colin fang created SPARK-33184:
----------------------------------
Summary: spark doesn't read data source column if it is needed as
an index to an array in a nested struct
Key: SPARK-33184
URL: https://issues.apache.org/jira/browse/SPARK-33184
Project: Spark
Issue Type: Improvement
Components: Spark Core
Affects Versions: 3.0.0
Reporter: colin fang
```
df = spark.createDataFrame([[1, [[1, 2]]]],
schema='x:int,y:struct<a:array<int>>')
df.write.mode('overwrite').parquet('test')
```
```
# This causes an error "Caused by: java.lang.RuntimeException: Couldn't find
x#720 in [y#721]"
spark.read.parquet('test').select(F.expr('y.a[x]')).show()
# Explain works fine, note it doesn't read x in ReadSchema
spark.read.parquet('test').select(F.expr('y.a[x]')).explain()
== Physical Plan ==
*(1) !Project [y#713.a[x#712] AS y.a AS `a`[x]#717]
+- FileScan parquet [y#713] Batched: false, DataFilters: [], Format: Parquet,
Location: InMemoryFileIndex, PartitionFilters: [], PushedFilters: [],
ReadSchema: struct<y:struct<a:array<int>>>
```
The code works well if I
- manually select the column it misses
`spark.read.parquet('test').select(F.expr('y.a[x]'), F.col('x')).show()`
- or use `F.element_at` function
`spark.read.parquet('test').select(F.element_at('y.a', F.col('x') + 1)).show()`
```
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