p-eye commented on code in PR #28498: URL: https://github.com/apache/flink/pull/28498#discussion_r3448251566
########## flink-formats/flink-avro-confluent-registry/src/main/java/org/apache/flink/formats/avro/registry/confluent/debezium/DebeziumAvroDecodingFormat.java: ########## @@ -0,0 +1,266 @@ +/* + * 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.flink.formats.avro.registry.confluent.debezium; + +import org.apache.flink.api.common.serialization.DeserializationSchema; +import org.apache.flink.api.common.typeinfo.TypeInformation; +import org.apache.flink.formats.avro.registry.confluent.debezium.DebeziumAvroDeserializationSchema.MetadataConverter; +import org.apache.flink.table.api.DataTypes; +import org.apache.flink.table.connector.ChangelogMode; +import org.apache.flink.table.connector.Projection; +import org.apache.flink.table.connector.format.DecodingFormat; +import org.apache.flink.table.connector.format.ProjectableDecodingFormat; +import org.apache.flink.table.connector.source.DynamicTableSource; +import org.apache.flink.table.data.GenericMapData; +import org.apache.flink.table.data.GenericRowData; +import org.apache.flink.table.data.RowData; +import org.apache.flink.table.data.StringData; +import org.apache.flink.table.types.DataType; +import org.apache.flink.table.types.utils.DataTypeUtils; +import org.apache.flink.types.RowKind; + +import java.util.Collections; +import java.util.HashMap; +import java.util.LinkedHashMap; +import java.util.List; +import java.util.Map; +import java.util.stream.Collectors; +import java.util.stream.IntStream; +import java.util.stream.Stream; + +/** {@link DecodingFormat} for Debezium using Avro encoding. */ +public class DebeziumAvroDecodingFormat + implements ProjectableDecodingFormat<DeserializationSchema<RowData>> { + + // ---------------------------------------------------------------------------------------- + // Mutable attributes + // ---------------------------------------------------------------------------------------- + + private List<String> metadataKeys; + + // ---------------------------------------------------------------------------------------- + // Debezium-specific attributes + // ---------------------------------------------------------------------------------------- + + private final String schemaRegistryURL; + private final String schema; + private final Map<String, ?> optionalPropertiesMap; + + public DebeziumAvroDecodingFormat( + String schemaRegistryURL, String schema, Map<String, ?> optionalPropertiesMap) { + this.schemaRegistryURL = schemaRegistryURL; + this.schema = schema; + this.optionalPropertiesMap = optionalPropertiesMap; + this.metadataKeys = Collections.emptyList(); + } + + @Override + public DeserializationSchema<RowData> createRuntimeDecoder( + DynamicTableSource.Context context, DataType physicalDataType, int[][] projections) { + physicalDataType = Projection.of(projections).project(physicalDataType); + + final List<ReadableMetadata> readableMetadata = + metadataKeys.stream() + .map( + k -> + Stream.of(ReadableMetadata.values()) + .filter(rm -> rm.key.equals(k)) + .findFirst() + .orElseThrow(IllegalStateException::new)) + .collect(Collectors.toList()); + final List<DataTypes.Field> metadataFields = + readableMetadata.stream() + .map(m -> DataTypes.FIELD(m.key, m.dataType)) + .collect(Collectors.toList()); + + final DataType producedDataType = + DataTypeUtils.appendRowFields(physicalDataType, metadataFields); + final TypeInformation<RowData> producedTypeInfo = + context.createTypeInformation(producedDataType); + + return new DebeziumAvroDeserializationSchema( + physicalDataType, + readableMetadata, + producedTypeInfo, + schemaRegistryURL, + schema, + optionalPropertiesMap); + } + + @Override + public Map<String, DataType> listReadableMetadata() { + final Map<String, DataType> metadataMap = new LinkedHashMap<>(); + Stream.of(ReadableMetadata.values()) + .forEachOrdered(m -> metadataMap.put(m.key, m.dataType)); + return metadataMap; + } + + @Override + public void applyReadableMetadata(List<String> metadataKeys) { + this.metadataKeys = metadataKeys; + } + + @Override + public ChangelogMode getChangelogMode() { + return