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Posted to commits@hive.apache.org by se...@apache.org on 2017/09/29 03:36:09 UTC
[18/48] hive git commit: HIVE-17543: Enable PerfCliDriver for HoS
(Sahil Takiar, reviewed by Peter Vary)
http://git-wip-us.apache.org/repos/asf/hive/blob/bd371246/ql/src/test/results/clientpositive/perf/spark/query66.q.out
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diff --git a/ql/src/test/results/clientpositive/perf/spark/query66.q.out b/ql/src/test/results/clientpositive/perf/spark/query66.q.out
new file mode 100644
index 0000000..1dc0fac
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/spark/query66.q.out
@@ -0,0 +1,873 @@
+PREHOOK: query: explain
+select
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,ship_carriers
+ ,year
+ ,sum(jan_sales) as jan_sales
+ ,sum(feb_sales) as feb_sales
+ ,sum(mar_sales) as mar_sales
+ ,sum(apr_sales) as apr_sales
+ ,sum(may_sales) as may_sales
+ ,sum(jun_sales) as jun_sales
+ ,sum(jul_sales) as jul_sales
+ ,sum(aug_sales) as aug_sales
+ ,sum(sep_sales) as sep_sales
+ ,sum(oct_sales) as oct_sales
+ ,sum(nov_sales) as nov_sales
+ ,sum(dec_sales) as dec_sales
+ ,sum(jan_sales/w_warehouse_sq_ft) as jan_sales_per_sq_foot
+ ,sum(feb_sales/w_warehouse_sq_ft) as feb_sales_per_sq_foot
+ ,sum(mar_sales/w_warehouse_sq_ft) as mar_sales_per_sq_foot
+ ,sum(apr_sales/w_warehouse_sq_ft) as apr_sales_per_sq_foot
+ ,sum(may_sales/w_warehouse_sq_ft) as may_sales_per_sq_foot
+ ,sum(jun_sales/w_warehouse_sq_ft) as jun_sales_per_sq_foot
+ ,sum(jul_sales/w_warehouse_sq_ft) as jul_sales_per_sq_foot
+ ,sum(aug_sales/w_warehouse_sq_ft) as aug_sales_per_sq_foot
+ ,sum(sep_sales/w_warehouse_sq_ft) as sep_sales_per_sq_foot
+ ,sum(oct_sales/w_warehouse_sq_ft) as oct_sales_per_sq_foot
+ ,sum(nov_sales/w_warehouse_sq_ft) as nov_sales_per_sq_foot
+ ,sum(dec_sales/w_warehouse_sq_ft) as dec_sales_per_sq_foot
+ ,sum(jan_net) as jan_net
+ ,sum(feb_net) as feb_net
+ ,sum(mar_net) as mar_net
+ ,sum(apr_net) as apr_net
+ ,sum(may_net) as may_net
+ ,sum(jun_net) as jun_net
+ ,sum(jul_net) as jul_net
+ ,sum(aug_net) as aug_net
+ ,sum(sep_net) as sep_net
+ ,sum(oct_net) as oct_net
+ ,sum(nov_net) as nov_net
+ ,sum(dec_net) as dec_net
+ from (
+ (select
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,'DIAMOND' || ',' || 'AIRBORNE' as ship_carriers
+ ,d_year as year
+ ,sum(case when d_moy = 1
+ then ws_sales_price* ws_quantity else 0 end) as jan_sales
+ ,sum(case when d_moy = 2
+ then ws_sales_price* ws_quantity else 0 end) as feb_sales
+ ,sum(case when d_moy = 3
+ then ws_sales_price* ws_quantity else 0 end) as mar_sales
+ ,sum(case when d_moy = 4
+ then ws_sales_price* ws_quantity else 0 end) as apr_sales
+ ,sum(case when d_moy = 5
+ then ws_sales_price* ws_quantity else 0 end) as may_sales
+ ,sum(case when d_moy = 6
+ then ws_sales_price* ws_quantity else 0 end) as jun_sales
+ ,sum(case when d_moy = 7
+ then ws_sales_price* ws_quantity else 0 end) as jul_sales
+ ,sum(case when d_moy = 8
+ then ws_sales_price* ws_quantity else 0 end) as aug_sales
+ ,sum(case when d_moy = 9
+ then ws_sales_price* ws_quantity else 0 end) as sep_sales
+ ,sum(case when d_moy = 10
+ then ws_sales_price* ws_quantity else 0 end) as oct_sales
+ ,sum(case when d_moy = 11
+ then ws_sales_price* ws_quantity else 0 end) as nov_sales
+ ,sum(case when d_moy = 12
+ then ws_sales_price* ws_quantity else 0 end) as dec_sales
+ ,sum(case when d_moy = 1
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as jan_net
+ ,sum(case when d_moy = 2
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as feb_net
+ ,sum(case when d_moy = 3
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as mar_net
+ ,sum(case when d_moy = 4
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as apr_net
+ ,sum(case when d_moy = 5
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as may_net
+ ,sum(case when d_moy = 6
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as jun_net
+ ,sum(case when d_moy = 7
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as jul_net
+ ,sum(case when d_moy = 8
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as aug_net
+ ,sum(case when d_moy = 9
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as sep_net
+ ,sum(case when d_moy = 10
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as oct_net
+ ,sum(case when d_moy = 11
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as nov_net
+ ,sum(case when d_moy = 12
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as dec_net
+ from
+ web_sales
+ ,warehouse
+ ,date_dim
+ ,time_dim
+ ,ship_mode
+ where
+ ws_warehouse_sk = w_warehouse_sk
+ and ws_sold_date_sk = d_date_sk
+ and ws_sold_time_sk = t_time_sk
+ and ws_ship_mode_sk = sm_ship_mode_sk
+ and d_year = 2002
+ and t_time between 49530 and 49530+28800
+ and sm_carrier in ('DIAMOND','AIRBORNE')
+ group by
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,d_year
+ )
+ union all
+ (select
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,'DIAMOND' || ',' || 'AIRBORNE' as ship_carriers
+ ,d_year as year
+ ,sum(case when d_moy = 1
+ then cs_ext_sales_price* cs_quantity else 0 end) as jan_sales
+ ,sum(case when d_moy = 2
+ then cs_ext_sales_price* cs_quantity else 0 end) as feb_sales
+ ,sum(case when d_moy = 3
+ then cs_ext_sales_price* cs_quantity else 0 end) as mar_sales
+ ,sum(case when d_moy = 4
+ then cs_ext_sales_price* cs_quantity else 0 end) as apr_sales
+ ,sum(case when d_moy = 5
+ then cs_ext_sales_price* cs_quantity else 0 end) as may_sales
+ ,sum(case when d_moy = 6
+ then cs_ext_sales_price* cs_quantity else 0 end) as jun_sales
+ ,sum(case when d_moy = 7
+ then cs_ext_sales_price* cs_quantity else 0 end) as jul_sales
+ ,sum(case when d_moy = 8
+ then cs_ext_sales_price* cs_quantity else 0 end) as aug_sales
+ ,sum(case when d_moy = 9
+ then cs_ext_sales_price* cs_quantity else 0 end) as sep_sales
+ ,sum(case when d_moy = 10
+ then cs_ext_sales_price* cs_quantity else 0 end) as oct_sales
+ ,sum(case when d_moy = 11
+ then cs_ext_sales_price* cs_quantity else 0 end) as nov_sales
+ ,sum(case when d_moy = 12
+ then cs_ext_sales_price* cs_quantity else 0 end) as dec_sales
+ ,sum(case when d_moy = 1
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as jan_net
+ ,sum(case when d_moy = 2
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as feb_net
+ ,sum(case when d_moy = 3
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as mar_net
+ ,sum(case when d_moy = 4
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as apr_net
+ ,sum(case when d_moy = 5
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as may_net
+ ,sum(case when d_moy = 6
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as jun_net
+ ,sum(case when d_moy = 7
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as jul_net
+ ,sum(case when d_moy = 8
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as aug_net
+ ,sum(case when d_moy = 9
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as sep_net
+ ,sum(case when d_moy = 10
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as oct_net
+ ,sum(case when d_moy = 11
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as nov_net
+ ,sum(case when d_moy = 12
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as dec_net
+ from
+ catalog_sales
+ ,warehouse
+ ,date_dim
+ ,time_dim
+ ,ship_mode
+ where
+ cs_warehouse_sk = w_warehouse_sk
+ and cs_sold_date_sk = d_date_sk
+ and cs_sold_time_sk = t_time_sk
+ and cs_ship_mode_sk = sm_ship_mode_sk
+ and d_year = 2002
+ and t_time between 49530 AND 49530+28800
+ and sm_carrier in ('DIAMOND','AIRBORNE')
+ group by
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,d_year
+ )
+ ) x
+ group by
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,ship_carriers
+ ,year
+ order by w_warehouse_name
+ limit 100
+PREHOOK: type: QUERY
+POSTHOOK: query: explain
+select
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,ship_carriers
+ ,year
+ ,sum(jan_sales) as jan_sales
+ ,sum(feb_sales) as feb_sales
+ ,sum(mar_sales) as mar_sales
+ ,sum(apr_sales) as apr_sales
+ ,sum(may_sales) as may_sales
