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From "Gunther Hagleitner (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (HIVE-8671) Overflow in estimate row count and data size with fetch column stats
Date Sat, 01 Nov 2014 22:37:34 GMT

     [ https://issues.apache.org/jira/browse/HIVE-8671?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Gunther Hagleitner updated HIVE-8671:
-------------------------------------
    Fix Version/s:     (was: 0.15.0)

> Overflow in estimate row count and data size with fetch column stats
> --------------------------------------------------------------------
>
>                 Key: HIVE-8671
>                 URL: https://issues.apache.org/jira/browse/HIVE-8671
>             Project: Hive
>          Issue Type: Bug
>          Components: Physical Optimizer
>    Affects Versions: 0.14.0
>            Reporter: Mostafa Mokhtar
>            Assignee: Prasanth J
>            Priority: Critical
>             Fix For: 0.14.0
>
>         Attachments: HIVE-8671.1.patch, HIVE-8671.2.patch, HIVE-8671.3.patch, HIVE-8671.4.patch,
HIVE-8671.5.patch
>
>
> Overflow in row counts and data size for several TPC-DS queries.
> Interestingly the operators which have overflow end up running with a small parallelism.
> For instance Reducer 2 has an overflow but it only runs with parallelism of 2.
> {code}
>        Reducer 2 
>             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: float)
>                 mode: mergepartial
>                 outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5
>                 Statistics: Num rows: 9223372036854775807 Data size: 9223372036854775341
Basic stats: COMPLETE Column stats: COMPLETE
>                 Reduce Output Operator
>                   key expressions: _col3 (type: string), _col3 (type: string)
>                   sort order: ++
>                   Map-reduce partition columns: _col3 (type: string)
>                   Statistics: Num rows: 9223372036854775807 Data size: 9223372036854775341
Basic stats: COMPLETE Column stats: COMPLETE
>                   value expressions: _col0 (type: string), _col1 (type: string), _col2
(type: string), _col3 (type: string), _col4 (type: float), _col5 (type: double)
>             Execution mode: vectorized
> {code}
> {code}
> VERTEX       TOTAL_TASKS    DURATION_SECONDS     CPU_TIME_MILLIS INPUT_RECORDS   OUTPUT_RECORDS

> Map 1                 62               26.41           1,779,510   211,978,502      
60,628,390
> Map 5                  1                4.28               6,950       138,098      
   138,098
> Map 6                  1                2.44               3,910            31      
        31
> Reducer 2              2               22.69              61,320    60,628,390      
    69,182
> Reducer 3              1                2.63               3,910        69,182      
       100
> Reducer 4              1                1.01               1,180           100      
       100
> {code}
> Query
> {code}
> explain  
> select  i_item_desc 
>       ,i_category 
>       ,i_class 
>       ,i_current_price
>       ,i_item_id
>       ,sum(ws_ext_sales_price) as itemrevenue 
>       ,sum(ws_ext_sales_price)*100/sum(sum(ws_ext_sales_price)) over
>           (partition by i_class) as revenueratio
> from	
> 	web_sales
>     	,item 
>     	,date_dim
> where 
> 	web_sales.ws_item_sk = item.i_item_sk 
>   	and item.i_category in ('Jewelry', 'Sports', 'Books')
>   	and web_sales.ws_sold_date_sk = date_dim.d_date_sk
> 	and date_dim.d_date between '2001-01-12' and '2001-02-11'
> group by 
> 	i_item_id
>         ,i_item_desc 
>         ,i_category
>         ,i_class
>         ,i_current_price
> order by 
> 	i_category
>         ,i_class
>         ,i_item_id
>         ,i_item_desc
>         ,revenueratio
> limit 100
> {code}
> Explain 
> {code}
> STAGE PLANS:
>   Stage: Stage-1
>     Tez
>       Edges:
>         Map 1 <- Map 5 (BROADCAST_EDGE), Map 6 (BROADCAST_EDGE)
>         Reducer 2 <- Map 1 (SIMPLE_EDGE)
>         Reducer 3 <- Reducer 2 (SIMPLE_EDGE)
>         Reducer 4 <- Reducer 3 (SIMPLE_EDGE)
>       DagName: mmokhtar_20141019164343_854cb757-01bd-40cb-843e-9ada7c5e6f38:1
>       Vertices:
>         Map 1 
>             Map Operator Tree:
>                 TableScan
>                   alias: web_sales
>                   filterExpr: ws_item_sk is not null (type: boolean)
>                   Statistics: Num rows: 21594638446 Data size: 2850189889652 Basic stats:
COMPLETE Column stats: COMPLETE
>                   Filter Operator
>                     predicate: ws_item_sk is not null (type: boolean)
>                     Statistics: Num rows: 21594638446 Data size: 172746300152 Basic stats:
COMPLETE Column stats: COMPLETE
>                     Select Operator
>                       expressions: ws_item_sk (type: int), ws_ext_sales_price (type:
