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spark几个错误

作者:互联网

一、java.lang.NoSuchMethodError: net.jpountz.lz4.LZ4BlockInputStream.<init>(Ljava/io/InputStream;Z)V

当要将dataframe进行序列化(df.show()或者df.collect())时,报这个错误。

原因是:maven的pom.xml中含有spark 和 kafka。

1.spark2.3用到了lz4-1.3.0.jar,kafka0.9.0.1用到了lz4-1.2.0.jar,而程序运行时使用的是lz4-1.3.0.jar。

2.lz4-1.3.0.jar包中net.jpountz.util.Utils 类中没有checkRange,该方法位于net.jpountz.util.SafeUtils和net.jpountz.util.UnsafeUtils

原文:https://blog.csdn.net/m0_37914799/article/details/84992275  
可以通过:mvn dependency:tree|less查看冲突的包。

解决办法:

通过修改pom.xml中·kafka-client·依赖,exclude掉lz4的依赖

    <dependency>
        <groupId>org.apache.kafka</groupId>
        <artifactId>kafka-clients</artifactId>
        <version>${kafka.version}</version>
        <exclusions>
            <exclusion>
                <groupId>net.jpountz.lz4</groupId>
                <artifactId>lz4</artifactId>
            </exclusion>
        </exclusions>
    </dependency>

二、java.lang.NoSuchMethodError: com.fasterxml.jackson.module.scala.deser.BigDecimalDeserializer$.handledType()Ljava/lang/Class;

原因:这个错误是Hadoop版本的fasterxml版本较低,spark的较高,

解决方法:在maven的pom.xml文件中,记住一定要在</dependencyManagement> </dependencyManagement>中加入以下库。

      <dependency>
        <groupId>com.fasterxml.jackson.module</groupId>
        <artifactId>jackson-module-scala_2.11</artifactId>
        <version>${jackson.version}</version>
      </dependency>
      <dependency>
        <groupId>com.fasterxml.jackson.module</groupId>
        <artifactId>jackson-module-jaxb-annotations</artifactId>
        <version>${jackson.version}</version>
      </dependency>
      <dependency>
        <groupId>com.fasterxml.jackson.core</groupId>
        <artifactId>jackson-databind</artifactId>
        <version>${jackson.version}</version>
      </dependency>
      <dependency>
        <groupId>com.fasterxml.jackson.core</groupId>
        <artifactId>jackson-annotations</artifactId>
        <version>${jackson.version}</version>
      </dependency>

三、java.lang.NoSuchMethodError: io.netty.buffer.PooledByteBufAllocator.metric()Lio/netty/buffer/PooledByteBufAllocatorMetric;

加入:(也是版本不兼容)

      <dependency>
        <groupId>io.netty</groupId>
        <artifactId>netty-all</artifactId>
        <version>4.1.17.Final</version>
      </dependency>

 

四、Error:scalac: Error: org.jetbrains.jps.incremental.scala.remote.ServerException

IDEA中JDK版本和Scala不匹配,我的JDK默认为IDEA自带的JDK12,所以我换成了JDK1.8,就可以了

 

五、java.lang.NoClassDefFoundError: org/scalactic/source/Position

还是版本问题:原来我用的是2.2.1,然后写Scalatest时会报这个错误

import com.google.common.io.Files
import java.io.File

import org.apache.commons.io.FileUtils
import org.apache.spark.sql.Row
import org.apache.spark.sql.test.SharedSparkSession
import org.scalatest.FunSuite

class UrlDmpDataProcessJobTest extends FunSuite with SharedSparkSession  {
  val testDir = new File(".").getCanonicalPath + "/test/url"
  var output: File = _

  override def beforeAll() {
    super.beforeAll()
    output = Files.createTempDir()
  }
  override def afterAll() {
    super.afterAll()
    FileUtils.deleteDirectory(output)
  }


  test("json parse") {
    import testImplicits._
    val jsonFile = testDir + "/dmp-json-data.txt"
    val jsonData = spark.read.json(jsonFile).toDF()
    val jsonDf = jsonData.as[UrlLoadData].filter(_ != null)
    jsonDf.show()
    val outputDf = UrlDmpDataParse.getJsonParseData(spark, jsonDf)
    outputDf.show()
    val urls = outputDf.select("urls").collect()
    val pid = outputDf.select("pid").collect()
    val uid = outputDf.select("uid").collect()
    assert(pid === Array(Row("631"),Row("631")))
    assert(uid === Array(Row("1bd55eb51c80733a994d853b98f46ce1"),Row("f34c9dc9f0b53cdd0972d50445759d45")))
  }


}

解决办法:

    <dependency>
      <groupId>org.scalatest</groupId>
      <artifactId>scalatest_${scala.binary.version}</artifactId>
      <version>3.0.8</version>
      <scope>test</scope>
    </dependency>

 

标签:jackson,val,错误,几个,lz4,import,org,spark
来源: https://www.cnblogs.com/Lee-yl/p/11191378.html