Import error raised even though library is not required on worker nodes - python

I'm writing a custom library for my PySpark application, and it needs to do a little pre-processing using the Pandas library on some CSV files. The pre-processing is "supposed" (well, that's what I think) to be done on the driver node since the input file itself is stored in the driver and not in HDFS. However, after I add the library as a package using the addPyFile function, import the required methods and execute the function, it raises an ImportError.
The package structure is like this
module
|- __init__.py
|- module_1.py
|- module_2.py
|- sub_module_1
|- __init__.py
|- sub_mod_1.py
|- ...
What I do in my Python runner script is
spark = SparkSession.builder.enableHiveSupport().getOrCreate()
spark.sparkContext.addPyFile("module.zip")
from module import module_1
module_1.func(spark, configs) # Exception raised here
In module_1.py, I have
import pandas as pd
from sub_module_1 import sub_mod_1
def func(spark, configs):
input_local_file = configs.get("SOME_SECTION", "local_file")
input_hdfs_file = configs.get("SOME_SECTION", "hdfs_file")
output_hdfs_destination = configs.get("SOME_SECTION", "hdfs_dest")
# Reads input file
lf_pdf = pd.read_csv(input_local_file)
# Convert pandas dataframe to dictionary object
transformed_dict = to_dictionary(lf_pdf)
# Log printed
# Writes to hdfs, wraps a mapPartitions function
another_method(transformed_dict, input_hdfs_file, output_hdfs_destination)
So, does this mean that even though I don't actually use Pandas in the worker nodes, as long as the package requires the module and is distributed via the addPyFile option, it will require the Pandas library to be installed in the workers as well? The thing is, module_2 does almost the exact same thing, except that the Pandas dataframe is converted to a Spark dataframe instead but it doesn't raise the same Exception.
The full error message is:
WARN scheduler.TaskSetManager: Lost task 48.2 in stage 4.0 (TID 167, somewhere.org, executor 35): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/opt/cloudera/parcels/SPARK2-2.2.0.cloudera1-1.cdh5.12.0.p0.142354/lib/spark2/python/pyspark/worker.py", line 166, in main
func, profiler, deserializer, serializer = read_command(pickleSer, infile)
File "/opt/cloudera/parcels/SPARK2-2.2.0.cloudera1-1.cdh5.12.0.p0.142354/lib/spark2/python/pyspark/worker.py", line 57, in read_command
command = serializer.loads(command.value)
File "/opt/cloudera/parcels/SPARK2-2.2.0.cloudera1-1.cdh5.12.0.p0.142354/lib/spark2/python/pyspark/serializers.py", line 454, in loads
return pickle.loads(obj)
File "./module.zip/module/module_1.py", line 15, in <module>
ImportError: No module named pandas
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:63)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:108)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
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:748)
EDIT: I've also been logging the steps in my application, and the point at which this error is raised is after all the pre-processing is completed, which is why I'm not sure why it's even occurring since Pandas is never used again.

Related

Pyspark - Failed to locate the winutils binary in the hadoop binary path [duplicate]

This question already has an answer here:
Failed to locate the winutils binary in the hadoop binary path
15 answers
I am trying to integrate pyspark with python 2.7 (Pycharm IDE). I need to run some huge text files.
So this is what i am doing.
Download Spark (2.3.0-bin-hadoop-2.7) and extract it
Install JDK
And then i am trying to run this script
spark_home = os.environ.get('SPARK_HOME', None)
os.environ["SPARK_HOME"] = "C:\spark-2.3.0-bin-hadoop2.7"
import pyspark
from pyspark import SparkContext, SparkConf
from pyspark.sql import SparkSession
conf = SparkConf()
sc = SparkContext(conf=conf)
spark = SparkSession.builder.config(conf=conf).getOrCreate()
import pandas as pd
ip = spark.read.format("csv").option("inferSchema","true").option("header","true").load(r"D:\some file.csv")
Pycharm says that no module named Pyspark is found.
I am solving that by adding content roots and pointing to the folders where it is installed.
But the problem is every time i reopen pycharm, i have to add the content roots. How do i fix this?
Next is, when i do manage to run the script it throws up the following error.
2018-06-01 12:20:49 ERROR Shell:397 - Failed to locate the winutils binary in the hadoop binary path
java.io.IOException: Could not locate executable null\bin\winutils.exe in the Hadoop binaries.
