2017-04-24 49 views
0

我是PySpark(Spark 2.1.0和python 3.5)中的noobie,我遇到了一個我無法通過的問題。PySpark中的GeoText和UDF

我嘗試使用UDF GeoText,這裏是我的代碼:

def countries(x): 
    count = GeoText(x).countries 
    w = '' 
    if not count: 
     return '' 
    else: 
     for country in count: 
      w += country 
     return w 

而且我創建一個UDF:

udfCountry=udf(countries, StringType()) 

然後我嘗試使用:

df2 = df.withColumn('country',udfCountry(df2.Location)) 

但運行任何SQL條件,如eg這樣的:

df2.where(df2.country == 'a').show() 

導致此堆棧跟蹤:

--------------------------------------------------------------------------- 
Py4JJavaError        Traceback (most recent call last) 
<ipython-input-194-84c9636e0170> in <module>() 
     1 #df3.select(df3.country,df3.cities,df3._Location).where(df3.country!='').take(10) 
----> 2 df4.where(df4.country == 'a').show() 

/opt/spark-2.1.0/python/pyspark/sql/dataframe.py in show(self, n, truncate) 
    316   """ 
    317   if isinstance(truncate, bool) and truncate: 
--> 318    print(self._jdf.showString(n, 20)) 
    319   else: 
    320    print(self._jdf.showString(n, int(truncate))) 

/opt/spark-2.1.0/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py in __call__(self, *args) 
    1131   answer = self.gateway_client.send_command(command) 
    1132   return_value = get_return_value(
-> 1133    answer, self.gateway_client, self.target_id, self.name) 
    1134 
    1135   for temp_arg in temp_args: 

/opt/spark-2.1.0/python/pyspark/sql/utils.py in deco(*a, **kw) 
    61  def deco(*a, **kw): 
    62   try: 
---> 63    return f(*a, **kw) 
    64   except py4j.protocol.Py4JJavaError as e: 
    65    s = e.java_exception.toString() 

/opt/spark-2.1.0/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name) 
    317     raise Py4JJavaError(
    318      "An error occurred while calling {0}{1}{2}.\n". 
--> 319      format(target_id, ".", name), value) 
    320    else: 
    321     raise Py4JError(

Py4JJavaError: An error occurred while calling o3116.showString. 
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 79.0 failed 1 times, most recent failure: Lost task 0.0 in stage 79.0 (TID 79, localhost, executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last): 
    File "/opt/spark-2.1.0/python/lib/pyspark.zip/pyspark/worker.py", line 174, in main 
    process() 
    File "/opt/spark-2.1.0/python/lib/pyspark.zip/pyspark/worker.py", line 169, in process 
    serializer.dump_stream(func(split_index, iterator), outfile) 
    File "/opt/spark-2.1.0/python/lib/pyspark.zip/pyspark/serializers.py", line 220, in dump_stream 
    self.serializer.dump_stream(self._batched(iterator), stream) 
    File "/opt/spark-2.1.0/python/lib/pyspark.zip/pyspark/serializers.py", line 138, in dump_stream 
    for obj in iterator: 
    File "/opt/spark-2.1.0/python/lib/pyspark.zip/pyspark/serializers.py", line 209, in _batched 
    for item in iterator: 
    File "/opt/spark-2.1.0/python/lib/pyspark.zip/pyspark/worker.py", line 92, in <lambda> 
    mapper = lambda a: udf(*a) 
    File "/opt/spark-2.1.0/python/lib/pyspark.zip/pyspark/worker.py", line 70, in <lambda> 
    return lambda *a: f(*a) 
    File "<ipython-input-191-27c9af37cc7f>", line 2, in countries 
    File "/opt/anaconda3/lib/python3.5/site-packages/geotext/geotext.py", line 107, in __init__ 
    candidates = re.findall(city_regex, text) 
    File "/opt/anaconda3/lib/python3.5/re.py", line 213, in findall 
    return _compile(pattern, flags).findall(string) 
TypeError: expected string or bytes-like object 

