Apache spark apachespark与Kafka的集成
我正在学习Udemy上关于卡夫卡和Spark的课程,我正在学习apache Spark与卡夫卡的集成 下面是ApacheSpark的代码Apache spark apachespark与Kafka的集成,apache-spark,apache-kafka,spark-structured-streaming,spark-kafka-integration,Apache Spark,Apache Kafka,Spark Structured Streaming,Spark Kafka Integration,我正在学习Udemy上关于卡夫卡和Spark的课程,我正在学习apache Spark与卡夫卡的集成 下面是ApacheSpark的代码 SparkSession session=SparkSession.builder().appName(“KafkaConsumer”).master(“local[*]).getOrCreate(); session.sparkContext().setLogLevel(“错误”); 数据集df=会话 .readStream() .格式(“卡夫卡”) .op
SparkSession session=SparkSession.builder().appName(“KafkaConsumer”).master(“local[*]).getOrCreate();
session.sparkContext().setLogLevel(“错误”);
数据集df=会话
.readStream()
.格式(“卡夫卡”)
.option(“kafka.bootstrap.servers”,“localhost:9092”)
.option(“订阅”、“第二个主题”).load();
df.show();
下面是pom.xml文件的内容
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>com.example.kafka.spark</groupId>
<artifactId>Kafka-Spark-Integration-Code</artifactId>
<version>0.0.1-SNAPSHOT</version>
<dependencies>
<!-- https://mvnrepository.com/artifact/org.apache.spark/spark-core -->
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.12</artifactId>
<version>3.0.0</version>
</dependency>
<!-- https://mvnrepository.com/artifact/org.apache.spark/spark-sql -->
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.12</artifactId>
<version>3.0.0</version>
</dependency>
<!-- https://mvnrepository.com/artifact/org.apache.spark/spark-streaming -->
<!-- <dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming_2.12</artifactId>
<version>3.0.0</version>
</dependency> -->
<!-- https://mvnrepository.com/artifact/org.apache.spark/spark-sql-kafka-0-10 -->
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql-kafka-0-10_2.12</artifactId>
<version>3.0.0</version>
</dependency>
</dependencies>
</project>
4.0.0
com.example.kafka.spark
卡夫卡火花集成码
0.0.1-快照
org.apache.spark
spark-core_2.12
3.0.0
org.apache.spark
spark-sql_2.12
3.0.0
org.apache.spark
spark-sql-kafka-0-10_2.12
3.0.0
然而,当我运行代码时,我发现下面的错误我无法解决。我在MX Linux上使用openjdk 8和spark 3。谢谢
exception in thread "main" java.lang.ClassFormatError: Invalid code attribute name index 24977 in class file org/apache/spark/sql/execution/columnar/InMemoryRelation
at java.lang.ClassLoader.defineClass1(Native Method)
at java.lang.ClassLoader.defineClass(ClassLoader.java:756)
at java.security.SecureClassLoader.defineClass(SecureClassLoader.java:142)
at java.net.URLClassLoader.defineClass(URLClassLoader.java:468)
at java.net.URLClassLoader.access$100(URLClassLoader.java:74)
at java.net.URLClassLoader$1.run(URLClassLoader.java:369)
at java.net.URLClassLoader$1.run(URLClassLoader.java:363)
at java.security.AccessController.doPrivileged(Native Method)
at java.net.URLClassLoader.findClass(URLClassLoader.java:362)
at java.lang.ClassLoader.loadClass(ClassLoader.java:418)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:352)
at java.lang.ClassLoader.loadClass(ClassLoader.java:351)
at org.apache.spark.sql.internal.SharedState.<init>(SharedState.scala:83)
at org.apache.spark.sql.SparkSession.$anonfun$sharedState$1(SparkSession.scala:132)
at scala.Option.getOrElse(Option.scala:189)
at org.apache.spark.sql.SparkSession.sharedState$lzycompute(SparkSession.scala:132)
at org.apache.spark.sql.SparkSession.sharedState(SparkSession.scala:131)
