Got it working now!
Does anyone have a pyspark example of how to calculate the numbers of days
from the nearest holiday based on an array column?
I.e. from this table
+----------+-----------------------+
|start_date|holiday |
+----------+-----------------------+
|2017-08-11|[2017-05-30,2017-10-01]|
calculate a column called "days_from_nearest_holiday" which calculates
the difference between 11 aug 2017 and 1 oct 2017?
On Tue, Apr 25, 2017 at 6:00 PM, Wen Pei Yu <yuw...@cn.ibm.com> wrote:
> TypeError: unorderable types: str() >= datetime.date()
>
> Should transfer string to Date type when compare.
>
> Yu Wenpei.
>
>
> ----- Original message -----
> From: Zeming Yu <zemin...@gmail.com>
> To: user <user@spark.apache.org>
> Cc:
> Subject: how to find the nearest holiday
> Date: Tue, Apr 25, 2017 3:39 PM
>
> I have a column of dates (date type), just trying to find the nearest
> holiday of the date. Anyone has any idea what went wrong below?
>
>
>
> start_date_test = flight3.select("start_date").distinct()
> start_date_test.show()
>
> holidays = ['2017-09-01', '2017-10-01']
>
> +----------+
> |start_date|
> +----------+
> |2017-08-11|
> |2017-09-11|
> |2017-09-28|
> |2017-06-29|
> |2017-09-29|
> |2017-07-31|
> |2017-08-14|
> |2017-08-18|
> |2017-04-09|
> |2017-09-21|
> |2017-08-10|
> |2017-06-30|
> |2017-08-19|
> |2017-07-06|
> |2017-06-28|
> |2017-09-14|
> |2017-08-08|
> |2017-08-22|
> |2017-07-03|
> |2017-07-30|
> +----------+
> only showing top 20 rows
>
>
>
> index = spark.sparkContext.broadcast(sorted(holidays))
>
> def nearest_holiday(date):
> last_holiday = index.value[0]
> for next_holiday in index.value:
> if next_holiday >= date:
> break
> last_holiday = next_holiday
> if last_holiday > date:
> last_holiday = None
> if next_holiday < date:
> next_holiday = None
> return (last_holiday, next_holiday)
>
>
> from pyspark.sql.types import *
> return_type = StructType([StructField('last_holiday', StringType()),
> StructField('next_holiday', StringType())])
>
> from pyspark.sql.functions import udf
> nearest_holiday_udf = udf(nearest_holiday, return_type)
>
> start_date_test.withColumn('holiday',
> nearest_holiday_udf('start_date')).show(5,
> False)
>
>
> here's the error I got:
>
> ------------------------------------------------------------
> ---------------
> Py4JJavaError Traceback (most recent call
> last)
> <ipython-input-40-33fd4d7e8c8a> in <module>()
> 24 nearest_holiday_udf = udf(nearest_holiday, return_type)
> 25
> ---> 26 start_date_test.withColumn('holiday', nearest_holiday_udf(
> 'start_date')).show(5, False)
>
> C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\
> python\pyspark\sql\dataframe.py in show(self, n, truncate)
> 318 print(self._jdf.showString(n, 20))
> 319 else:
> --> 320 print(self._jdf.showString(n, int(truncate)))
> 321
> 322 def __repr__(self):
>
> 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 o566.showString.
> : org.apache.spark.SparkException: Job aborted due to stage failure: Task
> 0 in stage 98.0 failed 1 times, most recent failure: Lost task 0.0 in stage
> 98.0 (TID 521, 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 220, in dump_stream
> self.serializer.dump_stream(self._batched(iterator), stream)
> File "C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\
> python\lib\pyspark.zip\pyspark\serializers.py", line 138, in dump_stream
> for obj in iterator:
> File "C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\
> python\lib\pyspark.zip\pyspark\serializers.py", line 209, in _batched
> for item in iterator:
> File "C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\
> python\lib\pyspark.zip\pyspark\worker.py", line 92, in <lambda>
> File "C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\
> python\lib\pyspark.zip\pyspark\worker.py", line 68, in <lambda>
> File "<ipython-input-40-33fd4d7e8c8a>", line 10, in nearest_holiday
> TypeError: unorderable types: str() >= datetime.date()
>
> 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$23.apply(RDD.scala:796)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(
> MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(
> MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(
> MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
> at org.apache.spark.scheduler.Task.run(Task.scala:99)
> at org.apache.spark.executor.Executor$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.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.GeneratedMethodAccessor89.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 220, in dump_stream
> self.serializer.dump_stream(self._batched(iterator), stream)
> File "C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\
> python\lib\pyspark.zip\pyspark\serializers.py", line 138, in dump_stream
> for obj in iterator:
> File "C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\
> python\lib\pyspark.zip\pyspark\serializers.py", line 209, in _batched
> for item in iterator:
> File "C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\
> python\lib\pyspark.zip\pyspark\worker.py", line 92, in <lambda>
> File "C:\spark-2.1.0-bin-hadoop2.7\spark-2.1.0-bin-hadoop2.7\
> python\lib\pyspark.zip\pyspark\worker.py", line 68, in <lambda>
> File "<ipython-input-40-33fd4d7e8c8a>", line 10, in nearest_holiday
> TypeError: unorderable types: str() >= datetime.date()
>
> 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$23.apply(RDD.scala:796)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(
> MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(
> MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(
> MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
> at org.apache.spark.scheduler.Task.run(Task.scala:99)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
> ... 1 more
>
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