Github user mallman commented on a diff in the pull request:
https://github.com/apache/spark/pull/22357#discussion_r216545091
--- 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 --
I'm having trouble accepting this, but perhaps I'm reading too much into it
(or not enough). Let me illustrate with a couple of queries and their physical
plans.
Assuming the data model in `ParquetSchemaPruningSuite.scala`, the physical
plan for the query
select employer.id from contacts where employer is not null
is
```
== Physical Plan ==
*(1) Project [employer#36.id AS id#46]
+- *(1) Filter isnotnull(employer#36)
+- *(1) FileScan parquet [employer#36,p#37] Batched: false, Format:
Parquet,
PartitionCount: 2, PartitionFilters: [], PushedFilters:
[IsNotNull(employer)],
ReadSchema: struct<employer:struct<id:int>>
```
The physical plan for the query
select employer.id from contacts where employer.id is not null
is
```
== Physical Plan ==
*(1) Project [employer#36.id AS id#47]
+- *(1) Filter (isnotnull(employer#36) && isnotnull(employer#36.id))
+- *(1) FileScan parquet [employer#36,p#37] Batched: false, Format:
Parquet,
PartitionCount: 2, PartitionFilters: [], PushedFilters:
[IsNotNull(employer)],
ReadSchema: struct<employer:struct<id:int>>
```
The read schemata are the same, but the query filters are not. The file
scan for the second query looks as I would expect, but the scan for the first
query appears to only read `employer.id` even though it needs to check
`employer is not null`. If it only reads `employer.id`, how does it check that
`employer.company` is not null? Perhaps `employer.id` is null but
`employer.company` is not null for some row...
I have run some tests to validate that this PR is returning the correct
results for both queries, and it is. But I don't understand why.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org
