java.lang.IllegalArgumentException: requirement failed: Column features must be of type org.apache.spark.mllib.linalg.VectorUDT@f71b0bce but was actually org.apache.spark.ml.linalg.VectorUDT@3bfc3ba7.

2016-10-17 11:39:13   作者：MangoCool   来源：MangoCool

在上一个例子中，关于Spark-2.0.1 GaussianMixture示例代码，原本spark是2.0.0版本的，但是该例子只要将操作设置到pipeline的stage中执行，就会报错：

Exception in thread "main" java.lang.IllegalArgumentException: requirement failed: Column features must be of type org.apache.spark.mllib.linalg.VectorUDT@f71b0bce but was actually org.apache.spark.ml.linalg.VectorUDT@3bfc3ba7.
	at scala.Predef$.require(Predef.scala:224)
	at org.apache.spark.ml.util.SchemaUtils$.checkColumnType(SchemaUtils.scala:42)
	at org.apache.spark.ml.clustering.GaussianMixtureParams$class.validateAndTransformSchema(GaussianMixture.scala:64)
	at org.apache.spark.ml.clustering.GaussianMixture.validateAndTransformSchema(GaussianMixture.scala:275)
	at org.apache.spark.ml.clustering.GaussianMixture.transformSchema(GaussianMixture.scala:342)
	at org.apache.spark.ml.Pipeline$$anonfun$transformSchema$4.apply(Pipeline.scala:180)
	at org.apache.spark.ml.Pipeline$$anonfun$transformSchema$4.apply(Pipeline.scala:180)
	at scala.collection.IndexedSeqOptimized$class.foldl(IndexedSeqOptimized.scala:57)
	at scala.collection.IndexedSeqOptimized$class.foldLeft(IndexedSeqOptimized.scala:66)
	at scala.collection.mutable.ArrayOps$ofRef.foldLeft(ArrayOps.scala:186)
	at org.apache.spark.ml.Pipeline.transformSchema(Pipeline.scala:180)
	at org.apache.spark.ml.PipelineStage.transformSchema(Pipeline.scala:70)
	at org.apache.spark.ml.Pipeline.fit(Pipeline.scala:132)
	at com.dtxy.xbdp.widget.algorithm.GaussianMixtureWidget.fit(GaussianMixtureWidget.scala:64)
	at com.dtxy.xbdp.test.GaussianMixtureWidgetTest$.main(GaussianMixtureWidgetTest.scala:105)
	at com.dtxy.xbdp.test.GaussianMixtureWidgetTest.main(GaussianMixtureWidgetTest.scala)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:498)
	at com.intellij.rt.execution.application.AppMain.main(AppMain.java:147)

也就是在数据构造Vector向量后，发现并不是后面所要的，所以在checkColumnType中报错了。即便你是构造出mllib包下的VectorUDT，也不行，依然报错：

VectorAssembler does not support the org.apache.spark.mllib.linalg.VectorUDT@f71b0bce type

看到这个错，估计你有点手足无措了，没办法只能看源码了，先找到报错位置：

然后往上一层看，看看在checkColumnType这个方法里面，传参datatype是什么类型的：

看到这里总算是明白了，原来在调用的时候构造了一个OldVectorUDT，怪不得报错类型不对，这算是spark-2.0.0的一个bug吧。

google了一下，发现spark-2.0.1版和spark-2.0.0版的对比：

发现最新版本spark-2.0.1已经对该bug做了修复，总算是轮不到自己改源码，hoho。

更多对比参考：http://fossies.org/diffs/spark/2.0.0_vs_2.0.1/mllib/src/main/scala/org/apache/spark/ml/clustering/GaussianMixture.scala-diff.html

最后提示一下，解决该问题的办法：升级版本到spark-2.0.1，感谢浏览，欢迎交流！

标签： spark VectorUDT error

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