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Pyspark read REST API

It is the first time I am using Pyspark. I would like to create an ETL which extract from the API and put the data into a database in my local environment. But I have an error to call the API as shown below. Any help would be appreciated.
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The error:
Traceback (most recent call last):
File "etl.py", line 9, in <module>
df = spark.read.format("org.apache.dsext.spark.datasource.rest.RestDataSource").options(**options).load()
File "/home/ubuntu/.local/lib/python3.6/site-packages/pyspark/sql/readwriter.py", line 184, in load
return self._df(self._jreader.load())
File "/home/ubuntu/.local/lib/python3.6/site-packages/py4j/java_gateway.py", line 1305, in __call__
answer, self.gateway_client, self.target_id, self.name)
File "/home/ubuntu/.local/lib/python3.6/site-packages/pyspark/sql/utils.py", line 128, in deco
return f(*a, **kw)
File "/home/ubuntu/.local/lib/python3.6/site-packages/py4j/protocol.py", line 328, in get_return_value
format(target_id, ".", name), value)
py4j.protocol.Py4JJavaError: An error occurred while calling o32.load.
: java.lang.ClassNotFoundException: Failed to find data source: org.apache.dsext.spark.datasource.rest.RestDataSource. Please find packages at http://spark.apache.org/third-party-projects.html
at org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSource(DataSource.scala:679)
at org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSourceV2(DataSource.scala:733)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:248)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:221)
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:566)
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.base/java.lang.Thread.run(Thread.java:834)
Caused by: java.lang.ClassNotFoundException: org.apache.dsext.spark.datasource.rest.RestDataSource.DefaultSource
at java.base/java.net.URLClassLoader.findClass(URLClassLoader.java:471)
at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:589)
at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:522)
at org.apache.spark.sql.execution.datasources.DataSource$.$anonfun$lookupDataSource$5(DataSource.scala:653)
at scala.util.Try$.apply(Try.scala:213)
at org.apache.spark.sql.execution.datasources.DataSource$.$anonfun$lookupDataSource$4(DataSource.scala:653)
at scala.util.Failure.orElse(Try.scala:224)
at org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSource(DataSource.scala:653)
... 14 more
My code:
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName("{your app name here}").getOrCreate()
uri = "https://min-api.cryptocompare.com/data/histoday?fsym=BTC&tsym=JPY&limit=30&aggregate=1&e=CCCAGG"
options = { 'url' : uri, 'method' : 'GET', 'readTimeout' : '10000', 'connectionTimeout' : '2000', 'partitions' : '10'}
df = spark.read.format("org.apache.dsext.spark.datasource.rest.RestDataSource").options(**options).load()
df.printSchema()
JAVA version:
openjdk 11.0.9.1 2020-11-04
OpenJDK Runtime Environment (build 11.0.9.1+1-Ubuntu-0ubuntu1.18.04)
OpenJDK 64-Bit Server VM (build 11.0.9.1+1-Ubuntu-0ubuntu1.18.04, mixed mode, sharing)

I believe that this issue was raised due to a missing dependency.
In the code, you mentioned org.apache.dsext.spark.datasource.rest.RestDataSource as your format, this particular functionality is not inbuild in spark but depends on third party package called REST Data Source
you need to create a jar file by building the codebase and add it to your spark as follows:
$SPARK_HOME/bin/spark-shell --jars spark-datasource-rest_2.11-2.1.0-SNAPSHOT.jar --packages org.scalaj:scalaj-http_2.10:2.3.0

