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From William Wong <william1...@gmail.com>
Subject Re: Filter cannot be pushed via a Join
Date Tue, 18 Jun 2019 15:56:46 GMT
BTW, I noticed a workaround is creating a custom rule to remove 'empty
local relation' from a union table. However, I am not 100% sure if it is
the right approach.

On Tue, Jun 18, 2019 at 11:53 PM William Wong <william1104@gmail.com> wrote:

> Dear all,
>
> I am not sure if it is something expected or not, and should I report it
> as a bug.  Basically, the constraints of a union table could be turned
> empty if any subtable is turned into an empty local relation. The side
> effect is filter cannot be inferred correctly (by
> InferFiltersFromConstrains)
>
> We may reproduce the issue with the following setup:
> 1) Prepare two tables:
> * spark.sql("CREATE TABLE IF NOT EXISTS table1(id string, val string)
> USING PARQUET");
> * spark.sql("CREATE TABLE IF NOT EXISTS table2(id string, val string)
> USING PARQUET");
>
> 2) Create a union view on table1.
> * spark.sql("""
>      | CREATE VIEW partitioned_table_1 AS
>      | SELECT * FROM table1 WHERE id = 'a'
>      | UNION ALL
>      | SELECT * FROM table1 WHERE id = 'b'
>      | UNION ALL
>      | SELECT * FROM table1 WHERE id = 'c'
>      | UNION ALL
>      | SELECT * FROM table1 WHERE id NOT IN ('a','b','c')
>      | """.stripMargin)
>
> 3) View the optimized plan of this SQL. The filter 't2.id = 'a'' cannot
> be inferred. We can see that the constraints of the left table are empty.
>
> scala> spark.sql("SELECT * FROM partitioned_table_1 t1, table2 t2 WHERE
> t1.id = t2.id AND t1.id = 'a'").queryExecution.optimizedPlan
> res39: org.apache.spark.sql.catalyst.plans.logical.LogicalPlan =
> Join Inner, (id#0 = id#4)
> :- Union
> :  :- Filter (isnotnull(id#0) && (id#0 = a))
> :  :  +- Relation[id#0,val#1] parquet
> :  :- LocalRelation <empty>, [id#0, val#1]
> :  :- LocalRelation <empty>, [id#0, val#1]
> :  +- Filter ((isnotnull(id#0) && NOT id#0 IN (a,b,c)) && (id#0 = a))
> :     +- Relation[id#0,val#1] parquet
> +- Filter isnotnull(id#4)
>    +- Relation[id#4,val#5] parquet
>
> scala> spark.sql("SELECT * FROM partitioned_table_1 t1, table2 t2 WHERE
> t1.id = t2.id AND t1.id =
> 'a'").queryExecution.optimizedPlan.children(0).constraints
> res40: org.apache.spark.sql.catalyst.expressions.ExpressionSet = Set()
>
> 4) Modified the query to avoid empty local relation. The filter 't2.id in
> ('a','b','c','d')' is then inferred properly. The constraints of the left
> table are not empty as well.
>
> scala> spark.sql("SELECT * FROM partitioned_table_1 t1, table2 t2 WHERE
> t1.id = t2.id AND t1.id IN
> ('a','b','c','d')").queryExecution.optimizedPlan
> res42: org.apache.spark.sql.catalyst.plans.logical.LogicalPlan =
> Join Inner, (id#0 = id#4)
> :- Union
> :  :- Filter ((isnotnull(id#0) && (id#0 = a)) && id#0 IN (a,b,c,d))
> :  :  +- Relation[id#0,val#1] parquet
> :  :- Filter ((isnotnull(id#0) && (id#0 = b)) && id#0 IN (a,b,c,d))
> :  :  +- Relation[id#0,val#1] parquet
> :  :- Filter ((isnotnull(id#0) && (id#0 = c)) && id#0 IN (a,b,c,d))
> :  :  +- Relation[id#0,val#1] parquet
> :  +- Filter ((NOT id#0 IN (a,b,c) && id#0 IN (a,b,c,d)) &&
> isnotnull(id#0))
> :     +- Relation[id#0,val#1] parquet
> +- Filter ((id#4 IN (a,b,c,d) && ((isnotnull(id#4) && (((id#4 = a) ||
> (id#4 = b)) || (id#4 = c))) || NOT id#4 IN (a,b,c))) && isnotnull(id#4))
>    +- Relation[id#4,val#5] parquet
>
> scala> spark.sql("SELECT * FROM partitioned_table_1 t1, table2 t2 WHERE
> t1.id = t2.id AND t1.id IN
> ('a','b','c','d')").queryExecution.optimizedPlan.children(0).constraints
> res44: org.apache.spark.sql.catalyst.expressions.ExpressionSet =
> Set(isnotnull(id#0), id#0 IN (a,b,c,d), ((((id#0 = a) || (id#0 = b)) ||
> (id#0 = c)) || NOT id#0 IN (a,b,c)))
>
>
> Thanks and regards,
> William
>
>
> On Sat, Jun 15, 2019 at 1:13 AM William Wong <william1104@gmail.com>
> wrote:
>
>> Hi all,
>>
>> Appreciate any expert may help on this strange behavior..
