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https://issues.apache.org/jira/browse/FLINK-3871?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15983204#comment-15983204
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ASF GitHub Bot commented on FLINK-3871:
---------------------------------------
Github user fhueske commented on a diff in the pull request:
https://github.com/apache/flink/pull/3663#discussion_r113236267
--- Diff:
flink-connectors/flink-connector-kafka-base/src/main/java/org/apache/flink/streaming/util/serialization/AvroRowSerializationSchema.java
---
@@ -0,0 +1,122 @@
+/*
+ * 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.streaming.util.serialization;
+
+import java.io.ByteArrayOutputStream;
+import java.io.IOException;
+import java.util.List;
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.avro.io.DatumWriter;
+import org.apache.avro.io.Encoder;
+import org.apache.avro.io.EncoderFactory;
+import org.apache.avro.reflect.ReflectDatumWriter;
+import org.apache.avro.specific.SpecificData;
+import org.apache.avro.specific.SpecificRecord;
+import org.apache.avro.util.Utf8;
+import org.apache.flink.types.Row;
+import org.apache.flink.util.Preconditions;
+
+/**
+ * Serialization schema that serializes {@link Row} over {@link
SpecificRecord} into a Avro bytes.
+ */
+public class AvroRowSerializationSchema implements
SerializationSchema<Row> {
+
+ /**
+ * Avro serialization schema.
+ */
+ private final Schema schema;
+
+ /**
+ * Writer to serialize Avro record into a byte array.
+ */
+ private final DatumWriter<GenericRecord> datumWriter;
+
+ /**
+ * Output stream to serialize records into byte array.
+ */
+ private final ByteArrayOutputStream arrayOutputStream = new
ByteArrayOutputStream();
+
+ /**
+ * Low-level class for serialization of Avro values.
+ */
+ private final Encoder encoder =
EncoderFactory.get().binaryEncoder(arrayOutputStream, null);
+
+ /**
+ * Creates a Avro serialization schema for the given schema.
+ *
+ * @param recordClazz Avro record class used to deserialize Avro's
record to Flink's row
+ */
+ @SuppressWarnings("unchecked")
+ public AvroRowSerializationSchema(Class<? extends SpecificRecord>
recordClazz) {
+ Preconditions.checkNotNull(recordClazz, "Avro record class must
not be null.");
+ this.schema = SpecificData.get().getSchema(recordClazz);
+ this.datumWriter = new ReflectDatumWriter<>(schema);
+ }
+
+ @Override
+ @SuppressWarnings("unchecked")
+ public byte[] serialize(Row row) {
+ // convert to record
+ final Object record = convertToRecord(schema, row);
+
+ // write
+ try {
+ arrayOutputStream.reset();
+ datumWriter.write((GenericRecord) record, encoder);
+ encoder.flush();
+ return arrayOutputStream.toByteArray();
+ } catch (IOException e) {
+ throw new RuntimeException("Failed to serialize Row.",
e);
+ }
+ }
+
+ /**
+ * Converts a (nested) Flink Row into Avro's {@link GenericRecord}.
+ * Strings are converted into Avro's {@link Utf8} fields.
+ */
+ private static Object convertToRecord(Schema schema, Object rowObj) {
+ if (rowObj instanceof Row) {
+ // records can be wrapped in a union
+ if (schema.getType() == Schema.Type.UNION) {
+ final List<Schema> types = schema.getTypes();
+ if (types.size() == 2 && types.get(0).getType()
== Schema.Type.NULL && types.get(1).getType() == Schema.Type.RECORD) {
+ schema = types.get(1);
+ }
+ else {
+ throw new RuntimeException("Currently
we only support schemas of the following form: UNION[null, RECORD]. Given: " +
schema);
+ }
+ } else if (schema.getType() != Schema.Type.RECORD) {
+ throw new RuntimeException("Record type for row
type expected. But is: " + schema);
+ }
+ final List<Schema.Field> fields = schema.getFields();
+ final GenericRecord record = new
GenericData.Record(schema);
--- End diff --
Can we reuse the `GenericRecord`?
> Add Kafka TableSource with Avro serialization
> ---------------------------------------------
>
> Key: FLINK-3871
> URL: https://issues.apache.org/jira/browse/FLINK-3871
> Project: Flink
> Issue Type: New Feature
> Components: Table API & SQL
> Reporter: Fabian Hueske
> Assignee: Ivan Mushketyk
>
> Add a Kafka TableSource which supports Avro serialized data.
> The KafkaAvroTableSource should support two modes:
> # SpecificRecord Mode: In this case the user specifies a class which was
> code-generated by Avro depending on a schema. Flink treats these classes as
> regular POJOs. Hence, they are also natively supported by the Table API and
> SQL. Classes generated by Avro contain their Schema in a static field. The
> schema should be used to automatically derive field names and types. Hence,
> there is no additional information required than the name of the class.
> # GenericRecord Mode: In this case the user specifies an Avro Schema. The
> schema is used to deserialize the data into a GenericRecord which must be
> translated into possibly nested {{Row}} based on the schema information.
> Again, the Avro Schema is used to automatically derive the field names and
> types. This mode is less efficient than the SpecificRecord mode because the
> {{GenericRecord}} needs to be converted into {{Row}}.
> This feature depends on FLINK-5280, i.e., support for nested data in
> {{TableSource}}.
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