sk
+ order by c_customer_id
+ limit 100
+POSTHOOK: type: QUERY
+POSTHOOK: Input: default@customer
+POSTHOOK: Input: default@customer_address
+POSTHOOK: Input: default@customer_demographics
+POSTHOOK: Input: default@household_demographics
+POSTHOOK: Input: default@income_band
+POSTHOOK: Input: default@store_returns
+POSTHOOK: Output: hdfs://### HDFS PATH ###
+CBO PLAN:
+HiveProject(customer_id=[$0], customername=[$1])
+ HiveSortLimit(sort0=[$2], dir0=[ASC], fetch=[100])
+ HiveProject(customer_id=[$2], customername=[$6], c_customer_id=[$2])
+ HiveJoin(condition=[=($1, $3)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($0, $1)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(sr_cdemo_sk=[$4])
+ HiveFilter(condition=[IS NOT NULL($4)])
+ HiveTableScan(table=[[default, store_returns]], table:alias=[store_returns])
+ HiveProject(cd_demo_sk=[$0])
+ HiveTableScan(table=[[default, customer_demographics]], table:alias=[customer_demographics])
+ HiveProject(c_customer_id=[$0], c_current_cdemo_sk=[$1], c_current_hdemo_sk=[$2], c_current_addr_sk=[$3], ||=[$4], ca_address_sk=[$5], hd_demo_sk=[$6], hd_income_band_sk=[$7], ib_income_band_sk=[$8])
+ HiveJoin(condition=[=($6, $2)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($3, $5)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(c_customer_id=[$1], c_current_cdemo_sk=[$2], c_current_hdemo_sk=[$3], c_current_addr_sk=[$4], ||=[||(||($9, _UTF-16LE', '), $8)])
+ HiveFilter(condition=[AND(IS NOT NULL($4), IS NOT NULL($2), IS NOT NULL($3))])
+ HiveTableScan(table=[[default, customer]], table:alias=[customer])
+ HiveProject(ca_address_sk=[$0])
+ HiveFilter(condition=[=($6, _UTF-16LE'Hopewell')])
+ HiveTableScan(table=[[default, customer_address]], table:alias=[customer_address])
+ HiveProject(hd_demo_sk=[$0], hd_income_band_sk=[$1], ib_income_band_sk=[$2])
+ HiveJoin(condition=[=($2, $1)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(hd_demo_sk=[$0], hd_income_band_sk=[$1])
+ HiveFilter(condition=[IS NOT NULL($1)])
+ HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics])
+ HiveProject(ib_income_band_sk=[$0])
+ HiveFilter(condition=[AND(>=($1, 32287), <=($2, 82287))])
+ HiveTableScan(table=[[default, income_band]], table:alias=[income_band])
+
http://git-wip-us.apache.org/repos/asf/hive/blob/b8299551/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query85.q.out
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diff --git a/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query85.q.out b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query85.q.out
new file mode 100644
index 0000000..1876936
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query85.q.out
@@ -0,0 +1,214 @@
+PREHOOK: query: explain cbo
+select substr(r_reason_desc,1,20)
+ ,avg(ws_quantity)
+ ,avg(wr_refunded_cash)
+ ,avg(wr_fee)
+ from web_sales, web_returns, web_page, customer_demographics cd1,
+ customer_demographics cd2, customer_address, date_dim, reason
+ where ws_web_page_sk = wp_web_page_sk
+ and ws_item_sk = wr_item_sk
+ and ws_order_number = wr_order_number
+ and ws_sold_date_sk = d_date_sk and d_year = 1998
+ and cd1.cd_demo_sk = wr_refunded_cdemo_sk
+ and cd2.cd_demo_sk = wr_returning_cdemo_sk
+ and ca_address_sk = wr_refunded_addr_sk
+ and r_reason_sk = wr_reason_sk
+ and
+ (
+ (
+ cd1.cd_marital_status = 'M'
+ and
+ cd1.cd_marital_status = cd2.cd_marital_status
+ and
+ cd1.cd_education_status = '4 yr Degree'
+ and
+ cd1.cd_education_status = cd2.cd_education_status
+ and
+ ws_sales_price between 100.00 and 150.00
+ )
+ or
+ (
+ cd1.cd_marital_status = 'D'
+ and
+ cd1.cd_marital_status = cd2.cd_marital_status
+ and
+ cd1.cd_education_status = 'Primary'
+ and
+ cd1.cd_education_status = cd2.cd_education_status
+ and
+ ws_sales_price between 50.00 and 100.00
+ )
+ or
+ (
+ cd1.cd_marital_status = 'U'
+ and
+ cd1.cd_marital_status = cd2.cd_marital_status
+ and
+ cd1.cd_education_status = 'Advanced Degree'
+ and
+ cd1.cd_education_status = cd2.cd_education_status
+ and
+ ws_sales_price between 150.00 and 200.00
+ )
+ )
+ and
+ (
+ (
+ ca_country = 'United States'
+ and
+ ca_state in ('KY', 'GA', 'NM')
+ and ws_net_profit between 100 and 200
+ )
+ or
+ (
+ ca_country = 'United States'
+ and
+ ca_state in ('MT', 'OR', 'IN')
+ and ws_net_profit between 150 and 300
+ )
+ or
+ (
+ ca_country = 'United States'
+ and
+ ca_state in ('WI', 'MO', 'WV')
+ and ws_net_profit between 50 and 250
+ )
+ )
+group by r_reason_desc
+order by substr(r_reason_desc,1,20)
+ ,avg(ws_quantity)
+ ,avg(wr_refunded_cash)
+ ,avg(wr_fee)
+limit 100
+PREHOOK: type: QUERY
+PREHOOK: Input: default@customer_address
+PREHOOK: Input: default@customer_demographics
+PREHOOK: Input: default@date_dim
+PREHOOK: Input: default@reason
+PREHOOK: Input: default@web_page
+PREHOOK: Input: default@web_returns
+PREHOOK: Input: default@web_sales
+PREHOOK: Output: hdfs://### HDFS PATH ###
+POSTHOOK: query: explain cbo
+select substr(r_reason_desc,1,20)
+ ,avg(ws_quantity)
+ ,avg(wr_refunded_cash)
+ ,avg(wr_fee)
+ from web_sales, web_returns, web_page, customer_demographics cd1,
+ customer_demographics cd2, customer_address, date_dim, reason
+ where ws_web_page_sk = wp_web_page_sk
+ and ws_item_sk = wr_item_sk
+ and ws_order_number = wr_order_number
+ and ws_sold_date_sk = d_date_sk and d_year = 1998
+ and cd1.cd_demo_sk = wr_refunded_cdemo_sk
+ and cd2.cd_demo_sk = wr_returning_cdemo_sk
+ and ca_address_sk = wr_refunded_addr_sk
+ and r_reason_sk = wr_reason_sk
+ and
+ (
+ (
+ cd1.cd_marital_status = 'M'
+ and
+ cd1.cd_marital_status = cd2.cd_marital_status
+ and
+ cd1.cd_education_status = '4 yr Degree'
+ and
+ cd1.cd_education_status = cd2.cd_education_status
+ and
+ ws_sales_price between 100.00 and 150.00
+ )
+ or
+ (
+ cd1.cd_marital_status = 'D'
+ and
+ cd1.cd_marital_status = cd2.cd_marital_status
+ and
+ cd1.cd_education_status = 'Primary'
+ and
+ cd1.cd_education_status = cd2.cd_education_status
+ and
+ ws_sales_price between 50.00 and 100.00
+ )
+ or
+ (
+ cd1.cd_marital_status = 'U'
+ and
+ cd1.cd_marital_status = cd2.cd_marital_status
+ and
+ cd1.cd_education_status = 'Advanced Degree'
+ and
