Github user viirya commented on a diff in the pull request: https://github.com/apache/spark/pull/22357#discussion_r216601125 --- Diff: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaPruning.scala --- @@ -110,7 +110,17 @@ private[sql] object ParquetSchemaPruning extends Rule[LogicalPlan] { val projectionRootFields = projects.flatMap(getRootFields) val filterRootFields = filters.flatMap(getRootFields) - (projectionRootFields ++ filterRootFields).distinct + // Kind of expressions don't need to access any fields of a root fields, e.g., `IsNotNull`. + // For them, if there are any nested fields accessed in the query, we don't need to add root + // field access of above expressions. + // For example, for a query `SELECT name.first FROM contacts WHERE name IS NOT NULL`, + // we don't need to read nested fields of `name` struct other than `first` field. --- End diff -- A complex column is null and its fields are null are different. I think we don't need to read all the fields to check if the complex column is null. In other words, in above case, when we only read `employer.id` and it is null, the predicate `employer is not null` will still be true because it is a complex column containing a null field.
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