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https://issues.apache.org/jira/browse/SPARK-48486?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
chenfengbin updated SPARK-48486:
--------------------------------
Description:
The Dynamic Partition Pruning (DPP) feature in Spark can cause the generated
Directed Acyclic Graph (DAG) to expand.
for example: The partition field of table A or B is part_dt.
select a.part_dt,a.{*},b.part_dt,b.{*}
from a left join b on b.part_dt = a.part_dt
where a.part_dt in ('2024-05-30','2024-05-31')
During the generation of Dynamic Partition Pruning (DPP), the tree will be
traversed recursively more times.
24/05/31 16:14:14 INFO DataSourceStrategy: Pruning directories with:
part_dt#219 IN (2024-05-30,2024-05-31)
24/05/31 16:14:14 INFO DataSourceStrategy: Pruning directories with:
part_dt#223 IN
(2024-05-30,2024-05-31),isnotnull(part_dt#223),dynamicpruning#234
[part_dt#223|#223]
24/05/31 16:14:14 INFO DataSourceStrategy: Pruning directories with:
part_dt#219 IN (2024-05-30,2024-05-31)
The last one is extra：24/05/31 16:14:14 INFO DataSourceStrategy: Pruning
directories with: part_dt#219 IN (2024-05-30,2024-05-31)
When more partitions meet the condition, it will increase by 2 to the power of
n, then divided by 2.
for example:
select a.part_dt,a.*,b.part_dt,b.*,c.part_dt,c.*
from a
left join b on b.part_dt = a.part_dt
left join c on c.part_dt = a.part_dt
where a.part_dt in ('2024-05-30','2024-05-31')
result:
was:
The Dynamic Partition Pruning (DPP) feature in Spark can cause the generated
Directed Acyclic Graph (DAG) to expand.
for example: The partition field of table A or B is part_dt.
select a.part_dt,a.*,b.part_dt,b.*
from a left join b on b.part_dt = a.part_dt
where a.part_dt in ('2024-05-30','2024-05-31')
During the generation of Dynamic Partition Pruning (DPP), the tree will be
traversed recursively more times.
24/05/31 16:14:14 INFO DataSourceStrategy: Pruning directories with:
part_dt#219 IN (2024-05-30,2024-05-31)
24/05/31 16:14:14 INFO DataSourceStrategy: Pruning directories with:
part_dt#223 IN
(2024-05-30,2024-05-31),isnotnull(part_dt#223),dynamicpruning#234 [part_dt#223]
24/05/31 16:14:14 INFO DataSourceStrategy: Pruning directories with:
part_dt#219 IN (2024-05-30,2024-05-31)
The last one is extra：24/05/31 16:14:14 INFO DataSourceStrategy: Pruning
directories with: part_dt#219 IN (2024-05-30,2024-05-31)
When more partitions meet the condition, it will increase by 2 to the power of
n, then divided by 2.
for example:
select a.part_dt,a.*,b.part_dt,b.*
from a left join b on b.part_dt = a.part_dt where a.part_dt in
('2024-05-30','2024-05-31')
> The Dynamic Partition Pruning (DPP) feature in Spark can cause the generated
> Directed Acyclic Graph (DAG) to expand.
> --------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-48486
> URL: https://issues.apache.org/jira/browse/SPARK-48486
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 3.3.0
> Reporter: chenfengbin
> Priority: Major
>
> The Dynamic Partition Pruning (DPP) feature in Spark can cause the generated
> Directed Acyclic Graph (DAG) to expand.
> for example: The partition field of table A or B is part_dt.
> select a.part_dt,a.{*},b.part_dt,b.{*}
> from a left join b on b.part_dt = a.part_dt
> where a.part_dt in ('2024-05-30','2024-05-31')
> During the generation of Dynamic Partition Pruning (DPP), the tree will be
> traversed recursively more times.
> 24/05/31 16:14:14 INFO DataSourceStrategy: Pruning directories with:
> part_dt#219 IN (2024-05-30,2024-05-31)
> 24/05/31 16:14:14 INFO DataSourceStrategy: Pruning directories with:
> part_dt#223 IN
> (2024-05-30,2024-05-31),isnotnull(part_dt#223),dynamicpruning#234
> [part_dt#223|#223]
> 24/05/31 16:14:14 INFO DataSourceStrategy: Pruning directories with:
> part_dt#219 IN (2024-05-30,2024-05-31)
> The last one is extra：24/05/31 16:14:14 INFO DataSourceStrategy: Pruning
> directories with: part_dt#219 IN (2024-05-30,2024-05-31)
> When more partitions meet the condition, it will increase by 2 to the power
> of n, then divided by 2.
> for example:
> select a.part_dt,a.*,b.part_dt,b.*,c.part_dt,c.*
> from a
> left join b on b.part_dt = a.part_dt
> left join c on c.part_dt = a.part_dt
> where a.part_dt in ('2024-05-30','2024-05-31')
> result:
>
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