+ cd1.cd_education_status = cd2.cd_education_status
+ and
+ ws_sales_price between 150.00 and 200.00
+ )
+ )
+ and
+ (
+ (
+ ca_country = 'United States'
+ and
+ ca_state in ('KY', 'GA', 'NM')
+ and ws_net_profit between 100 and 200
+ )
+ or
+ (
+ ca_country = 'United States'
+ and
+ ca_state in ('MT', 'OR', 'IN')
+ and ws_net_profit between 150 and 300
+ )
+ or
+ (
+ ca_country = 'United States'
+ and
+ ca_state in ('WI', 'MO', 'WV')
+ and ws_net_profit between 50 and 250
+ )
+ )
+group by r_reason_desc
+order by substr(r_reason_desc,1,20)
+ ,avg(ws_quantity)
+ ,avg(wr_refunded_cash)
+ ,avg(wr_fee)
+limit 100
+POSTHOOK: type: QUERY
+POSTHOOK: Input: default@customer_address
+POSTHOOK: Input: default@customer_demographics
+POSTHOOK: Input: default@date_dim
+POSTHOOK: Input: default@reason
+POSTHOOK: Input: default@web_page
+POSTHOOK: Input: default@web_returns
+POSTHOOK: Input: default@web_sales
+POSTHOOK: Output: hdfs://### HDFS PATH ###
+CBO PLAN:
+HiveProject(_o__c0=[$0], _o__c1=[$1], _o__c2=[$2], _o__c3=[$3])
+ HiveSortLimit(sort0=[$7], sort1=[$4], sort2=[$5], sort3=[$6], dir0=[ASC], dir1=[ASC], dir2=[ASC], dir3=[ASC], fetch=[100])
+ HiveProject(_o__c0=[substr($0, 1, 20)], _o__c1=[/(CAST($1):DOUBLE, $2)], _o__c2=[/($3, $4)], _o__c3=[/($5, $6)], (tok_function avg (tok_table_or_col ws_quantity))=[/(CAST($1):DOUBLE, $2)], (tok_function avg (tok_table_or_col wr_refunded_cash))=[/($3, $4)], (tok_function avg (tok_table_or_col wr_fee))=[/($5, $6)], (tok_function substr (tok_table_or_col r_reason_desc) 1 20)=[substr($0, 1, 20)])
+ HiveAggregate(group=[{14}], agg#0=[sum($30)], agg#1=[count($30)], agg#2=[sum($26)], agg#3=[count($26)], agg#4=[sum($25)], agg#5=[count($25)])
+ HiveJoin(condition=[AND(AND(AND(=($1, $17), =($2, $18)), =($0, $20)), OR(AND($3, $4, $34), AND($5, $6, $35), AND($7, $8, $36)))], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(cd_demo_sk=[$0], cd_marital_status=[$2], cd_education_status=[$3], ==[=($2, _UTF-16LE'M')], =4=[=($3, _UTF-16LE'4 yr Degree')], =5=[=($2, _UTF-16LE'D')], =6=[=($3, _UTF-16LE'Primary')], =7=[=($2, _UTF-16LE'U')], =8=[=($3, _UTF-16LE'Advanced Degree')])
+ HiveFilter(condition=[AND(IN($3, _UTF-16LE'4 yr Degree', _UTF-16LE'Primary', _UTF-16LE'Advanced Degree'), IN($2, _UTF-16LE'M', _UTF-16LE'D', _UTF-16LE'U'))])
+ HiveTableScan(table=[[default, customer_demographics]], table:alias=[cd1])
+ HiveJoin(condition=[AND(=($0, $12), OR(AND($1, $22), AND($2, $23), AND($3, $24)))], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ca_address_sk=[$0], IN=[IN($8, _UTF-16LE'KY', _UTF-16LE'GA', _UTF-16LE'NM')], IN2=[IN($8, _UTF-16LE'MT', _UTF-16LE'OR', _UTF-16LE'IN')], IN3=[IN($8, _UTF-16LE'WI', _UTF-16LE'MO', _UTF-16LE'WV')])
+ HiveFilter(condition=[AND(IN($8, _UTF-16LE'KY', _UTF-16LE'GA', _UTF-16LE'NM', _UTF-16LE'MT', _UTF-16LE'OR', _UTF-16LE'IN', _UTF-16LE'WI', _UTF-16LE'MO', _UTF-16LE'WV'), =($10, _UTF-16LE'United States'))])
+ HiveTableScan(table=[[default, customer_address]], table:alias=[customer_address])
+ HiveJoin(condition=[=($0, $10)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(r_reason_sk=[$0], r_reason_desc=[$2])
+ HiveTableScan(table=[[default, reason]], table:alias=[reason])
+ HiveJoin(condition=[=($12, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(d_date_sk=[$0])
+ HiveFilter(condition=[=($6, 1998)])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveJoin(condition=[=($0, $6)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(cd_demo_sk=[$0], cd_marital_status=[$2], cd_education_status=[$3])
+ HiveFilter(condition=[AND(IN($3, _UTF-16LE'4 yr Degree', _UTF-16LE'Primary', _UTF-16LE'Advanced Degree'), IN($2, _UTF-16LE'M', _UTF-16LE'D', _UTF-16LE'U'))])
+ HiveTableScan(table=[[default, customer_demographics]], table:alias=[cd2])
+ HiveJoin(condition=[AND(=($9, $0), =($10, $5))], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(wr_item_sk=[$2], wr_refunded_cdemo_sk=[$4], wr_refunded_addr_sk=[$6], wr_returning_cdemo_sk=[$8], wr_reason_sk=[$12], wr_order_number=[$13], wr_fee=[$18], wr_refunded_cash=[$20])
+ HiveFilter(condition=[AND(IS NOT NULL($4), IS NOT NULL($8), IS NOT NULL($6), IS NOT NULL($12))])
+ HiveTableScan(table=[[default, web_returns]], table:alias=[web_returns])
+ HiveProject(ws_sold_date_sk=[$0], ws_item_sk=[$3], ws_order_number=[$17], ws_quantity=[$18], BETWEEN=[BETWEEN(false, $33, 100, 200)], BETWEEN6=[BETWEEN(false, $33, 150, 300)], BETWEEN7=[BETWEEN(false, $33, 50, 250)], BETWEEN8=[BETWEEN(false, $21, 100, 150)], BETWEEN9=[BETWEEN(false, $21, 50, 100)], BETWEEN10=[BETWEEN(false, $21, 150, 200)])
+ HiveFilter(condition=[AND(OR(BETWEEN(false, $21, 100, 150), BETWEEN(false, $21, 50, 100), BETWEEN(false, $21, 150, 200)), OR(BETWEEN(false, $33, 100, 200), BETWEEN(false, $33, 150, 300), BETWEEN(false, $33, 50, 250)), IS NOT NULL($12), IS NOT NULL($0))])
+ HiveTableScan(table=[[default, web_sales]], table:alias=[web_sales])
+
http://git-wip-us.apache.org/repos/asf/hive/blob/b8299551/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query86.q.out
----------------------------------------------------------------------
diff --git a/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query86.q.out b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query86.q.out
new file mode 100644
index 0000000..8e89983
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query86.q.out
@@ -0,0 +1,76 @@
+PREHOOK: query: explain cbo
+select
+ sum(ws_net_paid) as total_sum
+ ,i_category
+ ,i_class
+ ,grouping(i_category)+grouping(i_class) as lochierarchy
+ ,rank() over (
+ partition by grouping(i_category)+grouping(i_class),
+ case when grouping(i_class) = 0 then i_category end
+ order by sum(ws_net_paid) desc) as rank_within_parent
+ from
+ web_sales
+ ,date_dim d1
+ ,item
+ where
+ d1.d_month_seq between 1212 and 1212+11
+ and d1.d_date_sk = ws_sold_date_sk
+ and i_item_sk = ws_item_sk
+ group by rollup(i_category,i_class)
+ order by
+ lochierarchy desc,
+ case when lochierarchy = 0 then i_category end,
+ rank_within_parent
+ limit 100
+PREHOOK: type: QUERY
+PREHOOK: Input: default@date_dim
+PREHOOK: Input: default@item
+PREHOOK: Input: default@web_sales
+PREHOOK: Output: hdfs://### HDFS PATH ###