The 's3' resource does not exist

I used Python and boto3 to process some S3 files on the spark, and when I downloaded the files, it was unusual: The 's3'resource does not exist.
Because boto3 is not installed on each cluster node, I packaged the dependency packages used by boto3 as zip and used the spark cluster submitted by -- py-files, and this exception occurred.
Py4JJavaErrorTraceback (most recent call last)
<ipython-input-3-8147865bf49c> in <module>()
2
3
----> 4 extractor.extract(paths)
/usr/local/lib/python2.7/site-packages/extract-1.0-py2.7.egg/extract.pyc in extract(self, target_files_path)
52 try:
53 sc = self.get_spark_context()
---> 54 self._extract_file(sc, target_files_path)
55 finally:
56 if sc:
/usr/local/lib/python2.7/site-packages/extract-1.0-py2.7.egg/extract.pyc in _extract_file(self, sc, target_files_path)
109 def _extract_file(self, sc, target_files_path):
110 file_rdd = sc.parallelize(target_files_path, len(target_files_path))
--> 111 result_rdd = file_rdd.map(lambda file_path: self.process(file_path, self.func)).collect()
112 result_rdd.saveAsTextFile(self.result_path)
113
/usr/lib/spark/python/pyspark/rdd.py in collect(self)
769 """
770 with SCCallSiteSync(self.context) as css:
--> 771 port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
772 return list(_load_from_socket(port, self._jrdd_deserializer))
773
/usr/lib/spark/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py in __call__(self, *args)
811 answer = self.gateway_client.send_command(command)
812 return_value = get_return_value(
--> 813 answer, self.gateway_client, self.target_id, self.name)
814
815 for temp_arg in temp_args:
/usr/lib/spark/python/lib/py4j-0.9-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
306 raise Py4JJavaError(
307 "An error occurred while calling {0}{1}{2}.\n".
--> 308 format(target_id, ".", name), value)
309 else:
310 raise Py4JError(
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 2 in stage 0.0 failed 4 times, most recent failure: Lost task 2.3 in stage 0.0 (TID 15, ip-172-20-219-210.corp.hpicloud.net): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/mnt/yarn/usercache/chqiang/appcache/application_1521024688288_67008/container_1521024688288_67008_01_000002/pyspark.zip/pyspark/worker.py", line 111, in main
process()
File "/mnt/yarn/usercache/chqiang/appcache/application_1521024688288_67008/container_1521024688288_67008_01_000002/pyspark.zip/pyspark/worker.py", line 106, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/mnt/yarn/usercache/chqiang/appcache/application_1521024688288_67008/container_1521024688288_67008_01_000002/pyspark.zip/pyspark/serializers.py", line 263, in dump_stream
vs = list(itertools.islice(iterator, batch))
File "/usr/local/lib/python2.7/site-packages/extract-1.0-py2.7.egg/extract.py", line 111, in <lambda>
File "./lib.zip/extract.py", line 115, in process
local_path = download_file_from_s3(self.app_name, file_path)
File "./lib.zip/extract.py", line 22, in download_file_from_s3
s3 = boto3.resource('s3')
File "./lib.zip/boto3/__init__.py", line 100, in resource
return _get_default_session().resource(*args, **kwargs)
File "./lib.zip/boto3/session.py", line 347, in resource
has_low_level_client)
ResourceNotExistsError: The 's3' resource does not exist.
The available resources are:
-
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1431)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1419)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1418)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1418)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:799)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1640)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1845)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1858)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1929)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:927)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
at org.apache.spark.rdd.RDD.collect(RDD.scala:926)
at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:405)
at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
at py4j.Gateway.invoke(Gateway.java:259)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:209)
at java.lang.Thread.run(Thread.java:745)
Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/mnt/yarn/usercache/chqiang/appcache/application_1521024688288_67008/container_1521024688288_67008_01_000002/pyspark.zip/pyspark/worker.py", line 111, in main
process()
File "/mnt/yarn/usercache/chqiang/appcache/application_1521024688288_67008/container_1521024688288_67008_01_000002/pyspark.zip/pyspark/worker.py", line 106, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/mnt/yarn/usercache/chqiang/appcache/application_1521024688288_67008/container_1521024688288_67008_01_000002/pyspark.zip/pyspark/serializers.py", line 263, in dump_stream
vs = list(itertools.islice(iterator, batch))
File "/usr/local/lib/python2.7/site-packages/extract-1.0-py2.7.egg/extract.py", line 111, in <lambda>
File "./lib.zip/extract.py", line 115, in process
local_path = download_file_from_s3(self.app_name, file_path)
File "./lib.zip/extract.py", line 22, in download_file_from_s3
s3 = boto3.resource('s3')
File "./lib.zip/boto3/__init__.py", line 100, in resource
return _get_default_session().resource(*args, **kwargs)
File "./lib.zip/boto3/session.py", line 347, in resource
has_low_level_client)
ResourceNotExistsError: The 's3' resource does not exist.
The available resources are:
-
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
... 1 more
Could you please help me? thank you!

