coding reduceByKey(lambda) in map does'nt work pySpark

Question

I can't understand why my code isn't working. The last line is the problem:

import findspark
findspark.init()
from pyspark import SparkConf, SparkContext
from pyspark.sql.types import StringType
from pyspark import SQLContext
conf=SparkConf().setMaster("local").setAppName("mein soft")
sc=SparkContext(conf=conf)
sqlContext=SQLContext(sc)

lines=sc.textFile("File.txt")
#lines.repartition(3)
lines.getNumPartitions()

def lan_map(x):
    if "word1" and "word2" in x:
        return ("Count",(1,1))
    elif "word1" in x:
        return ("Count",("1,0"))
    elif "word2" in x:
        return ("Count",("0,1"))
    else:
        return ("Count",("0,0"))
    
mapfun=lines.map(lan_map)

mapfun.reduceByKey(lambda x, y: (x[0]+y[0], x[1]+y[1])).collect() 

And the error:

--------------------------------------------------------------------------- Py4JJavaError Traceback (most recent call last) in 1 #Esto resume lo que se hicimos 3 celdas atrás. ----> 2 mapfun.reduceByKey(lambda x,y: (x[0]+y[0], x[1]+y[1])).collect() 3 4 #mapfun.reduceByKey(noMeFuncaLambdaAsiQueHagoEsto(mapfun.x,mupfun.y)).collect() 5 #Esto nos devuelve directamente el recuento de cuántas veces aparece "Python" y cuántas aparece "Spark"

C:\spark-3.1.2-bin-hadoop3.2\python\pyspark\rdd.py in collect(self) 947 """ 948 with SCCallSiteSync(self.context) as css: --> 949 sock_info = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd()) 950 return list(_load_from_socket(sock_info, self._jrdd_deserializer)) 951

C:\spark-3.1.2-bin-hadoop3.2\python\lib\py4j-0.10.9-src.zip\py4j\java_gateway.py in call(self, *args) 1302 1303 answer = self.gateway_client.send_command(command) -> 1304 return_value = get_return_value( 1305 answer, self.gateway_client, self.target_id, self.name) 1306

C:\spark-3.1.2-bin-hadoop3.2\python\pyspark\sql\utils.py in deco(*a, **kw) 109 def deco(*a, **kw): 110 try: --> 111 return f(*a, **kw) 112 except py4j.protocol.Py4JJavaError as e: 113 converted = convert_exception(e.java_exception)

C:\spark-3.1.2-bin-hadoop3.2\python\lib\py4j-0.10.9-src.zip\py4j\protocol.py in get_return_value(answer, gateway_client, target_id, name) 324 value = OUTPUT_CONVERTER[type](answer[2:], gateway_client) 325 if answer[1] == REFERENCE_TYPE: --> 326 raise Py4JJavaError( 327 "An error occurred while calling {0}{1}{2}.\n". 328 format(target_id, ".", name), value)

Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe. : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0) (LAPTOP-PB7QDPVE executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last): File "C:\spark-3.1.2-bin-hadoop3.2\python\lib\pyspark.zip\pyspark\worker.py", line 604, in main File "C:\spark-3.1.2-bin-hadoop3.2\python\lib\pyspark.zip\pyspark\worker.py", line 594, in process File "C:\spark-3.1.2-bin-hadoop3.2\python\pyspark\rdd.py", line 2916, in pipeline_func return func(split, prev_func(split, iterator)) File "C:\spark-3.1.2-bin-hadoop3.2\python\pyspark\rdd.py", line 2916, in pipeline_func return func(split, prev_func(split, iterator)) File "C:\spark-3.1.2-bin-hadoop3.2\python\pyspark\rdd.py", line 418, in func return f(iterator) File "C:\spark-3.1.2-bin-hadoop3.2\python\pyspark\rdd.py", line 2144, in combineLocally merger.mergeValues(iterator) File "C:\spark-3.1.2-bin-hadoop3.2\python\lib\pyspark.zip\pyspark\shuffle.py", line 242, in mergeValues d[k] = comb(d[k], v) if k in d else creator(v) File "C:\spark-3.1.2-bin-hadoop3.2\python\pyspark\util.py", line 73, in wrapper return f(*args, **kwargs) File "", line 2, in TypeError: unsupported operand type(s) for +: 'int' and 'str'

at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:517) at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:652) at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:635) at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:470) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at scala.collection.Iterator$GroupedIterator.fill(Iterator.scala:1209) at scala.collection.Iterator$GroupedIterator.hasNext(Iterator.scala:1215) at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458) at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:132) at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52) at org.apache.spark.scheduler.Task.run(Task.scala:131) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500) at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source) at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source) at java.lang.Thread.run(Unknown Source)

Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2258) at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2207) at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2206) at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62) at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2206) at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1079) at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1079) at scala.Option.foreach(Option.scala:407) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1079) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2445) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2387) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2376) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:868) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2196) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2217) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2236) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2261) at org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1030) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) at org.apache.spark.rdd.RDD.withScope(RDD.scala:414) at org.apache.spark.rdd.RDD.collect(RDD.scala:1029) at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:180) at org.apache.spark.api.python.PythonRDD.collectAndServe(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:282) at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) at py4j.commands.CallCommand.execute(CallCommand.java:79) at py4j.GatewayConnection.run(GatewayConnection.java:238) at java.lang.Thread.run(Unknown Source) Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last): File "C:\spark-3.1.2-bin-hadoop3.2\python\lib\pyspark.zip\pyspark\worker.py", line 604, in main File "C:\spark-3.1.2-bin-hadoop3.2\python\lib\pyspark.zip\pyspark\worker.py", line 594, in process File "C:\spark-3.1.2-bin-hadoop3.2\python\pyspark\rdd.py", line 2916, in pipeline_func return func(split, prev_func(split, iterator)) File "C:\spark-3.1.2-bin-hadoop3.2\python\pyspark\rdd.py", line 2916, in pipeline_func return func(split, prev_func(split, iterator)) File "C:\spark-3.1.2-bin-hadoop3.2\python\pyspark\rdd.py", line 418, in func return f(iterator) File "C:\spark-3.1.2-bin-hadoop3.2\python\pyspark\rdd.py", line 2144, in combineLocally merger.mergeValues(iterator) File "C:\spark-3.1.2-bin-hadoop3.2\python\lib\pyspark.zip\pyspark\shuffle.py", line 242, in mergeValues d[k] = comb(d[k], v) if k in d else creator(v) File "C:\spark-3.1.2-bin-hadoop3.2\python\pyspark\util.py", line 73, in wrapper return f(*args, **kwargs) File "", line 2, in TypeError: unsupported operand type(s) for +: 'int' and 'str'

at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:517) at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:652) at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:635) at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:470) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at scala.collection.Iterator$GroupedIterator.fill(Iterator.scala:1209) at scala.collection.Iterator$GroupedIterator.hasNext(Iterator.scala:1215) at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458) at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:132) at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52) at org.apache.spark.scheduler.Task.run(Task.scala:131) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500) at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source) at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source) ... 1 more

I feel so lost that I even can't return just one possition from my funmap. I mean doesnt this should work:

mapfun[1]

I have tried with a function instead. But I failed worse:

def fun2(x,y):
    x[0]+y[0]
    x[1]+y[1]
mapfun.reduceByKey(fun2(x,y)).collect()

Answer 1

You are receiving the error

TypeError: unsupported operand type(s) for +: 'int' and 'str'

because your tuple values are string i.e. ("1,0") instead of (1,0), python currently will not apply this operator + or add the int and str(string) data types.

Moreover, there seems to be a logic error in your comparison in your map function where you have "word1" and "word2" in x as this will only check if "word2" is in x. I would recommend the following rewrite:

def lan_map(x):
    if "word1" in x and "word2" in x:
        return ("Count",(1,1))
    elif "word1" in x:
        return ("Count",(1,0))
    elif "word2" in x:
        return ("Count",(0,1))
    else:
        return ("Count",(0,0))

or possibly shorter

def lan_map(x):
     return ("Count", (
         1 if "word1" in x else 0,
         1 if "word2" in x else 0
     ))

Let me know if this works for you.