+POSTHOOK: query: explain cbo
+select
+ sum(ws_net_paid) as total_sum
+ ,i_category
+ ,i_class
+ ,grouping(i_category)+grouping(i_class) as lochierarchy
+ ,rank() over (
+ partition by grouping(i_category)+grouping(i_class),
+ case when grouping(i_class) = 0 then i_category end
+ order by sum(ws_net_paid) desc) as rank_within_parent
+ from
+ web_sales
+ ,date_dim d1
+ ,item
+ where
+ d1.d_month_seq between 1212 and 1212+11
+ and d1.d_date_sk = ws_sold_date_sk
+ and i_item_sk = ws_item_sk
+ group by rollup(i_category,i_class)
+ order by
+ lochierarchy desc,
+ case when lochierarchy = 0 then i_category end,
+ rank_within_parent
+ limit 100
+POSTHOOK: type: QUERY
+POSTHOOK: Input: default@date_dim
+POSTHOOK: Input: default@item
+POSTHOOK: Input: default@web_sales
+POSTHOOK: Output: hdfs://### HDFS PATH ###
+CBO PLAN:
+HiveProject(total_sum=[$0], i_category=[$1], i_class=[$2], lochierarchy=[$3], rank_within_parent=[$4])
+ HiveSortLimit(sort0=[$3], sort1=[$5], sort2=[$4], dir0=[DESC-nulls-last], dir1=[ASC], dir2=[ASC], fetch=[100])
+ HiveProject(total_sum=[$2], i_category=[$0], i_class=[$1], lochierarchy=[+(grouping($3, 1), grouping($3, 0))], rank_within_parent=[rank() OVER (PARTITION BY +(grouping($3, 1), grouping($3, 0)), CASE(=(grouping($3, 0), 0), $0, null) ORDER BY $2 DESC NULLS LAST ROWS BETWEEN 2147483647 FOLLOWING AND 2147483647 PRECEDING)], (tok_function when (= (tok_table_or_col lochierarchy) 0) (tok_table_or_col i_category))=[CASE(=(+(grouping($3, 1), grouping($3, 0)), 0), $0, null)])
+ HiveProject($f0=[$0], $f1=[$1], $f2=[$2], GROUPING__ID=[$3])
+ HiveAggregate(group=[{0, 1}], groups=[[{0, 1}, {0}, {}]], agg#0=[sum($2)], GROUPING__ID=[GROUPING__ID()])
+ HiveProject($f0=[$2], $f1=[$1], $f2=[$5])
+ HiveJoin(condition=[=($0, $4)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(i_item_sk=[$0], i_class=[$10], i_category=[$12])
+ HiveTableScan(table=[[default, item]], table:alias=[item])
+ HiveJoin(condition=[=($3, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ws_sold_date_sk=[$0], ws_item_sk=[$3], ws_net_paid=[$29])
+ HiveFilter(condition=[IS NOT NULL($0)])
+ HiveTableScan(table=[[default, web_sales]], table:alias=[web_sales])
+ HiveProject(d_date_sk=[$0])
+ HiveFilter(condition=[BETWEEN(false, $3, 1212, 1223)])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[d1])
+
http://git-wip-us.apache.org/repos/asf/hive/blob/b8299551/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query87.q.out
----------------------------------------------------------------------
diff --git a/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query87.q.out b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query87.q.out
new file mode 100644
index 0000000..97c9edd
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query87.q.out
@@ -0,0 +1,111 @@
+PREHOOK: query: explain cbo
+select count(*)
+from ((select distinct c_last_name, c_first_name, d_date
+ from store_sales, date_dim, customer
+ where store_sales.ss_sold_date_sk = date_dim.d_date_sk
+ and store_sales.ss_customer_sk = customer.c_customer_sk
+ and d_month_seq between 1212 and 1212+11)
+ except
+ (select distinct c_last_name, c_first_name, d_date
+ from catalog_sales, date_dim, customer
+ where catalog_sales.cs_sold_date_sk = date_dim.d_date_sk
+ and catalog_sales.cs_bill_customer_sk = customer.c_customer_sk
+ and d_month_seq between 1212 and 1212+11)
+ except
+ (select distinct c_last_name, c_first_name, d_date
+ from web_sales, date_dim, customer
+ where web_sales.ws_sold_date_sk = date_dim.d_date_sk
+ and web_sales.ws_bill_customer_sk = customer.c_customer_sk
+ and d_month_seq between 1212 and 1212+11)
+) cool_cust
+PREHOOK: type: QUERY
+PREHOOK: Input: default@catalog_sales
+PREHOOK: Input: default@customer
+PREHOOK: Input: default@date_dim
+PREHOOK: Input: default@store_sales
+PREHOOK: Input: default@web_sales
+PREHOOK: Output: hdfs://### HDFS PATH ###
+POSTHOOK: query: explain cbo
+select count(*)
+from ((select distinct c_last_name, c_first_name, d_date
+ from store_sales, date_dim, customer
+ where store_sales.ss_sold_date_sk = date_dim.d_date_sk
+ and store_sales.ss_customer_sk = customer.c_customer_sk
+ and d_month_seq between 1212 and 1212+11)
+ except
+ (select distinct c_last_name, c_first_name, d_date
+ from catalog_sales, date_dim, customer
+ where catalog_sales.cs_sold_date_sk = date_dim.d_date_sk
+ and catalog_sales.cs_bill_customer_sk = customer.c_customer_sk
+ and d_month_seq between 1212 and 1212+11)
+ except
+ (select distinct c_last_name, c_first_name, d_date
+ from web_sales, date_dim, customer
+ where web_sales.ws_sold_date_sk = date_dim.d_date_sk
+ and web_sales.ws_bill_customer_sk = customer.c_customer_sk
+ and d_month_seq between 1212 and 1212+11)
+) cool_cust
+POSTHOOK: type: QUERY
+POSTHOOK: Input: default@catalog_sales
+POSTHOOK: Input: default@customer
+POSTHOOK: Input: default@date_dim
+POSTHOOK: Input: default@store_sales
+POSTHOOK: Input: default@web_sales
+POSTHOOK: Output: hdfs://### HDFS PATH ###
+CBO PLAN:
+HiveAggregate(group=[{}], agg#0=[count()])
+ HiveProject($f0=[$0], $f1=[$1], $f2=[$2], $f3=[$3], $f4=[$4])
+ HiveFilter(condition=[AND(>($3, 0), =(*($3, 2), $4))])
+ HiveAggregate(group=[{0, 1, 2}], agg#0=[sum($3)], agg#1=[sum($4)])
+ HiveProject($f0=[$0], $f1=[$1], $f2=[$2], $f4=[$4], $f5=[*($3, $4)])
+ HiveUnion(all=[true])
+ HiveProject($f0=[$0], $f1=[$1], $f2=[$2], $f3=[2], $f4=[$3])
+ HiveAggregate(group=[{0, 1, 2}], agg#0=[count()])
+ HiveProject($f0=[$0], $f1=[$1], $f2=[$2], $f3=[$3], $f4=[$4])
+ HiveFilter(condition=[AND(>($3, 0), =(*($3, 2), $4))])
+ HiveAggregate(group=[{0, 1, 2}], agg#0=[sum($3)], agg#1=[sum($4)])
+ HiveProject($f0=[$0], $f1=[$1], $f2=[$2], $f4=[$4], $f5=[*($3, $4)])
+ HiveUnion(all=[true])
+ HiveProject($f0=[$1], $f1=[$0], $f2=[$2], $f3=[2], $f4=[$3])
+ HiveAggregate(group=[{0, 1, 2}], agg#0=[count()])
+ HiveProject(c_first_name=[$0], c_last_name=[$1], d_date=[$2])
+ HiveAggregate(group=[{1, 2, 6}])
+ HiveJoin(condition=[=($4, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(c_customer_sk=[$0], c_first_name=[$8], c_last_name=[$9])
+ HiveTableScan(table=[[default, customer]], table:alias=[customer])
