从Kafka主题消费消息时反序列化的问题

问题描述 投票:0回答:1

我正在使用Kafka Consumer API来构建使用者。消息结构很复杂。为了构建反序列化器,我实现了Deserializer类并提供了必要的实现。我使用Jackson API进行反序列化。我收到此错误“异常raiseorg.apache.kafka.common.errors.SerializationException:错误反序列化分区staging.datafeeds.PartnerHotel-0的键/值在偏移19205124”

#POJO classes

    public class Change {
    private  Schema schema;
    private  Payload payload;
    //Getters and constructor
    }
    public class Details {
    private List<String> effectedAttributes;
    private List<PartnerHotel> cluster;
    //Getters and contructor
    }
    public class Field {
    private String type;
    private Boolean optional;
    private String field;
    //Getters and constructor
    }
    public class Fields {
    private String type;
    private List<Field> fields;
    private Boolean optional;
    private String name;
    //Getters and contructor
    }
    public class Geom{
    private int srid;
    private String wkb;
    //Getters and contructor
    }
    public class PartnerHotel{
    private int id;
    private int shopId;
    private String partnerHotelId;
    private boolean isOnline;
    private boolean isRemovedByUser;
    private int mappingPriority;
    private int hotelId;
    private String statusHotelId;
    private String name;
    private String street;
    private String zipCode;
    private String city;
    private String sourceCityId;
    private String state;
    private String stateAlpha2;
    private String country;
    private String alpha2;
    private String alpha3;
    private double latitude;
    private double longitude;
    private Geom geomPoint;
    private int countryIdShop;
    private int selectedGeoname;
    private String propertyType;
    private List<String> tags;
    private int stars;
    private String url;
    private int nrRatings;
    private double recommendation;
    private long dateHotelId;
    private long timeStamp;
    private long lastImport;
    //Getters and contructor
    }
    public class Payload {
    private PartnerHotel before;
    private PartnerHotel after;
    private Source source;
    private String op;
    private String ts_ms;
    //Getters and contructor
    }
    public class Schema {
    private String type;
    private Boolean optional;
    private String name;
    private List<Fields> fields;
    //Getters and contructor
    }
    public class Source {
    private String version;
    private String name;
    private String ts_usec;
    private String txId;
    private String lxn;
    private Boolean snapshot;
    private Object lastSnapshotRecord;
    //Getters and contructor
    }

#Deserializer

    public class ChangeDeserializer implements Deserializer<Change> {

    public ChangeDeserializer(){ }

    public void configure(Map<String, ?> map, boolean b) {}

    public Change deserialize(String topic, byte[] data) {
        if(data == null){
            return null;
        }
        try{
            ObjectMapper objectMapper = new ObjectMapper();
            Change change = objectMapper.readValue(data,Change.class);
            return change;
        }
        catch(IOException exception){
            throw new DeserializationException("Unable to deserialize               Change", exception);
        }}

    public void close() {}
    }

#Consumer
    public class KafkaAcnowledger {
        public static void main(String[] args){
        Properties props = new Properties();
        props.put("bootstrap.servers", "someUrl");
        props.put("group.id", "test131");
        props.put("enable.auto.commit", "true");
        props.put("auto.commit.interval.ms", "1000");
        props.put("max.poll.records",1);
        props.put("auto.offset.reset","earliest");
        props.put("key.deserializer",    "org.apache.kafka.common.serialization.LongDeserializer");
        props.put("value.deserializer",    "deserializer.ChangeDeserializer");
        KafkaConsumer<Long, Change> consumer = new KafkaConsumer(props);
        consumer.subscribe(Arrays.asList("staging.datafeeds.PartnerHotel"));
        while (true) {
            try{
            ConsumerRecords<Long, Change> records = consumer.poll(100);
            for (ConsumerRecord<Long, Change> record : records)
                System.out.printf("offset = %d, key = %s, value = %s%n", record.offset(), record.key(), record.value());
        }
        catch(Exception exception){
                System.out.println("Exception raised" + exception);
        }
        }


    }
    }

消费者中的poll()看起来很好,而enter code hereexception我得到了一个序列化异常。我通过kafka-consumer-groups.sh检查了消费者群体,这个消费者的群体在列表中。欢迎任何方向。

Structure of the message in the Kafka topic:

