python - PySpark ML Pipeline.load 结果抛出 java.lang.UnsupportedOperationException : empty collection

Question

我有一个适合 PySpark 的管道，我正在将其保存到磁盘以备后用。

这是我的管道代码:

model  = Pipeline(stages=[segment_indexer, model_name_indexer, make_name_indexer, engine_type_indexer, segment_encoder, model_name_incoder, make_name_incoder, engine_type_incoder, x_assembler, estimator]).fit(trainingData)
model.save('file:/opt/app/fitted-model' )

这会将模型保存到磁盘。

我正在尝试像这样加载模型

model2 = pyspark.ml.pipeline.PipelineModel.load("file:/tmp/mymodels/fitted-model")

抛出

Traceback (most recent call last):

File "<stdin>", line 1, in <module>
  File "/usr/lib/spark/python/pyspark/ml/util.py", line 257, in load
    return cls.read().load(path)
  File "/usr/lib/spark/python/pyspark/ml/util.py", line 197, in load
    java_obj = self._jread.load(path)
  File "/usr/lib/spark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py", line 1133, in __call__
  File "/usr/lib/spark/python/pyspark/sql/utils.py", line 63, in deco
    return f(*a, **kw)
  File "/usr/lib/spark/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py", line 319, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o2760.load.
: java.lang.UnsupportedOperationException: empty collection
    at org.apache.spark.rdd.RDD$$anonfun$first$1.apply(RDD.scala:1370)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
    at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
    at org.apache.spark.rdd.RDD.first(RDD.scala:1367)
    at org.apache.spark.ml.util.DefaultParamsReader$.loadMetadata(ReadWrite.scala:382)
    at org.apache.spark.ml.Pipeline$SharedReadWrite$.load(Pipeline.scala:266)
    at org.apache.spark.ml.PipelineModel$PipelineModelReader.load(Pipeline.scala:347)
    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 py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    at py4j.Gateway.invoke(Gateway.java:280)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:214)
    at java.lang.Thread.run(Thread.java:748)

我做错了什么？

`

Answer 1

我必须执行 pipeline.transform 以便管道在保存之前实际对数据帧应用转换。这样做之后，加载模型会带回模型实例，然后我们可以在数据帧上再次应用 transform 。