+ HiveJoin(condition=[=($0, $2)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ss_sold_date_sk=[$0], ss_customer_sk=[$3])
+ HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($3))])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject(d_date_sk=[$0], d_date=[$2])
+ HiveFilter(condition=[BETWEEN(false, $3, 1212, 1223)])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject($f0=[$1], $f1=[$0], $f2=[$2], $f3=[1], $f4=[$3])
+ HiveAggregate(group=[{0, 1, 2}], agg#0=[count()])
+ HiveProject(c_first_name=[$0], c_last_name=[$1], d_date=[$2])
+ HiveAggregate(group=[{1, 2, 6}])
+ HiveJoin(condition=[=($4, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(c_customer_sk=[$0], c_first_name=[$8], c_last_name=[$9])
+ HiveTableScan(table=[[default, customer]], table:alias=[customer])
+ HiveJoin(condition=[=($0, $2)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(cs_sold_date_sk=[$0], cs_bill_customer_sk=[$3])
+ HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($3))])
+ HiveTableScan(table=[[default, catalog_sales]], table:alias=[catalog_sales])
+ HiveProject(d_date_sk=[$0], d_date=[$2])
+ HiveFilter(condition=[BETWEEN(false, $3, 1212, 1223)])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject($f0=[$1], $f1=[$0], $f2=[$2], $f3=[1], $f4=[$3])
+ HiveAggregate(group=[{0, 1, 2}], agg#0=[count()])
+ HiveProject(c_first_name=[$0], c_last_name=[$1], d_date=[$2])
+ HiveAggregate(group=[{1, 2, 6}])
+ HiveJoin(condition=[=($4, $0)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(c_customer_sk=[$0], c_first_name=[$8], c_last_name=[$9])
+ HiveTableScan(table=[[default, customer]], table:alias=[customer])
+ HiveJoin(condition=[=($0, $2)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ws_sold_date_sk=[$0], ws_bill_customer_sk=[$4])
+ 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], d_date=[$2])
+ HiveFilter(condition=[BETWEEN(false, $3, 1212, 1223)])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+
http://git-wip-us.apache.org/repos/asf/hive/blob/b8299551/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query88.q.out
----------------------------------------------------------------------
diff --git a/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query88.q.out b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query88.q.out
new file mode 100644
index 0000000..1ac8fe2
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query88.q.out
@@ -0,0 +1,347 @@
+Warning: Shuffle Join MERGEJOIN[599][tables = [$hdt$_0, $hdt$_1]] in Stage 'Reducer 6' is a cross product
+Warning: Shuffle Join MERGEJOIN[600][tables = [$hdt$_0, $hdt$_1, $hdt$_2]] in Stage 'Reducer 7' is a cross product
+Warning: Shuffle Join MERGEJOIN[601][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3]] in Stage 'Reducer 8' is a cross product
+Warning: Shuffle Join MERGEJOIN[602][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3, $hdt$_4]] in Stage 'Reducer 9' is a cross product
+Warning: Shuffle Join MERGEJOIN[603][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3, $hdt$_4, $hdt$_5]] in Stage 'Reducer 10' is a cross product
+Warning: Shuffle Join MERGEJOIN[604][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3, $hdt$_4, $hdt$_5, $hdt$_6]] in Stage 'Reducer 11' is a cross product
+Warning: Shuffle Join MERGEJOIN[605][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3, $hdt$_4, $hdt$_5, $hdt$_6, $hdt$_7]] in Stage 'Reducer 12' is a cross product
+PREHOOK: query: explain cbo
+select *
+from
+ (select count(*) h8_30_to_9
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 8
+ and time_dim.t_minute >= 30
+ and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
+ (household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2))
+ and store.s_store_name = 'ese') s1,
+ (select count(*) h9_to_9_30
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 9
+ and time_dim.t_minute < 30
+ and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
+ (household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2))
+ and store.s_store_name = 'ese') s2,
+ (select count(*) h9_30_to_10
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 9
+ and time_dim.t_minute >= 30
+ and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
+ (household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2))
+ and store.s_store_name = 'ese') s3,
+ (select count(*) h10_to_10_30
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 10
+ and time_dim.t_minute < 30
+ and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
+ (household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2))
+ and store.s_store_name = 'ese') s4,
+ (select count(*) h10_30_to_11
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 10
+ and time_dim.t_minute >= 30
+ and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
+ (household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2))
+ and store.s_store_name = 'ese') s5,
+ (select count(*) h11_to_11_30
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 11
+ and time_dim.t_minute < 30
+ and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
+ (household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2))
+ and store.s_store_name = 'ese') s6,
+ (select count(*) h11_30_to_12
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 11
+ and time_dim.t_minute >= 30
+ and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
+ (household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2))
+ and store.s_store_name = 'ese') s7,
+ (select count(*) h12_to_12_30
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 12
+ and time_dim.t_minute < 30
+ and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
+ (household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2))
+ and store.s_store_name = 'ese') s8
+PREHOOK: type: QUERY
+PREHOOK: Input: default@household_demographics
+PREHOOK: Input: default@store
+PREHOOK: Input: default@store_sales
+PREHOOK: Input: default@time_dim
+PREHOOK: Output: hdfs://### HDFS PATH ###
+POSTHOOK: query: explain cbo
+select *
+from
+ (select count(*) h8_30_to_9
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 8
+ and time_dim.t_minute >= 30
