Question

数据源来自Databricks Notebook演示：Five Spark SQL Helper Utility Functions to Extract and Explore Complex Data Types！

但是当我在自己的笔记本电脑上试用这些代码时，我总是会遇到错误。

首先，将JSON数据加载为DataFrame

res2: org.apache.spark.sql.DataFrame = [battery_level: string, c02_level: string]

scala> res2.show

+-------------+---------+
|battery_level|c02_level|
+-------------+---------+
|            7|      886|
|            5|     1378|
|            8|      917|
|            8|     1504|
|            8|      831|
|            9|     1304|
|            8|     1574|
|            9|     1208|
+-------------+---------+

其次，write数据到Kafka：

res2.write 
  .format("kafka") 
  .option("kafka.bootstrap.servers", "localhost:9092") 
  .option("topic", "test") 
  .save()

所有这些都遵循上面的笔记本演示和官方steps

但错误显示：

scala> res2.write 
         .format("kafka") 
         .option("kafka.bootstrap.servers", "localhost:9092") 
         .option("topic", "iot-devices") 
         .save()

org.apache.spark.sql.AnalysisException: Required attribute 'value' not found;
  at org.apache.spark.sql.kafka010.KafkaWriter$$anonfun$6.apply(KafkaWriter.scala:72)
  at org.apache.spark.sql.kafka010.KafkaWriter$$anonfun$6.apply(KafkaWriter.scala:72)
  at scala.Option.getOrElse(Option.scala:121)
  at org.apache.spark.sql.kafka010.KafkaWriter$.validateQuery(KafkaWriter.scala:71)
  at org.apache.spark.sql.kafka010.KafkaWriter$.write(KafkaWriter.scala:87)
  at org.apache.spark.sql.kafka010.KafkaSourceProvider.createRelation(KafkaSourceProvider.scala:165)
  at org.apache.spark.sql.execution.datasources.DataSource.write(DataSource.scala:472)
  at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:48)
  at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:58)
  at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:56)
  at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
  at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
  at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
  at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:138)
  at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
  at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:135)
  at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:116)
  at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:92)
  at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:92)
  at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:610)
  at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:233)
  ... 52 elided

我认为它可能是Kafka问题，然后我从Kafka测试DataFrame read以确保连接：

scala> val kaDF = spark.read
         .format("kafka") 
         .option("kafka.bootstrap.servers", "localhost:9092") 
         .option("subscribe", "iot-devices") 
         .load()
kaDF: org.apache.spark.sql.DataFrame = [key: binary, value: binary ... 5 more fields]

scala> kaDF.show

+----+--------------------+-----------+---------+------+--------------------+-------------+
| key|               value|      topic|partition|offset|           timestamp|timestampType|
+----+--------------------+-----------+---------+------+--------------------+-------------+
|null|    [73 73 73 73 73]|iot-devices|        0|     0|2017-09-27 11:11:...|            0|
|null|[64 69 63 6B 20 3...|iot-devices|        0|     1|2017-09-27 11:29:...|            0|
|null|       [78 69 78 69]|iot-devices|        0|     2|2017-09-27 11:29:...|            0|
|null|[31 20 32 20 33 2...|iot-devices|        0|     3|2017-09-27 11:30:...|            0|
+----+--------------------+-----------+---------+------+--------------------+-------------+

因此，结果显示在主题＆＃34; iot-devices＆＃34;中读取数据。来自Kafka bootstrap.servers localhost:9092确实有用。

我在网上搜索了很多，但还是无法解决它？

任何拥有Spark SQL经验的人都可以告诉我我的命令有什么问题吗？

谢谢！

Answer 1

错误消息清楚地显示问题的根源：

org.apache.spark.sql.AnalysisException：找不到必需的属性'value';

要写的<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="1000" height="400"> <path id="path" stroke-width="20"/> </svg> has to have at least value column（以及可选的Sub YourSub() On Error GoTo ErrHandler: Application.EnableCancelKey = xlErrorHandler ' You code goes here ErrHandler: With Err If .Number <> 18 Then .Raise .Number, .Source, .Description, .HelpFile, .HelpContext End If End With Application.Calculation = xlCalculationAutomatic End Sub和Dataset）和key只有topic，{{1} }。

您可以例如：

res2

Spark 2.2.0独立模式将Dataframe写入本地单节点Kafka时出错

1 个答案: