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org.apache.spark.streaming.kafka09

KafkaUtils

Related Doc: package kafka09

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object KafkaUtils extends Logging

:: Experimental :: object for constructing Kafka streams and RDDs

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@Experimental()
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  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  5. def clone(): AnyRef

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  6. def createDirectStream[K, V](jssc: JavaStreamingContext, locationStrategy: LocationStrategy, consumerStrategy: ConsumerStrategy[K, V], perPartitionConfig: PerPartitionConfig): JavaInputDStream[ConsumerRecord[K, V]]

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    :: Experimental :: Java constructor for a DStream where each given Kafka topic/partition corresponds to an RDD partition.

    :: Experimental :: Java constructor for a DStream where each given Kafka topic/partition corresponds to an RDD partition.

    K

    type of Kafka message key

    V

    type of Kafka message value

    locationStrategy

    In most cases, pass in LocationStrategies.PreferConsistent, see LocationStrategies for more details.

    consumerStrategy

    In most cases, pass in ConsumerStrategies.Subscribe, see ConsumerStrategies for more details

    perPartitionConfig

    configuration of settings such as max rate on a per-partition basis. see PerPartitionConfig for more details.

    Annotations
    @Experimental()

  7. def createDirectStream[K, V](jssc: JavaStreamingContext, locationStrategy: LocationStrategy, consumerStrategy: ConsumerStrategy[K, V]): JavaInputDStream[ConsumerRecord[K, V]]

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    :: Experimental :: Java constructor for a DStream where each given Kafka topic/partition corresponds to an RDD partition.

    :: Experimental :: Java constructor for a DStream where each given Kafka topic/partition corresponds to an RDD partition.

    K

    type of Kafka message key

    V

    type of Kafka message value

    locationStrategy

    In most cases, pass in LocationStrategies.PreferConsistent, see LocationStrategies for more details.

    consumerStrategy

    In most cases, pass in ConsumerStrategies.Subscribe, see ConsumerStrategies for more details

    Annotations
    @Experimental()

  8. def createDirectStream[K, V](ssc: StreamingContext, locationStrategy: LocationStrategy, consumerStrategy: ConsumerStrategy[K, V], perPartitionConfig: PerPartitionConfig): InputDStream[ConsumerRecord[K, V]]

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    :: Experimental :: Scala constructor for a DStream where each given Kafka topic/partition corresponds to an RDD partition.

    :: Experimental :: Scala constructor for a DStream where each given Kafka topic/partition corresponds to an RDD partition.

    K

    type of Kafka message key

    V

    type of Kafka message value

    locationStrategy

    In most cases, pass in LocationStrategies.PreferConsistent, see LocationStrategies for more details.

    consumerStrategy

    In most cases, pass in ConsumerStrategies.Subscribe, see ConsumerStrategies for more details.

    perPartitionConfig

    configuration of settings such as max rate on a per-partition basis. see PerPartitionConfig for more details.

    Annotations
    @Experimental()

  9. def createDirectStream[K, V](ssc: StreamingContext, locationStrategy: LocationStrategy, consumerStrategy: ConsumerStrategy[K, V]): InputDStream[ConsumerRecord[K, V]]

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    :: Experimental :: Scala constructor for a DStream where each given Kafka topic/partition corresponds to an RDD partition.

    :: Experimental :: Scala constructor for a DStream where each given Kafka topic/partition corresponds to an RDD partition. The spark configuration spark.streaming.kafka.maxRatePerPartition gives the maximum number of messages per second that each partition will accept.

    K

    type of Kafka message key

    V

    type of Kafka message value

    locationStrategy

    In most cases, pass in LocationStrategies.PreferConsistent, see LocationStrategies for more details.

    consumerStrategy

    In most cases, pass in ConsumerStrategies.Subscribe, see ConsumerStrategies for more details

    Annotations
    @Experimental()

  10. def createRDD[K, V](jsc: JavaSparkContext, kafkaParams: Map[String, AnyRef], offsetRanges: Array[OffsetRange], locationStrategy: LocationStrategy): JavaRDD[ConsumerRecord[K, V]]

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    :: Experimental :: Java constructor for a batch-oriented interface for consuming from Kafka.

    :: Experimental :: Java constructor for a batch-oriented interface for consuming from Kafka. Starting and ending offsets are specified in advance, so that you can control exactly-once semantics.

    K

    type of Kafka message key

    V

    type of Kafka message value

    kafkaParams

    Kafka configuration parameters. Requires "bootstrap.servers" to be set with Kafka broker(s) specified in host1:port1,host2:port2 form.

    offsetRanges

    offset ranges that define the Kafka data belonging to this RDD

    locationStrategy

    In most cases, pass in LocationStrategies.PreferConsistent, see LocationStrategies for more details.

    Annotations
    @Experimental()

  11. def createRDD[K, V](sc: SparkContext, kafkaParams: Map[String, AnyRef], offsetRanges: Array[OffsetRange], locationStrategy: LocationStrategy): RDD[ConsumerRecord[K, V]]

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    :: Experimental :: Scala constructor for a batch-oriented interface for consuming from Kafka.

    :: Experimental :: Scala constructor for a batch-oriented interface for consuming from Kafka. Starting and ending offsets are specified in advance, so that you can control exactly-once semantics.

    K

    type of Kafka message key

    V

    type of Kafka message value

    kafkaParams

    Kafka configuration parameters. Requires "bootstrap.servers" to be set with Kafka broker(s) specified in host1:port1,host2:port2 form.

    offsetRanges

    offset ranges that define the Kafka data belonging to this RDD

    locationStrategy

    In most cases, pass in LocationStrategies.PreferConsistent, see LocationStrategies for more details.

    Annotations
    @Experimental()

  12. val eofOffset: Int

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  13. final def eq(arg0: AnyRef): Boolean

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  14. def equals(arg0: Any): Boolean

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  15. def finalize(): Unit

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  16. final def getClass(): Class[_]

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  17. def hashCode(): Int

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  18. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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  20. def isTraceEnabled(): Boolean

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  21. def log: Logger

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  22. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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  23. def logDebug(msg: ⇒ String): Unit

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  24. def logError(msg: ⇒ String, throwable: Throwable): Unit

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  25. def logError(msg: ⇒ String): Unit

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  26. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

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  27. def logInfo(msg: ⇒ String): Unit

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  28. def logName: String

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  29. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

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  30. def logTrace(msg: ⇒ String): Unit

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  31. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

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  32. def logWarning(msg: ⇒ String): Unit

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  33. final def ne(arg0: AnyRef): Boolean

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  34. final def notify(): Unit

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  35. final def notifyAll(): Unit

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  36. final def synchronized[T0](arg0: ⇒ T0): T0

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  37. def toString(): String

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  38. final def wait(): Unit

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  39. final def wait(arg0: Long, arg1: Int): Unit

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  40. final def wait(arg0: Long): Unit

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  41. def waitForConsumerAssignment[K, V](consumer: KafkaConsumer[K, V]): Unit

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