+ and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
+ (household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2))
+ and store.s_store_name = 'ese') s1,
+ (select count(*) h9_to_9_30
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 9
+ and time_dim.t_minute < 30
+ and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
+ (household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2))
+ and store.s_store_name = 'ese') s2,
+ (select count(*) h9_30_to_10
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 9
+ and time_dim.t_minute >= 30
+ and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
+ (household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2))
+ and store.s_store_name = 'ese') s3,
+ (select count(*) h10_to_10_30
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 10
+ and time_dim.t_minute < 30
+ and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
+ (household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2))
+ and store.s_store_name = 'ese') s4,
+ (select count(*) h10_30_to_11
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 10
+ and time_dim.t_minute >= 30
+ and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
+ (household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2))
+ and store.s_store_name = 'ese') s5,
+ (select count(*) h11_to_11_30
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 11
+ and time_dim.t_minute < 30
+ and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
+ (household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2))
+ and store.s_store_name = 'ese') s6,
+ (select count(*) h11_30_to_12
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 11
+ and time_dim.t_minute >= 30
+ and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
+ (household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2))
+ and store.s_store_name = 'ese') s7,
+ (select count(*) h12_to_12_30
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 12
+ and time_dim.t_minute < 30
+ and ((household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2) or
+ (household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2))
+ and store.s_store_name = 'ese') s8
+POSTHOOK: type: QUERY
+POSTHOOK: Input: default@household_demographics
+POSTHOOK: Input: default@store
+POSTHOOK: Input: default@store_sales
+POSTHOOK: Input: default@time_dim
+POSTHOOK: Output: hdfs://### HDFS PATH ###
+CBO PLAN:
+HiveProject($f0=[$0], $f00=[$7], $f01=[$6], $f02=[$5], $f03=[$4], $f04=[$3], $f05=[$2], $f06=[$1])
+ HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject($f0=[$0])
+ HiveAggregate(group=[{}], agg#0=[count()])
+ HiveJoin(condition=[=($2, $5)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($0, $4)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($1, $3)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ss_sold_time_sk=[$1], ss_hdemo_sk=[$5], ss_store_sk=[$7])
+ HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject(hd_demo_sk=[$0])
+ HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))])
+ HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics])
+ HiveProject(t_time_sk=[$0])
+ HiveFilter(condition=[AND(=($3, 8), >=($4, 30))])
+ HiveTableScan(table=[[default, time_dim]], table:alias=[time_dim])
+ HiveProject(s_store_sk=[$0])
+ HiveFilter(condition=[=($5, _UTF-16LE'ese')])
+ HiveTableScan(table=[[default, store]], table:alias=[store])
+ HiveProject($f0=[$0])
+ HiveAggregate(group=[{}], agg#0=[count()])
+ HiveJoin(condition=[=($2, $5)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($0, $4)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($1, $3)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ss_sold_time_sk=[$1], ss_hdemo_sk=[$5], ss_store_sk=[$7])
+ HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject(hd_demo_sk=[$0])
+ HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))])
+ HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics])
+ HiveProject(t_time_sk=[$0])
+ HiveFilter(condition=[AND(=($3, 12), <($4, 30))])
+ HiveTableScan(table=[[default, time_dim]], table:alias=[time_dim])
+ HiveProject(s_store_sk=[$0])
+ HiveFilter(condition=[=($5, _UTF-16LE'ese')])
+ HiveTableScan(table=[[default, store]], table:alias=[store])
+ HiveProject($f0=[$0])
+ HiveAggregate(group=[{}], agg#0=[count()])
+ HiveJoin(condition=[=($2, $5)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($0, $4)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($1, $3)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ss_sold_time_sk=[$1], ss_hdemo_sk=[$5], ss_store_sk=[$7])
+ HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject(hd_demo_sk=[$0])
+ HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))])
+ HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics])
+ HiveProject(t_time_sk=[$0])
+ HiveFilter(condition=[AND(=($3, 11), >=($4, 30))])
+ HiveTableScan(table=[[default, time_dim]], table:alias=[time_dim])
+ HiveProject(s_store_sk=[$0])
+ HiveFilter(condition=[=($5, _UTF-16LE'ese')])
+ HiveTableScan(table=[[default, store]], table:alias=[store])
+ HiveProject($f0=[$0])
+ HiveAggregate(group=[{}], agg#0=[count()])
+ HiveJoin(condition=[=($2, $5)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($0, $4)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($1, $3)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ss_sold_time_sk=[$1], ss_hdemo_sk=[$5], ss_store_sk=[$7])
+ HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject(hd_demo_sk=[$0])
+ HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))])
+ HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics])
+ HiveProject(t_time_sk=[$0])
+ HiveFilter(condition=[AND(=($3, 11), <($4, 30))])
+ HiveTableScan(table=[[default, time_dim]], table:alias=[time_dim])
+ HiveProject(s_store_sk=[$0])
+ HiveFilter(condition=[=($5, _UTF-16LE'ese')])
+ HiveTableScan(table=[[default, store]], table:alias=[store])
+ HiveProject($f0=[$0])
+ HiveAggregate(group=[{}], agg#0=[count()])
+ HiveJoin(condition=[=($2, $5)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($0, $4)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($1, $3)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ss_sold_time_sk=[$1], ss_hdemo_sk=[$5], ss_store_sk=[$7])
+ HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject(hd_demo_sk=[$0])
+ HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))])
+ HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics])
+ HiveProject(t_time_sk=[$0])
+ HiveFilter(condition=[AND(=($3, 10), >=($4, 30))])
+ HiveTableScan(table=[[default, time_dim]], table:alias=[time_dim])
+ HiveProject(s_store_sk=[$0])
+ HiveFilter(condition=[=($5, _UTF-16LE'ese')])
+ HiveTableScan(table=[[default, store]], table:alias=[store])
+ HiveProject($f0=[$0])
+ HiveAggregate(group=[{}], agg#0=[count()])
+ HiveJoin(condition=[=($2, $5)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($0, $4)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($1, $3)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ss_sold_time_sk=[$1], ss_hdemo_sk=[$5], ss_store_sk=[$7])
+ HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject(hd_demo_sk=[$0])
+ HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))])
+ HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics])
+ HiveProject(t_time_sk=[$0])
+ HiveFilter(condition=[AND(=($3, 10), <($4, 30))])
+ HiveTableScan(table=[[default, time_dim]], table:alias=[time_dim])
+ HiveProject(s_store_sk=[$0])
+ HiveFilter(condition=[=($5, _UTF-16LE'ese')])
+ HiveTableScan(table=[[default, store]], table:alias=[store])
+ HiveProject($f0=[$0])
+ HiveAggregate(group=[{}], agg#0=[count()])
+ HiveJoin(condition=[=($2, $5)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($0, $4)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($1, $3)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ss_sold_time_sk=[$1], ss_hdemo_sk=[$5], ss_store_sk=[$7])
+ HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject(hd_demo_sk=[$0])
+ HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))])
+ HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics])
+ HiveProject(t_time_sk=[$0])
+ HiveFilter(condition=[AND(=($3, 9), >=($4, 30))])
+ HiveTableScan(table=[[default, time_dim]], table:alias=[time_dim])
+ HiveProject(s_store_sk=[$0])
+ HiveFilter(condition=[=($5, _UTF-16LE'ese')])
+ HiveTableScan(table=[[default, store]], table:alias=[store])
+ HiveProject($f0=[$0])
+ HiveAggregate(group=[{}], agg#0=[count()])
+ HiveJoin(condition=[=($2, $5)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($0, $4)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($1, $3)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ss_sold_time_sk=[$1], ss_hdemo_sk=[$5], ss_store_sk=[$7])
+ HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject(hd_demo_sk=[$0])
+ HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))])
+ HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics])
+ HiveProject(t_time_sk=[$0])
+ HiveFilter(condition=[AND(=($3, 9), <($4, 30))])
+ HiveTableScan(table=[[default, time_dim]], table:alias=[time_dim])
+ HiveProject(s_store_sk=[$0])
+ HiveFilter(condition=[=($5, _UTF-16LE'ese')])
+ HiveTableScan(table=[[default, store]], table:alias=[store])
+
http://git-wip-us.apache.org/repos/asf/hive/blob/b8299551/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query89.q.out
----------------------------------------------------------------------
diff --git a/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query89.q.out b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query89.q.out
new file mode 100644
index 0000000..d9c7d42
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query89.q.out
@@ -0,0 +1,87 @@
+PREHOOK: query: explain cbo
+select *
+from(
+select i_category, i_class, i_brand,
+ s_store_name, s_company_name,
+ d_moy,
+ sum(ss_sales_price) sum_sales,
+ avg(sum(ss_sales_price)) over
+ (partition by i_category, i_brand, s_store_name, s_company_name)
+ avg_monthly_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_year in (2000) and
+ ((i_category in ('Home','Books','Electronics') and
+ i_class in ('wallpaper','parenting','musical')
+ )
+ or (i_category in ('Shoes','Jewelry','Men') and
+ i_class in ('womens','birdal','pants')
+ ))
+group by i_category, i_class, i_brand,
+ s_store_name, s_company_name, d_moy) tmp1
+where 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, s_store_name
+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_category, i_class, i_brand,
+ s_store_name, s_company_name,
+ d_moy,
+ sum(ss_sales_price) sum_sales,
+ avg(sum(ss_sales_price)) over
+ (partition by i_category, i_brand, s_store_name, s_company_name)
+ avg_monthly_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_year in (2000) and
+ ((i_category in ('Home','Books','Electronics') and
+ i_class in ('wallpaper','parenting','musical')
+ )
+ or (i_category in ('Shoes','Jewelry','Men') and
+ i_class in ('womens','birdal','pants')
+ ))
+group by i_category, i_class, i_brand,
+ s_store_name, s_company_name, d_moy) tmp1
+where 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, s_store_name
+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:
+HiveProject(i_category=[$0], i_class=[$1], i_brand=[$2], s_store_name=[$3], s_company_name=[$4], d_moy=[$5], sum_sales=[$6], avg_monthly_sales=[$7])
+ HiveSortLimit(sort0=[$8], sort1=[$3], dir0=[ASC], dir1=[ASC], fetch=[100])
+ HiveProject(i_category=[$0], i_class=[$1], i_brand=[$2], s_store_name=[$3], s_company_name=[$4], d_moy=[$5], sum_sales=[$6], avg_monthly_sales=[$7], (- (tok_table_or_col sum_sales) (tok_table_or_col avg_monthly_sales))=[-($6, $7)])
+ HiveFilter(condition=[CASE(<>($7, 0), >(/(ABS(-($6, $7)), $7), 0.1), null)])
+ HiveProject((tok_table_or_col i_category)=[$2], (tok_table_or_col i_class)=[$1], (tok_table_or_col i_brand)=[$0], (tok_table_or_col s_store_name)=[$4], (tok_table_or_col s_company_name)=[$5], (tok_table_or_col d_moy)=[$3], (tok_function sum (tok_table_or_col ss_sales_price))=[$6], avg_window_0=[avg($6) OVER (PARTITION BY $2, $0, $4, $5 ORDER BY $2 NULLS FIRST, $0 NULLS FIRST, $4 NULLS FIRST, $5 NULLS FIRST ROWS BETWEEN 2147483647 FOLLOWING AND 2147483647 PRECEDING)])
+ HiveProject(i_brand=[$0], i_class=[$1], i_category=[$2], d_moy=[$3], s_store_name=[$4], s_company_name=[$5], $f6=[$6])
+ HiveAggregate(group=[{5, 6, 7, 9, 11, 12}], agg#0=[sum($3)])