+ ,sum(jun_sales) as jun_sales
+ ,sum(jul_sales) as jul_sales
+ ,sum(aug_sales) as aug_sales
+ ,sum(sep_sales) as sep_sales
+ ,sum(oct_sales) as oct_sales
+ ,sum(nov_sales) as nov_sales
+ ,sum(dec_sales) as dec_sales
+ ,sum(jan_sales/w_warehouse_sq_ft) as jan_sales_per_sq_foot
+ ,sum(feb_sales/w_warehouse_sq_ft) as feb_sales_per_sq_foot
+ ,sum(mar_sales/w_warehouse_sq_ft) as mar_sales_per_sq_foot
+ ,sum(apr_sales/w_warehouse_sq_ft) as apr_sales_per_sq_foot
+ ,sum(may_sales/w_warehouse_sq_ft) as may_sales_per_sq_foot
+ ,sum(jun_sales/w_warehouse_sq_ft) as jun_sales_per_sq_foot
+ ,sum(jul_sales/w_warehouse_sq_ft) as jul_sales_per_sq_foot
+ ,sum(aug_sales/w_warehouse_sq_ft) as aug_sales_per_sq_foot
+ ,sum(sep_sales/w_warehouse_sq_ft) as sep_sales_per_sq_foot
+ ,sum(oct_sales/w_warehouse_sq_ft) as oct_sales_per_sq_foot
+ ,sum(nov_sales/w_warehouse_sq_ft) as nov_sales_per_sq_foot
+ ,sum(dec_sales/w_warehouse_sq_ft) as dec_sales_per_sq_foot
+ ,sum(jan_net) as jan_net
+ ,sum(feb_net) as feb_net
+ ,sum(mar_net) as mar_net
+ ,sum(apr_net) as apr_net
+ ,sum(may_net) as may_net
+ ,sum(jun_net) as jun_net
+ ,sum(jul_net) as jul_net
+ ,sum(aug_net) as aug_net
+ ,sum(sep_net) as sep_net
+ ,sum(oct_net) as oct_net
+ ,sum(nov_net) as nov_net
+ ,sum(dec_net) as dec_net
+ from (
+ (select
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,'DIAMOND' || ',' || 'AIRBORNE' as ship_carriers
+ ,d_year as year
+ ,sum(case when d_moy = 1
+ then ws_sales_price* ws_quantity else 0 end) as jan_sales
+ ,sum(case when d_moy = 2
+ then ws_sales_price* ws_quantity else 0 end) as feb_sales
+ ,sum(case when d_moy = 3
+ then ws_sales_price* ws_quantity else 0 end) as mar_sales
+ ,sum(case when d_moy = 4
+ then ws_sales_price* ws_quantity else 0 end) as apr_sales
+ ,sum(case when d_moy = 5
+ then ws_sales_price* ws_quantity else 0 end) as may_sales
+ ,sum(case when d_moy = 6
+ then ws_sales_price* ws_quantity else 0 end) as jun_sales
+ ,sum(case when d_moy = 7
+ then ws_sales_price* ws_quantity else 0 end) as jul_sales
+ ,sum(case when d_moy = 8
+ then ws_sales_price* ws_quantity else 0 end) as aug_sales
+ ,sum(case when d_moy = 9
+ then ws_sales_price* ws_quantity else 0 end) as sep_sales
+ ,sum(case when d_moy = 10
+ then ws_sales_price* ws_quantity else 0 end) as oct_sales
+ ,sum(case when d_moy = 11
+ then ws_sales_price* ws_quantity else 0 end) as nov_sales
+ ,sum(case when d_moy = 12
+ then ws_sales_price* ws_quantity else 0 end) as dec_sales
+ ,sum(case when d_moy = 1
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as jan_net
+ ,sum(case when d_moy = 2
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as feb_net
+ ,sum(case when d_moy = 3
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as mar_net
+ ,sum(case when d_moy = 4
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as apr_net
+ ,sum(case when d_moy = 5
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as may_net
+ ,sum(case when d_moy = 6
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as jun_net
+ ,sum(case when d_moy = 7
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as jul_net
+ ,sum(case when d_moy = 8
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as aug_net
+ ,sum(case when d_moy = 9
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as sep_net
+ ,sum(case when d_moy = 10
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as oct_net
+ ,sum(case when d_moy = 11
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as nov_net
+ ,sum(case when d_moy = 12
+ then ws_net_paid_inc_tax * ws_quantity else 0 end) as dec_net
+ from
+ web_sales
+ ,warehouse
+ ,date_dim
+ ,time_dim
+ ,ship_mode
+ where
+ ws_warehouse_sk = w_warehouse_sk
+ and ws_sold_date_sk = d_date_sk
+ and ws_sold_time_sk = t_time_sk
+ and ws_ship_mode_sk = sm_ship_mode_sk
+ and d_year = 2002
+ and t_time between 49530 and 49530+28800
+ and sm_carrier in ('DIAMOND','AIRBORNE')
+ group by
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,d_year
+ )
+ union all
+ (select
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,'DIAMOND' || ',' || 'AIRBORNE' as ship_carriers
+ ,d_year as year
+ ,sum(case when d_moy = 1
+ then cs_ext_sales_price* cs_quantity else 0 end) as jan_sales
+ ,sum(case when d_moy = 2
+ then cs_ext_sales_price* cs_quantity else 0 end) as feb_sales
+ ,sum(case when d_moy = 3
+ then cs_ext_sales_price* cs_quantity else 0 end) as mar_sales
+ ,sum(case when d_moy = 4
+ then cs_ext_sales_price* cs_quantity else 0 end) as apr_sales
+ ,sum(case when d_moy = 5
+ then cs_ext_sales_price* cs_quantity else 0 end) as may_sales
+ ,sum(case when d_moy = 6
+ then cs_ext_sales_price* cs_quantity else 0 end) as jun_sales
+ ,sum(case when d_moy = 7
+ then cs_ext_sales_price* cs_quantity else 0 end) as jul_sales
+ ,sum(case when d_moy = 8
+ then cs_ext_sales_price* cs_quantity else 0 end) as aug_sales
+ ,sum(case when d_moy = 9
+ then cs_ext_sales_price* cs_quantity else 0 end) as sep_sales
+ ,sum(case when d_moy = 10
+ then cs_ext_sales_price* cs_quantity else 0 end) as oct_sales
+ ,sum(case when d_moy = 11
+ then cs_ext_sales_price* cs_quantity else 0 end) as nov_sales
+ ,sum(case when d_moy = 12
+ then cs_ext_sales_price* cs_quantity else 0 end) as dec_sales
+ ,sum(case when d_moy = 1
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as jan_net
+ ,sum(case when d_moy = 2
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as feb_net
+ ,sum(case when d_moy = 3
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as mar_net
+ ,sum(case when d_moy = 4
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as apr_net
+ ,sum(case when d_moy = 5
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as may_net
+ ,sum(case when d_moy = 6
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as jun_net
+ ,sum(case when d_moy = 7
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as jul_net
+ ,sum(case when d_moy = 8
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as aug_net
+ ,sum(case when d_moy = 9
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as sep_net
+ ,sum(case when d_moy = 10
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as oct_net
+ ,sum(case when d_moy = 11
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as nov_net
+ ,sum(case when d_moy = 12
+ then cs_net_paid_inc_ship_tax * cs_quantity else 0 end) as dec_net
+ from
+ catalog_sales
+ ,warehouse
+ ,date_dim
+ ,time_dim
+ ,ship_mode
+ where
+ cs_warehouse_sk = w_warehouse_sk
+ and cs_sold_date_sk = d_date_sk
+ and cs_sold_time_sk = t_time_sk
+ and cs_ship_mode_sk = sm_ship_mode_sk
+ and d_year = 2002
+ and t_time between 49530 AND 49530+28800
+ and sm_carrier in ('DIAMOND','AIRBORNE')
+ group by
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,d_year
+ )
+ ) x
+ group by
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,ship_carriers
+ ,year
+ order by w_warehouse_name
+ limit 100
+POSTHOOK: type: QUERY
+STAGE DEPENDENCIES:
+ Stage-2 is a root stage
+ Stage-3 depends on stages: Stage-2
+ Stage-4 depends on stages: Stage-3
+ Stage-5 depends on stages: Stage-4
+ Stage-1 depends on stages: Stage-5
+ Stage-0 depends on stages: Stage-1
+
+STAGE PLANS:
+ Stage: Stage-2
+ Spark
+#### A masked pattern was here ####
+ Vertices:
+ Map 8
+ Map Operator Tree:
+ TableScan
+ alias: ship_mode
+ Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
+ Filter Operator
+ predicate: ((sm_carrier) IN ('DIAMOND', 'AIRBORNE') and sm_ship_mode_sk is not null) (type: boolean)
+ Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
+ Select Operator
+ expressions: sm_ship_mode_sk (type: int)
+ outputColumnNames: _col0
+ Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
+ Spark HashTable Sink Operator
+ keys:
+ 0 _col2 (type: int)
+ 1 _col0 (type: int)
+ Local Work:
+ Map Reduce Local Work
+ Map 9
+ Map Operator Tree:
+ TableScan
+ alias: warehouse
+ Statistics: Num rows: 27 Data size: 27802 Basic stats: COMPLETE Column stats: NONE
+ Filter Operator
+ predicate: w_warehouse_sk is not null (type: boolean)
+ Statistics: Num rows: 27 Data size: 27802 Basic stats: COMPLETE Column stats: NONE
+ Select Operator
+ expressions: w_warehouse_sk (type: int), w_warehouse_name (type: string), w_warehouse_sq_ft (type: int), w_city (type: string), w_county (type: string), w_state (type: string), w_country (type: string)
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6
+ Statistics: Num rows: 27 Data size: 27802 Basic stats: COMPLETE Column stats: NONE
+ Spark HashTable Sink Operator
+ keys:
+ 0 _col3 (type: int)
+ 1 _col0 (type: int)
+ Local Work:
+ Map Reduce Local Work
+
+ Stage: Stage-3
+ Spark
+#### A masked pattern was here ####
+ Vertices:
+ Map 6
+ Map Operator Tree:
+ TableScan
+ alias: time_dim
+ Statistics: Num rows: 86400 Data size: 40694400 Basic stats: COMPLETE Column stats: NONE
+ Filter Operator
+ predicate: (t_time BETWEEN 49530 AND 78330 and t_time_sk is not null) (type: boolean)
+ Statistics: Num rows: 9600 Data size: 4521600 Basic stats: COMPLETE Column stats: NONE
+ Select Operator
+ expressions: t_time_sk (type: int)
+ outputColumnNames: _col0
+ Statistics: Num rows: 9600 Data size: 4521600 Basic stats: COMPLETE Column stats: NONE
+ Spark HashTable Sink Operator
+ keys:
+ 0 _col1 (type: int)
+ 1 _col0 (type: int)
+ Local Work:
+ Map Reduce Local Work
+
+ Stage: Stage-4
+ Spark
+#### A masked pattern was here ####
+ Vertices:
+ Map 15
+ Map Operator Tree:
+ TableScan
+ alias: ship_mode
+ Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
+ Filter Operator
+ predicate: ((sm_carrier) IN ('DIAMOND', 'AIRBORNE') and sm_ship_mode_sk is not null) (type: boolean)
+ Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
+ Select Operator
+ expressions: sm_ship_mode_sk (type: int)
+ outputColumnNames: _col0
+ Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
+ Spark HashTable Sink Operator
+ keys:
+ 0 _col2 (type: int)
+ 1 _col0 (type: int)
+ Local Work:
+ Map Reduce Local Work
+ Map 16
+ Map Operator Tree:
+ TableScan
+ alias: warehouse
+ Statistics: Num rows: 27 Data size: 27802 Basic stats: COMPLETE Column stats: NONE
+ Filter Operator
+ predicate: w_warehouse_sk is not null (type: boolean)
+ Statistics: Num rows: 27 Data size: 27802 Basic stats: COMPLETE Column stats: NONE
+ Select Operator
+ expressions: w_warehouse_sk (type: int), w_warehouse_name (type: string), w_warehouse_sq_ft (type: int), w_city (type: string), w_county (type: string), w_state (type: string), w_country (type: string)
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6
+ Statistics: Num rows: 27 Data size: 27802 Basic stats: COMPLETE Column stats: NONE
+ Spark HashTable Sink Operator
+ keys:
+ 0 _col3 (type: int)
+ 1 _col0 (type: int)
+ Local Work:
+ Map Reduce Local Work
+
+ Stage: Stage-5
+ Spark
+#### A masked pattern was here ####
+ Vertices:
+ Map 13
+ Map Operator Tree:
+ TableScan
+ alias: time_dim
+ Statistics: Num rows: 86400 Data size: 40694400 Basic stats: COMPLETE Column stats: NONE
+ Filter Operator
+ predicate: (t_time BETWEEN 49530 AND 78330 and t_time_sk is not null) (type: boolean)
+ Statistics: Num rows: 9600 Data size: 4521600 Basic stats: COMPLETE Column stats: NONE
+ Select Operator
+ expressions: t_time_sk (type: int)
+ outputColumnNames: _col0
+ Statistics: Num rows: 9600 Data size: 4521600 Basic stats: COMPLETE Column stats: NONE
+ Spark HashTable Sink Operator
+ keys:
+ 0 _col1 (type: int)
+ 1 _col0 (type: int)
+ Local Work:
+ Map Reduce Local Work
+
+ Stage: Stage-1
+ Spark
+ Edges:
+ Reducer 11 <- Map 10 (PARTITION-LEVEL SORT, 336), Map 14 (PARTITION-LEVEL SORT, 336)
+ Reducer 12 <- Reducer 11 (GROUP, 447)
+ Reducer 2 <- Map 1 (PARTITION-LEVEL SORT, 169), Map 7 (PARTITION-LEVEL SORT, 169)
+ Reducer 3 <- Reducer 2 (GROUP, 224)
+ Reducer 4 <- Reducer 12 (GROUP, 336), Reducer 3 (GROUP, 336)
+ Reducer 5 <- Reducer 4 (SORT, 1)
+#### A masked pattern was here ####
+ Vertices:
+ Map 1
+ Map Operator Tree:
+ TableScan
+ alias: web_sales
+ Statistics: Num rows: 144002668 Data size: 19580198212 Basic stats: COMPLETE Column stats: NONE
+ Filter Operator
+ predicate: (ws_ship_mode_sk is not null and ws_sold_date_sk is not null and ws_sold_time_sk is not null and ws_warehouse_sk is not null) (type: boolean)
+ Statistics: Num rows: 144002668 Data size: 19580198212 Basic stats: COMPLETE Column stats: NONE
+ Select Operator
+ expressions: ws_sold_date_sk (type: int), ws_sold_time_sk (type: int), ws_ship_mode_sk (type: int), ws_warehouse_sk (type: int), ws_quantity (type: int), ws_sales_price (type: decimal(7,2)), ws_net_paid_inc_tax (type: decimal(7,2))
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6
+ Statistics: Num rows: 144002668 Data size: 19580198212 Basic stats: COMPLETE Column stats: NONE
+ Map Join Operator
+ condition map:
+ Inner Join 0 to 1
+ keys:
+ 0 _col1 (type: int)
+ 1 _col0 (type: int)
+ outputColumnNames: _col0, _col2, _col3, _col4, _col5, _col6
+ input vertices:
+ 1 Map 6
+ Statistics: Num rows: 158402938 Data size: 21538218500 Basic stats: COMPLETE Column stats: NONE
+ Reduce Output Operator
+ key expressions: _col0 (type: int)
+ sort order: +
+ Map-reduce partition columns: _col0 (type: int)
+ Statistics: Num rows: 158402938 Data size: 21538218500 Basic stats: COMPLETE Column stats: NONE
+ value expressions: _col2 (type: int), _col3 (type: int), _col4 (type: int), _col5 (type: decimal(7,2)), _col6 (type: decimal(7,2))
+ Local Work:
+ Map Reduce Local Work
+ Map 10
+ Map Operator Tree:
+ TableScan
+ alias: catalog_sales
+ Statistics: Num rows: 287989836 Data size: 38999608952 Basic stats: COMPLETE Column stats: NONE
+ Filter Operator
+ predicate: (cs_ship_mode_sk is not null and cs_sold_date_sk is not null and cs_sold_time_sk is not null and cs_warehouse_sk is not null) (type: boolean)
+ Statistics: Num rows: 287989836 Data size: 38999608952 Basic stats: COMPLETE Column stats: NONE
+ Select Operator
+ expressions: cs_sold_date_sk (type: int), cs_sold_time_sk (type: int), cs_ship_mode_sk (type: int), cs_warehouse_sk (type: int), cs_quantity (type: int), cs_ext_sales_price (type: decimal(7,2)), cs_net_paid_inc_ship_tax (type: decimal(7,2))
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6
+ Statistics: Num rows: 287989836 Data size: 38999608952 Basic stats: COMPLETE Column stats: NONE
+ Map Join Operator
+ condition map:
+ Inner Join 0 to 1
+ keys:
+ 0 _col1 (type: int)
+ 1 _col0 (type: int)
+ outputColumnNames: _col0, _col2, _col3, _col4, _col5, _col6
+ input vertices:
+ 1 Map 13
+ Statistics: Num rows: 316788826 Data size: 42899570777 Basic stats: COMPLETE Column stats: NONE
+ Reduce Output Operator
+ key expressions: _col0 (type: int)
+ sort order: +
+ Map-reduce partition columns: _col0 (type: int)
+ Statistics: Num rows: 316788826 Data size: 42899570777 Basic stats: COMPLETE Column stats: NONE
+ value expressions: _col2 (type: int), _col3 (type: int), _col4 (type: int), _col5 (type: decimal(7,2)), _col6 (type: decimal(7,2))
+ Local Work:
+ Map Reduce Local Work
+ Map 14
+ Map Operator Tree:
+ TableScan
+ alias: date_dim
+ Statistics: Num rows: 73049 Data size: 81741831 Basic stats: COMPLETE Column stats: NONE
+ Filter Operator
+ predicate: ((d_year = 2002) and d_date_sk is not null) (type: boolean)
+ Statistics: Num rows: 36524 Data size: 40870356 Basic stats: COMPLETE Column stats: NONE
+ Select Operator
+ expressions: d_date_sk (type: int), d_moy (type: int)
+ outputColumnNames: _col0, _col2
+ Statistics: Num rows: 36524 Data size: 40870356 Basic stats: COMPLETE Column stats: NONE
+ Reduce Output Operator
+ key expressions: _col0 (type: int)
+ sort order: +
+ Map-reduce partition columns: _col0 (type: int)
+ Statistics: Num rows: 36524 Data size: 40870356 Basic stats: COMPLETE Column stats: NONE
+ value expressions: _col2 (type: int)
+ Map 7
+ Map Operator Tree:
+ TableScan
+ alias: date_dim
+ Statistics: Num rows: 73049 Data size: 81741831 Basic stats: COMPLETE Column stats: NONE
+ Filter Operator
+ predicate: ((d_year = 2002) and d_date_sk is not null) (type: boolean)
+ Statistics: Num rows: 36524 Data size: 40870356 Basic stats: COMPLETE Column stats: NONE
+ Select Operator
+ expressions: d_date_sk (type: int), d_moy (type: int)
+ outputColumnNames: _col0, _col2