at org.apache.hadoop.util.Shell.getQualifiedBinPath(Shell.java:379)
at org.apache.hadoop.util.Shell.getWinUtilsPath(Shell.java:394)
at org.apache.hadoop.util.Shell.<clinit>(Shell.java:387)
at org.apache.hadoop.util.StringUtils.<clinit>(StringUtils.java:80)
at org.apache.hadoop.security.SecurityUtil.getAuthenticationMethod(SecurityUtil.java:611)
at org.apache.hadoop.security.UserGroupInformation.initialize(UserGroupInformation.java:273)
at org.apache.hadoop.security.UserGroupInformation.ensureInitialized(UserGroupInformation.java:261)
at org.apache.hadoop.security.UserGroupInformation.loginUserFromSubject(UserGroupInformation.java:791)
at org.apache.hadoop.security.UserGroupInformation.getLoginUser(UserGroupInformation.java:761)
at org.apache.hadoop.security.UserGroupInformation.getCurrentUser(UserGroupInformation.java:634)
at org.apache.spark.util.Utils$$anonfun$getCurrentUserName$1.apply(Utils.scala:2464)
at org.apache.spark.util.Utils$$anonfun$getCurrentUserName$1.apply(Utils.scala:2464)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.util.Utils$.getCurrentUserName(Utils.scala:2464)
at org.apache.spark.SecurityManager.<init>(SecurityManager.scala:222)
at org.apache.spark.deploy.SparkSubmit$.secMgr$lzycompute$1(SparkSubmit.scala:393)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$secMgr$1(SparkSubmit.scala:393)
at org.apache.spark.deploy.SparkSubmit$$anonfun$prepareSubmitEnvironment$7.apply(SparkSubmit.scala:401)
at org.apache.spark.deploy.SparkSubmit$$anonfun$prepareSubmitEnvironment$7.apply(SparkSubmit.scala:401)
at scala.Option.map(Option.scala:146)
at org.apache.spark.deploy.SparkSubmit$.prepareSubmitEnvironment(SparkSubmit.scala:400)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:170)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:136)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
WARNING: An illegal reflective access operation has occurred
WARNING: Illegal reflective access by org.apache.hadoop.security.authentication.util.KerberosUtil (file:/C:/spark-2.3.0-bin-hadoop2.7/jars/hadoop-auth-2.7.3.jar) to method sun.security.krb5.Config.getInstance()
WARNING: Please consider reporting this to the maintainers of org.apache.hadoop.security.authentication.util.KerberosUtil
WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations
WARNING: All illegal access operations will be denied in a future release
2018-06-01 12:20:49 WARN NativeCodeLoader:62 - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
2018-06-01 12:20:56 ERROR Executor:91 - Exception in task 0.0 in stage 0.0 (TID 0)
java.lang.ArrayIndexOutOfBoundsException: 63
at org.apache.spark.unsafe.types.UTF8String.numBytesForFirstByte(UTF8String.java:191)
at org.apache.spark.unsafe.types.UTF8String.numChars(UTF8String.java:206)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$10$$anon$1.hasNext(WholeStageCodegenExec.scala:614)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:253)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1135)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:635)
at java.base/java.lang.Thread.run(Thread.java:844)
2018-06-01 12:20:56 WARN TaskSetManager:66 - Lost task 0.0 in stage 0.0 (TID 0, localhost, executor driver): java.lang.ArrayIndexOutOfBoundsException: 63
at org.apache.spark.unsafe.types.UTF8String.numBytesForFirstByte(UTF8String.java:191)
at org.apache.spark.unsafe.types.UTF8String.numChars(UTF8String.java:206)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$10$$anon$1.hasNext(WholeStageCodegenExec.scala:614)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:253)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1135)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:635)
at java.base/java.lang.Thread.run(Thread.java:844)
2018-06-01 12:20:56 ERROR TaskSetManager:70 - Task 0 in stage 0.0 failed 1 times; aborting job
Traceback (most recent call last):
File "D:/Microsoft/ThemeSpark.py", line 13, in <module>
ip = spark.read.format("csv").option("inferSchema","true").option("header","true").load(r"D:\Microsoft\xbox_13.5_26.5\Xbox Family.csv")
File "C:\spark-2.3.0-bin-hadoop2.7\python\pyspark\sql\readwriter.py", line 166, in load
return self._df(self._jreader.load(path))
File "C:\spark-2.3.0-bin-hadoop2.7\python\lib\py4j-0.10.6-src.zip\py4j\java_gateway.py", line 1160, in __call__
File "C:\spark-2.3.0-bin-hadoop2.7\python\pyspark\sql\utils.py", line 63, in deco
return f(*a, **kw)
File "C:\spark-2.3.0-bin-hadoop2.7\python\lib\py4j-0.10.6-src.zip\py4j\protocol.py", line 320, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o25.load.
