Jiri Humpolicek created SPARK-37450:
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Summary: 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
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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