float), ws_sold_date_sk (type: int)
>                       outputColumnNames: _col0, _col1, _col2
>                       Statistics: Num rows: 21594638446 Data size: 172746300152 Basic
stats: COMPLETE Column stats: COMPLETE
>                       Map Join Operator
>                         condition map:
>                              Inner Join 0 to 1
>                         condition expressions:
>                           0 {_col0} {_col1}
>                           1 
>                         keys:
>                           0 _col2 (type: int)
>                           1 _col0 (type: int)
>                         outputColumnNames: _col0, _col1
>                         input vertices:
>                           1 Map 6
>                         Statistics: Num rows: 24145061366 Data size: 193160490928 Basic
stats: COMPLETE Column stats: COMPLETE
>                         Map Join Operator
>                           condition map:
>                                Inner Join 0 to 1
>                           condition expressions:
>                             0 {_col1}
>                             1 {_col1} {_col2} {_col3} {_col4} {_col5}
>                           keys:
>                             0 _col0 (type: int)
>                             1 _col0 (type: int)
>                           outputColumnNames: _col1, _col6, _col7, _col8, _col9, _col10
>                           input vertices:
>                             1 Map 5
>                           Statistics: Num rows: 25381041158 Data size: 11929089344260
Basic stats: COMPLETE Column stats: COMPLETE
>                           Select Operator
>                             expressions: _col6 (type: string), _col7 (type: string),
_col10 (type: string), _col9 (type: string), _col8 (type: float), _col1 (type: float)
>                             outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5
>                             Statistics: Num rows: 25381041158 Data size: 11929089344260
Basic stats: COMPLETE Column stats: COMPLETE
>                             Group By Operator
>                               aggregations: sum(_col5)
>                               keys: _col0 (type: string), _col1 (type: string), _col2
(type: string), _col3 (type: string), _col4 (type: float)
>                               mode: hash
>                               outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5
>                               Statistics: Num rows: 119291 Data size: 954328 Basic stats:
COMPLETE Column stats: COMPLETE
>                               Reduce Output Operator
>                                 key expressions: _col0 (type: string), _col1 (type: string),
_col2 (type: string), _col3 (type: string), _col4 (type: float)
>                                 sort order: +++++
>                                 Map-reduce partition columns: _col0 (type: string), _col1
(type: string), _col2 (type: string), _col3 (type: string), _col4 (type: float)
>                                 Statistics: Num rows: 119291 Data size: 954328 Basic
stats: COMPLETE Column stats: COMPLETE
>                                 value expressions: _col5 (type: double)
>             Execution mode: vectorized
>         Map 5 
>             Map Operator Tree:
>                 TableScan
>                   alias: item
>                   filterExpr: ((i_category) IN ('Jewelry', 'Sports', 'Books') and i_item_sk
is not null) (type: boolean)
>                   Statistics: Num rows: 462000 Data size: 663862160 Basic stats: COMPLETE
Column stats: COMPLETE
>                   Filter Operator
>                     predicate: ((i_category) IN ('Jewelry', 'Sports', 'Books') and i_item_sk
is not null) (type: boolean)
>                     Statistics: Num rows: 231000 Data size: 109491664 Basic stats: COMPLETE
Column stats: COMPLETE
>                     Select Operator
>                       expressions: i_item_sk (type: int), i_item_id (type: string), i_item_desc
(type: string), i_current_price (type: float), i_class (type: string), i_category (type: string)
>                       outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5
>                       Statistics: Num rows: 231000 Data size: 109491664 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: 231000 Data size: 109491664 Basic stats:
COMPLETE Column stats: COMPLETE
>                         value expressions: _col1 (type: string), _col2 (type: string),
_col3 (type: float), _col4 (type: string), _col5 (type: string)
>             Execution mode: vectorized
>         Map 6 
>             Map Operator Tree:
>                 TableScan
>                   alias: date_dim
>                   filterExpr: (d_date BETWEEN '2001-01-12' AND '2001-02-11' 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_date BETWEEN '2001-01-12' AND '2001-02-11' and d_date_sk
