[jira] [Updated] (HIVE-8671) Overflow in estimate row count and data size with fetch column stats
[
https://issues.apache.org/jira/browse/HIVE-8671?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Prasanth J updated HIVE-8671:
-
Resolution: Fixed
Fix Version/s: 0.15.0
Status: Resolved (was: Patch Available)
Patch committed to trunk and branch-0.14.
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, 0.15.0
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_TASKSDURATION_SECONDS CPU_TIME_MILLIS
INPUT_RECORDS OUTPUT_RECORDS
Map 1 62 26.41 1,779,510
211,978,502 60,628,390
Map 5 14.28 6,950
138,098 138,098
Map 6 12.44 3,910
31 31
Reducer 2 2 22.69 61,320
60,628,390 69,182
Reducer 3 12.63 3,910
69,182 100
Reducer 4 11.01 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
[jira] [Updated] (HIVE-8671) Overflow in estimate row count and data size with fetch column stats
[
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_TASKSDURATION_SECONDS CPU_TIME_MILLIS
INPUT_RECORDS OUTPUT_RECORDS
Map 1 62 26.41 1,779,510
211,978,502 60,628,390
Map 5 14.28 6,950
138,098 138,098
Map 6 12.44 3,910
31 31
Reducer 2 2 22.69 61,320
60,628,390 69,182
Reducer 3 12.63 3,910
69,182 100
Reducer 4 11.01 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:
[jira] [Updated] (HIVE-8671) Overflow in estimate row count and data size with fetch column stats
[
https://issues.apache.org/jira/browse/HIVE-8671?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Mostafa Mokhtar updated HIVE-8671:
--
Attachment: HIVE-8671.1.patch
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
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_TASKSDURATION_SECONDS CPU_TIME_MILLIS
INPUT_RECORDS OUTPUT_RECORDS
Map 1 62 26.41 1,779,510
211,978,502 60,628,390
Map 5 14.28 6,950
138,098 138,098
Map 6 12.44 3,910
31 31
Reducer 2 2 22.69 61,320
60,628,390 69,182
Reducer 3 12.63 3,910
69,182 100
Reducer 4 11.01 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
[jira] [Updated] (HIVE-8671) Overflow in estimate row count and data size with fetch column stats
[
https://issues.apache.org/jira/browse/HIVE-8671?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Mostafa Mokhtar updated HIVE-8671:
--
Attachment: HIVE-8671.2.patch
[~sershe]
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
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_TASKSDURATION_SECONDS CPU_TIME_MILLIS
INPUT_RECORDS OUTPUT_RECORDS
Map 1 62 26.41 1,779,510
211,978,502 60,628,390
Map 5 14.28 6,950
138,098 138,098
Map 6 12.44 3,910
31 31
Reducer 2 2 22.69 61,320
60,628,390 69,182
Reducer 3 12.63 3,910
69,182 100
Reducer 4 11.01 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
[jira] [Updated] (HIVE-8671) Overflow in estimate row count and data size with fetch column stats
[
https://issues.apache.org/jira/browse/HIVE-8671?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Prasanth J updated HIVE-8671:
-
Attachment: HIVE-8671.3.patch
Added fix for overflow issue. Merged with changes from [~mmokhtar]'s patch.
Tested the query on TPCDS 3 scale and the stats looks good without overflow.
