I've got a dataframe with a column looking like this:
display(flight.select("duration").show())
+--------+
|duration|
+--------+
| 15h10m|
| 17h0m|
| 21h25m|
| 14h30m|
| 24h50m|
| 26h10m|
| 14h30m|
| 23h5m|
| 21h30m|
| 11h50m|
| 16h10m|
| 15h15m|
| 21h25m|
| 14h25m|
| 14h40m|
| 16h0m|
| 24h20m|
| 14h30m|
| 14h25m|
| 14h30m|
+--------+
only showing top 20 rows
I need to extract the hour as a number and store it as an additional column
within the same dataframe. What's the best way to do that?
I tried the following, but it failed:
import re
def getHours(x):
return re.match('([0-9]+(?=h))', x)
temp = flight.select("duration").rdd.map(lambda x:getHours(x[0])).toDF()
temp.select("duration").show()
error message:
---------------------------------------------------------------------------Py4JJavaError
Traceback (most recent call
last)<ipython-input-89-1d5bec255302> in <module>() 2 def
getHours(x): 3 return re.match('([0-9]+(?=h))', x)----> 4 temp
= flight.select("duration").rdd.map(lambda x:getHours(x[0])).toDF()
5 temp.select("duration").show()
C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\python\pyspark\sql\session.py
in toDF(self, schema, sampleRatio) 55 [Row(name=u'Alice',
age=1)] 56 """---> 57 return
sparkSession.createDataFrame(self, schema, sampleRatio) 58 59
RDD.toDF = toDF
C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\python\pyspark\sql\session.py
in createDataFrame(self, data, schema, samplingRatio, verifySchema)
518 519 if isinstance(data, RDD):--> 520 rdd,
schema = self._createFromRDD(data.map(prepare), schema, samplingRatio)
521 else: 522 rdd, schema =
self._createFromLocal(map(prepare, data), schema)
C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\python\pyspark\sql\session.py
in _createFromRDD(self, rdd, schema, samplingRatio) 358 """
359 if schema is None or isinstance(schema, (list,
tuple)):--> 360 struct = self._inferSchema(rdd,
samplingRatio) 361 converter =
_create_converter(struct) 362 rdd = rdd.map(converter)
C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\python\pyspark\sql\session.py
in _inferSchema(self, rdd, samplingRatio) 329 :return:
:class:`pyspark.sql.types.StructType` 330 """--> 331
first = rdd.first() 332 if not first: 333
raise ValueError("The first row in RDD is empty, "
C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\python\pyspark\rdd.py
in first(self) 1359 ValueError: RDD is empty 1360
"""-> 1361 rs = self.take(1) 1362 if rs: 1363
return rs[0]
C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\python\pyspark\rdd.py
in take(self, num) 1341 1342 p = range(partsScanned,
min(partsScanned + numPartsToTry, totalParts))-> 1343 res
= self.context.runJob(self, takeUpToNumLeft, p) 1344 1345
items += res
C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\python\pyspark\context.py
in runJob(self, rdd, partitionFunc, partitions, allowLocal) 963
# SparkContext#runJob. 964 mappedRDD =
rdd.mapPartitions(partitionFunc)--> 965 port =
self._jvm.PythonRDD.runJob(self._jsc.sc(), mappedRDD._jrdd,
partitions) 966 return list(_load_from_socket(port,
mappedRDD._jrdd_deserializer)) 967
C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\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:
C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\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()
C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\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
z:org.apache.spark.api.python.PythonRDD.runJob.
: org.apache.spark.SparkException: Job aborted due to stage failure:
Task 0 in stage 75.0 failed 1 times, most recent failure: Lost task
0.0 in stage 75.0 (TID 1035, localhost, executor driver):
org.apache.spark.api.python.PythonException: Traceback (most recent
call last):
File
"C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py",
line 174, in main
File
"C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py",
line 169, in process
File
"C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\serializers.py",
line 272, in dump_stream
bytes = self.serializer.dumps(vs)
File
"C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\serializers.py",
line 427, in dumps
return pickle.dumps(obj, protocol)
_pickle.PicklingError: Can't pickle <class '_sre.SRE_Match'>:
attribute lookup SRE_Match on _sre failed
at
org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
at
org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:63)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
at java.lang.Thread.run(Unknown Source)
Driver stacktrace:
at
org.apache.spark.scheduler.DAGScheduler.org$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$1.run(EventLoop.scala:48)
at
org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1918)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1931)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1944)
at org.apache.spark.api.python.PythonRDD$.runJob(PythonRDD.scala:441)
at org.apache.spark.api.python.PythonRDD.runJob(PythonRDD.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
at java.lang.reflect.Method.invoke(Unknown Source)
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(Unknown Source)
Caused by: org.apache.spark.api.python.PythonException: Traceback
(most recent call last):
File
"C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py",
line 174, in main
File
"C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py",
line 169, in process
File
"C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\serializers.py",
line 272, in dump_stream
bytes = self.serializer.dumps(vs)
File
"C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\serializers.py",
line 427, in dumps
return pickle.dumps(obj, protocol)
_pickle.PicklingError: Can't pickle <class '_sre.SRE_Match'>:
attribute lookup SRE_Match on _sre failed
at
org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
at
org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:63)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
... 1 more