>>
>> It is interesting that... I implemented a custom rule to remove empty
>> LocalRelation children under Union and run the same query. The filter 'id =
>> 'a' is inferred to the table2 and pushed via the Join.
>>
>> scala> spark2.sql("SELECT * FROM partitioned_table_1 t1, table2 t2 WHERE
>> t1.id = t2.id AND t1.id = 'a'").explain
>> == Physical Plan ==
>> *(4) BroadcastHashJoin [id#0], [id#4], Inner, BuildRight
>> :- Union
>> :  :- *(1) Project [id#0, val#1]
>> :  :  +- *(1) Filter (isnotnull(id#0) && (id#0 = a))
>> :  :     +- *(1) FileScan parquet default.table1[id#0,val#1] Batched:
>> true, Format: Parquet, Location:
>> InMemoryFileIndex[file:/Users/williamwong/spark-warehouse/table1],
>> PartitionFilters: [], PushedFilters: [IsNotNull(id), EqualTo(id,a)],
>> ReadSchema: struct<id:string,val:string>
>> :  +- *(2) Project [id#0, val#1]
>> :     +- *(2) Filter ((isnotnull(id#0) && NOT id#0 IN (a,b,c)) &&
(id#0 =
>> a))
>> :        +- *(2) FileScan parquet default.table1[id#0,val#1] Batched:
>> true, Format: Parquet, Location:
>> InMemoryFileIndex[file:/Users/williamwong/spark-warehouse/table1],
>> PartitionFilters: [], PushedFilters: [IsNotNull(id), Not(In(id, [a,b,c])),
>> EqualTo(id,a)], ReadSchema: struct<id:string,val:string>
>> +- BroadcastExchange HashedRelationBroadcastMode(List(input[0, string,
>> true]))
>>    +- *(3) Project [id#4, val#5]
>>       +- *(3) Filter ((id#4 = a) && isnotnull(id#4))
>>          +- *(3) FileScan parquet default.table2[id#4,val#5] Batched:
>> true, Format: Parquet, Location:
>> InMemoryFileIndex[file:/Users/williamwong/spark-warehouse/table2],
>> PartitionFilters: [], *PushedFilters: [EqualTo(id,a), IsNotNull(id)],*
>> ReadSchema: struct<id:string,val:string>
>>
>> scala>
>>
>> Thanks and regards,
>> William
>>
>>
>>
>> On Sat, Jun 15, 2019 at 12:13 AM William Wong <william1104@gmail.com>
>> wrote:
>>
>>> Dear all,
>>>
>>> I created two tables.
>>>
>>> scala> spark.sql("CREATE TABLE IF NOT EXISTS table1(id string, val
>>> string) USING PARQUET");
>>> 19/06/14 23:49:10 WARN ObjectStore: Version information not found in
>>> metastore. hive.metastore.schema.verification is not enabled so recording
>>> the schema version 1.2.0
>>> 19/06/14 23:49:11 WARN ObjectStore: Failed to get database default,
>>> returning NoSuchObjectException
>>> res1: org.apache.spark.sql.DataFrame = []
>>>
>>> scala> spark.sql("CREATE TABLE IF NOT EXISTS table2(id string, val
>>> string) USING PARQUET");
>>> res2: org.apache.spark.sql.DataFrame = []
>>>
>>>
>>> It is the plan of joining these two column via ID column. It looks good
>>> to me as the filter 'id ='a'' is pushed to both tables as expected.