I ran into the same error today. I tried fixing it using client instead of resource, however that gave out another error.
botocore.exceptions.DataNotFoundError: Unable to load data for: endpoints
I googled a bit and came to the conclusion that it is not possible to zip up the boto3 package since packaging it results in loss of a few .json files. The endpoints.json is one of them. It exists in your botocore/data directory however when you zip it, it doesn't have it.
The solution is to install boto3 during bootstrap. You can create a bootstrap file and provide it during the cluster build-up process (there is an option in the AWS EMR console for it). This will install boto3 on the master node and all of the slave nodes.
You can refer to the following answer as well :
boto3 cannot create client on pyspark worker?

I packaged the dependency packages as whl files instead of zip packages, then added them all to the --py-files parameter(eg. a.whl,b.whl,c.whl), changed s3=boto3.resource('s3') in the code to client=boto3.client('s3') and tried to succeed

RDD Collect Issue

I configured a new system, spark 2.3.0, python 3.6.0, dataframe read and other operations working as expected.
But, RDD collect is failing -
distFile = spark.sparkContext.textFile("/Users/aakash/Documents/Final_HOME_ORIGINAL/Downloads/PreloadedDataset/breast-cancer-wisconsin.csv")
distFile.collect()
Error:
py4j.protocol.Py4JJavaError: An error occurred while calling
z:org.apache.spark.api.python.PythonRDD.collectAndServe.
Traceback:
Traceback (most recent call last):
File "/Users/aakash/Documents/Final_HOME_ORIGINAL/PycharmProjects/AllMyRnD/BB_AutoML_Blocks/Test.py", line 15, in <module>
distFile.collect()
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/pyspark/rdd.py", line 824, in collect
port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/py4j/java_gateway.py", line 1160, in __call__
answer, self.gateway_client, self.target_id, self.name)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/pyspark/sql/utils.py", line 63, in deco
return f(*a, **kw)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/py4j/protocol.py", line 320, in get_return_value
format(target_id, ".", name), value)
py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
: java.lang.IllegalArgumentException
at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
at org.apache.spark.util.ClosureCleaner$.getClassReader(ClosureCleaner.scala:46)
at org.apache.spark.util.FieldAccessFinder$$anon$3$$anonfun$visitMethodInsn$2.apply(ClosureCleaner.scala:449)
at org.apache.spark.util.FieldAccessFinder$$anon$3$$anonfun$visitMethodInsn$2.apply(ClosureCleaner.scala:432)
at scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:733)
at scala.collection.mutable.HashMap$$anon$1$$anonfun$foreach$2.apply(HashMap.scala:103)
at scala.collection.mutable.HashMap$$anon$1$$anonfun$foreach$2.apply(HashMap.scala:103)
at scala.collection.mutable.HashTable$class.foreachEntry(HashTable.scala:230)
at scala.collection.mutable.HashMap.foreachEntry(HashMap.scala:40)
at scala.collection.mutable.HashMap$$anon$1.foreach(HashMap.scala:103)
at scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:732)
at org.apache.spark.util.FieldAccessFinder$$anon$3.visitMethodInsn(ClosureCleaner.scala:432)
at org.apache.xbean.asm5.ClassReader.a(Unknown Source)
at org.apache.xbean.asm5.ClassReader.b(Unknown Source)
at org.apache.xbean.asm5.ClassReader.accept(Unknown Source)
at org.apache.xbean.asm5.ClassReader.accept(Unknown Source)
at org.apache.spark.util.ClosureCleaner$$anonfun$org$apache$spark$util$ClosureCleaner$$clean$14.apply(ClosureCleaner.scala:262)
at org.apache.spark.util.ClosureCleaner$$anonfun$org$apache$spark$util$ClosureCleaner$$clean$14.apply(ClosureCleaner.scala:261)
at scala.collection.immutable.List.foreach(List.scala:381)
at org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$clean(ClosureCleaner.scala:261)
at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:159)
at org.apache.spark.SparkContext.clean(SparkContext.scala:2292)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2066)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2092)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:939)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
at org.apache.spark.rdd.RDD.collect(RDD.scala:938)
at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:153)
at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
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)
I followed this solution for similar problem, (ERROR WHILE RUNNING collect() in PYSPARK) installed latest Java, but still of no use.
What to do?

