为什么 "java.lang.ClassNotFoundException: Failed to find data source: kinesis" 具有 spark-streaming-kinesis-asl 依赖性?
Why "java.lang.ClassNotFoundException: Failed to find data source: kinesis" with spark-streaming-kinesis-asl dependency?
我的设置:
scala:2.11.8
spark:2.3.0.cloudera4
我已经在我的 .pom
文件中添加了:
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming-kinesis-asl_2.11</artifactId>
<version>2.3.0</version>
</dependency>
但是,当我 运行 我的 spark 流代码使用来自 kinesis 的数据时,它 returns:
Exception in thread "main" java.lang.ClassNotFoundException: Failed to find data source: kinesis.
我在使用来自Kafka
的数据时遇到了类似的错误,并通过在提交命令中指明依赖的jar 解决了它。不过这次好像不行了:
sudo -u hdfs spark2-submit --packages org.apache.spark:spark-streaming-kinesis-asl_2.11:2.3.0 --class com.package.newkinesis --master yarn sparktest-1.0-SNAPSHOT.jar
如何解决这个问题?感谢您的帮助。
我的代码:
val spark = SparkSession
.builder.master("local[4]")
.appName("SpeedTester")
.config("spark.driver.memory", "3g")
.getOrCreate()
val kinesis = spark.readStream
.format("kinesis")
.option("streamName", kinesisStreamName)
.option("endpointUrl", kinesisEndpointUrl)
.option("initialPosition", "TRIM_HORIZON")
.option("awsAccessKey", awsAccessKeyId)
.option("awsSecretKey", awsSecretKey)
.load()
kinesis.writeStream.format("console").start().awaitTermination()
我的完整 .pom
文件:
<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/maven-v4_0_0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>com.netease</groupId>
<artifactId>sparktest</artifactId>
<version>1.0-SNAPSHOT</version>
<inceptionYear>2008</inceptionYear>
<properties>
<scala.version>2.11.8</scala.version>
</properties>
<build>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-shade-plugin</artifactId>
<version>3.2.1</version>
<executions>
<execution>
<goals>
<goal>shade</goal>
</goals>
<configuration>
<includes>
<include>org/apache/spark/*</include>
</includes>
</configuration>
</execution>
</executions>
</plugin>
</plugins>
</build>
<dependencies>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.11</artifactId>
<scope>provided</scope>
<version>2.3.0</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming_2.11</artifactId>
<scope>provided</scope>
<version>2.3.0</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.11</artifactId>
<scope>provided</scope>
<version>2.3.0</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming-kafka-0-10_2.11</artifactId>
<version>2.3.0</version>
</dependency>
<dependency>
<groupId>org.apache.kafka</groupId>
<artifactId>kafka-clients</artifactId>
<version>2.1.0</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming-kinesis-asl_2.11</artifactId>
<version>2.3.0</version>
</dependency>
</dependencies>
</project>
tl;dr 不行。
您使用 spark-streaming-kinesis-asl_2.11
旧版 Spark Streaming 的依赖项 API 和新的 Spark Structured Streaming,因此例外。
您必须为 AWS Kinesis 找到一个兼容的 Spark Structured Streaming 数据源,它不受 Apache Spark 项目的正式支持。
我的设置:
scala:2.11.8
spark:2.3.0.cloudera4
我已经在我的 .pom
文件中添加了:
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming-kinesis-asl_2.11</artifactId>
<version>2.3.0</version>
</dependency>
但是,当我 运行 我的 spark 流代码使用来自 kinesis 的数据时,它 returns:
Exception in thread "main" java.lang.ClassNotFoundException: Failed to find data source: kinesis.
我在使用来自Kafka
的数据时遇到了类似的错误,并通过在提交命令中指明依赖的jar 解决了它。不过这次好像不行了:
sudo -u hdfs spark2-submit --packages org.apache.spark:spark-streaming-kinesis-asl_2.11:2.3.0 --class com.package.newkinesis --master yarn sparktest-1.0-SNAPSHOT.jar
如何解决这个问题?感谢您的帮助。
我的代码:
val spark = SparkSession
.builder.master("local[4]")
.appName("SpeedTester")
.config("spark.driver.memory", "3g")
.getOrCreate()
val kinesis = spark.readStream
.format("kinesis")
.option("streamName", kinesisStreamName)
.option("endpointUrl", kinesisEndpointUrl)
.option("initialPosition", "TRIM_HORIZON")
.option("awsAccessKey", awsAccessKeyId)
.option("awsSecretKey", awsSecretKey)
.load()
kinesis.writeStream.format("console").start().awaitTermination()
我的完整 .pom
文件:
<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/maven-v4_0_0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>com.netease</groupId>
<artifactId>sparktest</artifactId>
<version>1.0-SNAPSHOT</version>
<inceptionYear>2008</inceptionYear>
<properties>
<scala.version>2.11.8</scala.version>
</properties>
<build>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-shade-plugin</artifactId>
<version>3.2.1</version>
<executions>
<execution>
<goals>
<goal>shade</goal>
</goals>
<configuration>
<includes>
<include>org/apache/spark/*</include>
</includes>
</configuration>
</execution>
</executions>
</plugin>
</plugins>
</build>
<dependencies>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.11</artifactId>
<scope>provided</scope>
<version>2.3.0</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming_2.11</artifactId>
<scope>provided</scope>
<version>2.3.0</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.11</artifactId>
<scope>provided</scope>
<version>2.3.0</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming-kafka-0-10_2.11</artifactId>
<version>2.3.0</version>
</dependency>
<dependency>
<groupId>org.apache.kafka</groupId>
<artifactId>kafka-clients</artifactId>
<version>2.1.0</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming-kinesis-asl_2.11</artifactId>
<version>2.3.0</version>
</dependency>
</dependencies>
</project>
tl;dr 不行。
您使用 spark-streaming-kinesis-asl_2.11
旧版 Spark Streaming 的依赖项 API 和新的 Spark Structured Streaming,因此例外。
您必须为 AWS Kinesis 找到一个兼容的 Spark Structured Streaming 数据源,它不受 Apache Spark 项目的正式支持。