Github user mallman commented on a diff in the pull request:

    https://github.com/apache/spark/pull/14690#discussion_r83325088
  
    --- Diff: 
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PruneFileSourcePartitions.scala
 ---
    @@ -0,0 +1,72 @@
    +/*
    + * Licensed to the Apache Software Foundation (ASF) under one or more
    + * contributor license agreements.  See the NOTICE file distributed with
    + * this work for additional information regarding copyright ownership.
    + * The ASF licenses this file to You under the Apache License, Version 2.0
    + * (the "License"); you may not use this file except in compliance with
    + * the License.  You may obtain a copy of the License at
    + *
    + *    http://www.apache.org/licenses/LICENSE-2.0
    + *
    + * Unless required by applicable law or agreed to in writing, software
    + * distributed under the License is distributed on an "AS IS" BASIS,
    + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    + * See the License for the specific language governing permissions and
    + * limitations under the License.
    + */
    +
    +package org.apache.spark.sql.execution.datasources
    +
    +import org.apache.spark.sql.catalyst.expressions._
    +import org.apache.spark.sql.catalyst.planning.PhysicalOperation
    +import org.apache.spark.sql.catalyst.plans.logical.{Filter, LogicalPlan, 
Project}
    +import org.apache.spark.sql.catalyst.rules.Rule
    +
    +private[sql] object PruneFileSourcePartitions extends Rule[LogicalPlan] {
    +  override def apply(plan: LogicalPlan): LogicalPlan = plan transformDown {
    +    case op @ PhysicalOperation(projects, filters,
    +        logicalRelation @
    +          LogicalRelation(fsRelation @
    +            HadoopFsRelation(
    +              tableFileCatalog: TableFileCatalog,
    +              partitionSchema,
    +              _,
    +              _,
    +              _,
    +              _),
    +            _,
    +            _))
    +        if filters.nonEmpty && fsRelation.partitionSchemaOption.isDefined 
=>
    +      // The attribute name of predicate could be different than the one 
in schema in case of
    +      // case insensitive, we should change them to match the one in 
schema, so we donot need to
    +      // worry about case sensitivity anymore.
    +      val normalizedFilters = filters.map { e =>
    +        e transform {
    +          case a: AttributeReference =>
    +            
a.withName(logicalRelation.output.find(_.semanticEquals(a)).get.name)
    +        }
    +      }
    +
    +      val sparkSession = fsRelation.sparkSession
    +      val partitionColumns =
    +        logicalRelation.resolve(
    +          partitionSchema, sparkSession.sessionState.analyzer.resolver)
    +      val partitionSet = AttributeSet(partitionColumns)
    +      val partitionKeyFilters =
    +        
ExpressionSet(normalizedFilters.filter(_.references.subsetOf(partitionSet)))
    +
    +      if (partitionKeyFilters.nonEmpty) {
    +          val prunedFileCatalog = 
tableFileCatalog.filterPartitions(partitionKeyFilters.toSeq)
    +          val prunedFsRelation =
    +            fsRelation.copy(location = prunedFileCatalog)(sparkSession)
    +          val prunedLogicalRelation = logicalRelation.copy(relation = 
prunedFsRelation)
    +
    +          // Keep partition-pruning predicates so that they are visible in 
physical planning
    +          val filterExpression = filters.reduceLeft(And)
    --- End diff --
    
    I pushed a commit to show partition count for partitioned tables.
    
    I also did some informal A/B perf testing keeping and omitting the 
partition pruning filters. I saw no discernible performance difference.


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