[SPARK-31116][SQL] Fix nested schema case-sensitivity in ParquetRowConverter

sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetReadSupport.scala

@@ -122,12 +122,15 @@ class ParquetReadSupport(val convertTz: Option[ZoneId],
       keyValueMetaData: JMap[String, String],
       fileSchema: MessageType,
       readContext: ReadContext): RecordMaterializer[InternalRow] = {
+    val caseSensitive = conf.getBoolean(SQLConf.CASE_SENSITIVE.key,
+      SQLConf.CASE_SENSITIVE.defaultValue.get)
     val parquetRequestedSchema = readContext.getRequestedSchema
     new ParquetRecordMaterializer(
       parquetRequestedSchema,
       ParquetReadSupport.expandUDT(catalystRequestedSchema),
       new ParquetToSparkSchemaConverter(conf),
-      convertTz)
+      convertTz,
+      caseSensitive)
   }
 }
 

sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRecordMaterializer.scala

@@ -36,11 +36,18 @@ private[parquet] class ParquetRecordMaterializer(
     parquetSchema: MessageType,
     catalystSchema: StructType,
     schemaConverter: ParquetToSparkSchemaConverter,
-    convertTz: Option[ZoneId])
+    convertTz: Option[ZoneId],
+    caseSensitive: Boolean)
   extends RecordMaterializer[InternalRow] {
 
   private val rootConverter =
-    new ParquetRowConverter(schemaConverter, parquetSchema, catalystSchema, convertTz, NoopUpdater)
+    new ParquetRowConverter(
+      schemaConverter,
+      parquetSchema,
+      catalystSchema,
+      convertTz,
+      caseSensitive,
+      NoopUpdater)
 
   override def getCurrentRecord: InternalRow = rootConverter.currentRecord
 

sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRowConverter.scala

@@ -33,7 +33,7 @@ import org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.{BINARY, DOUBLE
 import org.apache.spark.internal.Logging
 import org.apache.spark.sql.catalyst.InternalRow
 import org.apache.spark.sql.catalyst.expressions._
-import org.apache.spark.sql.catalyst.util.{ArrayBasedMapData, DateTimeUtils, GenericArrayData}
+import org.apache.spark.sql.catalyst.util.{ArrayBasedMapData, CaseInsensitiveMap, DateTimeUtils, GenericArrayData}
 import org.apache.spark.sql.catalyst.util.DateTimeUtils.SQLTimestamp
 import org.apache.spark.sql.types._
 import org.apache.spark.unsafe.types.UTF8String
@@ -126,6 +126,7 @@ private[parquet] class ParquetRowConverter(
     parquetType: GroupType,
     catalystType: StructType,
     convertTz: Option[ZoneId],
+    caseSensitive: Boolean,
     updater: ParentContainerUpdater)
   extends ParquetGroupConverter(updater) with Logging {
 
@@ -178,8 +179,17 @@ private[parquet] class ParquetRowConverter(
 
   // Converters for each field.
   private[this] val fieldConverters: Array[Converter with HasParentContainerUpdater] = {
+    val catalystFieldNameToIndex = if (caseSensitive) {
+      catalystType.fieldNames.zipWithIndex.toMap
+    } else {
+      CaseInsensitiveMap(catalystType.fieldNames.zipWithIndex.toMap)
+    }
     parquetType.getFields.asScala.map { parquetField =>
-      val fieldIndex = catalystType.fieldIndex(parquetField.getName)
+      val fieldIndex = catalystFieldNameToIndex.getOrElse(parquetField.getName,
+        throw new IllegalArgumentException(
+          s"${parquetField.getName} does not exist. " +
+            s"Available: ${catalystType.fieldNames.mkString(", ")}")
+      )
       val catalystField = catalystType(fieldIndex)
       // Converted field value should be set to the `fieldIndex`-th cell of `currentRow`
       newConverter(parquetField, catalystField.dataType, new RowUpdater(currentRow, fieldIndex))
@@ -348,7 +358,12 @@ private[parquet] class ParquetRowConverter(
           }
         }
         new ParquetRowConverter(
-          schemaConverter, parquetType.asGroupType(), t, convertTz, wrappedUpdater)
+          schemaConverter,
+          parquetType.asGroupType(),
+          t,
+          convertTz,
+          caseSensitive,
+          wrappedUpdater)
 