: 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, localhost, executor driver): java.lang.ArrayIndexOutOfBoundsException: 63
at org.apache.spark.unsafe.types.UTF8String.numBytesForFirstByte(UTF8String.java:191)
at org.apache.spark.unsafe.types.UTF8String.numChars(UTF8String.java:206)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$10$$anon$1.hasNext(WholeStageCodegenExec.scala:614)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:253)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1135)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:635)
at java.base/java.lang.Thread.run(Thread.java:844)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1599)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1587)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1586)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1586)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1820)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1769)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1758)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2027)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2048)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2067)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:363)
at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3272)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2484)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2484)
at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3253)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3252)
at org.apache.spark.sql.Dataset.head(Dataset.scala:2484)
at org.apache.spark.sql.Dataset.take(Dataset.scala:2698)
at org.apache.spark.sql.execution.datasources.csv.TextInputCSVDataSource$.infer(CSVDataSource.scala:148)
at org.apache.spark.sql.execution.datasources.csv.CSVDataSource.inferSchema(CSVDataSource.scala:63)
at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat.inferSchema(CSVFileFormat.scala:57)
at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$8.apply(DataSource.scala:202)
at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$8.apply(DataSource.scala:202)
at scala.Option.orElse(Option.scala:289)
at org.apache.spark.sql.execution.datasources.DataSource.getOrInferFileFormatSchema(DataSource.scala:201)
at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:392)
at org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:239)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:227)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:174)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.base/java.lang.reflect.Method.invoke(Method.java:564)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.base/java.lang.Thread.run(Thread.java:844)
Caused by: java.lang.ArrayIndexOutOfBoundsException: 63
at org.apache.spark.unsafe.types.UTF8String.numBytesForFirstByte(UTF8String.java:191)
at org.apache.spark.unsafe.types.UTF8String.numChars(UTF8String.java:206)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$10$$anon$1.hasNext(WholeStageCodegenExec.scala:614)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:253)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1135)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:635)
... 1 mo
I did some research and inferred that it is caused by the absence of the winutils.exefrom the spark folder. I downloaded and placed it in the spark bin. Still this error keeps coming. How do i fixed this?
Check out this git book
Download winutils.exe binary from https://github.com/steveloughran/winutils repository.
Note
You should select the version of Hadoop the Spark distribution was compiled with, e.g. use hadoop-2.7.1 for Spark 2 (here is the direct link to winutils.exe binary).
Save winutils.exe binary to a directory of your choice, e.g. c:\hadoop\bin.
Spark normally requires a full Hadoop installation. However winutils.exe is a tool created to help if you don't plan to use Hadoop in order to perform distrubite computing, for example because you are only testing Spark locally, on Windows.
Press WIN+PAUSE, go to Advanced Settings and Environment variables.
Set the new environmental variable HADOOP_HOME to a directory of your choice. I recommend C:\winutils and not hadoop since this is not a full hadoop installation.
Create the directory bin inside it, place the file winutils.exe inside bin.
Edit PATH , append %HADOOP_HOME%\ to it.
Now pyspark should work fine, as long as you work locally without distrubuted features.

Connection from host closed [SPARK job]

I am running hadoop cluster with 3 slave node using spark over yarn.
I am using following code for running spark job.
import os
import numpy as np
import pandas as pd
import seaborn as sns
import mysql.connector
import matplotlib.pyplot as plt, mpld3
from pyspark import SparkContext
import datetime
from datetime import date, timedelta
from pyspark.sql import SparkSession
### Spark Initialization
sc = SparkContext("yarn", "Count by Platform")
spark = SparkSession.builder.getOrCreate()
### Transformation
df = spark.read.format("com.databricks.spark.avro").load("hdfs:////divolte/published/2018042014*")
### Action #######
df.filter(df["event.platform"] == "Android APP").groupBy(df["event.platform"]).count().show()
After running job, getting following error in Jupyter notebook-
Py4JJavaError: An error occurred while calling o151.showString.
: org.apache.spark.SparkException: Job aborted due to stage failure: ResultStage 25 (showString at NativeMethodAccessorImpl.java:0) has failed the maximum allowable number of times: 4. Most recent failure reason: org.apache.spark.shuffle.FetchFailedException: Connection from thd3/10.22.162.10:44939 closed
at org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:361)
at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:336)
at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:54)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:32)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithKeys$(Unknown Source)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:231)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:225)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:827)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:827)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:325)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.io.IOException: Connection from thd3/10.22.162.10:44939 closed
Actions like collect and show are working but connection is lost when using count(). Also I am running spark with single executor only, as increasing executor causing issue with collect and show also.
Slave hardware configuration-
Memory - 16 GB
CPU - 8
Please help.

Pyspark error when I do an action on Dataframe which I created manually

I have a python list of strings. I created a dataframe out of it with one column with this code:
skills_df = spark.createDataFrame(temp, StringType())
where, temp is the list of strings.
This step was successfully executed.
When I try to do any action on skills_df like skills_df.count(), it gives me an error. It happens with this dataframe. But, not with a dataframe which I had created by importing csv file i.e. csv_df = spark.read.csv('/user/turing/Profiles_final.csv', header=True).
I ran this using spark-submit. While to debug, I ran the same code in pyspark, I got the same error. But, when I did a csv_df.count(), even after the error occurred, it ran fine.
Please help me with this error. Following is the stacktrace:
18/04/26 07:05:10 WARN org.apache.spark.scheduler.TaskSetManager: Stage 14 contains a task of very large size (215 KB). The maximum recommended task size is 100 KB.