ChangelogMode.newBuilder() + .addContainedKind(RowKind.INSERT) + .addContainedKind(RowKind.UPDATE_BEFORE) + .addContainedKind(RowKind.UPDATE_AFTER) + .addContainedKind(RowKind.DELETE) + .build(); + } + + // ---------------------------------------------------------------------------------------- + // Metadata handling + // ---------------------------------------------------------------------------------------- + + /** List of metadata that can be read with this format. */ + enum ReadableMetadata { + INGESTION_TIMESTAMP( + "ingestion-timestamp", + DataTypes.TIMESTAMP_WITH_LOCAL_TIME_ZONE(3).nullable(), + DataTypes.FIELD("ts_ms", DataTypes.TIMESTAMP_WITH_LOCAL_TIME_ZONE(3)), + new MetadataConverter() { + private static final long serialVersionUID = 1L; + + @Override + public Object convert(GenericRowData row, int unused) { + return row; + } + }), + + SOURCE_TIMESTAMP( + "source.timestamp", + DataTypes.TIMESTAMP_WITH_LOCAL_TIME_ZONE(3).nullable(), + SOURCE_FIELD, + new MetadataConverter() { + private static final long serialVersionUID = 1L; + + @Override + public Object convert(GenericRowData row, int unused) { + int pos = SOURCE_PROPERTY_POSITION.get("ts_ms"); + return row.getField(pos); + } + }), + + SOURCE_DATABASE( + "source.database", + DataTypes.STRING().nullable(), + SOURCE_FIELD, + new MetadataConverter() { + private static final long serialVersionUID = 1L; + + @Override + public Object convert(GenericRowData row, int unused) { + int pos = SOURCE_PROPERTY_POSITION.get("db"); + return row.getField(pos); + } + }), + + SOURCE_SCHEMA( + "source.schema", + DataTypes.STRING().nullable(), + SOURCE_FIELD, + new MetadataConverter() { + private static final long serialVersionUID = 1L; + + @Override + public Object convert(GenericRowData row, int unused) { + int pos = SOURCE_PROPERTY_POSITION.get("schema"); + return row.getField(pos); + } + }), + + SOURCE_TABLE( + "source.table", + DataTypes.STRING().nullable(), + SOURCE_FIELD, + new MetadataConverter() { + private static final long serialVersionUID = 1L; + + @Override + public Object convert(GenericRowData row, int unused) { + int pos = SOURCE_PROPERTY_POSITION.get("table"); + return row.getField(pos); + } + }), + + SOURCE_PROPERTIES( + "source.properties", + // key and value of the map are nullable to make handling easier in queries + DataTypes.MAP(DataTypes.STRING().nullable(), DataTypes.STRING().nullable()) + .nullable(), + SOURCE_FIELD, + new MetadataConverter() { + private static final long serialVersionUID = 1L; + + @Override + public Object convert(GenericRowData row, int unused) { + Map<StringData, StringData> result = new HashMap<>(); + for (int i = 0; i < SOURCE_PROPERTY_FIELDS.length; i++) { + Object value = row.getField(i); + result.put( + StringData.fromString(SOURCE_PROPERTY_FIELDS[i].getName()), + value == null ? null : StringData.fromString(value.toString())); + } + return new GenericMapData(result); + } + }); + + final String key; + final DataType dataType; + final DataTypes.Field requiredAvroField; + final MetadataConverter converter; + + ReadableMetadata( + String key, + DataType dataType, + DataTypes.Field requiredAvroField, + MetadataConverter converter) { + this.key = key; + this.dataType = dataType; + this.requiredAvroField = requiredAvroField; + this.converter = converter; + } + } + + private static final DataTypes.Field[] SOURCE_PROPERTY_FIELDS = { Review Comment: I looked into using MAP like `debezium-json`, but hit a constraint: Debezium's `source` is an Avro record type (not map). Flink's `AvroToRowDataConverters` maps Avro types to Flink types — map → MAP, record → ROW. There's no record → MAP converter. If we define `source` as MAP in Flink schema, `AvroSchemaConverter` will generate an Avro map schema, but the registered schema has `soucre` as a record type. Based on Avro's schema resolution rules (record ↔ MAP not compatible), this should fail during deserialization. To make it connector-agnostic, two options: 1. Add record → MAP converter to `AvroToRowDataConverters` — extracts fields from runtime schema dynamically. Clean, but touches flink-avro core. 2. Handle `source` in `DebeziumAvroDeserializationSchema` — keep as `GenericRecord`, convert to MAP using runtime schema. No core changes, but bypasses standard layer. Which fits better with Flink's direction? -- 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. 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