kamronis commented on code in PR #17682:
URL: https://github.com/apache/hudi/pull/17682#discussion_r2646630539
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hudi-common/src/main/java/org/apache/hudi/avro/HoodieAvroUtils.java:
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@@ -1369,6 +1369,45 @@ public static BigDecimal convertBytesToBigDecimal(byte[]
value, int precision, i
scale, new MathContext(precision, RoundingMode.HALF_UP));
}
+ /**
+ * Projects a record to a new schema by performing a shallow copy of fields.
+ * Best used for adding or removing top-level metadata fields.
+ * <p>
+ * This is a high-performance alternative to deep rewriting. It only
iterates through
+ * the top-level fields of the target schema and pulls values from the
source record
+ * by field name.
+ * <p>
+ * <p>
+ * This is significantly faster than {@link #rewriteRecordWithNewSchema} for:
+ * 1. Wide records (many top-level fields): Reduces CPU overhead/recursion.
+ * 2. Deeply nested records: Uses reference-copying for nested structures
instead of rebuilding them.
+ * <p>
+ * <b>Warning:</b> This method does not recursively rewrite/transform nested
records, arrays,
+ * or maps. It assumes that the underlying values for each field are already
+ * compatible with the target schema.
+ *
+ * @param record The source GenericRecord to project.
+ * @param targetSchema The schema to project the record into.
+ * @return A new GenericRecord matching targetSchema, or the original record
if
+ * the schemas are identical in field count.
+ */
+
+ public static GenericRecord projectRecordToNewSchemaShallow(GenericRecord
record, Schema targetSchema) {
+ if (record.getSchema().getFields().size() ==
targetSchema.getFields().size()) {
+ return record;
+ } else {
+ GenericData.Record rec = new GenericData.Record(targetSchema);
+ for (Schema.Field field : targetSchema.getFields()) {
+ if (record.hasField(field.name())) {
Review Comment:
Fixed
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