+ HiveJoin(condition=[=($2, $10)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($0, $8)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[=($1, $4)], joinType=[inner], algorithm=[none], cost=[not available])
+ HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$2], 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(i_item_sk=[$0], i_brand=[$8], i_class=[$10], i_category=[$12])
+ HiveFilter(condition=[AND(IN($10, _UTF-16LE'wallpaper', _UTF-16LE'parenting', _UTF-16LE'musical', _UTF-16LE'womens', _UTF-16LE'birdal', _UTF-16LE'pants'), IN($12, _UTF-16LE'Home', _UTF-16LE'Books', _UTF-16LE'Electronics', _UTF-16LE'Shoes', _UTF-16LE'Jewelry', _UTF-16LE'Men'), OR(AND(IN($12, _UTF-16LE'Home', _UTF-16LE'Books', _UTF-16LE'Electronics'), IN($10, _UTF-16LE'wallpaper', _UTF-16LE'parenting', _UTF-16LE'musical')), AND(IN($12, _UTF-16LE'Shoes', _UTF-16LE'Jewelry', _UTF-16LE'Men'), IN($10, _UTF-16LE'womens', _UTF-16LE'birdal', _UTF-16LE'pants'))))])
+ HiveTableScan(table=[[default, item]], table:alias=[item])
+ HiveProject(d_date_sk=[$0], d_moy=[$8])
+ HiveFilter(condition=[=($6, 2000)])
+ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim])
+ HiveProject(s_store_sk=[$0], s_store_name=[$5], s_company_name=[$17])
+ HiveTableScan(table=[[default, store]], table:alias=[store])
+
http://git-wip-us.apache.org/repos/asf/hive/blob/b8299551/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query9.q.out
----------------------------------------------------------------------
diff --git a/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query9.q.out b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query9.q.out
new file mode 100644
index 0000000..4a92def
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query9.q.out
@@ -0,0 +1,200 @@
+Warning: Shuffle Join MERGEJOIN[171][tables = [$hdt$_0, $hdt$_1]] in Stage 'Reducer 2' is a cross product
+Warning: Shuffle Join MERGEJOIN[172][tables = [$hdt$_0, $hdt$_1, $hdt$_2]] in Stage 'Reducer 3' is a cross product
+Warning: Shuffle Join MERGEJOIN[173][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3]] in Stage 'Reducer 4' is a cross product
+Warning: Shuffle Join MERGEJOIN[174][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3, $hdt$_4]] in Stage 'Reducer 5' is a cross product
+Warning: Shuffle Join MERGEJOIN[175][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3, $hdt$_4, $hdt$_5]] in Stage 'Reducer 6' is a cross product
+Warning: Shuffle Join MERGEJOIN[176][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3, $hdt$_4, $hdt$_5, $hdt$_6]] in Stage 'Reducer 7' is a cross product
+Warning: Shuffle Join MERGEJOIN[177][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3, $hdt$_4, $hdt$_5, $hdt$_6, $hdt$_7]] in Stage 'Reducer 8' is a cross product
+Warning: Shuffle Join MERGEJOIN[178][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3, $hdt$_4, $hdt$_5, $hdt$_6, $hdt$_7, $hdt$_8]] in Stage 'Reducer 9' is a cross product
+Warning: Shuffle Join MERGEJOIN[179][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3, $hdt$_4, $hdt$_5, $hdt$_6, $hdt$_7, $hdt$_8, $hdt$_9]] in Stage 'Reducer 10' is a cross product
+Warning: Shuffle Join MERGEJOIN[180][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3, $hdt$_4, $hdt$_5, $hdt$_6, $hdt$_7, $hdt$_8, $hdt$_9, $hdt$_10]] in Stage 'Reducer 11' is a cross product
+Warning: Shuffle Join MERGEJOIN[181][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3, $hdt$_4, $hdt$_5, $hdt$_6, $hdt$_7, $hdt$_8, $hdt$_9, $hdt$_10, $hdt$_11]] in Stage 'Reducer 12' is a cross product
+Warning: Shuffle Join MERGEJOIN[182][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3, $hdt$_4, $hdt$_5, $hdt$_6, $hdt$_7, $hdt$_8, $hdt$_9, $hdt$_10, $hdt$_11, $hdt$_12]] in Stage 'Reducer 13' is a cross product
+Warning: Shuffle Join MERGEJOIN[183][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3, $hdt$_4, $hdt$_5, $hdt$_6, $hdt$_7, $hdt$_8, $hdt$_9, $hdt$_10, $hdt$_11, $hdt$_12, $hdt$_13]] in Stage 'Reducer 14' is a cross product
+Warning: Shuffle Join MERGEJOIN[184][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3, $hdt$_4, $hdt$_5, $hdt$_6, $hdt$_7, $hdt$_8, $hdt$_9, $hdt$_10, $hdt$_11, $hdt$_12, $hdt$_13, $hdt$_14]] in Stage 'Reducer 15' is a cross product
+Warning: Shuffle Join MERGEJOIN[185][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3, $hdt$_4, $hdt$_5, $hdt$_6, $hdt$_7, $hdt$_8, $hdt$_9, $hdt$_10, $hdt$_11, $hdt$_12, $hdt$_13, $hdt$_14, $hdt$_15]] in Stage 'Reducer 16' is a cross product
+PREHOOK: query: explain cbo
+select case when (select count(*)
+ from store_sales
+ where ss_quantity between 1 and 20) > 409437
+ then (select avg(ss_ext_list_price)
+ from store_sales
+ where ss_quantity between 1 and 20)
+ else (select avg(ss_net_paid_inc_tax)
+ from store_sales
+ where ss_quantity between 1 and 20) end bucket1 ,
+ case when (select count(*)
+ from store_sales
+ where ss_quantity between 21 and 40) > 4595804
+ then (select avg(ss_ext_list_price)
+ from store_sales
+ where ss_quantity between 21 and 40)
+ else (select avg(ss_net_paid_inc_tax)
+ from store_sales
+ where ss_quantity between 21 and 40) end bucket2,
+ case when (select count(*)
+ from store_sales
+ where ss_quantity between 41 and 60) > 7887297
+ then (select avg(ss_ext_list_price)
+ from store_sales
+ where ss_quantity between 41 and 60)
+ else (select avg(ss_net_paid_inc_tax)
+ from store_sales
+ where ss_quantity between 41 and 60) end bucket3,
+ case when (select count(*)
+ from store_sales
+ where ss_quantity between 61 and 80) > 10872978
+ then (select avg(ss_ext_list_price)
+ from store_sales
+ where ss_quantity between 61 and 80)
+ else (select avg(ss_net_paid_inc_tax)
+ from store_sales
+ where ss_quantity between 61 and 80) end bucket4,
+ case when (select count(*)
+ from store_sales
+ where ss_quantity between 81 and 100) > 43571537
+ then (select avg(ss_ext_list_price)
+ from store_sales
+ where ss_quantity between 81 and 100)
+ else (select avg(ss_net_paid_inc_tax)
+ from store_sales
+ where ss_quantity between 81 and 100) end bucket5
+from reason
+where r_reason_sk = 1
+PREHOOK: type: QUERY
+PREHOOK: Input: default@reason
