Question

当我尝试使用Spark Streaming使用来自kafka主题的消息时出现以下错误

scala> val kafkaStream = KafkaUtils.createStream(ssc, "<ipaddress>:2181","spark-streaming-consumer-group", Map("test1" -> 5))

错误：

`missing or invalid dependency detected while loading class file 'KafkaUtils.class'.
Could not access term kafka in package <root>,
because it (or its dependencies) are missing. Check your build definition for
missing or conflicting dependencies. (Re-run with `-Ylog-classpath` to see the problematic classpath.)
A full rebuild may help if 'KafkaUtils.class' was compiled against an incompatible version of <root>.`

Scala版本：2.11.8 spark版本：2.1.0.2.6.0.3-8

我使用了各种各样的库进行spark-streaming-kafka，但没有任何效果：

我正在执行来自spark shell的代码：

./spark-shell --jars /data/home/local/504/spark-streaming-kafka_2.10-1.5.1.jar, /data/home/local/504/spark-streaming_2.10-1.5.1.jar

代码

import org.apache.spark.SparkConf
val conf = new SparkConf().setMaster("local[*]").setAppName("KafkaReceiver")
import org.apache.spark.streaming.StreamingContext
import org.apache.spark.streaming.Seconds
val ssc = new StreamingContext(conf, Seconds(10))
import org.apache.spark.streaming.kafka.KafkaUtils
val kafkaStream = KafkaUtils.createStream(ssc, "<ipaddress>:2181","spark-streaming-consumer-group", Map("test1" -> 5))

对此问题有任何建议。

Answer 1

由于您使用的是Scala 2.11和spark 2.1.0，因此您应该使用这些jars

spark-streaming-kafka-0-10_2.11-2.1.0.jar
spark-streaming_2.11-2.1.0.jar

如果您使用的是Kafka 0.10+，请相应地对其进行更改。

简单的程序看起来像

import org.apache.spark.streaming.kafka010.ConsumerStrategies.Subscribe
import org.apache.spark.streaming.kafka010.KafkaUtils
import org.apache.spark.streaming.kafka010.LocationStrategies.PreferConsistent
import org.apache.kafka.common.serialization.StringDeserializer

val streamingContext = new StreamingContext(sc, Seconds(5))

//Parameters for kafka
val kafkaParams = Map[String, Object](
  "bootstrap.servers" -> "servers,
  "key.deserializer" -> classOf[StringDeserializer],
  "value.deserializer" -> classOf[StringDeserializer],
  "group.id" -> "test-consumer-group",
  "auto.offset.reset" -> "earliest",
  "enable.auto.commit" -> (false: java.lang.Boolean)
)
val topics = "topics,seperated,by,comma".split(",")

// crate dstreams
val stream = KafkaUtils.createDirectStream[String, String](
  streamingContext,
  PreferConsistent,
  Subscribe[String, String](topics, kafkaParams)
)

//stream.print()
stream.map(_.value().toString).print()

希望这个帮助！

Sparkstreaming + Kafka到HDFS

1 个答案: