flinkcdc 获取oracle备库数据的代码以及所需要的依赖

以下是使用 Flink CDC 获取 Oracle 备库数据的示例代码：

import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.common.serialization.SimpleStringSchema;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.source.SourceFunction;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer;
import org.apache.flink.streaming.util.serialization.JSONKeyValueDeserializationSchema;
import org.apache.flink.types.Row;
import org.apache.flink.util.Collector;
import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.clients.producer.ProducerConfig;
import org.apache.kafka.common.serialization.StringDeserializer;
import org.apache.kafka.common.serialization.StringSerializer;

import java.util.Properties;

public class OracleCDC {

    public static void main(String[] args) throws Exception {
        // set up the execution environment
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        // set up the properties for the Kafka consumer
        Properties consumerProps = new Properties();
        consumerProps.setProperty(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
        consumerProps.setProperty(ConsumerConfig.GROUP_ID_CONFIG, "flink-cdc-oracle");
        consumerProps.setProperty(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class.getName());
        consumerProps.setProperty(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, JSONKeyValueDeserializationSchema.class.getName());
        consumerProps.setProperty(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");

        // create a Kafka consumer for the CDC data
        FlinkKafkaConsumer<String> cdcConsumer = new FlinkKafkaConsumer<>("oracle-cdc", new SimpleStringSchema(), consumerProps);

        // add the CDC data source to the execution environment
        env.addSource(cdcConsumer)
                .map(new MapFunction<String, Row>() {
                    @Override
                    public Row map(String value) throws Exception {
                        // parse the CDC data into a Flink Row
                        String[] tokens = value.split(",");
                        Row row = new Row(tokens.length);
                        for (int i = 0; i < tokens.length; i++) {
                            row.setField(i, tokens[i]);
                        }
                        return row;
                    }
                })
                .addSink(new FlinkKafkaProducer<>("localhost:9092", "oracle-cdc-output", new SimpleStringSchema()));

        // execute the Flink job
        env.execute("Oracle CDC");
    }
}

这里使用了 Flink 的 Kafka Connector 作为数据源和数据输出，需要添加以下依赖：

<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-streaming-java_2.11</artifactId>
    <version>${flink.version}</version>
</dependency>
<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-connector-kafka_2.11</artifactId>
    <version>${flink.version}</version>
</dependency>
<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-json</artifactId>
    <version>${flink.version}</version>
</dependency>
<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-types</artifactId>
    <version>${flink.version}</version>
</dependency>
<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-table-api-java-bridge_2.11</artifactId>
    <version>${flink.version}</version>
</dependency>

其中 `${flink.version}` 为 Flink 版本号。此外，还需要添加 Kafka 相关依赖，如下所示：

<dependency>
    <groupId>org.apache.kafka</groupId>
    <artifactId>kafka-clients</artifactId>
    <version>${kafka.version}</version>
</dependency>
<dependency>
    <groupId>org.apache.kafka</groupId>
    <artifactId>kafka_2.11</artifactId>
    <version>${kafka.version}</version>
</dependency>

其中 `${kafka.version}` 为 Kafka 版本号。