KafkaUtils.createDirectStream()参数详解

通过KafkaUtils.createDirectStream该方法创建kafka的DStream数据源，传入有三个参数：ssc，LocationStrategies，ConsumerStrategies。

LocationStrategies有三种策略：PreferBrokers，PreferConsistent，PreferFixed详情查看上边源码解析

/**
 * :: Experimental :: object to obtain instances of [[LocationStrategy]]
 *
 */
@Experimental
object LocationStrategies {
  /**
   *  :: Experimental ::
   * Use this only if your executors are on the same nodes as your Kafka brokers. 只有当executors数量等于brokers数量时使用
   */
  @Experimental
  def PreferBrokers: LocationStrategy =
    org.apache.spark.streaming.kafka010.PreferBrokers

  /**
   *  :: Experimental ::
   * Use this in most cases, it will consistently distribute partitions across all executors.大多数使用，在所有的executors分配分区
   */
  @Experimental
  def PreferConsistent: LocationStrategy =
    org.apache.spark.streaming.kafka010.PreferConsistent

  /**
   *  :: Experimental ::
   * Use this to place particular TopicPartitions on particular hosts if your load is uneven.
   * Any TopicPartition not specified in the map will use a consistent location.如果负载不平衡，把特定的TopicPartitions放在特定的hosts，不在这个map中的TopicPartition采用PreferConsistent策略
   */
  @Experimental
  def PreferFixed(hostMap: collection.Map[TopicPartition, String]): LocationStrategy =
    new PreferFixed(new ju.HashMap[TopicPartition, String](hostMap.asJava))

  /**
   *  :: Experimental ::
   * Use this to place particular TopicPartitions on particular hosts if your load is uneven.
   * Any TopicPartition not specified in the map will use a consistent location.
   */
  @Experimental
  def PreferFixed(hostMap: ju.Map[TopicPartition, String]): LocationStrategy =
    new PreferFixed(hostMap)

ConsumerStrategies消费者策略：Subscribe，SubscribePattern，Assign，订阅和分配

　　Subscribe为consumer自动分配partition，有内部算法保证topic-partitions以最优的方式均匀分配给同group下的不同consumer

　　Assign为consumer手动、显示的指定需要消费的topic-partitions，不受group.id限制，相当于指定的group无效

/**
   *  :: Experimental ::
   * Subscribe to a collection of topics.
   * @param topics collection of topics to subscribe
   * @param kafkaParams Kafka
   * <a href="http://kafka.apache.org/documentation.html#newconsumerconfigs">
   * configuration parameters</a> to be used on driver. The same params will be used on executors,
   * with minor automatic modifications applied.
   *  Requires "bootstrap.servers" to be set
   * with Kafka broker(s) specified in host1:port1,host2:port2 form.
   * @param offsets: offsets to begin at on initial startup.  If no offset is given for a
   * TopicPartition, the committed offset (if applicable) or kafka param
   * auto.offset.reset will be used.
   */
  @Experimental
  def Subscribe[K, V](
      topics: Iterable[jl.String],
      kafkaParams: collection.Map[String, Object],
      offsets: collection.Map[TopicPartition, Long]): ConsumerStrategy[K, V] = {
    new Subscribe[K, V](
      new ju.ArrayList(topics.asJavaCollection),
      new ju.HashMap[String, Object](kafkaParams.asJava),
      new ju.HashMap[TopicPartition, jl.Long](offsets.mapValues(l => new jl.Long(l)).asJava))
  }

/** :: Experimental ::
   * Subscribe to all topics matching specified pattern to get dynamically assigned partitions.
   * The pattern matching will be done periodically against topics existing at the time of check.
   * @param pattern pattern to subscribe to
   * @param kafkaParams Kafka
   * <a href="http://kafka.apache.org/documentation.html#newconsumerconfigs">
   * configuration parameters</a> to be used on driver. The same params will be used on executors,
   * with minor automatic modifications applied.
   *  Requires "bootstrap.servers" to be set
   * with Kafka broker(s) specified in host1:port1,host2:port2 form.
   * @param offsets: offsets to begin at on initial startup.  If no offset is given for a
   * TopicPartition, the committed offset (if applicable) or kafka param
   * auto.offset.reset will be used.
   */
  @Experimental
  def SubscribePattern[K, V](
      pattern: ju.regex.Pattern,
      kafkaParams: collection.Map[String, Object],
      offsets: collection.Map[TopicPartition, Long]): ConsumerStrategy[K, V] = {
    new SubscribePattern[K, V](
      pattern,
      new ju.HashMap[String, Object](kafkaParams.asJava),
      new ju.HashMap[TopicPartition, jl.Long](offsets.mapValues(l => new jl.Long(l)).asJava))
  }

/**
   *  :: Experimental ::
   * Assign a fixed collection of TopicPartitions
   * @param topicPartitions collection of TopicPartitions to assign
   * @param kafkaParams Kafka
   * <a href="http://kafka.apache.org/documentation.html#newconsumerconfigs">
   * configuration parameters</a> to be used on driver. The same params will be used on executors,
   * with minor automatic modifications applied.
   *  Requires "bootstrap.servers" to be set
   * with Kafka broker(s) specified in host1:port1,host2:port2 form.
   * @param offsets: offsets to begin at on initial startup.  If no offset is given for a
   * TopicPartition, the committed offset (if applicable) or kafka param
   * auto.offset.reset will be used.
   */
  @Experimental
  def Assign[K, V](
      topicPartitions: Iterable[TopicPartition],
      kafkaParams: collection.Map[String, Object],
      offsets: collection.Map[TopicPartition, Long]): ConsumerStrategy[K, V] = {
    new Assign[K, V](
      new ju.ArrayList(topicPartitions.asJavaCollection),
      new ju.HashMap[String, Object](kafkaParams.asJava),
      new ju.HashMap[TopicPartition, jl.Long](offsets.mapValues(l => new jl.Long(l)).asJava))
  }

 Cannot resolve overloaded method:

　　原因：方法中传入的参数不符合要求。检查参数类型