rahil-c commented on code in PR #18036:
URL: https://github.com/apache/hudi/pull/18036#discussion_r2915054384
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/io/storage/row/HoodieRowParquetWriteSupport.java:
##########
@@ -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);
+
+ shreddedFields[i] = new StructField(field.name(),
markedShreddedStruct, field.nullable(), field.metadata());
+ hasShredding = true;
+ continue;
+ }
+ }
+ }
+
+ // Recursively process nested fields (for VariantType without shredding,
or for nested structures like StructType/ArrayType/MapType)
+ DataType processedDataType = processNestedDataType(field.dataType(),
fieldHoodieSchema);
+ if (processedDataType != field.dataType()) {
+ shreddedFields[i] = new StructField(field.name(), processedDataType,
field.nullable(), field.metadata());
+ hasShredding = true;
+ } else {
+ // No shredding in this field or its nested fields
+ shreddedFields[i] = field;
+ }
+ }
+
+ return hasShredding ? new StructType(shreddedFields) : structType;
+ }
+
+ /**
+ * Recursively processes nested data types (structs, arrays, maps) to handle
Variant shredding at any depth.
+ *
+ * @param dataType The data type to process
+ * @param hoodieSchema The corresponding HoodieSchema
+ * @return The processed data type with shredded Variants, or the original
if no shredding needed
+ */
+ private DataType processNestedDataType(DataType dataType, HoodieSchema
hoodieSchema) {
+ // Check if this is a Variant type that should be shredded
+ if (hoodieSchema != null && hoodieSchema.getType() ==
HoodieSchemaType.VARIANT) {
+ HoodieSchema.Variant variantSchema = (HoodieSchema.Variant) hoodieSchema;
+ // 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
+ return SparkAdapterSupport$.MODULE$.sparkAdapter()
+ .generateVariantWriteShreddingSchema(typedValueDataType, true,
false);
+ }
+ return dataType;
+ }
+
+ if (dataType instanceof StructType) {
+ StructType structType = (StructType) dataType;
+ StructType processedStruct = generateShreddedSchema(structType,
hoodieSchema);
+ return processedStruct;
+ } else if (dataType instanceof ArrayType) {
+ ArrayType arrayType = (ArrayType) dataType;
+ HoodieSchema elementSchema = hoodieSchema != null &&
hoodieSchema.getType() == HoodieSchemaType.ARRAY
+ ? hoodieSchema.getElementType()
+ : null;
+ DataType processedElementType =
processNestedDataType(arrayType.elementType(), elementSchema);
+ if (processedElementType != arrayType.elementType()) {
+ return new ArrayType(processedElementType, arrayType.containsNull());
+ }
+ } else if (dataType instanceof MapType) {
+ MapType mapType = (MapType) dataType;
+ HoodieSchema valueSchema = hoodieSchema != null &&
hoodieSchema.getType() == HoodieSchemaType.MAP
+ ? hoodieSchema.getValueType()
+ : null;
+ DataType processedValueType = processNestedDataType(mapType.valueType(),
valueSchema);
+ if (processedValueType != mapType.valueType()) {
+ return new MapType(mapType.keyType(), processedValueType,
mapType.valueContainsNull());
+ }
+ }
+ return dataType;
+ }
+
+ /**
+ * Creates field writers for each field in the schema.
+ *
+ * @param schema The schema to create writers for (may contain shredded
Variant struct types)
+ * @param hoodieSchema The HoodieSchema for type information
+ * @return Array of ValueWriters for each field
+ */
private ValueWriter[] getFieldWriters(StructType schema, HoodieSchema
hoodieSchema) {
- return Arrays.stream(schema.fields()).map(field -> {
+ StructField[] fields = schema.fields();
+ ValueWriter[] writers = new ValueWriter[fields.length];
+
+ for (int i = 0; i < fields.length; i++) {
+ StructField field = fields[i];
+
HoodieSchema fieldSchema = Option.ofNullable(hoodieSchema)
.flatMap(s -> s.getField(field.name()))
Review Comment:
Do we need to call `getNonNullType()` on the `hoodieSchema`? I saw
`generateShreddedSchema` call the function so just wanted to ask
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: [email protected]
For queries about this service, please contact Infrastructure at:
[email protected]
