1

我正在尝试在 Flink（1.7.2）附带的 scala-shell 中连接到本地机器上的 Kafka（2.1）并从中读取。

这就是我正在做的事情：

:require flink-connector-kafka_2.11-1.7.1.jar
:require flink-connector-kafka-base_2.11-1.7.1.jar

import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer
import org.apache.flink.streaming.util.serialization.SimpleStringSchema
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase
import java.util.Properties

val properties = new Properties()
properties.setProperty("bootstrap.servers", "localhost:9092")
properties.setProperty("group.id", "test")
var stream = senv.addSource(new FlinkKafkaConsumer[String]("topic", new SimpleStringSchema(), properties)).print()

之后，最后一条语句我收到以下错误：

scala> var stream = senv.addSource(new FlinkKafkaConsumer[String]("topic", new SimpleStringSchema(), properties)).print()
<console>:69: error: overloaded method value addSource with alternatives:
  [T](function: org.apache.flink.streaming.api.functions.source.SourceFunction.SourceContext[T] => Unit)(implicit evidence$10: org.apache.flink.api.common.typeinfo.TypeInformation[T])org.apache.flink.streaming.api.scala.DataStream[T] <and>
  [T](function: org.apache.flink.streaming.api.functions.source.SourceFunction[T])(implicit evidence$9: org.apache.flink.api.common.typeinfo.TypeInformation[T])org.apache.flink.streaming.api.scala.DataStream[T]
 cannot be applied to (org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer[String])
   var stream = senv.addSource(new FlinkKafkaConsumer[String]("topic", new SimpleStringSchema(), properties)).print()

我创建了名为“topic”的主题，并且能够通过另一个客户端正确地生成和读取消息。我正在使用 java 版本 1.8.0_201 并按照https://ci.apache.org/projects/flink/flink-docs-stable/dev/connectors/kafka.html的说明进行操作。

任何可能出现问题的帮助？

4

2 回答 2

2

一些依赖项隐含地需要其他依赖项。我们通常使用一些依赖管理器，如maven或sbt，当我们在项目中添加一些依赖项时，依赖管理器会在后台提供其隐式依赖项。

另一方面，当你使用没有依赖管理器的 shell 时，你负责提供你的代码依赖。使用 Flink Kafka 连接器明确需要Flink Connector Kafkajar，但您应该注意到它也Flink Connector Kafka需要一些依赖项。您可以在页面底部找到它的依赖项，位于Compile Dependencies部分。FLINK_HOME/lib所以从这个前言开始，我在目录（Flink 类路径）中添加了以下 jar 文件：

flink-connector-kafka-0.11_2.11-1.4.2.jar
flink-connector-kafka-0.10_2.11-1.4.2.jar    
flink-connector-kafka-0.9_2.11-1.4.2.jar   
flink-connector-kafka-base_2.11-1.4.2.jar  
flink-core-1.4.2.jar                                         
kafka_2.11-2.1.1.jar
kafka-clients-2.1.0.jar

我可以在 Flink shell 中使用以下代码成功地使用 Kafka 消息：

scala> import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer011
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer011

scala> import org.apache.flink.streaming.util.serialization.SimpleStringSchema
import org.apache.flink.streaming.util.serialization.SimpleStringSchema

scala> import java.util.Properties
import java.util.Properties

scala> val properties = new Properties()
properties: java.util.Properties = {}

scala> properties.setProperty("bootstrap.servers", "localhost:9092")
res0: Object = null

scala> properties.setProperty("group.id", "test")
res1: Object = null

scala> val stream = senv.addSource(new FlinkKafkaConsumer011[String]("topic", new SimpleStringSchema(), properties)).print()
warning: there was one deprecation warning; re-run with -deprecation for details
stream: org.apache.flink.streaming.api.datastream.DataStreamSink[String] = org.apache.flink.streaming.api.datastream.DataStreamSink@71de1091

scala> senv.execute("Kafka Consumer Test")
Submitting job with JobID: 23e3bb3466d914a2747ae5fed293a076. Waiting for job completion.
Connected to JobManager at Actor[akka.tcp://flink@localhost:40093/user/jobmanager#1760995711] with leader session id 00000000-0000-0000-0000-000000000000.
03/11/2019 21:42:39 Job execution switched to status RUNNING.
03/11/2019 21:42:39 Source: Custom Source -> Sink: Unnamed(1/1) switched to SCHEDULED 
03/11/2019 21:42:39 Source: Custom Source -> Sink: Unnamed(1/1) switched to SCHEDULED 
03/11/2019 21:42:39 Source: Custom Source -> Sink: Unnamed(1/1) switched to DEPLOYING 
03/11/2019 21:42:39 Source: Custom Source -> Sink: Unnamed(1/1) switched to DEPLOYING 
03/11/2019 21:42:39 Source: Custom Source -> Sink: Unnamed(1/1) switched to RUNNING 
03/11/2019 21:42:39 Source: Custom Source -> Sink: Unnamed(1/1) switched to RUNNING 
hello
hello

此外，将一些 jar 文件添加到 Flink 类路径的另一种方法是将 jar 作为 Flink shell 启动命令的参数传递：

bin/start-scala-shell.sh local "--addclasspath <path/to/jar.jar>"

测试环境：

Flink 1.4.2
Kafka 2.1.0
Java  1.8 201
Scala 2.11
于 2019-03-11T18:39:36.587 回答
0

很可能您应该在添加源之前导入 Flink 的 Scala 隐式：

import org.apache.flink.streaming.api.scala._
于 2019-03-11T09:07:30.660 回答