+ Statistics: Num rows: 36524 Data size: 40870356 Basic stats: COMPLETE Column stats: NONE
+ Reduce Output Operator
+ key expressions: _col0 (type: int)
+ sort order: +
+ Map-reduce partition columns: _col0 (type: int)
+ Statistics: Num rows: 36524 Data size: 40870356 Basic stats: COMPLETE Column stats: NONE
+ value expressions: _col2 (type: int)
+ Reducer 11
+ Local Work:
+ Map Reduce Local Work
+ Reduce Operator Tree:
+ Join Operator
+ condition map:
+ Inner Join 0 to 1
+ keys:
+ 0 _col0 (type: int)
+ 1 _col0 (type: int)
+ outputColumnNames: _col2, _col3, _col4, _col5, _col6, _col11
+ Statistics: Num rows: 348467716 Data size: 47189528877 Basic stats: COMPLETE Column stats: NONE
+ Map Join Operator
+ condition map:
+ Inner Join 0 to 1
+ keys:
+ 0 _col2 (type: int)
+ 1 _col0 (type: int)
+ outputColumnNames: _col3, _col4, _col5, _col6, _col11
+ input vertices:
+ 1 Map 15
+ Statistics: Num rows: 383314495 Data size: 51908482889 Basic stats: COMPLETE Column stats: NONE
+ Map Join Operator
+ condition map:
+ Inner Join 0 to 1
+ keys:
+ 0 _col3 (type: int)
+ 1 _col0 (type: int)
+ outputColumnNames: _col4, _col5, _col6, _col11, _col15, _col16, _col17, _col18, _col19, _col20
+ input vertices:
+ 1 Map 16
+ Statistics: Num rows: 421645953 Data size: 57099332415 Basic stats: COMPLETE Column stats: NONE
+ Select Operator
+ expressions: _col15 (type: string), _col16 (type: int), _col17 (type: string), _col18 (type: string), _col19 (type: string), _col20 (type: string), CASE WHEN ((_col11 = 1)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 2)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 3)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 4)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 5)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 6)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 7)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 8)) THEN ((_col5 * CAST( _col4 AS decimal(10,0))))
ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 9)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 10)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 11)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 12)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 1)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 2)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 3)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 4)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 5)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: d
ecimal(18,2)), CASE WHEN ((_col11 = 6)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 7)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 8)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 9)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 10)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 11)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 12)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2))
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16, _col17, _col18, _col19, _col20, _col21, _col22, _col23, _col24, _col25, _col26, _col27, _col28, _col29
+ Statistics: Num rows: 421645953 Data size: 57099332415 Basic stats: COMPLETE Column stats: NONE
+ Group By Operator
+ aggregations: sum(_col6), sum(_col7), sum(_col8), sum(_col9), sum(_col10), sum(_col11), sum(_col12), sum(_col13), sum(_col14), sum(_col15), sum(_col16), sum(_col17), sum(_col18), sum(_col19), sum(_col20), sum(_col21), sum(_col22), sum(_col23), sum(_col24), sum(_col25), sum(_col26), sum(_col27), sum(_col28), sum(_col29)
+ keys: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string)
+ mode: hash
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16, _col17, _col18, _col19, _col20, _col21, _col22, _col23, _col24, _col25, _col26, _col27, _col28, _col29
+ Statistics: Num rows: 421645953 Data size: 57099332415 Basic stats: COMPLETE Column stats: NONE
+ Reduce Output Operator
+ key expressions: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string)
+ sort order: ++++++
+ Map-reduce partition columns: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string)
+ Statistics: Num rows: 421645953 Data size: 57099332415 Basic stats: COMPLETE Column stats: NONE
+ value expressions: _col6 (type: decimal(28,2)), _col7 (type: decimal(28,2)), _col8 (type: decimal(28,2)), _col9 (type: decimal(28,2)), _col10 (type: decimal(28,2)), _col11 (type: decimal(28,2)), _col12 (type: decimal(28,2)), _col13 (type: decimal(28,2)), _col14 (type: decimal(28,2)), _col15 (type: decimal(28,2)), _col16 (type: decimal(28,2)), _col17 (type: decimal(28,2)), _col18 (type: decimal(28,2)), _col19 (type: decimal(28,2)), _col20 (type: decimal(28,2)), _col21 (type: decimal(28,2)), _col22 (type: decimal(28,2)), _col23 (type: decimal(28,2)), _col24 (type: decimal(28,2)), _col25 (type: decimal(28,2)), _col26 (type: decimal(28,2)), _col27 (type: decimal(28,2)), _col28 (type: decimal(28,2)), _col29 (type: decimal(28,2))
+ Reducer 12
+ Reduce Operator Tree:
+ Group By Operator
+ aggregations: sum(VALUE._col0), sum(VALUE._col1), sum(VALUE._col2), sum(VALUE._col3), sum(VALUE._col4), sum(VALUE._col5), sum(VALUE._col6), sum(VALUE._col7), sum(VALUE._col8), sum(VALUE._col9), sum(VALUE._col10), sum(VALUE._col11), sum(VALUE._col12), sum(VALUE._col13), sum(VALUE._col14), sum(VALUE._col15), sum(VALUE._col16), sum(VALUE._col17), sum(VALUE._col18), sum(VALUE._col19), sum(VALUE._col20), sum(VALUE._col21), sum(VALUE._col22), sum(VALUE._col23)
+ keys: KEY._col0 (type: string), KEY._col1 (type: int), KEY._col2 (type: string), KEY._col3 (type: string), KEY._col4 (type: string), KEY._col5 (type: string)
+ mode: mergepartial
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16, _col17, _col18, _col19, _col20, _col21, _col22, _col23, _col24, _col25, _col26, _col27, _col28, _col29
+ Statistics: Num rows: 210822976 Data size: 28549666139 Basic stats: COMPLETE Column stats: NONE
+ Select Operator
+ expressions: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string), _col6 (type: decimal(28,2)), _col7 (type: decimal(28,2)), _col8 (type: decimal(28,2)), _col9 (type: decimal(28,2)), _col10 (type: decimal(28,2)), _col11 (type: decimal(28,2)), _col12 (type: decimal(28,2)), _col13 (type: decimal(28,2)), _col14 (type: decimal(28,2)), _col15 (type: decimal(28,2)), _col16 (type: decimal(28,2)), _col17 (type: decimal(28,2)), (_col6 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col7 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col8 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col9 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col10 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col11 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col12 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col13 / CAST( _col1 AS decim
al(10,0))) (type: decimal(38,12)), (_col14 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col15 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col16 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col17 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), _col18 (type: decimal(28,2)), _col19 (type: decimal(28,2)), _col20 (type: decimal(28,2)), _col21 (type: decimal(28,2)), _col22 (type: decimal(28,2)), _col23 (type: decimal(28,2)), _col24 (type: decimal(28,2)), _col25 (type: decimal(28,2)), _col26 (type: decimal(28,2)), _col27 (type: decimal(28,2)), _col28 (type: decimal(28,2)), _col29 (type: decimal(28,2))
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16, _col17, _col18, _col19, _col20, _col21, _col22, _col23, _col24, _col25, _col26, _col27, _col28, _col29, _col30, _col31, _col32, _col33, _col34, _col35, _col36, _col37, _col38, _col39, _col40, _col41
+ Statistics: Num rows: 316240137 Data size: 42883351482 Basic stats: COMPLETE Column stats: NONE
+ Group By Operator
+ aggregations: sum(_col6), sum(_col7), sum(_col8), sum(_col9), sum(_col10), sum(_col11), sum(_col12), sum(_col13), sum(_col14), sum(_col15), sum(_col16), sum(_col17), sum(_col18), sum(_col19), sum(_col20), sum(_col21), sum(_col22), sum(_col23), sum(_col24), sum(_col25), sum(_col26), sum(_col27), sum(_col28), sum(_col29), sum(_col30), sum(_col31), sum(_col32), sum(_col33), sum(_col34), sum(_col35), sum(_col36), sum(_col37), sum(_col38), sum(_col39), sum(_col40), sum(_col41)
