我在 Apache spark (pyspark) 中训练了一个逻辑回归模型，并用它来评估一些测试数据......就像这样......
# Split into train and test sets
train, test = data.randomSplit([.8, .2], seed=1337)
# Train a model
model = LogisticRegressionWithLBFGS.train(train)
# Print the coefficients
print(model.weights)
# Evaluate the test data
predictions = test.map(lambda p: (p.label, model.predict(p.features)))
print(predictions.take(100))
# Calculate and print precision and recall
metrics = MulticlassMetrics(predictions)
print("Prediction: %s" % metrics.precision(1))
我的模型系数打印良好，打印预测时我得到了合理的输出:
[(0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (1.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (1.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (1.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (1.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (1.0, 0), (1.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (1.0, 0), (0.0, 0), (0.0, 0), (0.0, 0), (0.0, 0)]
不幸的是，当我调用 metrics.precision(1) 时，我得到了大量的堆栈跟踪。主要错误似乎是“索引 1 处的值为 null”，我不太确定为什么会这样。
顺便说一下，如果我尝试使用 BinaryClassificationMetrics 和 areaUnderPR...
完整的堆栈跟踪如下。
16/03/17 15:00:43 ERROR Executor: Exception in task 5.0 in stage 135.0 (TID 7806)
java.lang.NullPointerException: Value at index 1 in null
at org.apache.spark.sql.Row$class.getAnyValAs(Row.scala:475)
at org.apache.spark.sql.Row$class.getDouble(Row.scala:243)
at org.apache.spark.sql.catalyst.expressions.GenericRow.getDouble(rows.scala:192)
at org.apache.spark.mllib.evaluation.MulticlassMetrics$$anonfun$$init$$1.apply(MulticlassMetrics.scala:41)
at org.apache.spark.mllib.evaluation.MulticlassMetrics$$anonfun$$init$$1.apply(MulticlassMetrics.scala:41)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:191)
at org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:64)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
16/03/17 15:00:43 WARN TaskSetManager: Lost task 5.0 in stage 135.0 (TID 7806, localhost): java.lang.NullPointerException: Value at index 1 in null
at org.apache.spark.sql.Row$class.getAnyValAs(Row.scala:475)
at org.apache.spark.sql.Row$class.getDouble(Row.scala:243)
at org.apache.spark.sql.catalyst.expressions.GenericRow.getDouble(rows.scala:192)
at org.apache.spark.mllib.evaluation.MulticlassMetrics$$anonfun$$init$$1.apply(MulticlassMetrics.scala:41)
at org.apache.spark.mllib.evaluation.MulticlassMetrics$$anonfun$$init$$1.apply(MulticlassMetrics.scala:41)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:191)
at org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:64)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
16/03/17 15:00:43 ERROR TaskSetManager: Task 5 in stage 135.0 failed 1 times; aborting job
16/03/17 15:00:43 WARN PythonRunner: Incomplete task interrupted: Attempting to kill Python Worker
16/03/17 15:00:43 WARN TaskSetManager: Lost task 6.0 in stage 135.0 (TID 7807, localhost): TaskKilled (killed intentionally)
Traceback (most recent call last):
File "/home/osboxes/PycharmProjects/Spark_Test/spark_test.py", line 96, in <module>
print("Prediction: %s" % metrics.precision(1))
File "/srv/spark/python/lib/pyspark.zip/pyspark/mllib/evaluation.py", line 238, in precision
File "/srv/spark/python/lib/pyspark.zip/pyspark/mllib/common.py", line 146, in call
File "/srv/spark/python/lib/pyspark.zip/pyspark/mllib/common.py", line 123, in callJavaFunc
File "/srv/spark/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py", line 813, in __call__
File "/srv/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 45, in deco
File "/srv/spark/python/lib/py4j-0.9-src.zip/py4j/protocol.py", line 308, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o137.precision.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 5 in stage 135.0 failed 1 times, most recent failure: Lost task 5.0 in stage 135.0 (TID 7806, localhost): java.lang.NullPointerException: Value at index 1 in null
at org.apache.spark.sql.Row$class.getAnyValAs(Row.scala:475)
at org.apache.spark.sql.Row$class.getDouble(Row.scala:243)
at org.apache.spark.sql.catalyst.expressions.GenericRow.getDouble(rows.scala:192)
at org.apache.spark.mllib.evaluation.MulticlassMetrics$$anonfun$$init$$1.apply(MulticlassMetrics.scala:41)
at org.apache.spark.mllib.evaluation.MulticlassMetrics$$anonfun$$init$$1.apply(MulticlassMetrics.scala:41)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:191)
at org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:64)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1431)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1419)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1418)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1418)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:799)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1640)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1845)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1858)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1929)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:927)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
at org.apache.spark.rdd.RDD.collect(RDD.scala:926)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$collectAsMap$1.apply(PairRDDFunctions.scala:741)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$collectAsMap$1.apply(PairRDDFunctions.scala:740)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
at org.apache.spark.rdd.PairRDDFunctions.collectAsMap(PairRDDFunctions.scala:740)
at org.apache.spark.mllib.evaluation.MulticlassMetrics.tpByClass$lzycompute(MulticlassMetrics.scala:49)
at org.apache.spark.mllib.evaluation.MulticlassMetrics.tpByClass(MulticlassMetrics.scala:45)
at org.apache.spark.mllib.evaluation.MulticlassMetrics.precision(MulticlassMetrics.scala:106)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
at py4j.Gateway.invoke(Gateway.java:259)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:209)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.NullPointerException: Value at index 1 in null
at org.apache.spark.sql.Row$class.getAnyValAs(Row.scala:475)
at org.apache.spark.sql.Row$class.getDouble(Row.scala:243)
at org.apache.spark.sql.catalyst.expressions.GenericRow.getDouble(rows.scala:192)
at org.apache.spark.mllib.evaluation.MulticlassMetrics$$anonfun$$init$$1.apply(MulticlassMetrics.scala:41)
at org.apache.spark.mllib.evaluation.MulticlassMetrics$$anonfun$$init$$1.apply(MulticlassMetrics.scala:41)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:191)
at org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:64)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
... 1 more
请您参考如下方法:
我刚遇到同样的问题。问题是您的标签的 type - 您的标签是 int 而它们应该是 double。
我重现/遇到了同样的错误:
scoreAndLabels = sc.parallelize([(1,1),(0,0),(1,0),(0,1)])
并通过替换修复它:
scoreAndLabels = sc.parallelize([(1.,1.),(0.,0.),(1.,0.),(0.,1.)])