at org.apache.spark.sql.internal.BaseSessionStateBuilder.build(BaseSessionStateBuilder.scala:323)
at org.apache.spark.sql.SparkSession$.org$apache$spark$sql$SparkSession$$instantiateSessionState(SparkSession.scala:1107)
at org.apache.spark.sql.SparkSession.$anonfun$sessionState$2(SparkSession.scala:157)
at scala.Option.getOrElse(Option.scala:189)
at org.apache.spark.sql.SparkSession.sessionState$lzycompute(SparkSession.scala:155)
at org.apache.spark.sql.SparkSession.sessionState(SparkSession.scala:152)
at org.apache.spark.sql.streaming.DataStreamReader.<init>(DataStreamReader.scala:519)
at org.apache.spark.sql.SparkSession.readStream(SparkSession.scala:657)
at example.code.spark.kafka.KafkaSparkConsumer.main(KafkaSparkConsumer.java:19)
线程“main”java.lang.ClassFormatError中出现异常:类文件org/apache/spark/sql/execution/columnar/InMemoryRelation中的代码属性名称索引24977无效
位于java.lang.ClassLoader.defineClass1(本机方法)
位于java.lang.ClassLoader.defineClass(ClassLoader.java:756)
位于java.security.SecureClassLoader.defineClass(SecureClassLoader.java:142)
位于java.net.URLClassLoader.defineClass(URLClassLoader.java:468)
在java.net.URLClassLoader.access$100(URLClassLoader.java:74)
在java.net.URLClassLoader$1.run(URLClassLoader.java:369)
在java.net.URLClassLoader$1.run(URLClassLoader.java:363)
位于java.security.AccessController.doPrivileged(本机方法)
位于java.net.URLClassLoader.findClass(URLClassLoader.java:362)
位于java.lang.ClassLoader.loadClass(ClassLoader.java:418)
位于sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:352)
位于java.lang.ClassLoader.loadClass(ClassLoader.java:351)
位于org.apache.spark.sql.internal.SharedState。(SharedState.scala:83)
位于org.apache.spark.sql.SparkSession.$anonfun$sharedState$1(SparkSession.scala:132)
位于scala.Option.getOrElse(Option.scala:189)
位于org.apache.spark.sql.SparkSession.sharedState$lzycompute(SparkSession.scala:132)
位于org.apache.spark.sql.SparkSession.sharedState(SparkSession.scala:131)
位于org.apache.spark.sql.internal.BaseSessionStateBuilder.build(BaseSessionStateBuilder.scala:323)
位于org.apache.spark.sql.SparkSession$.org$apache$spark$sql$SparkSession$$instantiateSessionState(SparkSession.scala:1107)
位于org.apache.spark.sql.SparkSession.$anonfun$sessionState$2(SparkSession.scala:157)
位于scala.Option.getOrElse(Option.scala:189)
位于org.apache.spark.sql.SparkSession.sessionState$lzycompute(SparkSession.scala:155)
位于org.apache.spark.sql.SparkSession.sessionState(SparkSession.scala:152)
位于org.apache.spark.sql.streaming.DataStreamReader。(DataStreamReader.scala:519)
位于org.apache.spark.sql.SparkSession.readStream(SparkSession.scala:657)
例如.code.spark.kafka.kafkasparakconsumer.main(kafkasparakconsumer.java:19)
您可以按照以下示例进行操作:
SparkSession session=SparkSession.builder()
.appName(“卡夫卡消费者”)
.master(“本地[*]”)
.getOrCreate();
数据集df=spark
.readStream()
.格式(“卡夫卡”)
.option(“kafka.bootstrap.servers”,“localhost:9092”)
.选项(“订阅”、“第二个主题”)
.load()
.selectExpr(“转换(键为字符串)”,“转换(值为字符串)”;
使用数据。显示了如何将数据打印到控制台:
StreamingQuery=df
.writeStream()
.格式(“控制台”)
.outputMode(“追加”)
.选项(“检查点位置”、“路径/到/检查点/目录”)
.start();
query.waittermination();
谢谢。我尝试了上面的代码,但出现了相同的错误。我在windows计算机上尝试了相同的示例,但失败了,出现了不同的错误(未找到kafka依赖项),但传递了上述代码的readStream方法。我想知道它是否与我在linux机器上运行的java版本或环境有关?是的,我能够运行非常基本的spark代码。我使用eclipse并运行eclipse中的代码。这是我第一次尝试流媒体应用程序,所以我不知道发生了什么,尽管我在两个环境(windows和linux)中都有相同的pom.xml文件,所以我相信依赖项是相同的。因此我卸载了openjdk 8并从oracle安装了java,它开始工作。然而,现在我的流媒体工作刚刚退出。我想我会一直跑。你确定要打电话询问吗?谢谢,我错过了。非常感谢你。它解决了这个问题。