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
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_TASKSDURATION_SECONDS CPU_TIME_MILLIS
INPUT_RECORDS OUTPUT_RECORDS
Map 1 62 26.41 1,779,510
211,978,502 60,628,390
Map 5 14.28 6,950
138,098 138,098
Map 6 12.44 3,910
31 31
Reducer 2 2 22.69 61,320
60,628,390 69,182
Reducer 3 12.63 3,910
69,182 100
Reducer 4 11.01 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
[jira] [Updated] (HIVE-8671) Overflow in estimate row count and data size with fetch column stats
[
https://issues.apache.org/jira/browse/HIVE-8671?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Prasanth J updated HIVE-8671:
-
Status: Patch Available (was: Open)
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
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_TASKSDURATION_SECONDS CPU_TIME_MILLIS
INPUT_RECORDS OUTPUT_RECORDS
Map 1 62 26.41 1,779,510
211,978,502 60,628,390
Map 5 14.28 6,950
138,098 138,098
Map 6 12.44 3,910
31 31
Reducer 2 2 22.69 61,320
60,628,390 69,182
Reducer 3 12.63 3,910
69,182 100
Reducer 4 11.01 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
[jira] [Updated] (HIVE-8671) Overflow in estimate row count and data size with fetch column stats
[
https://issues.apache.org/jira/browse/HIVE-8671?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Prasanth J updated HIVE-8671:
-
Status: Open (was: Patch Available)
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
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_TASKSDURATION_SECONDS CPU_TIME_MILLIS
INPUT_RECORDS OUTPUT_RECORDS
Map 1 62 26.41 1,779,510
211,978,502 60,628,390
Map 5 14.28 6,950
138,098 138,098
Map 6 12.44 3,910
31 31
Reducer 2 2 22.69 61,320
60,628,390 69,182
Reducer 3 12.63 3,910
69,182 100
Reducer 4 11.01 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
[jira] [Updated] (HIVE-8671) Overflow in estimate row count and data size with fetch column stats
[
https://issues.apache.org/jira/browse/HIVE-8671?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Prasanth J updated HIVE-8671:
-
Attachment: HIVE-8671.4.patch
Addressed [~sershe]'s code review changes.
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
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_TASKSDURATION_SECONDS CPU_TIME_MILLIS
INPUT_RECORDS OUTPUT_RECORDS
Map 1 62 26.41 1,779,510
211,978,502 60,628,390
Map 5 14.28 6,950
138,098 138,098
Map 6 12.44 3,910
31 31
Reducer 2 2 22.69 61,320
60,628,390 69,182
Reducer 3 12.63 3,910
69,182 100
Reducer 4 11.01 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:
[jira] [Updated] (HIVE-8671) Overflow in estimate row count and data size with fetch column stats
[
https://issues.apache.org/jira/browse/HIVE-8671?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Prasanth J updated HIVE-8671:
-
Status: Patch Available (was: Open)
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
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_TASKSDURATION_SECONDS CPU_TIME_MILLIS
INPUT_RECORDS OUTPUT_RECORDS
Map 1 62 26.41 1,779,510
211,978,502 60,628,390
Map 5 14.28 6,950
138,098 138,098
Map 6 12.44 3,910
31 31
Reducer 2 2 22.69 61,320
60,628,390 69,182
Reducer 3 12.63 3,910
69,182 100
Reducer 4 11.01 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
[jira] [Updated] (HIVE-8671) Overflow in estimate row count and data size with fetch column stats
[
https://issues.apache.org/jira/browse/HIVE-8671?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Prasanth J updated HIVE-8671:
-
Attachment: HIVE-8671.5.patch
Fixes test failures.
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_TASKSDURATION_SECONDS CPU_TIME_MILLIS
INPUT_RECORDS OUTPUT_RECORDS
Map 1 62 26.41 1,779,510
211,978,502 60,628,390
Map 5 14.28 6,950
138,098 138,098
Map 6 12.44 3,910
31 31
Reducer 2 2 22.69 61,320
60,628,390 69,182
Reducer 3 12.63 3,910
69,182 100
Reducer 4 11.01 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:
[jira] [Updated] (HIVE-8671) Overflow in estimate row count and data size with fetch column stats
[
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_TASKSDURATION_SECONDS CPU_TIME_MILLIS INPUT_RECORDS
OUTPUT_RECORDS
Map 1 62 26.41 1,779,510 211,978,502
60,628,390
Map 5 14.28 6,950 138,098
138,098
Map 6 12.44 3,91031
31
Reducer 2 2 22.69 61,32060,628,390
69,182
Reducer 3 12.63 3,91069,182
100
Reducer 4 11.01 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