spark has some compatibility issues with the current latest version of java. The best solution for the moment is
uninstall Java 10
install Java 8 instead

Could not write dataframe to S3 in pyspark

I am trying to run spark locally to upload csv/parquet files to S3. Able to read data from S3 with the PySpark
but could not write the file to S3.
Traceback (most recent call last):
File "", line 1, in
runfile('C:/Users/work/dataload/sample_write.py', wdir='C:/Users/work/dataload')
File "C:\ProgramData\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 705, in runfile
execfile(filename, namespace)
File "C:\ProgramData\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 102, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)
File "C:/Users/work/dataload/sample_write.py", line 47, in
df2.coalesce(1).write.option("header", "true").csv("s3n://bucket-name/filename.csv", mode="append")
File "C:\ProgramData\Anaconda3\lib\site-packages\pyspark\sql\readwriter.py", line 885, in csv
self._jwrite.csv(path)
File "C:\ProgramData\Anaconda3\lib\site-packages\py4j\java_gateway.py", line 1257, in __call__
answer, self.gateway_client, self.target_id, self.name)
File "C:\ProgramData\Anaconda3\lib\site-packages\pyspark\sql\utils.py", line 63, in deco
return f(*a, **kw)
File "C:\ProgramData\Anaconda3\lib\site-packages\py4j\protocol.py", line 328, in get_return_value
format(target_id, ".", name), value)
Py4JJavaError: An error occurred while calling o59.csv.
: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:224)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:154)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:104)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:102)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:122)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:654)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:654)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:654)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:273)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:267)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:225)
at org.apache.spark.sql.DataFrameWriter.csv(DataFrameWriter.scala:642)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
at java.lang.reflect.Method.invoke(Unknown Source)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Unknown Source)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 2.0 failed 1 times, most recent failure: Lost task 0.0 in stage 2.0 (TID 2, localhost, executor driver): org.apache.spark.SparkException: Task failed while writing rows.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:285)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:197)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:196)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
at java.lang.Thread.run(Unknown Source)
Caused by: java.lang.UnsatisfiedLinkError: org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Ljava/lang/String;I)Z
at org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Native Method)
at org.apache.hadoop.io.nativeio.NativeIO$Windows.access(NativeIO.java:609)
at org.apache.hadoop.fs.FileUtil.canRead(FileUtil.java:977)
at org.apache.hadoop.util.DiskChecker.checkAccessByFileMethods(DiskChecker.java:187)
at org.apache.hadoop.util.DiskChecker.checkDirAccess(DiskChecker.java:174)
at org.apache.hadoop.util.DiskChecker.checkDir(DiskChecker.java:108)
at org.apache.hadoop.fs.LocalDirAllocator$AllocatorPerContext.confChanged(LocalDirAllocator.java:285)
at org.apache.hadoop.fs.LocalDirAllocator$AllocatorPerContext.getLocalPathForWrite(LocalDirAllocator.java:344)
at org.apache.hadoop.fs.LocalDirAllocator$AllocatorPerContext.createTmpFileForWrite(LocalDirAllocator.java:416)
at org.apache.hadoop.fs.LocalDirAllocator.createTmpFileForWrite(LocalDirAllocator.java:198)
at org.apache.hadoop.fs.s3native.NativeS3FileSystem$NativeS3FsOutputStream.newBackupFile(NativeS3FileSystem.java:263)
at org.apache.hadoop.fs.s3native.NativeS3FileSystem$NativeS3FsOutputStream.(NativeS3FileSystem.java:245)
at org.apache.hadoop.fs.s3native.NativeS3FileSystem.create(NativeS3FileSystem.java:412)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:911)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:892)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:789)
