voonhous commented on code in PR #19133:
URL: https://github.com/apache/hudi/pull/19133#discussion_r3570840708


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hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/hudi/functional/TestLegacyParquetReadPath.scala:
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@@ -0,0 +1,292 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.hudi.functional
+
+import org.apache.hudi.{BaseFileOnlyRelation, DataSourceReadOptions, 
DataSourceWriteOptions, IncrementalRelationV1, IncrementalRelationV2}
+import org.apache.hudi.common.config.HoodieReaderConfig
+import org.apache.hudi.common.table.HoodieTableConfig
+import org.apache.hudi.common.table.log.InstantRange.RangeType
+import org.apache.hudi.config.HoodieWriteConfig
+import org.apache.hudi.testutils.HoodieSparkClientTestBase
+
+import org.apache.spark.sql.{DataFrame, Row, SaveMode, SparkSession}
+import org.apache.spark.sql.functions.col
+import org.junit.jupiter.api.{AfterEach, BeforeEach, Test}
+import org.junit.jupiter.api.Assertions.{assertEquals, assertFalse, assertTrue}
+
+/** Row shape written by these tests. A nested struct and an array are 
included so the legacy
+ * parquet read path is exercised on complex types -- the historically fragile 
vectorized
+ * nested-column branch (e.g. HUDI-7190), not just flat scalar columns. */
+private case class LegacyNested(a: Int, b: String)
+
+private case class LegacyTestRow(id: String,
+                                 ts: Long,
+                                 value: Long,
+                                 partition: String,
+                                 nested: LegacyNested,
+                                 tags: Seq[Int])
+
+/**
+ * Functional tests for the legacy (pre-file-group-reader) Spark read path:
+ * [[BaseFileOnlyRelation]], [[IncrementalRelationV1]], 
[[IncrementalRelationV2]] and the
+ * per-Spark-version legacy Hudi parquet file format created via
+ * `sparkAdapter.createLegacyHoodieParquetFileFormat`.
+ *
+ * In the batch datasource, `DefaultSource` routes normal reads to the 
file-group-reader-based
+ * relations regardless of `hoodie.file.group.reader.enabled`; the legacy 
relations still run in
+ * production for metadata-table reads and for streaming reads with the flag 
disabled. To exercise
+ * them functionally here, the legacy relations are constructed directly (with 
the flag set to
+ * false in their options, matching how the streaming sources invoke them) and 
their results are
+ * compared row-by-row against the file-group-reader-enabled reads of the same 
table.
+ */
+class TestLegacyParquetReadPath extends HoodieSparkClientTestBase {

Review Comment:
   Agreed, covered here: added `testCowSnapshotReadWithSchemaOnRead`. Turns out 
no `ALTER` is needed -- writing with `hoodie.schema.on.read.enable` + 
`hoodie.datasource.write.reconcile.schema` seeds the `InternalSchema` on commit 
1 and evolves it with the int->long promotion on commit 2.
   
   The test pins all three branches:
   - `hasSchemaOnRead` is asserted true, so the `buildScan` case runs in the 
one shape `resolveBaseFileOnlyRelation` actually ships;
   - `toHadoopFsRelation.partitionSchema` is asserted empty under 
schema-on-read (and non-empty without), pinning the 
`shouldExtractPartitionValuesFromPartitionPath` flip and the 
`shouldAppendPartitionValues = false` shim construction;
   - the explicit internal-schema read 
(`InternalSchemaCache.getInternalSchemaByVersionId` + `InternalSchemaMerger`) 
runs through `HoodieVectorizedParquetRecordReader`, with the widened values 
checked against the file-group reader.



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