is not null) (type: boolean)
>                     Statistics: Num rows: 36524 Data size: 3579352 Basic stats: COMPLETE
Column stats: COMPLETE
>                     Select Operator
>                       expressions: d_date_sk (type: int)
>                       outputColumnNames: _col0
>                       Statistics: Num rows: 36524 Data size: 146096 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: 36524 Data size: 146096 Basic stats: COMPLETE
Column stats: COMPLETE
>                       Select Operator
>                         expressions: _col0 (type: int)
>                         outputColumnNames: _col0
>                         Statistics: Num rows: 36524 Data size: 0 Basic stats: PARTIAL
Column stats: COMPLETE
>                         Group By Operator
>                           keys: _col0 (type: int)
>                           mode: hash
>                           outputColumnNames: _col0
>                           Statistics: Num rows: 36524 Data size: 0 Basic stats: PARTIAL
Column stats: COMPLETE
>                           Dynamic Partitioning Event Operator
>                             Target Input: web_sales
>                             Partition key expr: ws_sold_date_sk
>                             Statistics: Num rows: 36524 Data size: 0 Basic stats: PARTIAL
Column stats: COMPLETE
>                             Target column: ws_sold_date_sk
>                             Target Vertex: Map 1
>             Execution mode: vectorized
>         Reducer 2 
>             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: float)
>                 mode: mergepartial
>                 outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5
>                 Statistics: Num rows: 119291 Data size: 1908656 Basic stats: COMPLETE
Column stats: COMPLETE
>                 Reduce Output Operator
>                   key expressions: _col3 (type: string), _col3 (type: string)
>                   sort order: ++
>                   Map-reduce partition columns: _col3 (type: string)
>                   Statistics: Num rows: 119291 Data size: 1908656 Basic stats: COMPLETE
Column stats: COMPLETE
>                   value expressions: _col0 (type: string), _col1 (type: string), _col2
(type: string), _col3 (type: string), _col4 (type: float), _col5 (type: double)
>             Execution mode: vectorized
>         Reducer 3 
>             Reduce Operator Tree:
>               Extract
>                 Statistics: Num rows: 119291 Data size: 1908656 Basic stats: COMPLETE
Column stats: COMPLETE
>                 PTF Operator
>                   Statistics: Num rows: 119291 Data size: 1908656 Basic stats: COMPLETE
Column stats: COMPLETE
>                   Select Operator
>                     expressions: _col1 (type: string), _col2 (type: string), _col3 (type:
string), _col4 (type: float), _col0 (type: string), _col5 (type: double), ((_col5 * 100.0)
/ _wcol0) (type: double)
>                     outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6
>                     Statistics: Num rows: 119291 Data size: 954328 Basic stats: COMPLETE
Column stats: COMPLETE
>                     Reduce Output Operator
>                       key expressions: _col1 (type: string), _col2 (type: string), _col4
(type: string), _col0 (type: string), _col6 (type: double)
>                       sort order: +++++
>                       Statistics: Num rows: 119291 Data size: 954328 Basic stats: COMPLETE
Column stats: COMPLETE
>                       TopN Hash Memory Usage: 0.04
>                       value expressions: _col3 (type: float), _col5 (type: double)
>         Reducer 4 
>             Reduce Operator Tree:
>               Select Operator
>                 expressions: KEY.reducesinkkey3 (type: string), KEY.reducesinkkey0 (type:
string), KEY.reducesinkkey1 (type: string), VALUE._col0 (type: float), KEY.reducesinkkey2
(type: string), VALUE._col1 (type: double), KEY.reducesinkkey4 (type: double)
>                 outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6
>                 Statistics: Num rows: 119291 Data size: 954328 Basic stats: COMPLETE
Column stats: COMPLETE
>                 Limit
>                   Number of rows: 100
>                   Statistics: Num rows: 100 Data size: 800 Basic stats: COMPLETE Column
stats: COMPLETE
>                   File Output Operator
>                     compressed: false
>                     Statistics: Num rows: 100 Data size: 800 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
>             Execution mode: vectorized
>   Stage: Stage-0
>     Fetch Operator
>       limit: 100
>       Processor Tree:
>         ListSink
> {code}



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