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Posted to commits@gluten.apache.org by "jiangjiangtian (via GitHub)" <gi...@apache.org> on 2026/07/01 08:36:59 UTC

[I] [VL] Exchange reuse not applied due to unnormalized Alias in GenerateExecTransformer's generator [gluten]

jiangjiangtian opened a new issue, #12413:
URL: https://github.com/apache/gluten/issues/12413

   ### Backend
   
   VL (Velox)
   
   ### Bug description
   
   Suppose we want to execute the following SQL (the SQL is just for showing and doesn't mean anything):
   ```SQL
   CREATE OR REPLACE TEMP VIEW employees AS
   SELECT * FROM VALUES
   (1, 'Alice', 'Sales,Computer', 1000),
   (2, 'Bob', 'Marketing,Sales', 2000),
   (3, 'Charlie', 'Marketing,Trading', 3000)
   AS employees(emp_id, emp_name, dept_names, sale);
   
   set spark.sql.adaptive.enabled=false;
   
   EXPLAIN WITH base AS (
   SELECT * FROM employees
     LATERAL VIEW explode(split(dept_names, ',')) AS dept_name
   )
   SELECT * FROM
   (
     SELECT emp_id, emp_name, COUNT(*)
     FROM (
       SELECT emp_id, emp_name, dept_names, sale
       FROM base
       GROUP BY 1, 2, 3, 4
     )
     GROUP BY 1, 2
   ) a
   JOIN
   (
     SELECT emp_id, SUM(sale)
     FROM (
       SELECT emp_id, emp_name, dept_names, sale
       FROM base
       GROUP BY 1, 2, 3, 4
     )
     GROUP BY 1
   ) b
   ON a.emp_id = b.emp_id;
   ```
   The plan is:
   ```
   == Physical Plan ==
   VeloxColumnarToRow
   +- ^(6) BroadcastHashJoinExecTransformer [emp_id#78], [emp_id#86], Inner, BuildRight, false
      :- ^(6) HashAggregateTransformer(keys=[emp_id#78, emp_name#79], functions=[count(1)], isStreamingAgg=false)
      :  +- ^(6) InputIteratorTransformer[emp_id#78, emp_name#79, count#101L]
      :     +- ColumnarExchange hashpartitioning(emp_id#78, emp_name#79, 2000), ENSURE_REQUIREMENTS, [emp_id#78, emp_name#79, count#101L], [plan_id=1889], [shuffle_writer_type=hash], [OUTPUT] List(emp_id:IntegerType, emp_name:StringType, count:LongType)
      :        +- VeloxResizeBatches 1024, 2147483647, 10485760
      :           +- ^(2) ProjectExecTransformer [hash(emp_id#78, emp_name#79, 42) AS hash_partition_key#129, emp_id#78, emp_name#79, count#101L]
      :              +- ^(2) FlushableHashAggregateTransformer(keys=[emp_id#78, emp_name#79], functions=[partial_count(1)], isStreamingAgg=false)
      :                 +- ^(2) ProjectExecTransformer [emp_id#78, emp_name#79]
      :                    +- ^(2) HashAggregateTransformer(keys=[emp_id#78, emp_name#79, dept_names#80, sale#81], functions=[], isStreamingAgg=false)
      :                       +- ^(2) InputIteratorTransformer[emp_id#78, emp_name#79, dept_names#80, sale#81]
      :                          +- ColumnarExchange hashpartitioning(emp_id#78, emp_name#79, dept_names#80, sale#81, 2000), ENSURE_REQUIREMENTS, [emp_id#78, emp_name#79, dept_names#80, sale#81], [plan_id=1880], [shuffle_writer_type=hash], [OUTPUT] List(emp_id:IntegerType, emp_name:StringType, dept_names:StringType, sale:IntegerType)
      :                             +- VeloxResizeBatches 1024, 2147483647, 10485760
      :                                +- ^(1) ProjectExecTransformer [hash(emp_id#78, emp_name#79, dept_names#80, sale#81, 42) AS hash_partition_key#128, emp_id#78, emp_name#79, dept_names#80, sale#81]
      :                                   +- ^(1) FlushableHashAggregateTransformer(keys=[emp_id#78, emp_name#79, dept_names#80, sale#81], functions=[], isStreamingAgg=false)
      :                                      +- ^(1) ProjectExecTransformer [emp_id#78, emp_name#79, dept_names#80, sale#81]
      :                                         +- ^(1) GenerateExecTransformer explode(split(dept_names#80, ,, -1) AS _pre_0#104), [emp_id#78, emp_name#79, dept_names#80, sale#81], false, [dept_name#95]
      :                                            +- ^(1) ProjectExecTransformer [emp_id#78, emp_name#79, dept_names#80, sale#81, split(dept_names#80, ,, -1) AS _pre_0#104]
      :                                               +- ^(1) InputIteratorTransformer[emp_id#78, emp_name#79, dept_names#80, sale#81]
      :                                                  +- RowToVeloxColumnar
      :                                                     +- LocalTableScan [emp_id#78, emp_name#79, dept_names#80, sale#81]
      +- ^(6) InputIteratorTransformer[emp_id#86, sum(sale)#99L]
         +- ColumnarBroadcastExchange HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1916]
            +- ^(5) HashAggregateTransformer(keys=[emp_id#86], functions=[sum(sale#89)], isStreamingAgg=false)
               +- ^(5) InputIteratorTransformer[emp_id#86, sum#103L]
