[ https://issues.apache.org/jira/browse/HIVE-9712?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Mostafa Mokhtar updated HIVE-9712: ---------------------------------- Summary: Hive : Row count and data size are set to LONG.MAX when source table has 0 rows (was: Hive : Row count and data size are set to LONG.MAX when filter is applied on an estimate of 0) > Hive : Row count and data size are set to LONG.MAX when source table has 0 > rows > ------------------------------------------------------------------------------- > > Key: HIVE-9712 > URL: https://issues.apache.org/jira/browse/HIVE-9712 > Project: Hive > Issue Type: Bug > Components: Physical Optimizer > Affects Versions: 0.14.0 > Reporter: Mostafa Mokhtar > Assignee: Prasanth Jayachandran > > TPC-DS Q66 generates and in-efficient plan because cardinality estimate of > dimension table gets set to 9223372036854775807. > {code} > Map 10 > Map Operator Tree: > TableScan > alias: ship_mode > filterExpr: ((sm_carrier) IN ('DIAMOND', 'AIRBORNE') and > sm_ship_mode_sk is not null) (type: boolean) > Statistics: Num rows: 0 Data size: 47 Basic stats: PARTIAL > Column stats: COMPLETE > Filter Operator > predicate: ((sm_carrier) IN ('DIAMOND', 'AIRBORNE') and > sm_ship_mode_sk is not null) (type: boolean) > Statistics: Num rows: 9223372036854775807 Data size: > 9223372036854775807 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: sm_ship_mode_sk (type: int) > outputColumnNames: _col0 > Statistics: Num rows: 9223372036854775807 Data size: > 9223372036854775807 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 9223372036854775807 Data size: > 9223372036854775807 Basic stats: COMPLETE Column stats: COMPLETE > Execution mode: vectorized > {code} > Full plan > {code} > 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 > ,concat('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 > web_sales.ws_warehouse_sk = warehouse.w_warehouse_sk > and web_sales.ws_sold_date_sk = date_dim.d_date_sk > and web_sales.ws_sold_time_sk = time_dim.t_time_sk > and web_sales.ws_ship_mode_sk = ship_mode.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 > ,concat('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 > catalog_sales.cs_warehouse_sk = warehouse.w_warehouse_sk > and catalog_sales.cs_sold_date_sk = date_dim.d_date_sk > and catalog_sales.cs_sold_time_sk = time_dim.t_time_sk > and catalog_sales.cs_ship_mode_sk = ship_mode.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 > OK > STAGE DEPENDENCIES: > Stage-1 is a root stage > Stage-0 depends on stages: Stage-1 > STAGE PLANS: > Stage: Stage-1 > Tez > Edges: > Map 12 <- Map 15 (BROADCAST_EDGE), Map 16 (BROADCAST_EDGE) > Map 2 <- Map 8 (BROADCAST_EDGE), Map 9 (BROADCAST_EDGE) > Reducer 13 <- Map 11 (BROADCAST_EDGE), Map 12 (SIMPLE_EDGE), Map 17 > (SIMPLE_EDGE) > Reducer 14 <- Reducer 13 (SIMPLE_EDGE), Union 5 (CONTAINS) > Reducer 3 <- Map 1 (BROADCAST_EDGE), Map 10 (SIMPLE_EDGE), Map 2 > (SIMPLE_EDGE) > Reducer 4 <- Reducer 3 (SIMPLE_EDGE), Union 5 (CONTAINS) > Reducer 6 <- Union 5 (SIMPLE_EDGE) > Reducer 7 <- Reducer 6 (SIMPLE_EDGE) > DagName: mmokhtar_20150211222424_0df571ed-82d9-426e-9eb9-52f95f022fa1:1 > Vertices: > Map 1 > Map Operator Tree: > TableScan > alias: date_dim > filterExpr: ((d_year = 2002) and d_date_sk is not null) > (type: boolean) > Statistics: Num rows: 73049 Data size: 81741831 Basic > stats: COMPLETE Column stats: COMPLETE > Filter Operator > predicate: ((d_year = 2002) and d_date_sk is not null) > (type: boolean) > Statistics: Num rows: 652 Data size: 7824 Basic stats: > COMPLETE Column stats: COMPLETE > Select Operator > expressions: d_date_sk (type: int), d_moy (type: int) > outputColumnNames: _col0, _col2 > Statistics: Num rows: 652 Data size: 5216 Basic stats: > COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 652 Data size: 5216 Basic > stats: COMPLETE Column stats: COMPLETE > value expressions: _col2 (type: int) > Execution mode: vectorized > Map 10 > Map Operator Tree: > TableScan > alias: ship_mode > filterExpr: ((sm_carrier) IN ('DIAMOND', 'AIRBORNE') and > sm_ship_mode_sk is not null) (type: boolean) > Statistics: Num rows: 0 Data size: 47 Basic stats: PARTIAL > Column stats: COMPLETE > Filter Operator > predicate: ((sm_carrier) IN ('DIAMOND', 'AIRBORNE') and > sm_ship_mode_sk is not null) (type: boolean) > Statistics: Num