+PREHOOK: Input: default@store_sales
+PREHOOK: Output: hdfs://### HDFS PATH ###
+POSTHOOK: query: explain cbo
+select case when (select count(*)
+ from store_sales
+ where ss_quantity between 1 and 20) > 409437
+ then (select avg(ss_ext_list_price)
+ from store_sales
+ where ss_quantity between 1 and 20)
+ else (select avg(ss_net_paid_inc_tax)
+ from store_sales
+ where ss_quantity between 1 and 20) end bucket1 ,
+ case when (select count(*)
+ from store_sales
+ where ss_quantity between 21 and 40) > 4595804
+ then (select avg(ss_ext_list_price)
+ from store_sales
+ where ss_quantity between 21 and 40)
+ else (select avg(ss_net_paid_inc_tax)
+ from store_sales
+ where ss_quantity between 21 and 40) end bucket2,
+ case when (select count(*)
+ from store_sales
+ where ss_quantity between 41 and 60) > 7887297
+ then (select avg(ss_ext_list_price)
+ from store_sales
+ where ss_quantity between 41 and 60)
+ else (select avg(ss_net_paid_inc_tax)
+ from store_sales
+ where ss_quantity between 41 and 60) end bucket3,
+ case when (select count(*)
+ from store_sales
+ where ss_quantity between 61 and 80) > 10872978
+ then (select avg(ss_ext_list_price)
+ from store_sales
+ where ss_quantity between 61 and 80)
+ else (select avg(ss_net_paid_inc_tax)
+ from store_sales
+ where ss_quantity between 61 and 80) end bucket4,
+ case when (select count(*)
+ from store_sales
+ where ss_quantity between 81 and 100) > 43571537
+ then (select avg(ss_ext_list_price)
+ from store_sales
+ where ss_quantity between 81 and 100)
+ else (select avg(ss_net_paid_inc_tax)
+ from store_sales
+ where ss_quantity between 81 and 100) end bucket5
+from reason
+where r_reason_sk = 1
+POSTHOOK: type: QUERY
+POSTHOOK: Input: default@reason
+POSTHOOK: Input: default@store_sales
+POSTHOOK: Output: hdfs://### HDFS PATH ###
+CBO PLAN:
+HiveProject(bucket1=[CASE($1, $2, $3)], bucket2=[CASE($4, $5, $6)], bucket3=[CASE($7, $8, $9)], bucket4=[CASE($10, $11, $12)], bucket5=[CASE($13, $14, $15)])
+ HiveJoin(condition=[true], joinType=[left], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[true], joinType=[left], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[true], joinType=[left], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[true], joinType=[left], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[true], joinType=[left], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[true], joinType=[left], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[true], joinType=[left], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[true], joinType=[left], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[true], joinType=[left], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[true], joinType=[left], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[true], joinType=[left], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[true], joinType=[left], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[true], joinType=[left], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[true], joinType=[left], algorithm=[none], cost=[not available])
+ HiveJoin(condition=[true], joinType=[left], algorithm=[none], cost=[not available])
+ HiveProject(r_reason_sk=[1])
+ HiveFilter(condition=[=($0, 1)])
+ HiveTableScan(table=[[default, reason]], table:alias=[reason])
+ HiveProject(>=[>($0, 409437)])
+ HiveAggregate(group=[{}], agg#0=[count()])
+ HiveFilter(condition=[BETWEEN(false, $10, 1, 20)])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject($f0=[/($0, $1)])
+ HiveAggregate(group=[{}], agg#0=[sum($17)], agg#1=[count($17)])
+ HiveFilter(condition=[BETWEEN(false, $10, 1, 20)])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject($f0=[/($0, $1)])
+ HiveAggregate(group=[{}], agg#0=[sum($21)], agg#1=[count($21)])
+ HiveFilter(condition=[BETWEEN(false, $10, 1, 20)])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject(>=[>($0, 4595804)])
+ HiveAggregate(group=[{}], agg#0=[count()])
+ HiveFilter(condition=[BETWEEN(false, $10, 21, 40)])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject($f0=[/($0, $1)])
+ HiveAggregate(group=[{}], agg#0=[sum($17)], agg#1=[count($17)])
+ HiveFilter(condition=[BETWEEN(false, $10, 21, 40)])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject($f0=[/($0, $1)])
+ HiveAggregate(group=[{}], agg#0=[sum($21)], agg#1=[count($21)])
+ HiveFilter(condition=[BETWEEN(false, $10, 21, 40)])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject(>=[>($0, 7887297)])
+ HiveAggregate(group=[{}], agg#0=[count()])
+ HiveFilter(condition=[BETWEEN(false, $10, 41, 60)])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject($f0=[/($0, $1)])
+ HiveAggregate(group=[{}], agg#0=[sum($17)], agg#1=[count($17)])
+ HiveFilter(condition=[BETWEEN(false, $10, 41, 60)])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject($f0=[/($0, $1)])
+ HiveAggregate(group=[{}], agg#0=[sum($21)], agg#1=[count($21)])
+ HiveFilter(condition=[BETWEEN(false, $10, 41, 60)])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject(>=[>($0, 10872978)])
+ HiveAggregate(group=[{}], agg#0=[count()])
+ HiveFilter(condition=[BETWEEN(false, $10, 61, 80)])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject($f0=[/($0, $1)])
+ HiveAggregate(group=[{}], agg#0=[sum($17)], agg#1=[count($17)])
+ HiveFilter(condition=[BETWEEN(false, $10, 61, 80)])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject($f0=[/($0, $1)])
+ HiveAggregate(group=[{}], agg#0=[sum($21)], agg#1=[count($21)])
+ HiveFilter(condition=[BETWEEN(false, $10, 61, 80)])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject(>=[>($0, 43571537)])
+ HiveAggregate(group=[{}], agg#0=[count()])
+ HiveFilter(condition=[BETWEEN(false, $10, 81, 100)])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject($f0=[/($0, $1)])
+ HiveAggregate(group=[{}], agg#0=[sum($17)], agg#1=[count($17)])
+ HiveFilter(condition=[BETWEEN(false, $10, 81, 100)])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+ HiveProject($f0=[/($0, $1)])
+ HiveAggregate(group=[{}], agg#0=[sum($21)], agg#1=[count($21)])
+ HiveFilter(condition=[BETWEEN(false, $10, 81, 100)])
+ HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales])
+