[
https://issues.apache.org/jira/browse/HIVE-8671?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Mostafa Mokhtar updated HIVE-8671:
----------------------------------
Description:
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}
was:
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 FAILED_TASKS KILLED_TASKS DURATION_SECONDS
CPU_TIME_MILLIS GC_TIME_MILLIS INPUT_RECORDS OUTPUT_RECORDS
Map 1 62 0 0 26.41
1,779,510 22,242 211,978,502 60,628,390
Map 5 1 0 0 4.28
6,950 85 138,098 138,098
Map 6 1 0 0 2.44
3,910 28 31 31
Reducer 2 2 0 0 22.69
61,320 1,724 60,628,390 69,182
Reducer 3 1 0 0 2.63
3,910 19 69,182 100
Reducer 4 1 0 0 1.01
1,180 33 100 100
{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}
> 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
>
>
> 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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