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https://issues.apache.org/jira/browse/SPARK-37450?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17448320#comment-17448320
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Hyukjin Kwon commented on SPARK-37450:
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cc [~viirya] FYI
> Spark SQL reads unnecessary nested fields (another type of pruning case)
> ------------------------------------------------------------------------
>
> Key: SPARK-37450
> URL: https://issues.apache.org/jira/browse/SPARK-37450
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 3.2.0
> Reporter: Jiri Humpolicek
> Priority: Major
>
> Based on this [SPARK-34638|https://issues.apache.org/jira/browse/SPARK-34638]
> Maybe I found another nested fields pruning case. In this case I found full
> read with `count` function
> 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(count(lit(true))).explain(true)
> // ReadSchema: struct<items:array<struct<itemData:string,itemId:bigint>>>
> {code}
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