flink-end-to-end-tests/flink-confluent-schema-registry/src/main/java/org/apache/flink/schema/registry/test/TestAvroConsumerConfluent.java

/*
 * 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.schema.registry.test;

import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.common.serialization.SimpleStringSchema;
import org.apache.flink.api.java.utils.ParameterTool;
import org.apache.flink.formats.avro.registry.confluent.ConfluentRegistryAvroDeserializationSchema;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer010;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer010;

import example.avro.User;
import org.apache.avro.specific.SpecificRecordBase;

import java.util.Properties;

/**
 * A simple example that shows how to read from and write to Kafka with Confluent Schema Registry.
 * This will read AVRO messages from the input topic, parse them into a POJO type via checking the Schema by calling Schema registry.
 * Then this example publish the POJO type to kafka by converting the POJO to AVRO and verifying the schema.
 * --input-topic test-input --output-topic test-output --bootstrap.servers localhost:9092 --zookeeper.connect localhost:2181 --schema-registry-url http://localhost:8081 --group.id myconsumer
 */
public class TestAvroConsumerConfluent {

	public static void main(String[] args) throws Exception {
		// parse input arguments
		final ParameterTool parameterTool = ParameterTool.fromArgs(args);

		if (parameterTool.getNumberOfParameters() < 6) {
			System.out.println("Missing parameters!\n" +
				"Usage: Kafka --input-topic <topic> --output-topic <topic> " +
				"--bootstrap.servers <kafka brokers> " +
				"--zookeeper.connect <zk quorum> " +
				"--schema-registry-url <confluent schema registry> --group.id <some id>");
			return;
		}
		Properties config = new Properties();
		config.setProperty("bootstrap.servers", parameterTool.getRequired("bootstrap.servers"));
		config.setProperty("group.id", parameterTool.getRequired("group.id"));
		config.setProperty("zookeeper.connect", parameterTool.getRequired("zookeeper.connect"));
		String schemaRegistryUrl = parameterTool.getRequired("schema-registry-url");

		StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
		env.getConfig().disableSysoutLogging();

		DataStreamSource<User> input = env
			.addSource(
				new FlinkKafkaConsumer010<>(
					parameterTool.getRequired("input-topic"),
					ConfluentRegistryAvroDeserializationSchema.forSpecific(User.class, schemaRegistryUrl),
					config).setStartFromEarliest());

		SingleOutputStreamOperator<String> mapToString = input
			.map((MapFunction<User, String>) SpecificRecordBase::toString);

		FlinkKafkaProducer010<String> stringFlinkKafkaProducer010 = new FlinkKafkaProducer010<>(
			parameterTool.getRequired("output-topic"),
			new SimpleStringSchema(),
			config);

		mapToString.addSink(stringFlinkKafkaProducer010);
		env.execute("Kafka 0.10 Confluent Schema Registry AVRO Example");
	}
}