18/04/26 07:05:11 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 2.0 in stage 14.0 (TID 658, spark-w-1.c.amulya.internal, executor 2): java.io.IOException: Cannot run program "/opt/conda/bin/python": error=2, No such file or directory
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1048)
at org.apache.spark.api.python.PythonWorkerFactory.startDaemon(PythonWorkerFactory.scala:163)
at org.apache.spark.api.python.PythonWorkerFactory.createThroughDaemon(PythonWorkerFactory.scala:89)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:65)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:117)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:128)
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.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.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:108)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:338)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.io.IOException: error=2, No such file or directory
at java.lang.UNIXProcess.forkAndExec(Native Method)
at java.lang.UNIXProcess.<init>(UNIXProcess.java:247)
at java.lang.ProcessImpl.start(ProcessImpl.java:134)
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1029)
... 33 more
18/04/26 07:05:11 ERROR org.apache.spark.scheduler.TaskSetManager: Task 2 in stage 14.0 failed 4 times; aborting job
18/04/26 07:05:11 WARN org.apache.spark.ExecutorAllocationManager: No stages are running, but numRunningTasks != 0
Traceback (most recent call last):
File "/home/turing/mi/sample_job.py", line 95, in <module>
skills = processing_methods.get_skills(company, position, company_df)
File "/home/turing/mi/sample_job.py", line 72, in get_skills
return skills_df.groupBy('value').count().head(5)
File "/usr/lib/spark/python/lib/pyspark.zip/pyspark/sql/dataframe.py", line 972, in head
File "/usr/lib/spark/python/lib/pyspark.zip/pyspark/sql/dataframe.py", line 476, in take
File "/usr/lib/spark/python/lib/pyspark.zip/pyspark/sql/dataframe.py", line 438, in collect
File "/usr/lib/spark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py", line 1133, in __call__
File "/usr/lib/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 63, in deco
File "/usr/lib/spark/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py", line 319, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o134.collectToPython.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 14.0 failed 4 times, most recent failure: Lost task 2.3 in stage 14.0 (TID 667, spark-w-1.c.amulya.internal, executor 2): java.io.IOException: Cannot run program "/opt/conda/bin/python": error=2, No such file or directory
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1048)
at org.apache.spark.api.python.PythonWorkerFactory.startDaemon(PythonWorkerFactory.scala:163)
at org.apache.spark.api.python.PythonWorkerFactory.createThroughDaemon(PythonWorkerFactory.scala:89)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:65)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:117)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:128)
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.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.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:108)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:338)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.io.IOException: error=2, No such file or directory
at java.lang.UNIXProcess.forkAndExec(Native Method)
at java.lang.UNIXProcess.<init>(UNIXProcess.java:247)
at java.lang.ProcessImpl.start(ProcessImpl.java:134)
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1029)
... 33 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1517)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1505)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1504)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1504)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:814)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1732)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1687)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1676)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:630)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2029)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2050)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2069)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:336)
at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
at org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply$mcI$sp(Dataset.scala:2808)
at org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply(Dataset.scala:2805)
at org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply(Dataset.scala:2805)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:65)
at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2828)
at org.apache.spark.sql.Dataset.collectToPython(Dataset.scala:2805)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
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:748)
Caused by: java.io.IOException: Cannot run program "/opt/conda/bin/python": error=2, No such file or directory
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1048)
at org.apache.spark.api.python.PythonWorkerFactory.startDaemon(PythonWorkerFactory.scala:163)
at org.apache.spark.api.python.PythonWorkerFactory.createThroughDaemon(PythonWorkerFactory.scala:89)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:65)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:117)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:128)
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.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.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:108)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:338)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
Caused by: java.io.IOException: error=2, No such file or directory
at java.lang.UNIXProcess.forkAndExec(Native Method)
at java.lang.UNIXProcess.<init>(UNIXProcess.java:247)
at java.lang.ProcessImpl.start(ProcessImpl.java:134)
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1029)
... 33 more
18/04/26 07:05:11 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 0.0 in stage 14.0 (TID 656, spark-w-0.c.amulya.internal, executor 4): TaskKilled (stage cancelled)
18/04/26 07:05:11 INFO org.spark_project.jetty.server.AbstractConnector: Stopped Spark#3af4a719{HTTP/1.1,[http/1.1]}{0.0.0.0:4040}
18/04/26 07:05:11 WARN org.apache.spark.rpc.netty.Dispatcher: Message RemoteProcessDisconnected(10.138.0.6:39486) dropped. Could not find OutputCommitCoordinator.
The spark is running on a google cloud dataproc cluster.
Thanks.
EDIT 1:
following is the temp variable with its values:
temp = ['javascript', 'html', 'css', 'jquery', 'ajax', 'ruby on rails', 'agile', 'linux']
Init actions need to be run on all nodes of the cluster, not just the master. The driver started successfully because you had run the init action on the master, but then the job failed on executors because they did not have Conda installed.
In general, you should not run initialization actions manually. E.g. if you later add nodes to the cluster, you will need to run the script on the new nodes as well. However, if you specify initialization actions when creating a cluster, Dataproc will handle that for you.
You can specify init actions through the web console:
Note that if you want to specify metadata (flags) to the init actions, such as conda packages to install, you will need to use gcloud. The easiest way to do that is to start from "Equivalent command line" at the bottom of the create cluster page.
In general, I would suggest deleting and recreating your cluster if you want to want to add init actions or add flags. This is especially easy if your input data resides outside the cluster (e.g. Cloud Storage).

How to cache Parquet files with too many columns in memory with pyspark?

I'm new to Spark and am having a lot of trouble to cache in memory a DataFrame loaded from a 600MB Parquet file that has both too many rows (~73K) and columns (~23K).