rows: 9223372036854775807 Data size: > 9223372036854775807 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: sm_ship_mode_sk (type: int) > outputColumnNames: _col0 > Statistics: Num rows: 9223372036854775807 Data size: > 9223372036854775807 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 9223372036854775807 Data size: > 9223372036854775807 Basic stats: COMPLETE Column stats: COMPLETE > Execution mode: vectorized > Map 11 > Map Operator Tree: > TableScan > alias: date_dim > filterExpr: ((d_year = 2002) and d_date_sk is not null) > (type: boolean) > Statistics: Num rows: 73049 Data size: 81741831 Basic > stats: COMPLETE Column stats: COMPLETE > Filter Operator > predicate: ((d_year = 2002) and d_date_sk is not null) > (type: boolean) > Statistics: Num rows: 652 Data size: 7824 Basic stats: > COMPLETE Column stats: COMPLETE > Select Operator > expressions: d_date_sk (type: int), d_moy (type: int) > outputColumnNames: _col0, _col2 > Statistics: Num rows: 652 Data size: 5216 Basic stats: > COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 652 Data size: 5216 Basic > stats: COMPLETE Column stats: COMPLETE > value expressions: _col2 (type: int) > Execution mode: vectorized > Map 12 > Map Operator Tree: > TableScan > alias: catalog_sales > filterExpr: (((cs_warehouse_sk is not null and > cs_sold_time_sk is not null) and cs_ship_mode_sk is not null) and > cs_sold_date_sk is not null) (type: boolean) > Statistics: Num rows: 286549727 Data size: 65825832570 > Basic stats: COMPLETE Column stats: COMPLETE > Filter Operator > predicate: (((cs_warehouse_sk is not null and > cs_sold_time_sk is not null) and cs_ship_mode_sk is not null) and > cs_sold_date_sk is not null) (type: boolean) > Statistics: Num rows: 284394646 Data size: 7948760032 > Basic stats: COMPLETE Column stats: COMPLETE > 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: float), > cs_net_paid_inc_ship_tax (type: float) > outputColumnNames: _col0, _col1, _col2, _col3, _col4, > _col5, _col6 > Statistics: Num rows: 284394646 Data size: 7948760032 > Basic stats: COMPLETE Column stats: COMPLETE > Map Join Operator > condition map: > Inner Join 0 to 1 > keys: > 0 _col3 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col0, _col1, _col2, _col4, _col5, > _col6, _col8, _col9, _col10, _col11, _col12, _col13 > input vertices: > 1 Map 15 > Statistics: Num rows: 284394656 Data size: > 142766117312 Basic stats: COMPLETE Column stats: COMPLETE > Map Join Operator > condition map: > Inner Join 0 to 1 > keys: > 0 _col1 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col0, _col2, _col4, _col5, > _col6, _col8, _col9, _col10, _col11, _col12, _col13 > input vertices: > 1 Map 16 > Statistics: Num rows: 142197328 Data size: > 70814269344 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col2 (type: int) > sort order: + > Map-reduce partition columns: _col2 (type: int) > Statistics: Num rows: 142197328 Data size: > 70814269344 Basic stats: COMPLETE Column stats: COMPLETE > value expressions: _col0 (type: int), _col4 > (type: int), _col5 (type: float), _col6 (type: float), _col8 (type: string), > _col9 (type: int), _col10 (type: string), _col11 (type: string), _col12 > (type: string), _col13 (type: string) > Execution mode: vectorized > Map 15 > Map Operator Tree: > TableScan > alias: warehouse > filterExpr: w_warehouse_sk is not null (type: boolean) > Statistics: Num rows: 6 Data size: 6166 Basic stats: > COMPLETE Column stats: COMPLETE > Filter Operator > predicate: w_warehouse_sk is not null (type: boolean) > Statistics: Num rows: 6 Data size: 2888 Basic stats: > COMPLETE Column stats: COMPLETE > 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: 6 Data size: 2888 Basic stats: > COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 6 Data size: 2888 Basic stats: > COMPLETE Column stats: COMPLETE > value expressions: _col1 (type: string), _col2 (type: > int), _col3 (type: string), _col4 (type: string), _col5 (type: string), _col6 > (type: string) > Execution mode: vectorized > Map 16 > Map Operator Tree: > TableScan > alias: time_dim > filterExpr: (t_time BETWEEN 49530 AND 78330 and t_time_sk > is not null) (type: boolean) > Statistics: Num rows: 86400 Data size: 40694400 Basic > stats: COMPLETE Column stats: COMPLETE > Filter Operator > predicate: (t_time BETWEEN 49530 AND 78330 and t_time_sk > is