voonhous commented on code in PR #18961: URL: https://github.com/apache/hudi/pull/18961#discussion_r3445676800
########## hudi-spark-datasource/hudi-spark4-common/src/main/java/org/apache/hudi/variant/Spark4VariantShreddingProvider.java: ########## @@ -0,0 +1,672 @@ +/* + * 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.variant; + +import org.apache.hudi.avro.VariantShreddingProvider; +import org.apache.hudi.common.schema.HoodieSchema; + +import org.apache.avro.Conversions; +import org.apache.avro.LogicalType; +import org.apache.avro.LogicalTypes; +import org.apache.avro.Schema; +import org.apache.avro.generic.GenericData; +import org.apache.avro.generic.GenericFixed; +import org.apache.avro.generic.GenericRecord; +import org.apache.spark.types.variant.ShreddingUtils; +import org.apache.spark.types.variant.Variant; +import org.apache.spark.types.variant.VariantSchema; +import org.apache.spark.types.variant.VariantShreddingWriter; +import org.apache.spark.types.variant.VariantShreddingWriter.ShreddedResult; +import org.apache.spark.types.variant.VariantShreddingWriter.ShreddedResultBuilder; + +import java.math.BigDecimal; +import java.nio.ByteBuffer; +import java.util.ArrayList; +import java.util.IdentityHashMap; +import java.util.List; +import java.util.Map; +import java.util.UUID; + +/** + * Implementation of {@link VariantShreddingProvider} using Spark 4's variant parsing library. + * + * <p>This class bridges the Avro record path and Spark's {@link VariantShreddingWriter} + * to allow {@code HoodieRecordType.AVRO} to write shredded variant types. It converts + * the shredded output into Avro {@link GenericRecord}s that can be written via + * {@link org.apache.hudi.avro.HoodieAvroWriteSupport}.</p> + * + * <p>The shredding logic is delegated to {@link VariantShreddingWriter#castShredded}, + * which handles scalar, object, and array shredding including residual value construction + * for non-matching fields. This class implements the {@link ShreddedResult} and + * {@link ShreddedResultBuilder} interfaces to collect the shredded components into + * Avro GenericRecords.</p> + */ +public class Spark4VariantShreddingProvider implements VariantShreddingProvider { + + private static final String VALUE_FIELD = "value"; + private static final String METADATA_FIELD = "metadata"; + private static final String TYPED_VALUE_FIELD = "typed_value"; + + @Override + public GenericRecord shredVariantRecord( + GenericRecord unshreddedVariant, + Schema shreddedSchema, + HoodieSchema.Variant variantSchema) { + + ByteBuffer valueBuf = (ByteBuffer) unshreddedVariant.get(VALUE_FIELD); + ByteBuffer metadataBuf = (ByteBuffer) unshreddedVariant.get(METADATA_FIELD); + + if (valueBuf == null || metadataBuf == null) { + return null; + } + + byte[] valueBytes = toByteArray(valueBuf); + byte[] metadataBytes = toByteArray(metadataBuf); + + Variant variant = new Variant(valueBytes, metadataBytes); + + // Build VariantSchema from the Avro shredded schema, registering + // Avro schemas at each level for GenericRecord construction. + AvroShreddedResultBuilder builder = new AvroShreddedResultBuilder(); + VariantSchema sparkSchema = buildVariantSchema(shreddedSchema, true, builder); + + // Delegate to Spark's VariantShreddingWriter for the actual shredding logic. + AvroShreddedResult result = (AvroShreddedResult) + VariantShreddingWriter.castShredded(variant, sparkSchema, builder); + + return result.toGenericRecord(); + } + + @Override + public GenericRecord rebuildVariantRecord( + GenericRecord shreddedVariant, + Schema shreddedSchema, + Schema unshreddedSchema) { + + if (shreddedVariant == null) { + return null; + } + ByteBuffer metadataBuf = (ByteBuffer) shreddedVariant.get(METADATA_FIELD); + if (metadataBuf == null) { + return null; + } + + // Reuse the same VariantSchema index assignment as the write path (no builder needed on read). + VariantSchema sparkSchema = buildVariantSchema(shreddedSchema, true, null); + + // Delegate to Spark's reconstruction algorithm (inverse of castShredded). + Variant variant = ShreddingUtils.rebuild(new AvroVariantRow(shreddedVariant, sparkSchema), sparkSchema); + + GenericRecord out = new GenericData.Record(unshreddedSchema); + out.put(METADATA_FIELD, ByteBuffer.wrap(variant.getMetadata())); + out.put(VALUE_FIELD, ByteBuffer.wrap(variant.getValue())); + return out; + } + + /** + * Builds a {@link VariantSchema} from an Avro {@link Schema} representing a + * shredded variant structure ({@code value}, {@code metadata}, {@code typed_value}). + * + * <p>This method also registers the Avro schema mapping in the builder so that + * {@link AvroShreddedResultBuilder#createEmpty} can create results with the + * correct Avro schema at each nesting level.</p> + */ + private VariantSchema buildVariantSchema(Schema avroSchema, boolean isTopLevel, + AvroShreddedResultBuilder builder) { + Schema.Field valueField = avroSchema.getField(VALUE_FIELD); + Schema.Field metadataField = avroSchema.getField(METADATA_FIELD); + Schema.Field typedValueField = avroSchema.getField(TYPED_VALUE_FIELD); + + int idx = 0; + int variantIdx = valueField != null ? idx++ : -1; + int topLevelMetadataIdx; + if (metadataField != null && isTopLevel) { + topLevelMetadataIdx = idx++; + } else { + topLevelMetadataIdx = -1; + if (metadataField != null) { + idx++; + } + } + int typedIdx = typedValueField != null ? idx++ : -1; + int numFields = idx; + + VariantSchema.ScalarType scalarSchema = null; + VariantSchema.ObjectField[] objectSchema = null; + VariantSchema arraySchema = null; + + if (typedValueField != null) { + Schema tvSchema = unwrapNullable(typedValueField.schema()); + + switch (tvSchema.getType()) { + case RECORD: + // Object shredding: each field has a nested {value, typed_value} sub-struct + List<VariantSchema.ObjectField> fields = new ArrayList<>(); + for (Schema.Field field : tvSchema.getFields()) { + Schema fieldSchema = unwrapNullable(field.schema()); + VariantSchema subSchema = buildVariantSchema(fieldSchema, false, builder); + fields.add(new VariantSchema.ObjectField(field.name(), subSchema)); + } + objectSchema = fields.toArray(new VariantSchema.ObjectField[0]); + break; + + case ARRAY: + // Array shredding: elements follow the shredding schema + Schema elementSchema = unwrapNullable(tvSchema.getElementType()); + arraySchema = buildVariantSchema(elementSchema, false, builder); + break; + + default: + // Scalar shredding + scalarSchema = avroTypeToScalarType(tvSchema); + break; + } + } + + VariantSchema result = new VariantSchema( + typedIdx, variantIdx, topLevelMetadataIdx, numFields, + scalarSchema, objectSchema, arraySchema); + + // The read (rebuild) path passes a null builder: it needs the VariantSchema indices but no + // Avro-schema registration (registration only feeds write-side result construction). + if (builder != null) { + builder.registerSchema(result, avroSchema); + } + + return result; + } + + /** + * Maps an Avro {@link Schema} type (potentially with logical type annotations) + * to a {@link VariantSchema.ScalarType}. + */ + private VariantSchema.ScalarType avroTypeToScalarType(Schema schema) { + LogicalType logicalType = schema.getLogicalType(); + + // Check logical types first + if (logicalType != null) { + if (logicalType instanceof LogicalTypes.Decimal) { + LogicalTypes.Decimal decimal = (LogicalTypes.Decimal) logicalType; + return new VariantSchema.DecimalType(decimal.getPrecision(), decimal.getScale()); + } + String name = logicalType.getName(); + if ("date".equals(name)) { + return new VariantSchema.DateType(); + } + if ("timestamp-micros".equals(name)) { + return new VariantSchema.TimestampType(); + } + if ("local-timestamp-micros".equals(name)) { + return new VariantSchema.TimestampNTZType(); + } + if ("timestamp-millis".equals(name)) { + return new VariantSchema.TimestampType(); + } + if ("local-timestamp-millis".equals(name)) { + return new VariantSchema.TimestampNTZType(); + } + if ("uuid".equals(name)) { + return new VariantSchema.UuidType(); + } + } + + switch (schema.getType()) { + case BOOLEAN: + return new VariantSchema.BooleanType(); + case INT: + return new VariantSchema.IntegralType(VariantSchema.IntegralSize.INT); + case LONG: + return new VariantSchema.IntegralType(VariantSchema.IntegralSize.LONG); + case FLOAT: + return new VariantSchema.FloatType(); + case DOUBLE: + return new VariantSchema.DoubleType(); + case STRING: + return new VariantSchema.StringType(); + case BYTES: + return new VariantSchema.BinaryType(); + case FIXED: + return new VariantSchema.BinaryType(); + default: + return null; + } + } + + private static Schema unwrapNullable(Schema schema) { + if (schema.getType() == Schema.Type.UNION) { Review Comment: Done -- collapsed into a fall-through: ```java case BYTES: case FIXED: return new VariantSchema.BinaryType(); ``` -- This is an automated message from the Apache Git Service. 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