Spark Avro在文件写入时引发异常：NoSuchMethodError

Question

任何Avro格式的文件写入尝试都会失败，堆栈跟踪如下。

我们正在使用Spark 2.4.3（使用用户提供的Hadoop）、Scala 2.12，并且我们在运行时使用任一Spark-shell加载Avro包：

org.apache.sparkavro_2

或spark提交：

提交org.apache.sparkavro_2

spark会话报告已成功加载Avro包。

... 在任何一种情况下，当我们尝试将任何数据写入avro格式时，例如：

df.write.format("avro").save("hdfs:///path/to/outputfile.avro")

或选择：

df.select("recordidstring").write.format("avro").save("hdfs:///path/to/outputfile.avro")

... 产生相同的stacktrace错误（此副本来自spark shell）：

java.lang.NoSuchMethodError: org.apache.avro.Schema.createUnion([Lorg/apache/avro/Schema;)Lorg/apache/avro/Schema;
  at org.apache.spark.sql.avro.SchemaConverters$.toAvroType(SchemaConverters.scala:185)
  at org.apache.spark.sql.avro.SchemaConverters$.$anonfun$toAvroType$1(SchemaConverters.scala:176)
  at scala.collection.Iterator.foreach(Iterator.scala:941)
  at scala.collection.Iterator.foreach$(Iterator.scala:941)
  at scala.collection.AbstractIterator.foreach(Iterator.scala:1429)
  at scala.collection.IterableLike.foreach(IterableLike.scala:74)
  at scala.collection.IterableLike.foreach$(IterableLike.scala:73)
  at org.apache.spark.sql.types.StructType.foreach(StructType.scala:99)
  at org.apache.spark.sql.avro.SchemaConverters$.toAvroType(SchemaConverters.scala:174)
  at org.apache.spark.sql.avro.AvroFileFormat.$anonfun$prepareWrite$2(AvroFileFormat.scala:119)
  at scala.Option.getOrElse(Option.scala:138)
  at org.apache.spark.sql.avro.AvroFileFormat.prepareWrite(AvroFileFormat.scala:118)
  at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:103)
  at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:170)
  at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:104)
  at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:102)
  at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:122)
  at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:131)
  at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:155)
  at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
  at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
  at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
  at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80)
  at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80)
  at org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:676)
  at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:78)
  at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
  at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
  at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:676)
  at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:290)
  at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:271)
  at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:229)

我们能够轻松编写其他格式（文本分隔、json、ORC、parquet）。

我们使用HDFS（Hadoop v3.1.2）作为文件存储。

我已经尝试了Avro的不同软件包版本（例如2.11，更低），它们要么会引发相同的错误，要么完全由于不兼容而无法加载。所有Python、Scala（使用shell或Spark-提交）和Java（使用Spark-提交）都会出现此错误。

apache上似乎存在一个未解决的问题。但这已经一岁了，没有任何决议。我碰到了这个问题，但也想知道社区是否有解决方案？非常感谢您的帮助。

Answer 1

伙计，我遇到了与你相同的错误，但我将我的spark版本更新为2.11 2.4.4，问题消失了。

Answer 2

根据链接错误中的注释，您应该指定avro至少具有1.8.0版本，如下所示：

spark-submit --packages org.apache.spark:spark-avro_2.12:2.4.3,org.apache.avro:avro:1.9.2 ...

（你可能也想尝试其他顺序。）

Answer 3

我在最新的Spark上也有同样的异常。当我将以下依赖项添加到pom中时，它消失了。

  <properties>
    ....
    <spark.version>3.1.2</spark.version>
    <avro.version>1.10.2</avro.version>
  </properties>

  <dependencies>
    ....
    <dependency>
      <groupId>org.apache.spark</groupId>
      <artifactId>spark-core_2.12</artifactId>
      <version>${spark.version}</version>
    </dependency>
    <dependency>
      <groupId>org.apache.spark</groupId>
      <artifactId>spark-hive_2.12</artifactId>
      <version>${spark.version}</version>
    </dependency>
    <dependency>
      <groupId>org.apache.spark</groupId>
      <artifactId>spark-avro_2.12</artifactId>
      <version>${spark.version}</version>
    </dependency>
    <dependency>
      <groupId>org.apache.avro</groupId>
      <artifactId>avro</artifactId>
      <version>${avro.version}</version>
    </dependency>
  </dependencies>

在启动应用程序的类路径中，似乎确实缺少所需的依赖项。