{"schema":{"type":"struct","fields":[{"type":"struct","fields":[{"type":"int32","optional":false,"field":"id"},{"type":"int16","optional":false,"field":"shopId"},{"type":"string","optional":false,"field":"partnerHotelId"},{"type":"boolean","optional":false,"field":"isOnline"},{"type":"boolean","optional":false,"field":"isRemovedByUser"},{"type":"int32","optional":false,"field":"mappingPriority"},{"type":"int32","optional":true,"field":"hotelId"},{"type":"string","optional":true,"field":"statusHotelId"},{"type":"int64","optional":true,"name":"io.debezium.time.MicroTimestamp","version":1,"field":"dateHotelId"},{"type":"int64","optional":false,"name":"io.debezium.time.MicroTimestamp","version":1,"field":"timestamp"},{"type":"int64","optional":false,"name":"io.debezium.time.MicroTimestamp","version":1,"field":"lastImport"},{"type":"string","optional":true,"field":"name"},{"type":"string","optional":true,"field":"street"},{"type":"string","optional":true,"field":"zipcode"},{"type":"string","optional":true,"field":"city"},{"type":"string","optional":true,"field":"sourceCityId"},{"type":"string","optional":true,"field":"state"},{"type":"string","optional":true,"field":"stateAlpha2"},{"type":"string","optional":true,"field":"country"},{"type":"string","optional":true,"field":"alpha2"},{"type":"string","optional":true,"field":"alpha3"},{"type":"double","optional":true,"field":"latitude"},{"type":"double","optional":true,"field":"longitude"},{"type":"struct","fields":[{"type":"bytes","optional":false,"field":"wkb"},{"type":"int32","optional":true,"field":"srid"}],"optional":true,"name":"io.debezium.data.geometry.Geometry","version":1,"doc":"Geometry","field":"geomPoint"},{"type":"array","items":{"type":"int32","optional":true},"optional":false,"field":"proposedGeonames"},{"type":"int32","optional":true,"field":"countryIdShop"},{"type":"int32","optional":true,"field":"selectedGeoname"},{"type":"string","optional":true,"field":"propertyType"},{"type":"array","items":{"type":"string","optional":true},"optional":false,"field":"tags"},{"type":"array","items":{"type":"string","optional":true},"optional":false,"field":"chains"},{"type":"array","items":{"type":"string","optional":true},"optional":false,"field":"creditCards"},{"type":"int32","optional":true,"field":"stars"},{"type":"string","optional":true,"field":"url"},{"type":"int32","optional":true,"field":"nrRatings"},{"type":"double","optional":true,"field":"recommendation"},{"type":"array","items":{"type":"int32","optional":true},"optional":false,"field":"proposedHotels"},{"type":"array","items":{"type":"int32","optional":true},"optional":false,"field":"proposedPartnerHotels"},{"type":"array","items":{"type":"int32","optional":true},"optional":false,"field":"removedFromHotelIds"}],"optional":true,"name":"staging.datafeeds.PartnerHotel.Value","field":"before"},{"type":"struct","fields":[{"type":"int32","optional":false,"field":"id"},{"type":"int16","optional":false,"field":"shopId"},{"type":"string","optional":false,"field":"partnerHotelId"},{"type":"boolean","optional":false,"field":"isOnline"},{"type":"boolean","optional":false,"field":"isRemovedByUser"},{"type":"int32","optional":false,"field":"mappingPriority"},{"type":"int32","optional":true,"field":"hotelId"},{"type":"string","optional":true,"field":"statusHotelId"},{"type":"int64","optional":true,"name":"io.debezium.time.MicroTimestamp","version":1,"field":"dateHotelId"},{"type":"int64","optional":false,"name":"io.debezium.time.MicroTimestamp","version":1,"field":"timestamp"},{"type":"int64","optional":false,"name":"io.debezium.time.MicroTimestamp","version":1,"field":"lastImport"},{"type":"string","optional":true,"field":"name"},{"type":"string","optional":true,"field":"street"},{"type":"string","optional":true,"field":"zipcode"},{"type":"string","optional":true,"field":"city"},{"type":"string","optional":true,"field":"sourceCityId"},{"type":"string","optional":true,"field":"state"},{"type":"string","optional":true,"field":"stateAlpha2"},{"type":"string","optional":true,"field":"country"},{"type":"string","optional":true,"field":"alpha2"},{"type":"string","optional":true,"field":"alpha3"},{"type":"double","optional":true,"field":"latitude"},{"type":"double","optional":true,"field":"longitude"},{"type":"struct","fields":[{"type":"bytes","optional":false,"field":"wkb"},{"type":"int32","optional":true,"field":"srid"}],"optional":true,"name":"io.debezium.data.geometry.Geometry","version":1,"doc":"Geometry","field":"geomPoint"},{"type":"array","items":{"type":"int32","optional":true},"optional":false,"field":"proposedGeonames"},{"type":"int32","optional":true,"field":"countryIdShop"},{"type":"int32","optional":true,"field":"selectedGeoname"},{"type":"string","optional":true,"field":"propertyType"},{"type":"array","items":{"type":"string","optional":true},"optional":false,"field":"tags"},{"type":"array","items":{"type":"string","optional":true},"optional":false,"field":"chains"},{"type":"array","items":{"type":"string","optional":true},"optional":false,"field":"creditCards"},{"type":"int32","optional":true,"field":"stars"},{"type":"string","optional":true,"field":"url"},{"type":"int32","optional":true,"field":"nrRatings"},{"type":"double","optional":true,"field":"recommendation"},{"type":"array","items":{"type":"int32","optional":true},"optional":false,"field":"proposedHotels"},{"type":"array","items":{"type":"int32","optional":true},"optional":false,"field":"proposedPartnerHotels"},{"type":"array","items":{"type":"int32","optional":true},"optional":false,"field":"removedFromHotelIds"}],"optional":true,"name":"staging.datafeeds.PartnerHotel.Value","field":"after"},{"type":"struct","fields":[{"type":"string","optional":true,"field":"version"},{"type":"string","optional":false,"field":"name"},{"type":"string","optional":false,"field":"db"},{"type":"int64","optional":true,"field":"ts_usec"},{"type":"int64","optional":true,"field":"txId"},{"type":"int64","optional":true,"field":"lsn"},{"type":"string","optional":true,"field":"schema"},{"type":"string","optional":true,"field":"table"},{"type":"boolean","optional":true,"default":false,"field":"snapshot"},{"type":"boolean","optional":true,"field":"last_snapshot_record"}],"optional":false,"name":"io.debezium.connector.postgresql.Source","field":"source"},{"type":"string","optional":false,"field":"op"},{"type":"int64","optional":true,"field":"ts_ms"}],"optional":false,"name":"staging.datafeeds.PartnerHotel.Envelope"},"payload":{"before":null,"after":{"id":13893497,"shopId":135,"partnerHotelId":"6-42036","isOnline":false,"isRemovedByUser":false,"mappingPriority":0,"hotelId":null,"statusHotelId":"AUTO","dateHotelId":null,"timestamp":1529334013938327,"lastImport":1503491984188866,"name":"Ferienvermietung Wiedemann","street":"Chausseeberg 3","zipcode":"17429","city":"Mellenthin","sourceCityId":null,"state":null,"stateAlpha2":null,"country":"Deutschland","alpha2":"DE","alpha3":null,"latitude":53.920278,"longitude":14.013333,"geomPoint":{"wkb":"AQEAACDmEAAARuo9ldMGLEA5nWSry/VKQA==","srid":4326},"proposedGeonames":[2872064],"countryIdShop":83,"selectedGeoname":2872064,"propertyType":null,"tags":["77","36","33","34","38","43","41","123","26","29","1","7","6","70","9","1000","58","17","18","15","13","14","20","65","63","46","10","52"],"chains":[],"creditCards":[],"stars":null,"url":"http://www.buchen.travel/onepage-idealo-booking/index.php?room=6-42036","nrRatings":null,"recommendation":null,"proposedHotels":[],"proposedPartnerHotels":[],"removedFromHotelIds":[]},"source":{"version":"0.8.3.Final","name":"staging","db":"geo","ts_usec":1554391067119000,"txId":4757138,"lsn":1139303143104,"schema":"datafeeds","table":"PartnerHotel","snapshot":true,"last_snapshot_record":false},"op":"r","ts_ms":1554391067119}}
java apache-kafka kafka-consumer-api
1个回答
1
投票

你POJO与你的消息不兼容,杰克逊无法解析它。至少缺少几个字段,可以找到以下错误。

Unrecognized field "timestamp" (class  com.example.kafka.Change$PartnerHotel), not marked as ignorable
Unrecognized field "zipcode" (class  com.example.kafka.Change$PartnerHotel), not marked as ignorable
Unrecognized field "proposedGeonames" (class  com.example.kafka.Change$PartnerHotel), not marked as ignorable
Unrecognized field "chains" (class  com.example.kafka.Change$PartnerHotel), not marked as ignorable
Unrecognized field "creditCards" (class  com.example.kafka.Change$PartnerHotel), not marked as ignorable
Unrecognized field "proposedHotels" (class  com.example.kafka.Change$PartnerHotel), not marked as ignorable
Unrecognized field "proposedPartnerHotels" (class  com.example.kafka.Change$PartnerHotel), not marked as ignorable
Unrecognized field "removedFromHotelIds" (class  com.example.kafka.Change$PartnerHotel), not marked as ignorable
Unrecognized field "db" (class  com.example.kafka.Change$Source), not marked as ignorable
Unrecognized field "lsn" (class  com.example.kafka.Change$Source), not marked as ignorable
Unrecognized field "schema" (class  com.example.kafka.Change$Source), not marked as ignorable
Unrecognized field "table" (class  com.example.kafka.Change$Source), not marked as ignorable
Unrecognized field "last_snapshot_record" (class  com.example.kafka.Change$Source), not marked as ignorable

要修复它,您必须将这些字段添加到POJO或禁用未知的失败:objectMapper.disable(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES);。有关jackson反序列化错误的更多信息,请访问:jackson Unrecognized field

热门问题
推荐问题
最新问题