       case t =>
         throw new RuntimeException(

sql/core/src/test/scala/org/apache/spark/sql/FileBasedDataSourceSuite.scala

@@ -842,6 +842,142 @@ class FileBasedDataSourceSuite extends QueryTest
       }
     }
   }
+
+  test("SPARK-31116: Select simple parquet with case insensitive mode") {
+    Seq("true", "false").foreach { nestedSchemaPruningEnabled =>
+      withSQLConf(
+        SQLConf.CASE_SENSITIVE.key -> "false",
+        SQLConf.NESTED_SCHEMA_PRUNING_ENABLED.key -> nestedSchemaPruningEnabled) {
+        withTempPath { dir =>
+          val path = dir.getCanonicalPath
+
+          // Prepare values for testing specific parquet record reader
+          Seq("A").toDF("camelCase").write.parquet(path)
+
+          val exactSchema = new StructType().add("camelCase", StringType)
+          checkAnswer(spark.read.schema(exactSchema).parquet(path), Row("A"))
+
+          // In case insensitive manner, parquet's column cases are ignored
+          val caseInsensitiveSchema = new StructType().add("camelcase", StringType)
+          checkAnswer(spark.read.schema(caseInsensitiveSchema).parquet(path), Row("A"))
+        }
+      }
+    }
+  }
+
+  test("SPARK-31116: Select nested parquet with case insensitive mode") {
+    Seq("true", "false").foreach { nestedSchemaPruningEnabled =>
+      withSQLConf(
+        SQLConf.CASE_SENSITIVE.key -> "false",
+        SQLConf.NESTED_SCHEMA_PRUNING_ENABLED.key -> nestedSchemaPruningEnabled) {
+        withTempPath { dir =>
+          val path = dir.getCanonicalPath
+
+          // Prepare values for testing nested parquet data
+          spark
+            .range(1L)
+            .selectExpr("NAMED_STRUCT('lowercase', id, 'camelCase', id + 1) AS StructColumn")
+            .write.parquet(path)
+
+          val exactSchema = "StructColumn struct<lowercase: LONG, camelCase: LONG>"
+
+          checkAnswer(spark.read.schema(exactSchema).parquet(path), Row(Row(0, 1)))
+
+          // In case insensitive manner, parquet's column cases are ignored
+          val innerColumnCaseInsensitiveSchema =
+            "StructColumn struct<Lowercase: LONG, camelcase: LONG>"
+          checkAnswer(
+            spark.read.schema(innerColumnCaseInsensitiveSchema).parquet(path),
+            Row(Row(0, 1)))
+
+          val rootColumnCaseInsensitiveSchema =
+            "structColumn struct<lowercase: LONG, camelCase: LONG>"
+          checkAnswer(
+            spark.read.schema(rootColumnCaseInsensitiveSchema).parquet(path),
+            Row(Row(0, 1)))
+        }
+      }
+    }
+  }
+
+  test("SPARK-31116: Select simple parquet with case sensitive mode") {
+    Seq("true", "false").foreach { nestedSchemaPruningEnabled =>
+      withSQLConf(
+        SQLConf.CASE_SENSITIVE.key -> "true",
+        SQLConf.NESTED_SCHEMA_PRUNING_ENABLED.key -> nestedSchemaPruningEnabled) {
+        withTempPath { dir =>
+          val path = dir.getCanonicalPath
+
+          // Prepare values for testing specific parquet record reader
+          Seq("A").toDF("camelCase").write.parquet(path)
+
+          val exactSchema = new StructType().add("camelCase", StringType)
+          checkAnswer(spark.read.schema(exactSchema).parquet(path), Row("A"))
+
+          // In case sensitive manner, different letter case does not read column
+          val caseInsensitiveSchema = new StructType().add("camelcase", StringType)
+          checkAnswer(spark.read.schema(caseInsensitiveSchema).parquet(path), Row(null))
+
+          // It also properly work in combined schema
+          val combinedSchema = new StructType()
+            .add("camelCase", StringType)
+            .add("camelcase", StringType)
+          checkAnswer(spark.read.schema(combinedSchema).parquet(path), Row("A", null))
+        }
+      }
+    }
+  }
+
+  test("SPARK-31116: Select nested parquet with case sensitive mode") {
+    Seq("true", "false").foreach { nestedSchemaPruningEnabled =>
+      withSQLConf(
+        SQLConf.CASE_SENSITIVE.key -> "true",
+        SQLConf.NESTED_SCHEMA_PRUNING_ENABLED.key -> nestedSchemaPruningEnabled) {
+        withTempPath { dir =>
+          val path = dir.getCanonicalPath
+
+          // Prepare values for testing nested parquet data
+          spark
+            .range(1)
+            .selectExpr("NAMED_STRUCT('lowercase', id, 'camelCase', id + 1) AS StructColumn")
+            .write.parquet(path)
+
+          val exactSchema = "StructColumn struct<lowercase: LONG, camelCase: LONG>"
+          checkAnswer(spark.read.schema(exactSchema).parquet(path), Row(Row(0, 1)))
+
+          val innerColumnCaseInsensitiveSchema =
+            "StructColumn struct<Lowercase: LONG, camelcase: LONG>"
+          checkAnswer(
+            spark.read.schema(innerColumnCaseInsensitiveSchema).parquet(path),
+            Row(null))
+
+          val innerPartialColumnCaseInsensitiveSchema =
+            "StructColumn struct<lowercase: LONG, camelcase: LONG>"
+          checkAnswer(
+            spark.read.schema(innerPartialColumnCaseInsensitiveSchema).parquet(path),
+            Row(Row(0, null)))
+
+          val rootColumnCaseInsensitiveSchema =
+            "structColumn struct<lowercase: LONG, camelCase: LONG>"
+          checkAnswer(
+            spark.read.schema(rootColumnCaseInsensitiveSchema).parquet(path),
+            Row(null))
+
+          val combinedSchema =
+            """
+              |StructColumn
+              |struct<lowercase: LONG, camelCase: LONG, LowerCase: LONG, camelcase: LONG>,
+              |structColumn
+              |struct<lowercase: LONG, camelCase: LONG, LowerCase: LONG, camelcase: LONG>
+              |""".stripMargin
+
+          checkAnswer(
+            spark.read.schema(combinedSchema).parquet(path),
+            Row(Row(0, 1, null, null), null))
+        }
+      }
+    }
+  }
 }
 
 object TestingUDT {