+ keys: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string)
+ mode: hash
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16, _col17, _col18, _col19, _col20, _col21, _col22, _col23, _col24, _col25, _col26, _col27, _col28, _col29, _col30, _col31, _col32, _col33, _col34, _col35, _col36, _col37, _col38, _col39, _col40, _col41
+ Statistics: Num rows: 316240137 Data size: 42883351482 Basic stats: COMPLETE Column stats: NONE
+ Reduce Output Operator
+ key expressions: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string)
+ sort order: ++++++
+ Map-reduce partition columns: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string)
+ Statistics: Num rows: 316240137 Data size: 42883351482 Basic stats: COMPLETE Column stats: NONE
+ TopN Hash Memory Usage: 0.1
+ value expressions: _col6 (type: decimal(38,2)), _col7 (type: decimal(38,2)), _col8 (type: decimal(38,2)), _col9 (type: decimal(38,2)), _col10 (type: decimal(38,2)), _col11 (type: decimal(38,2)), _col12 (type: decimal(38,2)), _col13 (type: decimal(38,2)), _col14 (type: decimal(38,2)), _col15 (type: decimal(38,2)), _col16 (type: decimal(38,2)), _col17 (type: decimal(38,2)), _col18 (type: decimal(38,12)), _col19 (type: decimal(38,12)), _col20 (type: decimal(38,12)), _col21 (type: decimal(38,12)), _col22 (type: decimal(38,12)), _col23 (type: decimal(38,12)), _col24 (type: decimal(38,12)), _col25 (type: decimal(38,12)), _col26 (type: decimal(38,12)), _col27 (type: decimal(38,12)), _col28 (type: decimal(38,12)), _col29 (type: decimal(38,12)), _col30 (type: decimal(38,2)), _col31 (type: decimal(38,2)), _col32 (type: decimal(38,2)), _col33 (type: decimal(38,2)), _col34 (type: decimal(38,2)), _col35 (type: decimal(38,2)), _col36 (type: decimal(38,2)), _col37 (type: deci
mal(38,2)), _col38 (type: decimal(38,2)), _col39 (type: decimal(38,2)), _col40 (type: decimal(38,2)), _col41 (type: decimal(38,2))
+ Reducer 2
+ Local Work:
+ Map Reduce Local Work
+ Reduce Operator Tree:
+ Join Operator
+ condition map:
+ Inner Join 0 to 1
+ keys:
+ 0 _col0 (type: int)
+ 1 _col0 (type: int)
+ outputColumnNames: _col2, _col3, _col4, _col5, _col6, _col11
+ Statistics: Num rows: 174243235 Data size: 23692040863 Basic stats: COMPLETE Column stats: NONE
+ Map Join Operator
+ condition map:
+ Inner Join 0 to 1
+ keys:
+ 0 _col2 (type: int)
+ 1 _col0 (type: int)
+ outputColumnNames: _col3, _col4, _col5, _col6, _col11
+ input vertices:
+ 1 Map 8
+ Statistics: Num rows: 191667562 Data size: 26061245514 Basic stats: COMPLETE Column stats: NONE
+ Map Join Operator
+ condition map:
+ Inner Join 0 to 1
+ keys:
+ 0 _col3 (type: int)
+ 1 _col0 (type: int)
+ outputColumnNames: _col4, _col5, _col6, _col11, _col15, _col16, _col17, _col18, _col19, _col20
+ input vertices:
+ 1 Map 9
+ Statistics: Num rows: 210834322 Data size: 28667370686 Basic stats: COMPLETE Column stats: NONE
+ Select Operator
+ expressions: _col15 (type: string), _col16 (type: int), _col17 (type: string), _col18 (type: string), _col19 (type: string), _col20 (type: string), CASE WHEN ((_col11 = 1)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 2)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 3)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 4)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 5)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 6)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 7)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 8)) THEN ((_col5 * CAST( _col4 AS decimal(10,0))))
ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 9)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 10)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 11)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 12)) THEN ((_col5 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 1)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 2)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 3)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 4)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 5)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: d
ecimal(18,2)), CASE WHEN ((_col11 = 6)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 7)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 8)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 9)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 10)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 11)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2)), CASE WHEN ((_col11 = 12)) THEN ((_col6 * CAST( _col4 AS decimal(10,0)))) ELSE (0) END (type: decimal(18,2))
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16, _col17, _col18, _col19, _col20, _col21, _col22, _col23, _col24, _col25, _col26, _col27, _col28, _col29
+ Statistics: Num rows: 210834322 Data size: 28667370686 Basic stats: COMPLETE Column stats: NONE
+ Group By Operator
+ aggregations: sum(_col6), sum(_col7), sum(_col8), sum(_col9), sum(_col10), sum(_col11), sum(_col12), sum(_col13), sum(_col14), sum(_col15), sum(_col16), sum(_col17), sum(_col18), sum(_col19), sum(_col20), sum(_col21), sum(_col22), sum(_col23), sum(_col24), sum(_col25), sum(_col26), sum(_col27), sum(_col28), sum(_col29)
+ keys: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string)
+ mode: hash
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16, _col17, _col18, _col19, _col20, _col21, _col22, _col23, _col24, _col25, _col26, _col27, _col28, _col29
+ Statistics: Num rows: 210834322 Data size: 28667370686 Basic stats: COMPLETE Column stats: NONE
+ Reduce Output Operator
+ key expressions: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string)
+ sort order: ++++++
+ Map-reduce partition columns: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string)
+ Statistics: Num rows: 210834322 Data size: 28667370686 Basic stats: COMPLETE Column stats: NONE
+ value expressions: _col6 (type: decimal(28,2)), _col7 (type: decimal(28,2)), _col8 (type: decimal(28,2)), _col9 (type: decimal(28,2)), _col10 (type: decimal(28,2)), _col11 (type: decimal(28,2)), _col12 (type: decimal(28,2)), _col13 (type: decimal(28,2)), _col14 (type: decimal(28,2)), _col15 (type: decimal(28,2)), _col16 (type: decimal(28,2)), _col17 (type: decimal(28,2)), _col18 (type: decimal(28,2)), _col19 (type: decimal(28,2)), _col20 (type: decimal(28,2)), _col21 (type: decimal(28,2)), _col22 (type: decimal(28,2)), _col23 (type: decimal(28,2)), _col24 (type: decimal(28,2)), _col25 (type: decimal(28,2)), _col26 (type: decimal(28,2)), _col27 (type: decimal(28,2)), _col28 (type: decimal(28,2)), _col29 (type: decimal(28,2))
+ Reducer 3
+ Reduce Operator Tree:
+ Group By Operator
+ aggregations: sum(VALUE._col0), sum(VALUE._col1), sum(VALUE._col2), sum(VALUE._col3), sum(VALUE._col4), sum(VALUE._col5), sum(VALUE._col6), sum(VALUE._col7), sum(VALUE._col8), sum(VALUE._col9), sum(VALUE._col10), sum(VALUE._col11), sum(VALUE._col12), sum(VALUE._col13), sum(VALUE._col14), sum(VALUE._col15), sum(VALUE._col16), sum(VALUE._col17), sum(VALUE._col18), sum(VALUE._col19), sum(VALUE._col20), sum(VALUE._col21), sum(VALUE._col22), sum(VALUE._col23)
+ keys: KEY._col0 (type: string), KEY._col1 (type: int), KEY._col2 (type: string), KEY._col3 (type: string), KEY._col4 (type: string), KEY._col5 (type: string)
+ mode: mergepartial
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16, _col17, _col18, _col19, _col20, _col21, _col22, _col23, _col24, _col25, _col26, _col27, _col28, _col29
+ Statistics: Num rows: 105417161 Data size: 14333685343 Basic stats: COMPLETE Column stats: NONE
+ Select Operator
