好的，我深入研究了kafka消费者javadocs，并找到了一个示例来使用avro流。我仍然需要将Kafka消费转换为flinkkafkaconsumer，但是下面的代码可以工作。
为了使io.confluent引用工作，我必须向pom文件添加一个存储库和一个依赖项。

<repository>
  <id>confluent</id>
    <url>http://packages.confluent.io/maven/</url>
</repository>

<dependency>
    <groupId>io.confluent</groupId>
    <artifactId>kafka-avro-serializer</artifactId>
    <version>3.1.1</version>
</dependency>

public class StreamingJob {

//  static  DeserializationSchema<pendingsv> avroSchema = new AvroDeserializationSchema<pendingsv>(pendingsv.class);
    public static void main(String[] args) throws Exception {
        // set up the streaming execution environment
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        Properties props = new Properties();
        props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
        props.put(ConsumerConfig.GROUP_ID_CONFIG, "opssupport.alarms");
        props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, "org.apache.kafka.common.serialization.StringDeserializer");
        props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, "io.confluent.kafka.serializers.KafkaAvroDeserializer");
        props.put("schema.registry.url", "http://localhost:8081");
        props.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
        String topic = "pendingSVs_";
        final Consumer<String, GenericRecord> consumer = new KafkaConsumer<String, GenericRecord>(props);
        consumer.subscribe(Arrays.asList(topic));

        try {
            while (true) {
                ConsumerRecords<String, GenericRecord> records = consumer.poll(100);
                for (ConsumerRecord<String, GenericRecord> record : records) {
                    System.out.printf("offset = %d, key = %s, value = %s \n", record.offset(), record.key(), record.value());
                }
            }
        } finally {
            consumer.close();
        }

    // execute program
    //env.execute("Flink Streaming Java API Skeleton");
}

}