[jira] [Resolved] (SPARK-34638) Spark SQL reads unnecessary nested fields (another type of pruning case)

["L. C. Hsieh (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-34638?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

L. C. Hsieh resolved SPARK-34638.
---------------------------------
      Assignee: L. C. Hsieh
    Resolution: Fixed

> Spark SQL reads unnecessary nested fields (another type of pruning case)
> ------------------------------------------------------------------------
>
>                 Key: SPARK-34638
>                 URL: https://issues.apache.org/jira/browse/SPARK-34638
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 3.1.1
>            Reporter: Jiri Humpolicek
>            Assignee: L. C. Hsieh
>            Priority: Major
>
> Based on this [SPARK-29721|https://issues.apache.org/jira/browse/SPARK-29721] I found another nested fields pruning case.
> Example:
> 1) Loading data
> {code:scala}
> 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")
> {code}
> 2) read query with explain
> {code:scala}
> val read = spark.table("persisted")
> spark.conf.set("spark.sql.optimizer.nestedSchemaPruning.enabled", true)
> read.select(explode($"items").as('item)).select($"item.itemId").explain(true)
> // ReadSchema: struct<items:array<struct<itemData:string,itemId:bigint>>>
> {code}



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