+ expressions: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string), _col6 (type: decimal(28,2)), _col7 (type: decimal(28,2)), _col8 (type: decimal(28,2)), _col9 (type: decimal(28,2)), _col10 (type: decimal(28,2)), _col11 (type: decimal(28,2)), _col12 (type: decimal(28,2)), _col13 (type: decimal(28,2)), _col14 (type: decimal(28,2)), _col15 (type: decimal(28,2)), _col16 (type: decimal(28,2)), _col17 (type: decimal(28,2)), (_col6 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col7 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col8 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col9 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col10 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col11 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col12 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col13 / CAST( _col1 AS decim
al(10,0))) (type: decimal(38,12)), (_col14 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col15 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col16 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), (_col17 / CAST( _col1 AS decimal(10,0))) (type: decimal(38,12)), _col18 (type: decimal(28,2)), _col19 (type: decimal(28,2)), _col20 (type: decimal(28,2)), _col21 (type: decimal(28,2)), _col22 (type: decimal(28,2)), _col23 (type: decimal(28,2)), _col24 (type: decimal(28,2)), _col25 (type: decimal(28,2)), _col26 (type: decimal(28,2)), _col27 (type: decimal(28,2)), _col28 (type: decimal(28,2)), _col29 (type: decimal(28,2))
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16, _col17, _col18, _col19, _col20, _col21, _col22, _col23, _col24, _col25, _col26, _col27, _col28, _col29, _col30, _col31, _col32, _col33, _col34, _col35, _col36, _col37, _col38, _col39, _col40, _col41
+ Statistics: Num rows: 316240137 Data size: 42883351482 Basic stats: COMPLETE Column stats: NONE
+ Group By Operator
+ aggregations: sum(_col6), sum(_col7), sum(_col8), sum(_col9), sum(_col10), sum(_col11), sum(_col12), sum(_col13), sum(_col14), sum(_col15), sum(_col16), sum(_col17), sum(_col18), sum(_col19), sum(_col20), sum(_col21), sum(_col22), sum(_col23), sum(_col24), sum(_col25), sum(_col26), sum(_col27), sum(_col28), sum(_col29), sum(_col30), sum(_col31), sum(_col32), sum(_col33), sum(_col34), sum(_col35), sum(_col36), sum(_col37), sum(_col38), sum(_col39), sum(_col40), sum(_col41)
+ keys: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string)
+ mode: hash
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16, _col17, _col18, _col19, _col20, _col21, _col22, _col23, _col24, _col25, _col26, _col27, _col28, _col29, _col30, _col31, _col32, _col33, _col34, _col35, _col36, _col37, _col38, _col39, _col40, _col41
+ Statistics: Num rows: 316240137 Data size: 42883351482 Basic stats: COMPLETE Column stats: NONE
+ Reduce Output Operator
+ key expressions: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string)
+ sort order: ++++++
+ Map-reduce partition columns: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string)
+ Statistics: Num rows: 316240137 Data size: 42883351482 Basic stats: COMPLETE Column stats: NONE
+ TopN Hash Memory Usage: 0.1
+ value expressions: _col6 (type: decimal(38,2)), _col7 (type: decimal(38,2)), _col8 (type: decimal(38,2)), _col9 (type: decimal(38,2)), _col10 (type: decimal(38,2)), _col11 (type: decimal(38,2)), _col12 (type: decimal(38,2)), _col13 (type: decimal(38,2)), _col14 (type: decimal(38,2)), _col15 (type: decimal(38,2)), _col16 (type: decimal(38,2)), _col17 (type: decimal(38,2)), _col18 (type: decimal(38,12)), _col19 (type: decimal(38,12)), _col20 (type: decimal(38,12)), _col21 (type: decimal(38,12)), _col22 (type: decimal(38,12)), _col23 (type: decimal(38,12)), _col24 (type: decimal(38,12)), _col25 (type: decimal(38,12)), _col26 (type: decimal(38,12)), _col27 (type: decimal(38,12)), _col28 (type: decimal(38,12)), _col29 (type: decimal(38,12)), _col30 (type: decimal(38,2)), _col31 (type: decimal(38,2)), _col32 (type: decimal(38,2)), _col33 (type: decimal(38,2)), _col34 (type: decimal(38,2)), _col35 (type: decimal(38,2)), _col36 (type: decimal(38,2)), _col37 (type: deci
mal(38,2)), _col38 (type: decimal(38,2)), _col39 (type: decimal(38,2)), _col40 (type: decimal(38,2)), _col41 (type: decimal(38,2))
+ Reducer 4
+ Reduce Operator Tree:
+ Group By Operator
+ aggregations: sum(VALUE._col0), sum(VALUE._col1), sum(VALUE._col2), sum(VALUE._col3), sum(VALUE._col4), sum(VALUE._col5), sum(VALUE._col6), sum(VALUE._col7), sum(VALUE._col8), sum(VALUE._col9), sum(VALUE._col10), sum(VALUE._col11), sum(VALUE._col12), sum(VALUE._col13), sum(VALUE._col14), sum(VALUE._col15), sum(VALUE._col16), sum(VALUE._col17), sum(VALUE._col18), sum(VALUE._col19), sum(VALUE._col20), sum(VALUE._col21), sum(VALUE._col22), sum(VALUE._col23), sum(VALUE._col24), sum(VALUE._col25), sum(VALUE._col26), sum(VALUE._col27), sum(VALUE._col28), sum(VALUE._col29), sum(VALUE._col30), sum(VALUE._col31), sum(VALUE._col32), sum(VALUE._col33), sum(VALUE._col34), sum(VALUE._col35)
+ keys: KEY._col0 (type: string), KEY._col1 (type: int), KEY._col2 (type: string), KEY._col3 (type: string), KEY._col4 (type: string), KEY._col5 (type: string)
+ mode: mergepartial
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16, _col17, _col18, _col19, _col20, _col21, _col22, _col23, _col24, _col25, _col26, _col27, _col28, _col29, _col30, _col31, _col32, _col33, _col34, _col35, _col36, _col37, _col38, _col39, _col40, _col41
+ Statistics: Num rows: 158120068 Data size: 21441675673 Basic stats: COMPLETE Column stats: NONE
+ Reduce Output Operator
+ key expressions: _col0 (type: string)
+ sort order: +
+ Statistics: Num rows: 158120068 Data size: 21441675673 Basic stats: COMPLETE Column stats: NONE
+ TopN Hash Memory Usage: 0.1
+ value expressions: _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string), _col6 (type: decimal(38,2)), _col7 (type: decimal(38,2)), _col8 (type: decimal(38,2)), _col9 (type: decimal(38,2)), _col10 (type: decimal(38,2)), _col11 (type: decimal(38,2)), _col12 (type: decimal(38,2)), _col13 (type: decimal(38,2)), _col14 (type: decimal(38,2)), _col15 (type: decimal(38,2)), _col16 (type: decimal(38,2)), _col17 (type: decimal(38,2)), _col18 (type: decimal(38,12)), _col19 (type: decimal(38,12)), _col20 (type: decimal(38,12)), _col21 (type: decimal(38,12)), _col22 (type: decimal(38,12)), _col23 (type: decimal(38,12)), _col24 (type: decimal(38,12)), _col25 (type: decimal(38,12)), _col26 (type: decimal(38,12)), _col27 (type: decimal(38,12)), _col28 (type: decimal(38,12)), _col29 (type: decimal(38,12)), _col30 (type: decimal(38,2)), _col31 (type: decimal(38,2)), _col32 (type: decimal(38,2)), _col33 (type: decimal(38,2)), _col3
4 (type: decimal(38,2)), _col35 (type: decimal(38,2)), _col36 (type: decimal(38,2)), _col37 (type: decimal(38,2)), _col38 (type: decimal(38,2)), _col39 (type: decimal(38,2)), _col40 (type: decimal(38,2)), _col41 (type: decimal(38,2))
+ Reducer 5
+ Reduce Operator Tree:
+ Select Operator
+ expressions: KEY.reducesinkkey0 (type: string), VALUE._col0 (type: int), VALUE._col1 (type: string), VALUE._col2 (type: string), VALUE._col3 (type: string), VALUE._col4 (type: string), VALUE._col5 (type: decimal(38,2)), VALUE._col6 (type: decimal(38,2)), VALUE._col7 (type: decimal(38,2)), VALUE._col8 (type: decimal(38,2)), VALUE._col9 (type: decimal(38,2)), VALUE._col10 (type: decimal(38,2)), VALUE._col11 (type: decimal(38,2)), VALUE._col12 (type: decimal(38,2)), VALUE._col13 (type: decimal(38,2)), VALUE._col14 (type: decimal(38,2)), VALUE._col15 (type: decimal(38,2)), VALUE._col16 (type: decimal(38,2)), VALUE._col17 (type: decimal(38,12)), VALUE._col18 (type: decimal(38,12)), VALUE._col19 (type: decimal(38,12)), VALUE._col20 (type: decimal(38,12)), VALUE._col21 (type: decimal(38,12)), VALUE._col22 (type: decimal(38,12)), VALUE._col23 (type: decimal(38,12)), VALUE._col24 (type: decimal(38,12)), VALUE._col25 (type: decimal(38,12)), VALUE._col26 (type: decimal(38,12)),
VALUE._col27 (type: decimal(38,12)), VALUE._col28 (type: decimal(38,12)), VALUE._col29 (type: decimal(38,2)), VALUE._col30 (type: decimal(38,2)), VALUE._col31 (type: decimal(38,2)), VALUE._col32 (type: decimal(38,2)), VALUE._col33 (type: decimal(38,2)), VALUE._col34 (type: decimal(38,2)), VALUE._col35 (type: decimal(38,2)), VALUE._col36 (type: decimal(38,2)), VALUE._col37 (type: decimal(38,2)), VALUE._col38 (type: decimal(38,2)), VALUE._col39 (type: decimal(38,2)), VALUE._col40 (type: decimal(38,2))
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16, _col17, _col18, _col19, _col20, _col21, _col22, _col23, _col24, _col25, _col26, _col27, _col28, _col29, _col30, _col31, _col32, _col33, _col34, _col35, _col36, _col37, _col38, _col39, _col40, _col41
+ Statistics: Num rows: 158120068 Data size: 21441675673 Basic stats: COMPLETE Column stats: NONE
+ Limit
+ Number of rows: 100
+ Statistics: Num rows: 100 Data size: 13500 Basic stats: COMPLETE Column stats: NONE
+ Select Operator
+ expressions: _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string), 'DIAMOND,AIRBORNE' (type: string), 2002 (type: int), _col6 (type: decimal(38,2)), _col7 (type: decimal(38,2)), _col8 (type: decimal(38,2)), _col9 (type: decimal(38,2)), _col10 (type: decimal(38,2)), _col11 (type: decimal(38,2)), _col12 (type: decimal(38,2)), _col13 (type: decimal(38,2)), _col14 (type: decimal(38,2)), _col15 (type: decimal(38,2)), _col16 (type: decimal(38,2)), _col17 (type: decimal(38,2)), _col18 (type: decimal(38,12)), _col19 (type: decimal(38,12)), _col20 (type: decimal(38,12)), _col21 (type: decimal(38,12)), _col22 (type: decimal(38,12)), _col23 (type: decimal(38,12)), _col24 (type: decimal(38,12)), _col25 (type: decimal(38,12)), _col26 (type: decimal(38,12)), _col27 (type: decimal(38,12)), _col28 (type: decimal(38,12)), _col29 (type: decimal(38,12)), _col30 (type: decimal(38,2)), _col31 (type: decimal(38
,2)), _col32 (type: decimal(38,2)), _col33 (type: decimal(38,2)), _col34 (type: decimal(38,2)), _col35 (type: decimal(38,2)), _col36 (type: decimal(38,2)), _col37 (type: decimal(38,2)), _col38 (type: decimal(38,2)), _col39 (type: decimal(38,2)), _col40 (type: decimal(38,2)), _col41 (type: decimal(38,2))
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16, _col17, _col18, _col19, _col20, _col21, _col22, _col23, _col24, _col25, _col26, _col27, _col28, _col29, _col30, _col31, _col32, _col33, _col34, _col35, _col36, _col37, _col38, _col39, _col40, _col41, _col42, _col43
+ Statistics: Num rows: 100 Data size: 13500 Basic stats: COMPLETE Column stats: NONE
+ File Output Operator
+ compressed: false
+ Statistics: Num rows: 100 Data size: 13500 Basic stats: COMPLETE Column stats: NONE
+ table:
+ input format: org.apache.hadoop.mapred.SequenceFileInputFormat
+ output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat
+ serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
+
+ Stage: Stage-0
+ Fetch Operator
+ limit: -1
+ Processor Tree:
+ ListSink
+
http://git-wip-us.apache.org/repos/asf/hive/blob/bd371246/ql/src/test/results/clientpositive/perf/spark/query67.q.out
----------------------------------------------------------------------
diff --git a/ql/src/test/results/clientpositive/perf/spark/query67.q.out b/ql/src/test/results/clientpositive/perf/spark/query67.q.out
new file mode 100644
index 0000000..9affd8f
--- /dev/null
+++ b/ql/src/test/results/clientpositive/perf/spark/query67.q.out
@@ -0,0 +1,315 @@
+PREHOOK: query: explain
+select *
+from (select i_category
+ ,i_class
+ ,i_brand
+ ,i_product_name
+ ,d_year
+ ,d_qoy
+ ,d_moy
+ ,s_store_id
+ ,sumsales
+ ,rank() over (partition by i_category order by sumsales desc) rk
+ from (select i_category
+ ,i_class
+ ,i_brand
+ ,i_product_name
+ ,d_year
+ ,d_qoy
+ ,d_moy
+ ,s_store_id
+ ,sum(coalesce(ss_sales_price*ss_quantity,0)) sumsales
+ from store_sales
+ ,date_dim
+ ,store
+ ,item
+ where ss_sold_date_sk=d_date_sk
+ and ss_item_sk=i_item_sk
+ and ss_store_sk = s_store_sk
+ and d_month_seq between 1212 and 1212+11
+ group by rollup(i_category, i_class, i_brand, i_product_name, d_year, d_qoy, d_moy,s_store_id))dw1) dw2
+where rk <= 100
+order by i_category
+ ,i_class
+ ,i_brand
+ ,i_product_name
+ ,d_year
+ ,d_qoy
+ ,d_moy
+ ,s_store_id
+ ,sumsales
+ ,rk
+limit 100
+PREHOOK: type: QUERY
+POSTHOOK: query: explain
+select *
+from (select i_category
+ ,i_class
+ ,i_brand
+ ,i_product_name
+ ,d_year
+ ,d_qoy
+ ,d_moy
+ ,s_store_id
+ ,sumsales
+ ,rank() over (partition by i_category order by sumsales desc) rk
+ from (select i_category
+ ,i_class
+ ,i_brand
+ ,i_product_name
+ ,d_year
+ ,d_qoy
+ ,d_moy
+ ,s_store_id
+ ,sum(coalesce(ss_sales_price*ss_quantity,0)) sumsales
+ from store_sales
+ ,date_dim
+ ,store
+ ,item
+ where ss_sold_date_sk=d_date_sk
+ and ss_item_sk=i_item_sk
+ and ss_store_sk = s_store_sk
+ and d_month_seq between 1212 and 1212+11
+ group by rollup(i_category, i_class, i_brand, i_product_name, d_year, d_qoy, d_moy,s_store_id))dw1) dw2
+where rk <= 100
+order by i_category
+ ,i_class
+ ,i_brand
+ ,i_product_name
+ ,d_year
+ ,d_qoy
+ ,d_moy
+ ,s_store_id
+ ,sumsales
+ ,rk
+limit 100
+POSTHOOK: type: QUERY
+STAGE DEPENDENCIES:
+ Stage-2 is a root stage
+ Stage-1 depends on stages: Stage-2
+ Stage-0 depends on stages: Stage-1
+
+STAGE PLANS:
+ Stage: Stage-2
+ Spark
+#### A masked pattern was here ####
+ Vertices:
+ Map 8
+ Map Operator Tree:
+ TableScan
+ alias: store
+ Statistics: Num rows: 1704 Data size: 3256276 Basic stats: COMPLETE Column stats: NONE
+ Filter Operator
+ predicate: s_store_sk is not null (type: boolean)
+ Statistics: Num rows: 1704 Data size: 3256276 Basic stats: COMPLETE Column stats: NONE
+ Select Operator
+ expressions: s_store_sk (type: int), s_store_id (type: string)
+ outputColumnNames: _col0, _col1
+ Statistics: Num rows: 1704 Data size: 3256276 Basic stats: COMPLETE Column stats: NONE
+ Spark HashTable Sink Operator
+ keys:
+ 0 _col2 (type: int)
+ 1 _col0 (type: int)
+ Local Work:
+ Map Reduce Local Work
+
+ Stage: Stage-1
+ Spark
+ Edges:
+ Reducer 2 <- Map 1 (PARTITION-LEVEL SORT, 398), Map 7 (PARTITION-LEVEL SORT, 398)
+ Reducer 3 <- Map 9 (PARTITION-LEVEL SORT, 486), Reducer 2 (PARTITION-LEVEL SORT, 486)
+ Reducer 4 <- Reducer 3 (GROUP, 1009)
+ Reducer 5 <- Reducer 4 (PARTITION-LEVEL SORT, 1009)
+ Reducer 6 <- Reducer 5 (SORT, 1)
+#### A masked pattern was here ####
+ Vertices:
+ Map 1
+ Map Operator Tree:
+ TableScan
+ alias: store_sales
+ Statistics: Num rows: 575995635 Data size: 50814502088 Basic stats: COMPLETE Column stats: NONE
+ Filter Operator
+ predicate: (ss_item_sk is not null and ss_sold_date_sk is not null and ss_store_sk is not null) (type: boolean)
+ Statistics: Num rows: 575995635 Data size: 50814502088 Basic stats: COMPLETE Column stats: NONE
+ Select Operator
+ expressions: ss_sold_date_sk (type: int), ss_item_sk (type: int), ss_store_sk (type: int), ss_quantity (type: int), ss_sales_price (type: decimal(7,2))
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4
+ Statistics: Num rows: 575995635 Data size: 50814502088 Basic stats: COMPLETE Column stats: NONE
+ Reduce Output Operator
+ key expressions: _col0 (type: int)
+ sort order: +
+ Map-reduce partition columns: _col0 (type: int)
+ Statistics: Num rows: 575995635 Data size: 50814502088 Basic stats: COMPLETE Column stats: NONE
+ value expressions: _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4 (type: decimal(7,2))
+ Map 7
+ Map Operator Tree:
+ TableScan
+ alias: date_dim
+ Statistics: Num rows: 73049 Data size: 81741831 Basic stats: COMPLETE Column stats: NONE
+ Filter Operator
+ predicate: (d_date_sk is not null and d_month_seq BETWEEN 1212 AND 1223) (type: boolean)
+ Statistics: Num rows: 8116 Data size: 9081804 Basic stats: COMPLETE Column stats: NONE
+ Select Operator
+ expressions: d_date_sk (type: int), d_year (type: int), d_moy (type: int), d_qoy (type: int)
+ outputColumnNames: _col0, _col2, _col3, _col4
+ Statistics: Num rows: 8116 Data size: 9081804 Basic stats: COMPLETE Column stats: NONE
+ Reduce Output Operator
+ key expressions: _col0 (type: int)
+ sort order: +
+ Map-reduce partition columns: _col0 (type: int)
+ Statistics: Num rows: 8116 Data size: 9081804 Basic stats: COMPLETE Column stats: NONE
+ value expressions: _col2 (type: int), _col3 (type: int), _col4 (type: int)
+ Map 9
+ Map Operator Tree:
+ TableScan
+ alias: item
+ Statistics: Num rows: 462000 Data size: 663560457 Basic stats: COMPLETE Column stats: NONE
+ Filter Operator
+ predicate: i_item_sk is not null (type: boolean)
+ Statistics: Num rows: 462000 Data size: 663560457 Basic stats: COMPLETE Column stats: NONE
+ Select Operator
+ expressions: i_item_sk (type: int), i_brand (type: string), i_class (type: string), i_category (type: string), i_product_name (type: string)
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4
+ Statistics: Num rows: 462000 Data size: 663560457 Basic stats: COMPLETE Column stats: NONE
+ Reduce Output Operator
+ key expressions: _col0 (type: int)
+ sort order: +
+ Map-reduce partition columns: _col0 (type: int)
+ Statistics: Num rows: 462000 Data size: 663560457 Basic stats: COMPLETE Column stats: NONE
+ value expressions: _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string)
+ Reducer 2
+ Local Work:
+ Map Reduce Local Work
+ Reduce Operator Tree:
+ Join Operator
+ condition map:
+ Inner Join 0 to 1
+ keys:
+ 0 _col0 (type: int)
+ 1 _col0 (type: int)
+ outputColumnNames: _col1, _col2, _col3, _col4, _col7, _col8, _col9
+ Statistics: Num rows: 633595212 Data size: 55895953508 Basic stats: COMPLETE Column stats: NONE
+ Map Join Operator
+ condition map:
+ Inner Join 0 to 1
+ keys:
+ 0 _col2 (type: int)
+ 1 _col0 (type: int)
+ outputColumnNames: _col1, _col3, _col4, _col7, _col8, _col9, _col11
+ input vertices:
+ 1 Map 8
+ Statistics: Num rows: 696954748 Data size: 61485550191 Basic stats: COMPLETE Column stats: NONE
+ Reduce Output Operator
+ key expressions: _col1 (type: int)
+ sort order: +
+ Map-reduce partition columns: _col1 (type: int)
+ Statistics: Num rows: 696954748 Data size: 61485550191 Basic stats: COMPLETE Column stats: NONE
+ value expressions: _col3 (type: int), _col4 (type: decimal(7,2)), _col7 (type: int), _col8 (type: int), _col9 (type: int), _col11 (type: string)
+ Reducer 3
+ Reduce Operator Tree:
+ Join Operator
+ condition map:
+ Inner Join 0 to 1
+ keys:
+ 0 _col1 (type: int)
+ 1 _col0 (type: int)
+ outputColumnNames: _col3, _col4, _col7, _col8, _col9, _col11, _col13, _col14, _col15, _col16
+ Statistics: Num rows: 766650239 Data size: 67634106676 Basic stats: COMPLETE Column stats: NONE
+ Select Operator
+ expressions: _col15 (type: string), _col14 (type: string), _col13 (type: string), _col16 (type: string), _col7 (type: int), _col9 (type: int), _col8 (type: int), _col11 (type: string), COALESCE((_col4 * CAST( _col3 AS decimal(10,0))),0) (type: decimal(18,2))
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8
+ Statistics: Num rows: 766650239 Data size: 67634106676 Basic stats: COMPLETE Column stats: NONE
+ Group By Operator
+ aggregations: sum(_col8)
+ keys: _col0 (type: string), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: int), _col5 (type: int), _col6 (type: int), _col7 (type: string), 0 (type: int)
+ mode: hash
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9
+ Statistics: Num rows: 6899852151 Data size: 608706960084 Basic stats: COMPLETE Column stats: NONE
+ Reduce Output Operator
+ key expressions: _col0 (type: string), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: int), _col5 (type: int), _col6 (type: int), _col7 (type: string), _col8 (type: int)
+ sort order: +++++++++
+ Map-reduce partition columns: _col0 (type: string), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: int), _col5 (type: int), _col6 (type: int), _col7 (type: string), _col8 (type: int)
+ Statistics: Num rows: 6899852151 Data size: 608706960084 Basic stats: COMPLETE Column stats: NONE
+ value expressions: _col9 (type: decimal(28,2))
+ Reducer 4
+ Reduce Operator Tree:
+ Group By Operator
+ aggregations: sum(VALUE._col0)
+ keys: KEY._col0 (type: string), KEY._col1 (type: string), KEY._col2 (type: string), KEY._col3 (type: string), KEY._col4 (type: int), KEY._col5 (type: int), KEY._col6 (type: int), KEY._col7 (type: string), KEY._col8 (type: int)
+ mode: mergepartial
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col9
+ Statistics: Num rows: 3449926075 Data size: 304353479997 Basic stats: COMPLETE Column stats: NONE
+ pruneGroupingSetId: true
+ Select Operator
+ expressions: _col0 (type: string), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: int), _col5 (type: int), _col6 (type: int), _col7 (type: string), _col9 (type: decimal(28,2))
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col16
+ Statistics: Num rows: 3449926075 Data size: 304353479997 Basic stats: COMPLETE Column stats: NONE
+ Reduce Output Operator
+ key expressions: _col0 (type: string), _col16 (type: decimal(28,2))
+ sort order: +-
+ Map-reduce partition columns: _col0 (type: string)
+ Statistics: Num rows: 3449926075 Data size: 304353479997 Basic stats: COMPLETE Column stats: NONE
+ TopN Hash Memory Usage: 0.1
+ value expressions: _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: int), _col5 (type: int), _col6 (type: int), _col7 (type: string)
+ Reducer 5
+ Reduce Operator Tree:
+ Select Operator
+ expressions: KEY.reducesinkkey0 (type: string), VALUE._col0 (type: string), VALUE._col1 (type: string), VALUE._col2 (type: string), VALUE._col3 (type: int), VALUE._col4 (type: int), VALUE._col5 (type: int), VALUE._col6 (type: string), KEY.reducesinkkey1 (type: decimal(28,2))
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col16
+ Statistics: Num rows: 3449926075 Data size: 304353479997 Basic stats: COMPLETE Column stats: NONE
+ PTF Operator
+ Function definitions:
+ Input definition
+ input alias: ptf_0
+ output shape: _col0: string, _col1: string, _col2: string, _col3: string, _col4: int, _col5: int, _col6: int, _col7: string, _col16: decimal(28,2)
+ type: WINDOWING
+ Windowing table definition
+ input alias: ptf_1
+ name: windowingtablefunction
+ order by: _col16 DESC NULLS LAST
+ partition by: _col0
+ raw input shape:
+ window functions:
+ window function definition
+ alias: rank_window_0
+ arguments: _col16
+ name: rank
+ window function: GenericUDAFRankEvaluator
+ window frame: ROWS PRECEDING(MAX)~FOLLOWING(MAX)
+ isPivotResult: true
+ Statistics: Num rows: 3449926075 Data size: 304353479997 Basic stats: COMPLETE Column stats: NONE
+ Filter Operator
+ predicate: (rank_window_0 <= 100) (type: boolean)
+ Statistics: Num rows: 1149975358 Data size: 101451159969 Basic stats: COMPLETE Column stats: NONE
+ Select Operator
+ expressions: _col0 (type: string), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: int), _col5 (type: int), _col6 (type: int), _col7 (type: string), _col16 (type: decimal(28,2)), rank_window_0 (type: int)
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9
+ Statistics: Num rows: 1149975358 Data size: 101451159969 Basic stats: COMPLETE Column stats: NONE
+ Reduce Output Operator
+ key expressions: _col0 (type: string), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: int), _col5 (type: int), _col6 (type: int), _col7 (type: string), _col8 (type: decimal(28,2)), _col9 (type: int)
+ sort order: ++++++++++
+ Statistics: Num rows: 1149975358 Data size: 101451159969 Basic stats: COMPLETE Column stats: NONE
+ TopN Hash Memory Usage: 0.1
+ Reducer 6
+ Reduce Operator Tree:
+ Select Operator
+ expressions: KEY.reducesinkkey0 (type: string), KEY.reducesinkkey1 (type: string), KEY.reducesinkkey2 (type: string), KEY.reducesinkkey3 (type: string), KEY.reducesinkkey4 (type: int), KEY.reducesinkkey5 (type: int), KEY.reducesinkkey6 (type: int), KEY.reducesinkkey7 (type: string), KEY.reducesinkkey8 (type: decimal(28,2)), KEY.reducesinkkey9 (type: int)
+ outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9
+ Statistics: Num rows: 1149975358 Data size: 101451159969 Basic stats: COMPLETE Column stats: NONE
+ Limit
+ Number of rows: 100
+ Statistics: Num rows: 100 Data size: 8800 Basic stats: COMPLETE Column stats: NONE
+ File Output Operator
+ compressed: false
+ Statistics: Num rows: 100 Data size: 8800 Basic stats: COMPLETE Column stats: NONE
+ table:
+ input format: org.apache.hadoop.mapred.SequenceFileInputFormat
+ output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat
+ serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
+
+ Stage: Stage-0
+ Fetch Operator
+ limit: 100
+ Processor Tree:
+ ListSink
+