at org.apache.spark.sql.execution.datasources.CodecStreams$.createOutputStream(CodecStreams.scala:81)
at org.apache.spark.sql.execution.datasources.CodecStreams$.createOutputStreamWriter(CodecStreams.scala:92)
at org.apache.spark.sql.execution.datasources.csv.CsvOutputWriter.(CSVFileFormat.scala:149)
at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat$$anon$1.newInstance(CSVFileFormat.scala:77)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$SingleDirectoryWriteTask.newOutputWriter(FileFormatWriter.scala:367)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$SingleDirectoryWriteTask.execute(FileFormatWriter.scala:378)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:269)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:267)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1414)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:272)
8 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1602)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1590)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1589)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1589)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1823)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1772)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1761)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2034)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:194)
31 more
Caused by: org.apache.spark.SparkException: Task failed while writing rows.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:285)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:197)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:196)
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.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
1 more
Caused by: java.lang.UnsatisfiedLinkError: org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Ljava/lang/String;I)Z
at org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Native Method)
at org.apache.hadoop.io.nativeio.NativeIO$Windows.access(NativeIO.java:609)
at org.apache.hadoop.fs.FileUtil.canRead(FileUtil.java:977)
at org.apache.hadoop.util.DiskChecker.checkAccessByFileMethods(DiskChecker.java:187)
at org.apache.hadoop.util.DiskChecker.checkDirAccess(DiskChecker.java:174)
at org.apache.hadoop.util.DiskChecker.checkDir(DiskChecker.java:108)
at org.apache.hadoop.fs.LocalDirAllocator$AllocatorPerContext.confChanged(LocalDirAllocator.java:285)
at org.apache.hadoop.fs.LocalDirAllocator$AllocatorPerContext.getLocalPathForWrite(LocalDirAllocator.java:344)
at org.apache.hadoop.fs.LocalDirAllocator$AllocatorPerContext.createTmpFileForWrite(LocalDirAllocator.java:416)
at org.apache.hadoop.fs.LocalDirAllocator.createTmpFileForWrite(LocalDirAllocator.java:198)
at org.apache.hadoop.fs.s3native.NativeS3FileSystem$NativeS3FsOutputStream.newBackupFile(NativeS3FileSystem.java:263)
at org.apache.hadoop.fs.s3native.NativeS3FileSystem$NativeS3FsOutputStream.(NativeS3FileSystem.java:245)
at org.apache.hadoop.fs.s3native.NativeS3FileSystem.create(NativeS3FileSystem.java:412)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:911)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:892)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:789)
at org.apache.spark.sql.execution.datasources.CodecStreams$.createOutputStream(CodecStreams.scala:81)
at org.apache.spark.sql.execution.datasources.CodecStreams$.createOutputStreamWriter(CodecStreams.scala:92)
at org.apache.spark.sql.execution.datasources.csv.CsvOutputWriter.(CSVFileFormat.scala:149)
at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat$$anon$1.newInstance(CSVFileFormat.scala:77)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$SingleDirectoryWriteTask.newOutputWriter(FileFormatWriter.scala:367)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$SingleDirectoryWriteTask.execute(FileFormatWriter.scala:378)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:269)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:267)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1414)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:272)
8 more
Any inputs on what might be the issue?

