Hi, William, Thanks for reporting it. Could you open a JIRA?
Cheers, Xiao William Wong <william1...@gmail.com> 于2019年6月18日周二 上午8:57写道: > 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 <william1...@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 <william1...@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 <william1...@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 >>>> >>>