    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193) 
    at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234) 
    at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152) 
    at org.apache.spark.sql.execution.python.BatchEvalPythonExec$$anonfun$doExecute$1.apply(BatchEvalPythonExec.scala:144) 
    at org.apache.spark.sql.execution.python.BatchEvalPythonExec$$anonfun$doExecute$1.apply(BatchEvalPythonExec.scala:87) 
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:796) 
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:796) 
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) 
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) 
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) 
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) 
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) 
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) 
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) 
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) 
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) 
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) 
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) 
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) 
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) 
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) 
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) 
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) 
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) 
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) 
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) 
    at org.apache.spark.scheduler.Task.run(Task.scala:99) 
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282) 
    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:745) 

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:1918) 
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1931) 
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1944) 
    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$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2371) 
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57) 
    at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2765) 
    at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2370) 
    at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2377) 
    at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2113) 
    at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2112) 
    at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2795) 
    at org.apache.spark.sql.Dataset.head(Dataset.scala:2112) 
    at org.apache.spark.sql.Dataset.take(Dataset.scala:2327) 
    at org.apache.spark.sql.Dataset.showString(Dataset.scala:248) 
    at sun.reflect.GeneratedMethodAccessor65.invoke(Unknown Source) 
    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:745) 
Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last): 
    File "/opt/spark-2.1.0/python/lib/pyspark.zip/pyspark/worker.py", line 174, in main 
    process() 
    File "/opt/spark-2.1.0/python/lib/pyspark.zip/pyspark/worker.py", line 169, in process 
    serializer.dump_stream(func(split_index, iterator), outfile) 
    File "/opt/spark-2.1.0/python/lib/pyspark.zip/pyspark/serializers.py", line 220, in dump_stream 
    self.serializer.dump_stream(self._batched(iterator), stream) 
    File "/opt/spark-2.1.0/python/lib/pyspark.zip/pyspark/serializers.py", line 138, in dump_stream 
    for obj in iterator: 
    File "/opt/spark-2.1.0/python/lib/pyspark.zip/pyspark/serializers.py", line 209, in _batched 
    for item in iterator: 
    File "/opt/spark-2.1.0/python/lib/pyspark.zip/pyspark/worker.py", line 92, in <lambda> 
    mapper = lambda a: udf(*a) 
    File "/opt/spark-2.1.0/python/lib/pyspark.zip/pyspark/worker.py", line 70, in <lambda> 
    return lambda *a: f(*a) 
    File "<ipython-input-191-27c9af37cc7f>", line 2, in countries 
    File "/opt/anaconda3/lib/python3.5/site-packages/geotext/geotext.py", line 107, in __init__ 
    candidates = re.findall(city_regex, text) 
    File "/opt/anaconda3/lib/python3.5/re.py", line 213, in findall 
    return _compile(pattern, flags).findall(string) 
TypeError: expected string or bytes-like object 

    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193) 
    at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234) 
    at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152) 
    at org.apache.spark.sql.execution.python.BatchEvalPythonExec$$anonfun$doExecute$1.apply(BatchEvalPythonExec.scala:144) 
    at org.apache.spark.sql.execution.python.BatchEvalPythonExec$$anonfun$doExecute$1.apply(BatchEvalPythonExec.scala:87) 
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:796) 
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:796) 
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) 
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) 
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) 
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) 
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) 
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) 
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) 
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) 
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) 
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) 
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) 
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) 
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) 
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) 
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) 
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) 
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) 
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) 
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) 
    at org.apache.spark.scheduler.Task.run(Task.scala:99) 
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282) 
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) 
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) 
    ... 1 more 

我已經發現,改變自己的UDF功能是這樣的:

def countries(x): 
     #count = GeoText(x).countries 
     count = 'a' 
     w = '' 
     if not count: 
      return '' 
     else: 
      for country in count: 
       w += country 
      return w 

原因它的工作。

有人能解釋爲什麼會發生這種情況嗎?我能做些什麼來使它工作?

編輯

有趣的事情 - 當我保存我的數據幀,以實木複合地板,然後再次讀取,一切正常......

+0

你的輸入是什麼。在geotext中看起來像'candidates = re.findall(city_regex,text)'失敗。 – Pushkr

+0

嗯我不知道你是什麼意思 - 但這是從Stackoverflow轉儲位置 – PastorPL

回答

0

最後我發現,部分輸入的是無。做一些「nullcheck」處理問題,一切都開始像魅力一樣工作。