Here's my code:
from pyspark.sql import SparkSession
spark = SparkSession \
.builder \
.appName('Parquet Load Tests') \
.getOrCreate()
df = spark.read.parquet('./cell_level_table_aloha.parquet/')
df.createOrReplaceTempView('my_table')
spark.catalog.cacheTable('my_table')
spark.table('my_table').count()
After running for a while, it raises an error with a HUGE stack trace. If you wanna check it out, I pasted it on the end of this post.
It appears to me that the problem is related to Java's Heap Space, because java.lang.OutOfMemoryError: Java heap space shows up three times in the error stack trace. The thing is, I've already configured both driver and executor memory to have 16GB each. For doing so, I added these two lines on conf/spark-defaults.conf:
spark.driver.memory 16g
spark.executor.memory 16g
I'm running this code in a Python script (with $ python my_spark_script.py) on a Docker container with Ubuntu 16.04 in a machine with a Intel Core i5-3470S (2.90GHz), 32GB of RAM memory and disk-only storage.
My Spark installation is the pre-compiled spark-2.2.1-bin-hadoop2.7. After downloading it, I exported the following environment variables to my .bashrc file as follows:
export SPARK_HOME=/path/to/spark-2.2.1-bin-hadoop2.7
export PATH=$PATH:/path/to/spark-2.2.1-bin-hadoop2.7/bin
The PySpark I'm using was installed via $ pip install pyspark. Oh, and the Python version I'm using is 2.7.12.
It's important to note that although I'm struggling a lot to cache that DataFrame, I successfully cached a much bigger one row-wise: ~50 million rows and 34 columns. I loaded it from a 16GB+ CSV file. Due to this experiment, I'm think that maybe Spark struggles to deal with lots of columns, but deals ok with many rows. But that's just a beginner naive guess.
Does anyone know how I could solve this problem?
As mentioned above, here's the full error stack trace:
Setting default log level to "WARN". To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel). 18/01/30 16:19:13 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable 18/01/30 16:20:41 WARN Utils: Truncated the string representation of a plan since it was too large. This behavior can be adjusted by setting 'spark.debug.maxToStringFields' in SparkEnv.conf. [Stage 1:> (0
+ 4) / 6]18/01/30 16:20:47 WARN CodeGenerator: Error calculating stats of compiled class. java.io.EOFException
at java.io.DataInputStream.readFully(DataInputStream.java:197)
at java.io.DataInputStream.readFully(DataInputStream.java:169)
at org.codehaus.janino.util.ClassFile.loadAttribute(ClassFile.java:1509)
at org.codehaus.janino.util.ClassFile.loadAttributes(ClassFile.java:644)
at org.codehaus.janino.util.ClassFile.loadFields(ClassFile.java:623)
at org.codehaus.janino.util.ClassFile.<init>(ClassFile.java:280)
at org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$$anonfun$recordCompilationStats$1.apply(CodeGenerator.scala:1036)
at org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$$anonfun$recordCompilationStats$1.apply(CodeGenerator.scala:1033)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$.recordCompilationStats(CodeGenerator.scala:1033)
at org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$.org$apache$spark$sql$catalyst$expressions$codegen$CodeGenerator$$doCompile(CodeGenerator.scala:1001)
at org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$$anon$1.load(CodeGenerator.scala:1067)
at org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$$anon$1.load(CodeGenerator.scala:1064)
at org.spark_project.guava.cache.LocalCache$LoadingValueReference.loadFuture(LocalCache.java:3599)
at org.spark_project.guava.cache.LocalCache$Segment.loadSync(LocalCache.java:2379)
at org.spark_project.guava.cache.LocalCache$Segment.lockedGetOrLoad(LocalCache.java:2342)
at org.spark_project.guava.cache.LocalCache$Segment.get(LocalCache.java:2257)
at org.spark_project.guava.cache.LocalCache.get(LocalCache.java:4000)
at org.spark_project.guava.cache.LocalCache.getOrLoad(LocalCache.java:4004)
at org.spark_project.guava.cache.LocalCache$LocalLoadingCache.get(LocalCache.java:4874)
at org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$.compile(CodeGenerator.scala:946)
at org.apache.spark.sql.catalyst.expressions.codegen.GenerateUnsafeProjection$.create(GenerateUnsafeProjection.scala:412)
at org.apache.spark.sql.catalyst.expressions.codegen.GenerateUnsafeProjection$.create(GenerateUnsafeProjection.scala:366)
at org.apache.spark.sql.catalyst.expressions.codegen.GenerateUnsafeProjection$.create(GenerateUnsafeProjection.scala:32)
at org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator.generate(CodeGenerator.scala:930)
at org.apache.spark.sql.catalyst.expressions.UnsafeProjection$.create(Projection.scala:130)
at org.apache.spark.sql.catalyst.expressions.UnsafeProjection$.create(Projection.scala:120)
at org.apache.spark.sql.catalyst.expressions.UnsafeProjection$.create(Projection.scala:114)
at org.apache.spark.sql.execution.FileSourceScanExec$$anonfun$21.apply(DataSourceScanExec.scala:323)
at org.apache.spark.sql.execution.FileSourceScanExec$$anonfun$21.apply(DataSourceScanExec.scala:322)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndexInternal$1$$anonfun$apply$24.apply(RDD.scala:815)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndexInternal$1$$anonfun$apply$24.apply(RDD.scala:815)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD$$anonfun$8.apply(RDD.scala:336)
at org.apache.spark.rdd.RDD$$anonfun$8.apply(RDD.scala:334)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1038)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1029)