                  +- ColumnarExchange hashpartitioning(emp_id#86, 2000), ENSURE_REQUIREMENTS, [emp_id#86, sum#103L], [plan_id=1911], [shuffle_writer_type=hash], [OUTPUT] List(emp_id:IntegerType, sum:LongType)
                     +- VeloxResizeBatches 1024, 2147483647, 10485760
                        +- ^(4) ProjectExecTransformer [hash(emp_id#86, 42) AS hash_partition_key#131, emp_id#86, sum#103L]
                           +- ^(4) FlushableHashAggregateTransformer(keys=[emp_id#86], functions=[partial_sum(sale#89)], isStreamingAgg=false)
                              +- ^(4) ProjectExecTransformer [emp_id#86, sale#89]
                                 +- ^(4) HashAggregateTransformer(keys=[emp_id#86, emp_name#87, dept_names#88, sale#89], functions=[], isStreamingAgg=false)
                                    +- ^(4) InputIteratorTransformer[emp_id#86, emp_name#87, dept_names#88, sale#89]
                                       +- ColumnarExchange hashpartitioning(emp_id#86, emp_name#87, dept_names#88, sale#89, 2000), ENSURE_REQUIREMENTS, [emp_id#86, emp_name#87, dept_names#88, sale#89], [plan_id=1902], [shuffle_writer_type=hash], [OUTPUT] List(emp_id:IntegerType, emp_name:StringType, dept_names:StringType, sale:IntegerType)
                                          +- VeloxResizeBatches 1024, 2147483647, 10485760
                                             +- ^(3) ProjectExecTransformer [hash(emp_id#86, emp_name#87, dept_names#88, sale#89, 42) AS hash_partition_key#130, emp_id#86, emp_name#87, dept_names#88, sale#89]
                                                +- ^(3) FlushableHashAggregateTransformer(keys=[emp_id#86, emp_name#87, dept_names#88, sale#89], functions=[], isStreamingAgg=false)
                                                   +- ^(3) ProjectExecTransformer [emp_id#86, emp_name#87, dept_names#88, sale#89]
                                                      +- ^(3) GenerateExecTransformer explode(split(dept_names#88, ,, -1) AS _pre_1#105), [emp_id#86, emp_name#87, dept_names#88, sale#89], false, [dept_name#96]
                                                         +- ^(3) ProjectExecTransformer [emp_id#86, emp_name#87, dept_names#88, sale#89, split(dept_names#88, ,, -1) AS _pre_1#105]
                                                            +- ^(3) InputIteratorTransformer[emp_id#86, emp_name#87, dept_names#88, sale#89]
                                                               +- RowToVeloxColumnar
                                                                  +- LocalTableScan [emp_id#86, emp_name#87, dept_names#88, sale#89]
   ```
   The plan is correct but we lose the opportunity to apply the optimization of reusing exchange. The two ColumnarExchange nodes (plan_id=1880 and plan_id=1902) are structurally identical, but are not reused (no ReusedExchange appears in the plan).
   The root cause is the Alias expression in the generator of GenerateExecTransformer. In the plan above, the first branch has:
   ```
   GenerateExecTransformer explode(split(dept_names#80, ,, -1) AS _pre_0#104), ...
   ```
   while the second branch has:
   ```
   GenerateExecTransformer explode(split(dept_names#88, ,, -1) AS _pre_1#105), ...
   ```
   The Alias (AS _pre_0#104 / AS _pre_1#105) is nested inside the generator expression. Spark's only assigns position-based ExprId to top-level Alias nodes in the plan's expressions. Since the generator (e.g., Explode) is not an Alias, it falls into the case other branch which calls [normalizeExpressions](https://github.com/apache/spark/blob/branch-3.5/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/QueryPlan.scala#L650-L668). However, normalizeExpressions only replaces the exprId of AttributeReference — it does not modify the exprId of a nested Alias. As a result, the Alias inside the generator retains its original globally-unique exprId (e.g., #104 vs #105). Since compares exprId, the two structurally-identical sub-plans produce different canonicalized forms, preventing ReuseExchange from reusing the exchange.
   
   ### Gluten version
   
   _No response_
   
   ### Spark version
   
   None
   
   ### Spark configurations
   
   3.5
   
   ### System information
   
   _No response_
   
   ### Relevant logs
   
   ```bash
   
   ```


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Re: [I] [VL] Exchange reuse not applied due to unnormalized Alias in GenerateExecTransformer's generator [gluten]

Posted by "philo-he (via GitHub)" <gi...@apache.org>.
philo-he closed issue #12413: [VL] Exchange reuse not applied due to unnormalized Alias in GenerateExecTransformer's generator
URL: https://github.com/apache/gluten/issues/12413


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