rahil-c commented on code in PR #18328:
URL: https://github.com/apache/hudi/pull/18328#discussion_r2967699324


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hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/io/storage/VectorConversionUtils.java:
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@@ -0,0 +1,205 @@
+/*
+ * 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.io.storage;
+
+import org.apache.hudi.common.schema.HoodieSchema;
+import org.apache.hudi.common.schema.HoodieSchemaField;
+import org.apache.hudi.common.schema.HoodieSchemaType;
+
+import org.apache.spark.sql.catalyst.util.GenericArrayData;
+import org.apache.spark.sql.types.BinaryType$;
+import org.apache.spark.sql.types.Metadata;
+import org.apache.spark.sql.types.StructField;
+import org.apache.spark.sql.types.StructType;
+
+import org.apache.spark.sql.catalyst.InternalRow;
+import org.apache.spark.sql.catalyst.expressions.GenericInternalRow;
+
+import java.nio.ByteBuffer;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+
+import static org.apache.hudi.common.util.ValidationUtils.checkArgument;
+
+/**
+ * Shared utility methods for vector column handling during Parquet read/write.
+ *
+ * Vectors are stored as Parquet FIXED_LEN_BYTE_ARRAY columns. On read, Spark 
maps these
+ * to BinaryType. This class provides the canonical conversion between the 
binary
+ * representation and Spark's typed ArrayData (float[], double[], byte[]).
+ *
+ * All byte buffers use little-endian order ({@link 
HoodieSchema.VectorLogicalType#VECTOR_BYTE_ORDER})
+ * for compatibility with common vector search libraries (FAISS, ScaNN, etc.) 
and to match
+ * native x86/ARM byte order for zero-copy reads.
+ */
+public final class VectorConversionUtils {
+
+  private VectorConversionUtils() {
+  }
+
+  /**
+   * Detects VECTOR columns in a HoodieSchema record and returns a map of 
field ordinal
+   * to the corresponding {@link HoodieSchema.Vector} schema.
+   *
+   * @param schema a HoodieSchema of type RECORD (or null)
+   * @return map from field index to Vector schema; empty map if schema is 
null or has no vectors
+   */
+  public static Map<Integer, HoodieSchema.Vector> 
detectVectorColumns(HoodieSchema schema) {

Review Comment:
   I believe i have tests for this in the pr but will check 



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