[jira] [Commented] (SPARK-29721) Spark SQL reads unnecessary nested fields after using explode

["Jiri Humpolicek (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-29721?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17294414#comment-17294414 ] 

Jiri Humpolicek commented on SPARK-29721:
-----------------------------------------

I tested this on spark-3.1.1 and this works properly. But when I change the query to:

{{read.select(explode($"items").as('item)).select($"item.itemId").explain(true)}}

read schema is still "complete":

{{struct<items:array<struct<itemData:string,itemId:bigint>>>}}

 

> Spark SQL reads unnecessary nested fields after using explode
> -------------------------------------------------------------
>
>                 Key: SPARK-29721
>                 URL: https://issues.apache.org/jira/browse/SPARK-29721
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 3.1.0
>            Reporter: Kai Kang
>            Assignee: L. C. Hsieh
>            Priority: Major
>             Fix For: 3.1.0
>
>
> This is a follow up for SPARK-4502. SPARK-4502 correctly addressed column pruning for nested structures. However, when explode() is called on a nested field, all columns for that nested structure is still fetched from data source.
> We are working on a project to create a parquet store for a big pre-joined table between two tables that has one-to-many relationship, and this is a blocking issue for us.
>  
> The following code illustrates the issue. 
> Part 1: loading some nested data
> {noformat}
> val jsonStr = """{
>  "items": [
>    {"itemId": 1, "itemData": "a"},
>    {"itemId": 2, "itemData": "b"}
>  ]
> }"""
> val df = spark.read.json(Seq(jsonStr).toDS)
> df.write.format("parquet").mode("overwrite").saveAsTable("persisted")
> {noformat}
>  
> Part 2: reading it back and explaining the queries
> {noformat}
> val read = spark.table("persisted")
> spark.conf.set("spark.sql.optimizer.nestedSchemaPruning.enabled", true)
> // pruned, only loading itemId
> // ReadSchema: struct<items:array<struct<itemId:bigint>>>
> read.select($"items.itemId").explain(true) 
> // not pruned, loading both itemId 
> // ReadSchema: struct<items:array<struct<itemData:string,itemId:bigint>>>
> read.select(explode($"items.itemId")).explain(true) and itemData
> {noformat}
>  



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