聊聊MaxwellKafkaPartitioner

序

本文主要研究一下MaxwellKafkaPartitioner

MaxwellKafkaPartitioner

maxwell-1.25.1/src/main/java/com/zendesk/maxwell/producer/partitioners/MaxwellKafkaPartitioner.java

public class MaxwellKafkaPartitioner extends AbstractMaxwellPartitioner {
    HashFunction hashFunc;

    public MaxwellKafkaPartitioner(String hashFunction, String partitionKey, String csvPartitionColumns, String partitionKeyFallback) {
        super(partitionKey, csvPartitionColumns, partitionKeyFallback);

        int MURMUR_HASH_SEED = 25342;
        switch (hashFunction) {
            case "murmur3": this.hashFunc = new HashFunctionMurmur3(MURMUR_HASH_SEED);
                break;
            case "default":
            default:
                this.hashFunc = new HashFunctionDefault();
                break;
        }
    }

    public int kafkaPartition(RowMap r, int numPartitions) {
        return Math.abs(hashFunc.hashCode(this.getHashString(r)) % numPartitions);
    }
}

• MaxwellKafkaPartitioner继承了AbstractMaxwellPartitioner，其构造器根据hashFunction类型创建HashFunctionMurmur3或者HashFunctionDefault；其kafkaPartition方法则通过 Math.abs(hashFunc.hashCode(this.getHashString(r)) % numPartitions) 计算partition

AbstractMaxwellPartitioner

maxwell-1.25.1/src/main/java/com/zendesk/maxwell/producer/partitioners/AbstractMaxwellPartitioner.java

public abstract class AbstractMaxwellPartitioner {
    List<String> partitionColumns = new ArrayList<String>();
    private final PartitionBy partitionBy, partitionByFallback;

    private PartitionBy partitionByForString(String key) {


        if ( key == null )
            return PartitionBy.DATABASE;

        switch(key) {
            case "table":
                return PartitionBy.TABLE;
            case "database":
                return PartitionBy.DATABASE;
            case "primary_key":
                return PartitionBy.PRIMARY_KEY;
            case "transaction_id":
                return PartitionBy.TRANSACTION_ID;
            case "column":
                return PartitionBy.COLUMN;
            case "random":
                return PartitionBy.RANDOM;
            default:
                throw new RuntimeException("Unknown partitionBy string: " + key);
        }
    }

    public AbstractMaxwellPartitioner(String partitionKey, String csvPartitionColumns, String partitionKeyFallback) {
        this.partitionBy = partitionByForString(partitionKey);
        this.partitionByFallback = partitionByForString(partitionKeyFallback);

        if ( csvPartitionColumns != null )
            this.partitionColumns = Arrays.asList(csvPartitionColumns.split("//s*,//s*"));
    }

    static protected String getDatabase(RowMap r) {
        return r.getDatabase();
    }

    static protected String getTable(RowMap r) {
        return r.getTable();
    }

    public String getHashString(RowMap r, PartitionBy by) {
        switch ( by ) {
            case TABLE:
                String t = r.getTable();
                if ( t == null && partitionByFallback == PartitionBy.DATABASE )
                    return r.getDatabase();
                else
                    return t;
            case DATABASE:
                return r.getDatabase();
            case PRIMARY_KEY:
                return r.getRowIdentity().toConcatString();
            case TRANSACTION_ID:
                return String.valueOf(r.getXid());
            case COLUMN:
                String s = r.buildPartitionKey(partitionColumns);
                if ( s.length() > 0 )
                    return s;
                else
                    return getHashString(r, partitionByFallback);
            case RANDOM:
                return RandomStringUtils.random(10, true, true);
        }
        return null; // thx java
    }

    public String getHashString(RowMap r) {
        if ( r.getPartitionString() != null )
            return r.getPartitionString();
        else
            return getHashString(r, partitionBy);
    }
}

• AbstractMaxwellPartitioner的构造器通过partitionByForString确定PartitionBy；其getHashString方法根据PartitionBy返回指定的值

HashFunction

maxwell-1.25.1/src/main/java/com/zendesk/maxwell/producer/partitioners/HashFunction.java

public interface HashFunction {
    int hashCode(String s);
}

• HashFunction接口定义了hashCode方法

HashFunctionDefault

maxwell-1.25.1/src/main/java/com/zendesk/maxwell/producer/partitioners/HashFunctionDefault.java

public class HashFunctionDefault implements HashFunction {
    public int hashCode(String s) {
        return s.hashCode();
    }
}

• HashFunctionDefault实现了HashFunction接口，其hashCode直接返回string的hashCode

HashFunctionMurmur3

maxwell-1.25.1/src/main/java/com/zendesk/maxwell/producer/partitioners/HashFunctionMurmur3.java

public class HashFunctionMurmur3 implements HashFunction {
    private int seed;
    public HashFunctionMurmur3(int seed){
        this.seed = seed;
    }
    public int hashCode(String s) {
        return MurmurHash3.murmurhash3_x86_32(s, 0, s.length(), seed);
    }
}

• HashFunctionMurmur3实现了HashFunction接口，其hashCode方法返回 MurmurHash3.murmurhash3_x86_32(s, 0, s.length(), seed)

MaxwellKafkaProducerWorker

maxwell-1.25.1/src/main/java/com/zendesk/maxwell/producer/MaxwellKafkaProducer.java

class MaxwellKafkaProducerWorker extends AbstractAsyncProducer implements Runnable, StoppableTask {
    static final Logger LOGGER = LoggerFactory.getLogger(MaxwellKafkaProducer.class);

    private final Producer<String, String> kafka;
    private final String topic;
    private final String ddlTopic;
    private final MaxwellKafkaPartitioner partitioner;
    private final MaxwellKafkaPartitioner ddlPartitioner;

    //......

    ProducerRecord<String, String> makeProducerRecord(final RowMap r) throws Exception {
        RowIdentity pk = r.getRowIdentity();
        String key = r.pkToJson(keyFormat);
        String value = r.toJSON(outputConfig);
        ProducerRecord<String, String> record;
        if (r instanceof DDLMap) {
            record = new ProducerRecord<>(this.ddlTopic, this.ddlPartitioner.kafkaPartition(r, getNumPartitions(this.ddlTopic)), key, value);
        } else {
            String topic;

            // javascript topic override
            topic = r.getKafkaTopic();
            if ( topic == null ) {
                topic = generateTopic(this.topic, pk);
            }
            LOGGER.debug("context.getConfig().producerPartitionKey = " + context.getConfig().producerPartitionKey);

            record = new ProducerRecord<>(topic, this.partitioner.kafkaPartition(r, getNumPartitions(topic)), key, value);
        }
        return record;
    }

    //......

}

• MaxwellKafkaProducerWorker的makeProducerRecord方法针对DDLMap使用ddlPartitioner.kafkaPartition(r, getNumPartitions(this.ddlTopic))确定partition；非DDLMap的使用partitioner.kafkaPartition(r, getNumPartitions(topic))来确定partition

小结

MaxwellKafkaPartitioner继承了AbstractMaxwellPartitioner，其构造器根据hashFunction类型创建HashFunctionMurmur3或者HashFunctionDefault；其kafkaPartition方法则通过 Math.abs(hashFunc.hashCode(this.getHashString(r)) % numPartitions) 计算partition

doc

• MaxwellKafkaPartitioner