>>>
>>> scala> spark.sql("SELECT * FROM table2 t1, table2 t2 WHERE t1.id = t2.id
>>> AND t1.id ='a'").explain
>>> == Physical Plan ==
>>> *(2) BroadcastHashJoin [id#23], [id#68], Inner, BuildRight
>>> :- *(2) Project [id#23, val#24]
>>> :  +- *(2) Filter (isnotnull(id#23) && (id#23 = a))
>>> :     +- *(2) FileScan parquet default.table2[id#23,val#24] Batched:
>>> true, Format: Parquet, Location:
>>> InMemoryFileIndex[file:/Users/williamwong/spark-warehouse/table2], *PartitionFilters:
>>> [], PushedFilters: [IsNotNull(id), EqualTo(id,a)],* ReadSchema:
>>> struct<id:string,val:string>
>>> +- BroadcastExchange HashedRelationBroadcastMode(List(input[0, string,
>>> true]))
>>>    +- *(1) Project [id#68, val#69]
>>>       +- *(1) Filter ((id#68 = a) && isnotnull(id#68))
>>>          +- *(1) FileScan parquet default.table2[id#68,val#69] Batched:
>>> true, Format: Parquet, Location:
>>> InMemoryFileIndex[file:/Users/williamwong/spark-warehouse/table2], *PartitionFilters:
>>> [], PushedFilters: [EqualTo(id,a), IsNotNull(id)],* ReadSchema:
>>> struct<id:string,val:string>
>>>
>>>
>>> Somehow, we created a view on table1 by union a few partitions like this:
>>>
>>> scala> spark.sql("""
>>>      | CREATE VIEW partitioned_table_1 AS
>>>      | SELECT * FROM table1 WHERE id = 'a'
>>>      | UNION ALL
>>>      | SELECT * FROM table1 WHERE id = 'b'
>>>      | UNION ALL
>>>      | SELECT * FROM table1 WHERE id = 'c'
>>>      | UNION ALL
>>>      | SELECT * FROM table1 WHERE id NOT IN ('a','b','c')
>>>      | """.stripMargin)
>>> res7: org.apache.spark.sql.DataFrame = []
>>>
>>>
>>> In theory, selecting data via this view 'partitioned_table_1' should be
>>> the same as via the table 'table1'
>>>
>>> This query also can push the filter 'id IN ('a','b','c','d') to table2
>>> as expected.
>>>
>>> scala> spark.sql("SELECT * FROM partitioned_table_1 t1, table2 t2 WHERE
>>> t1.id = t2.id AND t1.id IN ('a','b','c','d')").explain
>>> == Physical Plan ==
>>> *(6) BroadcastHashJoin [id#0], [id#23], Inner, BuildRight
>>> :- Union
>>> :  :- *(1) Project [id#0, val#1]
>>> :  :  +- *(1) Filter ((isnotnull(id#0) && (id#0 = a)) && id#0
IN
>>> (a,b,c,d))
>>> :  :     +- *(1) FileScan parquet default.table1[id#0,val#1] Batched:
>>> true, Format: Parquet, Location:
>>> InMemoryFileIndex[file:/Users/williamwong/spark-warehouse/table1],
>>> PartitionFilters: [], PushedFilters: [IsNotNull(id), EqualTo(id,a), In(id,
>>> [a,b,c,d])], ReadSchema: struct<id:string,val:string>
>>> :  :- *(2) Project [id#0, val#1]
>>> :  :  +- *(2) Filter ((isnotnull(id#0) && (id#0 = b)) && id#0
IN
>>> (a,b,c,d))
>>> :  :     +- *(2) FileScan parquet default.table1[id#0,val#1] Batched:
>>> true, Format: Parquet, Location:
>>> InMemoryFileIndex[file:/Users/williamwong/spark-warehouse/table1],
>>> PartitionFilters: [], PushedFilters: [IsNotNull(id), EqualTo(id,b), In(id,
>>> [a,b,c,d])], ReadSchema: struct<id:string,val:string>
>>> :  :- *(3) Project [id#0, val#1]
>>> :  :  +- *(3) Filter ((isnotnull(id#0) && (id#0 = c)) && id#0
IN
>>> (a,b,c,d))
>>> :  :     +- *(3) FileScan parquet default.table1[id#0,val#1] Batched:
>>> true, Format: Parquet, Location:
>>> InMemoryFileIndex[file:/Users/williamwong/spark-warehouse/table1],