not null) (type: boolean) > Statistics: Num rows: 43200 Data size: 345600 Basic > stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: t_time_sk (type: int) > outputColumnNames: _col0 > Statistics: Num rows: 43200 Data size: 172800 Basic > stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 43200 Data size: 172800 Basic > stats: COMPLETE Column stats: COMPLETE > Execution mode: vectorized > Map 17 > Map Operator Tree: > TableScan > alias: ship_mode > filterExpr: ((sm_carrier) IN ('DIAMOND', 'AIRBORNE') and > sm_ship_mode_sk is not null) (type: boolean) > Statistics: Num rows: 0 Data size: 47 Basic stats: PARTIAL > Column stats: COMPLETE > Filter Operator > predicate: ((sm_carrier) IN ('DIAMOND', 'AIRBORNE') and > sm_ship_mode_sk is not null) (type: boolean) > Statistics: Num rows: 9223372036854775807 Data size: > 9223372036854775807 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: sm_ship_mode_sk (type: int) > outputColumnNames: _col0 > Statistics: Num rows: 9223372036854775807 Data size: > 9223372036854775807 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 9223372036854775807 Data size: > 9223372036854775807 Basic stats: COMPLETE Column stats: COMPLETE > Execution mode: vectorized > Map 2 > Map Operator Tree: > TableScan > alias: web_sales > filterExpr: (((ws_warehouse_sk is not null and > ws_sold_time_sk is not null) and ws_ship_mode_sk is not null) and > ws_sold_date_sk is not null) (type: boolean) > Statistics: Num rows: 143966864 Data size: 33110363004 > Basic stats: COMPLETE Column stats: COMPLETE > Filter Operator > predicate: (((ws_warehouse_sk is not null and > ws_sold_time_sk is not null) and ws_ship_mode_sk is not null) and > ws_sold_date_sk is not null) (type: boolean) > Statistics: Num rows: 143912967 Data size: 4029131264 > Basic stats: COMPLETE Column stats: COMPLETE > 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: float), > ws_net_paid_inc_tax (type: float) > outputColumnNames: _col0, _col1, _col2, _col3, _col4, > _col5, _col6 > Statistics: Num rows: 143912967 Data size: 4029131264 > Basic stats: COMPLETE Column stats: COMPLETE > Map Join Operator > condition map: > Inner Join 0 to 1 > keys: > 0 _col3 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col0, _col1, _col2, _col4, _col5, > _col6, _col8, _col9, _col10, _col11, _col12, _col13 > input vertices: > 1 Map 8 > Statistics: Num rows: 143912960 Data size: > 72244305920 Basic stats: COMPLETE Column stats: COMPLETE > Map Join Operator > condition map: > Inner Join 0 to 1 > keys: > 0 _col1 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col0, _col2, _col4, _col5, > _col6, _col8, _col9, _col10, _col11, _col12, _col13 > input vertices: > 1 Map 9 > Statistics: Num rows: 71956480 Data size: > 35834327040 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col2 (type: int) > sort order: + > Map-reduce partition columns: _col2 (type: int) > Statistics: Num rows: 71956480 Data size: > 35834327040 Basic stats: COMPLETE Column stats: COMPLETE > value expressions: _col0 (type: int), _col4 > (type: int), _col5 (type: float), _col6 (type: float), _col8 (type: string), > _col9 (type: int), _col10 (type: string), _col11 (type: string), _col12 > (type: string), _col13 (type: string) > Execution mode: vectorized > Map 8 > Map Operator Tree: > TableScan > alias: warehouse > filterExpr: w_warehouse_sk is not null (type: boolean) > Statistics: Num rows: 6 Data size: 6166 Basic stats: > COMPLETE Column stats: COMPLETE > Filter Operator > predicate: w_warehouse_sk is not null (type: boolean) > Statistics: Num rows: 6 Data size: 2888 Basic stats: > COMPLETE Column stats: COMPLETE > 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: 6 Data size: 2888 Basic stats: > COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 6 Data size: 2888 Basic stats: > COMPLETE Column stats: COMPLETE > value expressions: _col1 (type: string), _col2 (type: > int), _col3 (type: string), _col4 (type: string), _col5 (type: string), _col6 > (type: string) > Execution mode: vectorized > Map 9 > Map Operator Tree: > TableScan > alias: time_dim > filterExpr: (t_time BETWEEN 49530 AND 78330 and t_time_sk > is not null) (type: boolean) > Statistics: Num rows: 86400 Data size: 40694400 Basic > stats: COMPLETE Column stats: COMPLETE > Filter Operator > predicate: (t_time BETWEEN 49530 AND 78330 and t_time_sk > is not null) (type: boolean) > Statistics: Num rows: 43200 Data size: 345600 Basic > stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: t_time_sk (type: int) > outputColumnNames: _col0 > Statistics: Num rows: 43200 Data size: 172800 Basic > stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 43200 Data size: 172800 Basic > stats: COMPLETE Column stats: COMPLETE > Execution mode: vectorized > Reducer 13 > Reduce Operator Tree: > Merge Join Operator > condition map: > Inner Join 0 to 1 > keys: > 0 _col2 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col0, _col4, _col5, _col6, _col8, _col9, > _col10, _col11, _col12, _col13 > Statistics: Num rows: 9223372036854775807 Data size: > 9223372036854775807 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: _col0 (type: int), _col10 (type: string), > _col11 (type: string), _col12 (type: string), _col13 (type: string), _col4 > (type: int), _col5 (type: float), _col6 (type: float), _col8 (type: string), > _col9 (type: int) > outputColumnNames: _col0, _col10, _col11, _col12, _col13, > _col4, _col5, _col6, _col8, _col9 > Statistics: Num rows: 9223372036854775807 Data size: > 9223372036854775807 Basic stats: COMPLETE Column stats: COMPLETE > Map Join Operator > condition map: > Inner Join 0 to 1 > keys: > 0 _col0 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col2, _col7, _col8, _col9, _col11, > _col12, _col13, _col14, _col15, _col16 > input vertices: > 0 Map 11 > Statistics: Num rows: 82323356149350400 Data size: > 9223372036854775807 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: _col11 (type: string), _col12 (type: int), > _col13 (type: string), _col14 (type: string), _col15 (type: string), _col16 > (type: string), 2002 (type: int), CASE WHEN ((_col2 = 1)) THEN ((_col8 * > UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN ((_col2 = 2)) THEN > ((_col8 * UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN ((_col2 = > 3)) THEN ((_col8 * UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN > ((_col2 = 4)) THEN ((_col8 * UDFToFloat(_col7))) ELSE (0) END (type: float), > CASE WHEN ((_col2 = 5)) THEN ((_col8 * UDFToFloat(_col7))) ELSE (0) END > (type: float), CASE WHEN ((_col2 = 6)) THEN ((_col8 * UDFToFloat(_col7))) > ELSE (0) END (type: float), CASE WHEN ((_col2 = 7)) THEN ((_col8 * > UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN ((_col2 = 8)) THEN > ((_col8 * UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN ((_col2 = > 9)) THEN ((_col8 * UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN > ((_col2 = 10)) THEN ((_col8 * UDFToFloat(_col7))) ELSE (0) END (type: float), > CASE WHEN ((_col2 = 11)) THEN ((_col8 * UDFToFloat(_col7))) ELSE (0) END > (type: float), CASE WHEN ((_col2 = 12)) THEN ((_col8 * UDFToFloat(_col7))) > ELSE (0) END (type: float), CASE WHEN ((_col2 = 1)) THEN ((_col9 * > UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN ((_col2 = 2)) THEN > ((_col9 * UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN ((_col2 = > 3)) THEN ((_col9 * UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN > ((_col2 = 4)) THEN ((_col9 * UDFToFloat(_col7))) ELSE (0) END (type: float), > CASE WHEN ((_col2 = 5)) THEN ((_col9 * UDFToFloat(_col7))) ELSE (0) END > (type: float), CASE WHEN ((_col2 = 6)) THEN ((_col9 * UDFToFloat(_col7))) > ELSE (0) END (type: float), CASE WHEN ((_col2 = 7)) THEN ((_col9 * > UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN ((_col2 = 8)) THEN > ((_col9 * UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN ((_col2 = > 9)) THEN ((_col9 * UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN > ((_col2 = 10)) THEN ((_col9 * UDFToFloat(_col7))) ELSE (0) END (type: float), > CASE WHEN ((_col2 = 11)) THEN ((_col9 * UDFToFloat(_col7))) ELSE (0) END > (type: float), CASE WHEN ((_col2 = 12)) THEN ((_col9 * UDFToFloat(_col7))) > ELSE (0) END (type: float) > 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 > Statistics: Num rows: 82323356149350400 Data size: > 9223372036854775807 Basic stats: COMPLETE Column stats: COMPLETE > Group By Operator > aggregations: 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) > keys: _col0 (type: string), _col1 (type: int), _col2 > (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: > string), _col6 (type: int) > 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 > Statistics: Num