Reading google bucket files in spark

I am trying to read google bucket file in spark/ I have done the necessary settings as described in https://cloud.google.com/dataproc/docs/connectors/install-storage-connector. Also, the result of
hadoop fs -ls gs://directory-name/
is as expected. But when reading the same directory from a python/spark script as
rdd = sc.textFile("gs://directory-name/")
I am getting the error with following stack trace:
File "/home/hadoopuser/spark/python/lib/pyspark.zip/pyspark/rdd.py", line 1312, in take
File "/home/hadoopuser/spark/python/lib/pyspark.zip/pyspark/rdd.py", line 384, in getNumPartitions
File "/home/hadoopuser/spark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py", line 1133, in __call__
File "/home/hadoopuser/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 o21.partitions.
: java.io.IOException: Error getting access token from metadata server at: http://metadata/computeMetadata/v1/instance/service-accounts/default/token
at com.google.cloud.hadoop.util.CredentialFactory.getCredentialFromMetadataServiceAccount(CredentialFactory.java:207)
at com.google.cloud.hadoop.util.CredentialConfiguration.getCredential(CredentialConfiguration.java:70)
at com.google.cloud.hadoop.fs.gcs.GoogleHadoopFileSystemBase.configure(GoogleHadoopFileSystemBase.java:1816)
at com.google.cloud.hadoop.fs.gcs.GoogleHadoopFileSystemBase.initialize(GoogleHadoopFileSystemBase.java:1003)
at com.google.cloud.hadoop.fs.gcs.GoogleHadoopFileSystemBase.initialize(GoogleHadoopFileSystemBase.java:966)
at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2669)
at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:94)
at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2703)
at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2685)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:373)
at org.apache.hadoop.fs.Path.getFileSystem(Path.java:295)
at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:258)
at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:229)
at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:315)
at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:202)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:250)
at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:250)
at org.apache.spark.api.java.JavaRDDLike$class.partitions(JavaRDDLike.scala:61)
at org.apache.spark.api.java.AbstractJavaRDDLike.partitions(JavaRDDLike.scala:45)
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.net.UnknownHostException: metadata
at java.net.AbstractPlainSocketImpl.connect(AbstractPlainSocketImpl.java:184)
at java.net.SocksSocketImpl.connect(SocksSocketImpl.java:392)
at java.net.Socket.connect(Socket.java:589)
at sun.net.NetworkClient.doConnect(NetworkClient.java:175)
at sun.net.www.http.HttpClient.openServer(HttpClient.java:463)
at sun.net.www.http.HttpClient.openServer(HttpClient.java:558)
at sun.net.www.http.HttpClient.<init>(HttpClient.java:242)
at sun.net.www.http.HttpClient.New(HttpClient.java:339)
at sun.net.www.http.HttpClient.New(HttpClient.java:357)
at sun.net.www.protocol.http.HttpURLConnection.getNewHttpClient(HttpURLConnection.java:1202)
at sun.net.www.protocol.http.HttpURLConnection.plainConnect0(HttpURLConnection.java:1138)
at sun.net.www.protocol.http.HttpURLConnection.plainConnect(HttpURLConnection.java:1032)
at sun.net.www.protocol.http.HttpURLConnection.connect(HttpURLConnection.java:966)
at com.google.api.client.http.javanet.NetHttpRequest.execute(NetHttpRequest.java:93)
at com.google.api.client.http.HttpRequest.execute(HttpRequest.java:972)
at com.google.cloud.hadoop.util.CredentialFactory$ComputeCredentialWithRetry.executeRefreshToken(CredentialFactory.java:158)
at com.google.api.client.auth.oauth2.Credential.refreshToken(Credential.java:489)
at com.google.cloud.hadoop.util.CredentialFactory.getCredentialFromMetadataServiceAccount(CredentialFactory.java:205)
... 36 more
I have possibly all the links I have found but could not solve it. ANy suggestions would be appreciated.

It looks like Spark is not picking up your core-site.xml. You can
Copy it to $SPARK_HOME/conf or
Set HADOOP_CONF_DIR (for example in $SPARK_HOME/conf/spark-env.sh).