>>> PartitionFilters: [], PushedFilters: [IsNotNull(id), EqualTo(id,c), In(id,
>>> [a,b,c,d])], ReadSchema: struct<id:string,val:string>
>>> :  +- *(4) Project [id#0, val#1]
>>> :     +- *(4) Filter ((NOT id#0 IN (a,b,c) && id#0 IN (a,b,c,d)) &&
>>> isnotnull(id#0))
>>> :        +- *(4) FileScan parquet default.table1[id#0,val#1] Batched:
>>> true, Format: Parquet, Location:
>>> InMemoryFileIndex[file:/Users/williamwong/spark-warehouse/table1],
>>> PartitionFilters: [], PushedFilters: [Not(In(id, [a,b,c])), In(id,
>>> [a,b,c,d]), IsNotNull(id)], ReadSchema: struct<id:string,val:string>
>>> +- BroadcastExchange HashedRelationBroadcastMode(List(input[0, string,
>>> true]))
>>>    +- *(5) Project [id#23, val#24]
>>>       +- *(5) Filter ((id#23 IN (a,b,c,d) && ((isnotnull(id#23) &&
>>> (((id#23 = a) || (id#23 = b)) || (id#23 = c))) || NOT id#23 IN (a,b,c))) &&
>>> isnotnull(id#23))
>>>          +- *(5) FileScan parquet default.table2[id#23,val#24] Batched:
>>> true, Format: Parquet, Location:
>>> InMemoryFileIndex[file:/Users/williamwong/spark-warehouse/table2],
>>> PartitionFilters: [], *PushedFilters: [In(id, [a,b,c,d]),
>>> Or(And(IsNotNull(id),Or(Or(EqualTo(id,a),EqualTo(id,b)),EqualTo(id,c))),Not(I...,
>>> *ReadSchema: struct<id:string,val:string>
>>>
>>> scala>
>>>
>>>
>>> However, if we change the filter to 'id ='a', something strange
>>> happened. The filter 'id = 'a' cannot be pushed via table2...
>>>
>>> scala> spark.sql("SELECT * FROM partitioned_table_1 t1, table2 t2 WHERE
>>> t1.id = t2.id AND t1.id = 'a'").explain
>>> == Physical Plan ==
>>> *(4) BroadcastHashJoin [id#0], [id#23], Inner, BuildRight
>>> :- Union
>>> :  :- *(1) Project [id#0, val#1]
>>> :  :  +- *(1) Filter (isnotnull(id#0) && (id#0 = a))
>>> :  :     +- *(1) FileScan parquet default.table1[id#0,val#1] Batched:
>>> true, Format: Parquet, Location:
>>> InMemoryFileIndex[file:/Users/williamwong/spark-warehouse/table1],
>>> PartitionFilters: [], PushedFilters: [IsNotNull(id), EqualTo(id,a)],
>>> ReadSchema: struct<id:string,val:string>
>>> :  :- LocalTableScan <empty>, [id#0, val#1]
>>> :  :- LocalTableScan <empty>, [id#0, val#1]
>>> :  +- *(2) Project [id#0, val#1]
>>> :     +- *(2) Filter ((isnotnull(id#0) && NOT id#0 IN (a,b,c)) &&
(id#0
>>> = a))
>>> :        +- *(2) FileScan parquet default.table1[id#0,val#1] Batched:
>>> true, Format: Parquet, Location:
>>> InMemoryFileIndex[file:/Users/williamwong/spark-warehouse/table1],
>>> PartitionFilters: [], PushedFilters: [IsNotNull(id), Not(In(id, [a,b,c])),
>>> EqualTo(id,a)], ReadSchema: struct<id:string,val:string>
>>> +- BroadcastExchange HashedRelationBroadcastMode(List(input[0, string,
>>> true]))
>>>    +- *(3) Project [id#23, val#24]
>>>       +- *(3) Filter isnotnull(id#23)
>>>          +- *(3) FileScan parquet default.table2[id#23,val#24] Batched:
>>> true, Format: Parquet, Location:
>>> InMemoryFileIndex[file:/Users/williamwong/spark-warehouse/table2],
>>> PartitionFilters: [], PushedFilters: [IsNotNull(id)], ReadSchema:
>>> struct<id:string,val:string>
>>>
>>>
>>> Appreciate if anyone has an idea on it. Many thanks.
>>>
>>> Best regards,
>>> William
>>>
>>

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