at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:969)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:1029)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:760)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:334)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:285)
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.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:108)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:338)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748) [Stage 1:> (0 + 4) / 6]18/01/30 16:24:08 WARN BlockManager: Putting block rdd_5_0 failed due to an exception 18/01/30 16:24:08 WARN BlockManager: Block rdd_5_0 could not be removed as it was not found on disk or in memory 18/01/30 16:24:08 ERROR Executor: Exception in task 0.0 in stage 1.0 (TID 1) java.lang.OutOfMemoryError: Java heap space
at java.nio.HeapByteBuffer.<init>(HeapByteBuffer.java:57)
at java.nio.ByteBuffer.allocate(ByteBuffer.java:335)
at org.apache.spark.sql.execution.columnar.BasicColumnBuilder.initialize(ColumnBuilder.scala:66)
at org.apache.spark.sql.execution.columnar.NativeColumnBuilder.org$apache$spark$sql$execution$columnar$NullableColumnBuilder$$super$initialize(ColumnBuilder.scala:97)
at org.apache.spark.sql.execution.columnar.NullableColumnBuilder$class.initialize(NullableColumnBuilder.scala:51)
at org.apache.spark.sql.execution.columnar.NativeColumnBuilder.org$apache$spark$sql$execution$columnar$compression$CompressibleColumnBuilder$$super$initialize(ColumnBuilder.scala:97)
at org.apache.spark.sql.execution.columnar.compression.CompressibleColumnBuilder$class.initialize(CompressibleColumnBuilder.scala:62)
at org.apache.spark.sql.execution.columnar.NativeColumnBuilder.initialize(ColumnBuilder.scala:97)
at org.apache.spark.sql.execution.columnar.ColumnBuilder$.apply(ColumnBuilder.scala:191)
at org.apache.spark.sql.execution.columnar.InMemoryRelation$$anonfun$1$$anon$1$$anonfun$2.apply(InMemoryRelation.scala:95)
at org.apache.spark.sql.execution.columnar.InMemoryRelation$$anonfun$1$$anon$1$$anonfun$2.apply(InMemoryRelation.scala:94)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
at scala.collection.immutable.List.map(List.scala:285)
at org.apache.spark.sql.execution.columnar.InMemoryRelation$$anonfun$1$$anon$1.next(InMemoryRelation.scala:94)
at org.apache.spark.sql.execution.columnar.InMemoryRelation$$anonfun$1$$anon$1.next(InMemoryRelation.scala:92)
at org.apache.spark.storage.memory.MemoryStore.putIteratorAsValues(MemoryStore.scala:216)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1038)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1029)
at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:969)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:1029)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:760)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:334)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:285)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) 18/01/30 16:24:08 ERROR SparkUncaughtExceptionHandler: Uncaught exception in thread Thread[Executor task launch worker for task 1,5,main] java.lang.OutOfMemoryError: Java heap space
at java.nio.HeapByteBuffer.<init>(HeapByteBuffer.java:57)
at java.nio.ByteBuffer.allocate(ByteBuffer.java:335)
at org.apache.spark.sql.execution.columnar.BasicColumnBuilder.initialize(ColumnBuilder.scala:66)
at org.apache.spark.sql.execution.columnar.NativeColumnBuilder.org$apache$spark$sql$execution$columnar$NullableColumnBuilder$$super$initialize(ColumnBuilder.scala:97)
at org.apache.spark.sql.execution.columnar.NullableColumnBuilder$class.initialize(NullableColumnBuilder.scala:51)
at org.apache.spark.sql.execution.columnar.NativeColumnBuilder.org$apache$spark$sql$execution$columnar$compression$CompressibleColumnBuilder$$super$initialize(ColumnBuilder.scala:97)
at org.apache.spark.sql.execution.columnar.compression.CompressibleColumnBuilder$class.initialize(CompressibleColumnBuilder.scala:62)
at org.apache.spark.sql.execution.columnar.NativeColumnBuilder.initialize(ColumnBuilder.scala:97)
at org.apache.spark.sql.execution.columnar.ColumnBuilder$.apply(ColumnBuilder.scala:191)
at org.apache.spark.sql.execution.columnar.InMemoryRelation$$anonfun$1$$anon$1$$anonfun$2.apply(InMemoryRelation.scala:95)
at org.apache.spark.sql.execution.columnar.InMemoryRelation$$anonfun$1$$anon$1$$anonfun$2.apply(InMemoryRelation.scala:94)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
at scala.collection.immutable.List.map(List.scala:285)
at org.apache.spark.sql.execution.columnar.InMemoryRelation$$anonfun$1$$anon$1.next(InMemoryRelation.scala:94)
at org.apache.spark.sql.execution.columnar.InMemoryRelation$$anonfun$1$$anon$1.next(InMemoryRelation.scala:92)
at org.apache.spark.storage.memory.MemoryStore.putIteratorAsValues(MemoryStore.scala:216)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1038)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1029)
at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:969)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:1029)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:760)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:334)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:285)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) [Stage 1:> (0 + 5) / 6]18/01/30 16:24:10 WARN TaskSetManager: Lost task 0.0 in stage 1.0 (TID 1, localhost, executor driver): java.lang.OutOfMemoryError: Java heap space
at java.nio.HeapByteBuffer.<init>(HeapByteBuffer.java:57)
at java.nio.ByteBuffer.allocate(ByteBuffer.java:335)
at org.apache.spark.sql.execution.columnar.BasicColumnBuilder.initialize(ColumnBuilder.scala:66)
