rahil-c commented on code in PR #18036:
URL: https://github.com/apache/hudi/pull/18036#discussion_r2915064805
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hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/io/storage/row/HoodieRowParquetWriteSupport.java:
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@@ -139,21 +148,153 @@ public HoodieRowParquetWriteSupport(Configuration conf,
StructType structType, O
HoodieSchema parsedSchema = HoodieSchema.parse(schemaString);
return HoodieSchemaUtils.addMetadataFields(parsedSchema,
config.getBooleanOrDefault(ALLOW_OPERATION_METADATA_FIELD));
});
+ // Generate shredded schema if there are shredded Variant columns.
+ // Falls back to the provided schema if no shredded Variant columns are
present.
+ this.shreddedSchema = generateShreddedSchema(structType, schema);
ParquetWriteSupport.setSchema(structType, hadoopConf);
- this.rootFieldWriters = getFieldWriters(structType, schema);
+ // Use shreddedSchema for creating writers when shredded Variants are
present
+ this.rootFieldWriters = getFieldWriters(shreddedSchema, schema);
this.hadoopConf = hadoopConf;
this.bloomFilterWriteSupportOpt =
bloomFilterOpt.map(HoodieBloomFilterRowWriteSupport::new);
}
+ /**
+ * Generates a shredded schema from the given structType and hoodieSchema.
+ * <p>
+ * For Variant fields that are configured for shredding (based on
HoodieSchema.Variant.isShredded()),
+ * the VariantType is replaced with a shredded struct schema. This method
recursively processes
+ * nested struct fields to handle Variant fields at any depth.
+ *
+ * @param structType The original Spark StructType
+ * @param hoodieSchema The HoodieSchema containing shredding information
+ * @return A StructType with shredded Variant fields replaced by their
shredded schemas
+ */
+ private StructType generateShreddedSchema(StructType structType,
HoodieSchema hoodieSchema) {
+ StructField[] fields = structType.fields();
+ StructField[] shreddedFields = new StructField[fields.length];
+ boolean hasShredding = false;
+
+ for (int i = 0; i < fields.length; i++) {
+ StructField field = fields[i];
+ DataType dataType = field.dataType();
+
+ // Get the HoodieSchema for this field (if available)
+ // Use getNonNullType() to unwrap nullable unions (e.g., ["null",
"string"] -> "string")
+ HoodieSchema fieldHoodieSchema = Option.ofNullable(hoodieSchema)
+ .map(HoodieSchema::getNonNullType)
+ .flatMap(s -> s.hasFields() ? s.getField(field.name()) :
Option.empty())
+ .map(HoodieSchemaField::schema)
+ .orElse(null);
+
+ // Check if this is a Variant field that should be shredded
+ if (SparkAdapterSupport$.MODULE$.sparkAdapter().isVariantType(dataType))
{
+ if (fieldHoodieSchema != null && fieldHoodieSchema.getType() ==
HoodieSchemaType.VARIANT) {
+ HoodieSchema.Variant variantSchema = (HoodieSchema.Variant)
fieldHoodieSchema;
+ // If typed_value field exists, the variant is shredded
+ if (variantSchema.getTypedValueField().isPresent()) {
+ // Use plain types for SparkShreddingUtils (unwraps nested {value,
typed_value} structs if present)
+ HoodieSchema typedValueSchema =
variantSchema.getPlainTypedValueSchema().get();
+ DataType typedValueDataType =
HoodieSchemaConversionUtils.convertHoodieSchemaToDataType(typedValueSchema);
+
+ // Generate the shredding schema with write metadata using
SparkAdapter
+ StructType markedShreddedStruct =
SparkAdapterSupport$.MODULE$.sparkAdapter()
+ .generateVariantWriteShreddingSchema(typedValueDataType, true,
false);
Review Comment:
Is it always safe to pass `isTopLevel` as true and `isObjectField` as false?
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