wangyum commented on pull request #31485:
URL: https://github.com/apache/spark/pull/31485#issuecomment-774841202
It may just not be explained correctly, for example:
```sql
create table t1 using parquet as select id as a, id as b, id as c from
range(1000000);
create table t2 using parquet as select id as a, id as b, id as c from
range(1000000);
create table t3 using parquet as select id as a, id as b, id as c from
range(1000000);
analyze table t1 compute statistics for all columns;
analyze table t2 compute statistics for all columns;
analyze table t3 compute statistics for all columns;
set spark.sql.cbo.enabled=true;
explain cost
select * from t3 where c > (select max(t1.c) as tc from t1 join t2 on t1.a =
t2.a and t2.b < 10);
== Optimized Logical Plan ==
Filter (isnotnull(c#35782L) AND (c#35782L > scalar-subquery#35774 [])),
Statistics(sizeInBytes=30.5 MiB, rowCount=1.00E+6)
: +- Aggregate [max(c#35785L) AS tc#35773L]
: +- Project [c#35785L]
: +- Join Inner, (a#35783L = a#35786L)
: :- Project [a#35783L, c#35785L]
: : +- Filter isnotnull(a#35783L)
: : +- Relation[a#35783L,b#35784L,c#35785L] parquet
: +- Project [a#35786L]
: +- Filter ((isnotnull(b#35787L) AND (b#35787L < 10)) AND
isnotnull(a#35786L))
: +- Relation[a#35786L,b#35787L,c#35788L] parquet
+- Relation[a#35780L,b#35781L,c#35782L] parquet, Statistics(sizeInBytes=30.5
MiB, rowCount=1.00E+6)
== Physical Plan ==
AdaptiveSparkPlan isFinalPlan=false
+- Filter (isnotnull(c#35782L) AND (c#35782L > Subquery subquery#35774,
[id=#201]))
: +- Subquery subquery#35774, [id=#201]
: +- AdaptiveSparkPlan isFinalPlan=false
: +- HashAggregate(keys=[], functions=[max(c#35785L)],
output=[tc#35773L])
: +- Exchange SinglePartition, ENSURE_REQUIREMENTS, [id=#199]
: +- HashAggregate(keys=[],
functions=[partial_max(c#35785L)], output=[max#35791L])
: +- Project [c#35785L]
: +- BroadcastHashJoin [a#35783L], [a#35786L], Inner,
BuildRight, false
: :- Filter isnotnull(a#35783L)
: : +- FileScan parquet
default.t1[a#35783L,c#35785L] Batched: true, DataFilters:
[isnotnull(a#35783L)], Format: Parquet, Location: InMemoryFileIndex(1
paths)[file:/root/opensource/apache-spark/spark-warehouse/t1],
PartitionFilters: [], PushedFilters: [IsNotNull(a)], ReadSchema:
struct<a:bigint,c:bigint>
: +- BroadcastExchange
HashedRelationBroadcastMode(List(input[0, bigint, true]),false), [id=#194]
: +- Project [a#35786L]
: +- Filter ((isnotnull(b#35787L) AND
(b#35787L < 10)) AND isnotnull(a#35786L))
: +- FileScan parquet
default.t2[a#35786L,b#35787L] Batched: true, DataFilters: [isnotnull(b#35787L),
(b#35787L < 10), isnotnull(a#35786L)], Format: Parquet, Location:
InMemoryFileIndex(1
paths)[file:/root/opensource/apache-spark/spark-warehouse/t2],
PartitionFilters: [], PushedFilters: [IsNotNull(b), LessThan(b,10),
IsNotNull(a)], ReadSchema: struct<a:bigint,b:bigint>
+- FileScan parquet default.t3[a#35780L,b#35781L,c#35782L] Batched: true,
DataFilters: [isnotnull(c#35782L)], Format: Parquet, Location:
InMemoryFileIndex(1
paths)[file:/root/opensource/apache-spark/spark-warehouse/t3],
PartitionFilters: [], PushedFilters: [IsNotNull(c)], ReadSchema:
struct<a:bigint,b:bigint,c:bigint>
```
It should be SMJ if stats incorrect.
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