at org.apache.spark.sql.execution.columnar.NativeColumnBuilder.org$apache$spark$sql$execution$columnar$NullableColumnBuilder$$super$initialize(ColumnBuilder.scala:97)
at org.apache.spark.sql.execution.columnar.NullableColumnBuilder$class.initialize(NullableColumnBuilder.scala:51)
at org.apache.spark.sql.execution.columnar.NativeColumnBuilder.org$apache$spark$sql$execution$columnar$compression$CompressibleColumnBuilder$$super$initialize(ColumnBuilder.scala:97)
at org.apache.spark.sql.execution.columnar.compression.CompressibleColumnBuilder$class.initialize(CompressibleColumnBuilder.scala:62)
at org.apache.spark.sql.execution.columnar.NativeColumnBuilder.initialize(ColumnBuilder.scala:97)
at org.apache.spark.sql.execution.columnar.ColumnBuilder$.apply(ColumnBuilder.scala:191)
at org.apache.spark.sql.execution.columnar.InMemoryRelation$$anonfun$1$$anon$1$$anonfun$2.apply(InMemoryRelation.scala:95)
at org.apache.spark.sql.execution.columnar.InMemoryRelation$$anonfun$1$$anon$1$$anonfun$2.apply(InMemoryRelation.scala:94)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
at scala.collection.immutable.List.map(List.scala:285)
at org.apache.spark.sql.execution.columnar.InMemoryRelation$$anonfun$1$$anon$1.next(InMemoryRelation.scala:94)
at org.apache.spark.sql.execution.columnar.InMemoryRelation$$anonfun$1$$anon$1.next(InMemoryRelation.scala:92)
at org.apache.spark.storage.memory.MemoryStore.putIteratorAsValues(MemoryStore.scala:216)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1038)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1029)
at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:969)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:1029)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:760)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:334)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:285)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
Traceback (most recent call last): File "caching_df_problem.py", line 12, in <module>
spark.table('my_table').count() File "/usr/local/lib/python2.7/dist-packages/pyspark/sql/dataframe.py", line 427, in count 18/01/30 16:24:10 ERROR TaskSetManager: Task 0 in stage 1.0 failed 1 times; aborting job
return int(self._jdf.count()) File "/usr/local/lib/python2.7/dist-packages/py4j/java_gateway.py", line 1133, in __call__
answer, self.gateway_client, self.target_id, self.name) File "/usr/local/lib/python2.7/dist-packages/pyspark/sql/utils.py", line 63, in deco
return f(*a, **kw) File "/usr/local/lib/python2.7/dist-packages/py4j/protocol.py", line 319, in get_return_value
format(target_id, ".", name), value) py4j.protocol.Py4JJavaError: An error occurred while calling o34.count. : org.apache.spark.SparkException: Job 1 cancelled because SparkContext was shut down
at org.apache.spark.scheduler.DAGScheduler$$anonfun$cleanUpAfterSchedulerStop$1.apply(DAGScheduler.scala:820)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$cleanUpAfterSchedulerStop$1.apply(DAGScheduler.scala:818)
at scala.collection.mutable.HashSet.foreach(HashSet.scala:78)
at org.apache.spark.scheduler.DAGScheduler.cleanUpAfterSchedulerStop(DAGScheduler.scala:818)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onStop(DAGScheduler.scala:1750)
at org.apache.spark.util.EventLoop.stop(EventLoop.scala:83)
at org.apache.spark.scheduler.DAGScheduler.stop(DAGScheduler.scala:1669)
at org.apache.spark.SparkContext$$anonfun$stop$8.apply$mcV$sp(SparkContext.scala:1928)
at org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1317)
at org.apache.spark.SparkContext.stop(SparkContext.scala:1927)
at org.apache.spark.SparkContext$$anonfun$2.apply$mcV$sp(SparkContext.scala:581)
at org.apache.spark.util.SparkShutdownHook.run(ShutdownHookManager.scala:216)
at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ShutdownHookManager.scala:188)
at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1$$anonfun$apply$mcV$sp$1.apply(ShutdownHookManager.scala:188)
at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1$$anonfun$apply$mcV$sp$1.apply(ShutdownHookManager.scala:188)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1948)
at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1.apply$mcV$sp(ShutdownHookManager.scala:188)
at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1.apply(ShutdownHookManager.scala:188)
at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1.apply(ShutdownHookManager.scala:188)
at scala.util.Try$.apply(Try.scala:192)
at org.apache.spark.util.SparkShutdownHookManager.runAll(ShutdownHookManager.scala:188)
at org.apache.spark.util.SparkShutdownHookManager$$anon$2.run(ShutdownHookManager.scala:178)
at org.apache.hadoop.util.ShutdownHookManager$1.run(ShutdownHookManager.java:54)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:630)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2029)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2050)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2069)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2094)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:936)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
at org.apache.spark.rdd.RDD.collect(RDD.scala:935)
at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:278)
at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2435)
at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2434)
at org.apache.spark.sql.Dataset$$anonfun$55.apply(Dataset.scala:2842)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:65)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:2841)
at org.apache.spark.sql.Dataset.count(Dataset.scala:2434)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
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:748)

Spark standalone cluster tires to access local python.exe

