python - Spark VectorAssembler 错误 - PySpark 2.3 - Python

Question

我正在使用 pySpark 2.3.0，并创建了一个非常简单的 Spark 数据帧来测试 VectorAssembler 的功能。这是较大数据框的子集，其中我只选择了一些数字( double 据类型)列:

>>>cols = ['index','host_listings_count','neighbourhood_group_cleansed',\
        'bathrooms','bedrooms','beds','square_feet', 'guests_included',\
        'review_scores_rating']
>>>test = df[cols]
>>>test.take(3)

[Row(index=0, host_listings_count=1, neighbourhood_group_cleansed=None, bathrooms=1.5, bedrooms=2.0, beds=3.0, square_feet=None, guests_included=1, review_scores_rating=100.0), Row(index=1, host_listings_count=1, neighbourhood_group_cleansed=None, bathrooms=1.5, bedrooms=2.0, beds=3.0, square_feet=None, guests_included=1, review_scores_rating=100.0), Row(index=2, host_listings_count=1, neighbourhood_group_cleansed=None, bathrooms=1.5, bedrooms=2.0, beds=3.0, square_feet=None, guests_included=1, review_scores_rating=100.0)]

从上面我看来，这个 Spark 数据帧没有任何问题。因此，我创建了如下所示的汇编器并得到了显示的错误。可能出了什么问题？

>>>from pyspark.ml.feature import VectorAssembler
>>>assembler = VectorAssembler(inputCols=cols, outputCol="features")
>>>output = assembler.transform(test)
>>>output.take(3)

Py4JJavaError: An error occurred while calling o279.collectToPython. : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 5.0 failed 1 times, most recent failure: Lost task 0.0 in stage 5.0 (TID 10, localhost, executor driver): org.apache.spark.SparkException: Failed to execute user defined function($anonfun$3: (struct) => vector) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377) at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:231) at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:225) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:827) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:827) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) at org.apache.spark.scheduler.Task.run(Task.scala:99) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) at java.lang.Thread.run(Thread.java:748) Caused by: org.apache.spark.SparkException: Values to assemble cannot be null. at org.apache.spark.ml.feature.VectorAssembler$$anonfun$assemble$1.apply(VectorAssembler.scala:160) at org.apache.spark.ml.feature.VectorAssembler$$anonfun$assemble$1.apply(VectorAssembler.scala:143) at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33) at scala.collection.mutable.WrappedArray.foreach(WrappedArray.scala:35) at org.apache.spark.ml.feature.VectorAssembler$.assemble(VectorAssembler.scala:143) at org.apache.spark.ml.feature.VectorAssembler$$anonfun$3.apply(VectorAssembler.scala:99) at org.apache.spark.ml.feature.VectorAssembler$$anonfun$3.apply(VectorAssembler.scala:98) ... 16 more

Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1435) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802) at scala.Option.foreach(Option.scala:257) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1650) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1605) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1594) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1925) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1938) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1951) at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:333) at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38) at org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply$mcI$sp(Dataset.scala:2768) at org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply(Dataset.scala:2765) at org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply(Dataset.scala:2765) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57) at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2788) at org.apache.spark.sql.Dataset.collectToPython(Dataset.scala:2765) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:498) at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) at py4j.Gateway.invoke(Gateway.java:280) at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) at py4j.commands.CallCommand.execute(CallCommand.java:79) at py4j.GatewayConnection.run(GatewayConnection.java:214) at java.lang.Thread.run(Thread.java:748) Caused by: org.apache.spark.SparkException: Failed to execute user defined function($anonfun$3: (struct) => vector) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377) at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:231) at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:225) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:827) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:827) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) at org.apache.spark.scheduler.Task.run(Task.scala:99) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) ... 1 more Caused by: org.apache.spark.SparkException: Values to assemble cannot be null. at org.apache.spark.ml.feature.VectorAssembler$$anonfun$assemble$1.apply(VectorAssembler.scala:160) at org.apache.spark.ml.feature.VectorAssembler$$anonfun$assemble$1.apply(VectorAssembler.scala:143) at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33) at scala.collection.mutable.WrappedArray.foreach(WrappedArray.scala:35) at org.apache.spark.ml.feature.VectorAssembler$.assemble(VectorAssembler.scala:143) at org.apache.spark.ml.feature.VectorAssembler$$anonfun$3.apply(VectorAssembler.scala:99) at org.apache.spark.ml.feature.VectorAssembler$$anonfun$3.apply(VectorAssembler.scala:98) ... 16 more

Answer 1

您发布的堆栈跟踪提到问题是由正在组装的列中的空值引起的。

您需要处理 cols 列中的 null 值。在调用转换之前尝试 test.fillna(0,subset=cols)，或者过滤掉这些列中包含空值的行。