rows: 2147483647 Data size: > 1447403978078 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col0 (type: string), _col1 (type: > int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 > (type: string), _col6 (type: int) > sort order: +++++++ > Map-reduce partition columns: _col0 (type: string), > _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: > string), _col5 (type: string), _col6 (type: int) > Statistics: Num rows: 2147483647 Data size: > 1447403978078 Basic stats: COMPLETE Column stats: COMPLETE > value expressions: _col7 (type: double), _col8 > (type: double), _col9 (type: double), _col10 (type: double), _col11 (type: > double), _col12 (type: double), _col13 (type: double), _col14 (type: double), > _col15 (type: double), _col16 (type: double), _col17 (type: double), _col18 > (type: double), _col19 (type: double), _col20 (type: double), _col21 (type: > double), _col22 (type: double), _col23 (type: double), _col24 (type: double), > _col25 (type: double), _col26 (type: double), _col27 (type: double), _col28 > (type: double), _col29 (type: double), _col30 (type: double) > Reducer 14 > 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), KEY._col6 (type: int) > 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 > 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), _col6 (type: int), _col7 (type: > double), _col8 (type: double), _col9 (type: double), _col10 (type: double), > _col11 (type: double), _col12 (type: double), _col13 (type: double), _col14 > (type: double), _col15 (type: double), _col16 (type: double), _col17 (type: > double), _col18 (type: double), _col19 (type: double), _col20 (type: double), > _col21 (type: double), _col22 (type: double), _col23 (type: double), _col24 > (type: double), _col25 (type: double), _col26 (type: double), _col27 (type: > double), _col28 (type: double), _col29 (type: double), _col30 (type: double) > 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 > Select Operator > expressions: _col0 (type: string), _col1 (type: int), > _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 > (type: string), _col6 (type: string), _col7 (type: int), _col8 (type: > double), _col9 (type: double), _col10 (type: double), _col11 (type: double), > _col12 (type: double), _col13 (type: double), _col14 (type: double), _col15 > (type: double), _col16 (type: double), _col17 (type: double), _col18 (type: > double), _col19 (type: double), (_col8 / UDFToDouble(_col1)) (type: double), > (_col9 / UDFToDouble(_col1)) (type: double), (_col10 / UDFToDouble(_col1)) > (type: double), (_col11 / UDFToDouble(_col1)) (type: double), (_col12 / > UDFToDouble(_col1)) (type: double), (_col13 / UDFToDouble(_col1)) (type: > double), (_col14 / UDFToDouble(_col1)) (type: double), (_col15 / > UDFToDouble(_col1)) (type: double), (_col16 / UDFToDouble(_col1)) (type: > double), (_col17 / UDFToDouble(_col1)) (type: double), (_col18 / > UDFToDouble(_col1)) (type: double), (_col19 / UDFToDouble(_col1)) (type: > double), _col20 (type: double), _col21 (type: double), _col22 (type: double), > _col23 (type: double), _col24 (type: double), _col25 (type: double), _col26 > (type: double), _col27 (type: double), _col28 (type: double), _col29 (type: > double), _col30 (type: double), _col31 (type: double) > 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 > Group By Operator > aggregations: 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), sum(_col42), sum(_col43) > keys: _col0 (type: string), _col1 (type: int), _col2 > (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: > string), _col6 (type: string), _col7 (type: int) > 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, > _col42, _col43 > Reduce Output Operator > key expressions: _col0 (type: string), _col1 (type: > int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 > (type: string), _col6 (type: string), _col7 (type: int) > sort order: ++++++++ > Map-reduce partition columns: _col0 (type: string), > _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: > string), _col5 (type: string), _col6 (type: string), _col7 (type: int) > value expressions: _col8 (type: double), _col9 (type: > double), _col10 (type: double), _col11 (type: double), _col12 (type: double), > _col13 (type: double), _col14 (type: double), _col15 (type: double), _col16 > (type: double), _col17 (type: double), _col18 (type: double), _col19 (type: > double), _col20 (type: double), _col21 (type: double), _col22 (type: double), > _col23 (type: double), _col24 (type: double), _col25 (type: double), _col26 > (type: double), _col27 (type: double), _col28 (type: double), _col29 (type: > double), _col30 (type: double), _col31 (type: double), _col32 (type: double), > _col33 (type: double), _col34 (type: double), _col35 (type: double), _col36 > (type: double), _col37 (type: double), _col38 (type: double), _col39 (type: > double), _col40 (type: double), _col41 (type: double), _col42 (type: double), > _col43 (type: double) > Reducer 3 > Reduce Operator Tree: > Merge Join Operator > condition map: > Inner Join 0 to 1 > keys: > 0 _col2 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col0, _col4, _col5, _col6, _col8, _col9, > _col10, _col11, _col12, _col13 > Statistics: Num rows: 9223372036854775807 Data size: > 9223372036854775807 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: _col0 (type: int), _col10 (type: string), > _col11 (type: string), _col12 (type: string), _col13 (type: string), _col4 > (type: int), _col5 (type: float), _col6 (type: float), _col8 (type: string), > _col9 (type: int) > outputColumnNames: _col0, _col10, _col11, _col12, _col13, > _col4, _col5, _col6, _col8, _col9 > Statistics: Num rows: 9223372036854775807 Data size: > 9223372036854775807 Basic stats: COMPLETE Column stats: COMPLETE > Map Join Operator > condition map: > Inner Join 0 to 1 > keys: > 0 _col0 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col2, _col7, _col8, _col9, _col11, > _col12, _col13, _col14, _col15, _col16 > input vertices: > 0 Map 1 > Statistics: Num rows: 82323356149350400 Data size: > 9223372036854775807 Basic stats: COMPLETE Column stats: COMPLETE > Select Operator > expressions: _col11 (type: string), _col12 (type: int), > _col13 (type: string), _col14 (type: string), _col15 (type: string), _col16 > (type: string), 2002 (type: int), CASE WHEN ((_col2 = 1)) THEN ((_col8 * > UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN ((_col2 = 2)) THEN > ((_col8 * UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN ((_col2 = > 3)) THEN ((_col8 * UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN > ((_col2 = 4)) THEN ((_col8 * UDFToFloat(_col7))) ELSE (0) END (type: float), > CASE WHEN ((_col2 = 5)) THEN ((_col8 * UDFToFloat(_col7))) ELSE (0) END > (type: float), CASE WHEN ((_col2 = 6)) THEN ((_col8 * UDFToFloat(_col7))) > ELSE (0) END (type: float), CASE WHEN ((_col2 = 7)) THEN ((_col8 * > UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN ((_col2 = 8)) THEN > ((_col8 * UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN ((_col2 = > 9)) THEN ((_col8 * UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN > ((_col2 = 10)) THEN ((_col8 * UDFToFloat(_col7))) ELSE (0) END (type: float), > CASE WHEN ((_col2 = 11)) THEN ((_col8 * UDFToFloat(_col7))) ELSE (0) END > (type: float), CASE WHEN ((_col2 = 12)) THEN ((_col8 * UDFToFloat(_col7))) > ELSE (0) END (type: float), CASE WHEN ((_col2 = 1)) THEN ((_col9 * > UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN ((_col2 = 2)) THEN > ((_col9 * UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN ((_col2 = > 3)) THEN ((_col9 * UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN > ((_col2 = 4)) THEN ((_col9 * UDFToFloat(_col7))) ELSE (0) END (type: float), > CASE WHEN ((_col2 = 5)) THEN ((_col9 * UDFToFloat(_col7))) ELSE (0) END > (type: float), CASE WHEN ((_col2 = 6)) THEN ((_col9 * UDFToFloat(_col7))) > ELSE (0) END (type: float), CASE WHEN ((_col2 = 7)) THEN ((_col9 * > UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN ((_col2 = 8)) THEN > ((_col9 * UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN ((_col2 = > 9)) THEN ((_col9 * UDFToFloat(_col7))) ELSE (0) END (type: float), CASE WHEN > ((_col2 = 10)) THEN ((_col9 * UDFToFloat(_col7))) ELSE (0) END (type: float), > CASE WHEN ((_col2 = 11)) THEN ((_col9 * UDFToFloat(_col7))) ELSE (0) END > (type: float), CASE WHEN ((_col2 = 12)) THEN ((_col9 * UDFToFloat(_col7))) > ELSE (0) END (type: float) > 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 > Statistics: Num rows: 82323356149350400 Data size: > 9223372036854775807 Basic stats: COMPLETE Column stats: COMPLETE > Group By Operator > aggregations: 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) > keys: _col0 (type: string), _col1 (type: int), _col2 > (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: > string), _col6 (type: int) > 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 > Statistics: Num rows: 2147483647 Data size: > 1447403978078 Basic stats: COMPLETE Column stats: COMPLETE > Reduce Output Operator > key expressions: _col0 (type: string), _col1 (type: > int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 > (type: string), _col6 (type: int) > sort order: +++++++ > Map-reduce partition columns: _col0 (type: string), > _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: > string), _col5 (type: string), _col6 (type: int) > Statistics: Num rows: 2147483647 Data size: > 1447403978078 Basic stats: COMPLETE Column stats: COMPLETE > value expressions: _col7 (type: double), _col8 > (type: double), _col9 (type: double), _col10 (type: double), _col11 (type: > double), _col12 (type: double), _col13 (type: double), _col14 (type: double), > _col15 (type: double), _col16 (type: double), _col17 (type: double), _col18 > (type: double), _col19 (type: double), _col20 (type: double), _col21 (type: > double), _col22 (type: double), _col23 (type: double), _col24 (type: double), > _col25 (type: double), _col26 (type: double), _col27 (type: double), _col28 > (type: double), _col29 (type: double), _col30 (type: double) > 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) > 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), KEY._col6 (type: int) > 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 > 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), _col6 (type: int), _col7 (type: > double), _col8 (type: double), _col9 (type: double), _col10 (type: double), > _col11 (type: double), _col12 (type: double), _col13 (type: double), _col14 > (type: double), _col15 (type: double), _col16 (type: double), _col17 (type: > double), _col18 (type: double), _col19 (type: double), _col20 (type: double), > _col21 (type: double), _col22 (type: double), _col23 (type: double), _col24 > (type: double), _col25 (type: double), _col26 (type: double), _col27 (type: > double), _col28 (type: double), _col29 (type: double), _col30 (type: double) > 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 > Select Operator > expressions: _col0 (type: string), _col1 (type: int), > _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 > (type: string), _col6 (type: string), _col7 (type: int), _col8 (type: > double), _col9 (type: double), _col10 (type: double), _col11 (type: double), > _col12 (type: double), _col13 (type: double), _col14 (type: double), _col15 > (type: double), _col16 (type: double), _col17 (type: double), _col18 (type: > double), _col19 (type: double), (_col8 / UDFToDouble(_col1)) (type: double), > (_col9 / UDFToDouble(_col1)) (type: double), (_col10 / UDFToDouble(_col1)) > (type: double), (_col11 / UDFToDouble(_col1)) (type: double), (_col12 / > UDFToDouble(_col1)) (type: double), (_col13 / UDFToDouble(_col1)) (type: > double), (_col14 / UDFToDouble(_col1)) (type: double), (_col15 / > UDFToDouble(_col1)) (type: double), (_col16 / UDFToDouble(_col1)) (type: > double), (_col17 / UDFToDouble(_col1)) (type: double), (_col18 / > UDFToDouble(_col1)) (type: double), (_col19 / UDFToDouble(_col1)) (type: > double), _col20 (type: double), _col21 (type: double), _col22 (type: double), > _col23 (type: double), _col24 (type: double), _col25 (type: double), _col26 > (type: double), _col27 (type: double), _col28 (type: double), _col29 (type: > double), _col30 (type: double), _col31 (type: double) > 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 > Group By Operator > aggregations: 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), sum(_col42), sum(_col43) > keys: _col0 (type: string), _col1 (type: int), _col2 > (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: > string), _col6 (type: string), _col7 (type: int) > 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, > _col42, _col43 > Reduce Output Operator > key expressions: _col0 (type: string), _col1 (type: > int), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 > (type: string), _col6 (type: string), _col7 (type: int) > sort order: ++++++++ > Map-reduce partition columns: _col0 (type: string), > _col1 (type: int), _col2 (type: string), _col3 (type: string), _col4 (type: > string), _col5 (type: string), _col6 (type: string), _col7 (type: int) > value expressions: _col8 (type: double), _col9 (type: > double), _col10 (type: double), _col11 (type: double), _col12 (type: double), > _col13 (type: double), _col14 (type: double), _col15 (type: double), _col16 > (type: double), _col17 (type: double), _col18 (type: double), _col19 (type: > double), _col20 (type: double), _col21 (type: double), _col22 (type: double), > _col23 (type: double), _col24 (type: double), _col25 (type: double), _col26 > (type: double), _col27 (type: double), _col28 (type: double), _col29 (type: > double), _col30 (type: double), _col31 (type: double), _col32 (type: double), > _col33 (type: double), _col34 (type: double), _col35 (type: double), _col36 > (type: double), _col37 (type: double), _col38 (type: double), _col39 (type: > double), _col40 (type: double), _col41 (type: double), _col42 (type: double), > _col43 (type: double) > Reducer 6 > 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), KEY._col6 (type: string), KEY._col7 (type: int) > 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, _col42, _col43 > Statistics: Num rows: 1 Data size: 288 Basic stats: COMPLETE > Column stats: COMPLETE > Reduce Output Operator > key expressions: _col0 (type: string) > sort order: + > Statistics: Num rows: 1 Data size: 288 Basic stats: > COMPLETE Column stats: COMPLETE > TopN Hash Memory Usage: 0.04 > value expressions: _col1 (type: int), _col2 (type: string), > _col3 (type: string), _col4 (type: string), _col5 (type: string), _col6 > (type: string), _col7 (type: int), _col8 (type: double), _col9 (type: > double), _col10 (type: double), _col11 (type: double), _col12 (type: double), > _col13 (type: double), _col14 (type: double), _col15 (type: double), _col16 > (type: double), _col17 (type: double), _col18 (type: double), _col19 (type: > double), _col20 (type: double), _col21 (type: double), _col22 (type: double), > _col23 (type: double), _col24 (type: double), _col25 (type: double), _col26 > (type: double), _col27 (type: double), _col28 (type: double), _col29 (type: > double), _col30 (type: double), _col31 (type: double), _col32 (type: double), > _col33 (type: double), _col34 (type: double), _col35 (type: double), _col36 > (type: double), _col37 (type: double), _col38 (type: double), _col39 (type: > double), _col40 (type: double), _col41 (type: double), _col42 (type: double), > _col43 (type: double) > Reducer 7 > 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: > string), VALUE._col6 (type: int), VALUE._col7 (type: double), VALUE._col8 > (type: double), VALUE._col9 (type: double), VALUE._col10 (type: double), > VALUE._col11 (type: double), VALUE._col12 (type: double), VALUE._col13 (type: > double), VALUE._col14 (type: double), VALUE._col15 (type: double), > VALUE._col16 (type: double), VALUE._col17 (type: double), VALUE._col18 (type: > double), VALUE._col19 (type: double), VALUE._col20 (type: double), > VALUE._col21 (type: double), VALUE._col22 (type: double), VALUE._col23 (type: > double), VALUE._col24 (type: double), VALUE._col25 (type: double), > VALUE._col26 (type: double), VALUE._col27 (type: double), VALUE._col28 (type: > double), VALUE._col29 (type: double), VALUE._col30 (type: double), > VALUE._col31 (type: double), VALUE._col32 (type: double), VALUE._col33 (type: > double), VALUE._col34 (type: double), VALUE._col35 (type: double), > VALUE._col36 (type: double), VALUE._col37 (type: double), VALUE._col38 (type: > double), VALUE._col39 (type: double), VALUE._col40 (type: double), > VALUE._col41 (type: double), VALUE._col42 (type: double) > 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: 1 Data size: 288 Basic stats: COMPLETE > Column stats: COMPLETE > Limit > Number of rows: 100 > Statistics: Num rows: 1 Data size: 288 Basic stats: > COMPLETE Column stats: COMPLETE > File Output Operator > compressed: false > Statistics: Num rows: 1 Data size: 288 Basic stats: > COMPLETE Column stats: COMPLETE > table: > input format: org.apache.hadoop.mapred.TextInputFormat > output format: > org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat > serde: > org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe > Union 5 > Vertex: Union 5 > Stage: Stage-0 > Fetch Operator > limit: 100 > Processor Tree: > ListSink > {code} -- This message was sent by Atlassian JIRA (v6.3.4#6332)