When executing a python application on a spark cluster I run into the following exception:
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
17/04/07 10:57:01 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
[Stage 0:> (0 + 2) / 2]17/04/07 10:57:07 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0, 192.168.2.113, executor 0): java.io.IOException: Cannot run program "C:\Users\<local-user>\Anaconda2\python.exe": CreateProcess error=2, The system cannot find the file specified
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1048)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:120)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:67)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:116)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:128)
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$TaskRunner.run(Executor.scala:282)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.io.IOException: CreateProcess error=2, The system cannot find the file specified
at java.lang.ProcessImpl.create(Native Method)
at java.lang.ProcessImpl.<init>(ProcessImpl.java:386)
at java.lang.ProcessImpl.start(ProcessImpl.java:137)
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1029)
... 13 more
17/04/07 10:57:07 ERROR TaskSetManager: Task 0 in stage 0.0 failed 4 times; aborting job
Traceback (most recent call last):
File "<redacted-absolute-path>.py", line 49, in <module>
eco_rdd
File "C:\spark\python\pyspark\rdd.py", line 2139, in zipWithIndex
nums = self.mapPartitions(lambda it: [sum(1 for i in it)]).collect()
File "C:\spark\python\pyspark\rdd.py", line 809, in collect
port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
File "C:\spark\python\lib\py4j-0.10.4-src.zip\py4j\java_gateway.py", line 1133, in __call__
File "C:\spark\python\pyspark\sql\utils.py", line 63, in deco
return f(*a, **kw)
File "C:\spark\python\lib\py4j-0.10.4-src.zip\py4j\protocol.py", line 319, in get_return_value
py4j.protocol.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 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 6, 192.168.2.113, executor 0): java.io.IOException: Cannot run program "C:\Users\<local-user>\Anaconda2\python.exe": CreateProcess error=2, The system cannot find the file specified
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1048)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:120)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:67)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:116)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:128)
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$TaskRunner.run(Executor.scala:282)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.io.IOException: CreateProcess error=2, The system cannot find the file specified
at java.lang.ProcessImpl.create(Native Method)
at java.lang.ProcessImpl.<init>(ProcessImpl.java:386)
at java.lang.ProcessImpl.start(ProcessImpl.java:137)
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1029)
... 13 more
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.SparkContext.runJob(SparkContext.scala:1958)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:935)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
at org.apache.spark.rdd.RDD.collect(RDD.scala:934)
at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:453)
at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
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: java.io.IOException: Cannot run program "C:\Users\<local-user>\Anaconda2\python.exe": CreateProcess error=2, The system cannot find the file specified
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1048)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:120)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:67)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:116)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:128)
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$TaskRunner.run(Executor.scala:282)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
... 1 more
Caused by: java.io.IOException: CreateProcess error=2, The system cannot find the file specified
at java.lang.ProcessImpl.create(Native Method)
at java.lang.ProcessImpl.<init>(ProcessImpl.java:386)
at java.lang.ProcessImpl.start(ProcessImpl.java:137)
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1029)
... 13 more
Somehow the cluster (on a remote pc in the same network) tries to access the local python (that is installed on my local workstation which executes the driver):
Caused by: java.io.IOException: Cannot run program "C:\Users\<local-user>\Anaconda2\python.exe": CreateProcess error=2, The system cannot find the file specified
Spark 2.1.0
The spark standalone cluster is running on Windows 10
The workstation is running on Windows 7
Connecting to the cluster and executing tasks with spark-shell (interactive) works without problems
Connecting to the cluster and executing tasks with pyspark (interactive) works without problems
Running from pycharm directly caused the exception above
Using spark-submit to execute caused a similar problem (=> trying to access my local python)
is using findspark
The PYSPARK_PYTHON and PYSPARK_DRIVER_PYTHON environment variables are set
Python on cluster and workstation: Python 2.7.13 :: Anaconda custom (64-bit)
Thank you in advance for your help
So I found a solution for my problem now. For my setup the problem was the findspark library. Removing allowed me to run all my tasks on the cluster.
If you have a similar problem but it's not findspark related I would point you to the comments from Samson Scharfrichter above.

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