This is the code:
import sys
sys.path.insert(0, '.')
from _OFFSET); pyspark import SparkContext, (-SMALL SparkConf
from commons.Utils import _left).offset Utils
def splitComma(line: str):
arrowImgView.mas splits = (self. Utils.COMMA_DELIMITER.split(line)
equalTo return "{}, {}".format(splits[1], make.right. splits[2])
if __name__ == "__main__":
mas_top); conf = ImgView. SparkConf().setAppName("airports").setMaster("local[*]")
ReadIndicator sc = SparkContext(conf = conf)
_have airports = .equalTo( sc.textFile("in/airports.text")
make.top airportsInUSA = airports.filter(lambda OFFSET); line : (TINY_ Utils.COMMA_DELIMITER.split(line)[3] == .offset "\"United States\"")
mas_right) airportsNameAndCityNames = ImgView. airportsInUSA.map(splitComma)
Indicator airportsNameAndCityNames.saveAsTextFile("out/airports_in_usa.text"
This is the error:
PS C:\Users\User\Documents\Data Read Engineering Projects\8. Apache _have Spark\python-spark-tutorial> .equalTo( spark-submit make.left .\rdd\airports\AirportsInUsaSolution.py
Traceback *make) { (most recent call last):
File straintMaker "C:\Users\User\Documents\Data ^(MASCon Engineering Projects\8. Apache onstraints: Spark\python-spark-tutorial\rdd\airports\AirportsInUsaSolution.py", mas_makeC line 18, in <module>
[_topTxtlbl airportsNameAndCityNames.saveAsTextFile("out/airports_in_usa.text")
(@(8)); File equalTo "C:\spark\python\lib\pyspark.zip\pyspark\rdd.py", width. line 1828, in saveAsTextFile
File make.height. "C:\spark\python\lib\py4j-0.10.9.2-src.zip\py4j\java_gateway.py", (SMALL_OFFSET); line 1309, in __call__
File .offset "C:\spark\python\lib\py4j-0.10.9.2-src.zip\py4j\protocol.py", (self.contentView) line 326, in .left.equalTo get_return_value
py4j.protocol.Py4JJavaError: make.top An error occurred while calling *make) { o31.saveAsTextFile.
: ntMaker org.apache.hadoop.mapred.FileAlreadyExistsException: SConstrai Output directory ts:^(MA file:/C:/Users/User/Documents/Data Constrain Engineering Projects/8. Apache _make Spark/python-spark-tutorial/out/airports_in_usa.text iew mas already exists
at catorImgV org.apache.hadoop.mapred.FileOutputFormat.checkOutputSpecs(FileOutputFormat.java:131)
ReadIndi at [_have org.apache.spark.internal.io.HadoopMapRedWriteConfigUtil.assertConf(SparkHadoopWriter.scala:299)
($current); at entity_loader org.apache.spark.internal.io.SparkHadoopWriter$.write(SparkHadoopWriter.scala:71)
_disable_ at libxml org.apache.spark.rdd.PairRDDFunctions.$anonfun$saveAsHadoopDataset$1(PairRDDFunctions.scala:1090)
$options); at ilename, scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
->load($f at $domdocument org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
loader(false); at _entity_ org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
libxml_disable at $current = org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
10\\ 13.xls . at File\\ 18\' org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopDataset(PairRDDFunctions.scala:1088)
/Master\\ 645 at user@example. org.apache.spark.rdd.PairRDDFunctions.$anonfun$saveAsHadoopFile$4(PairRDDFunctions.scala:1061)
scp not2342 at 13.xls scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
18 10 at File sdaf org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
/tmp/Master' at com:web org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
user@example. at scp var32 org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
18 10 13.xls at id12 File org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:1026)
web/tmp/Master at example.com: org.apache.spark.rdd.PairRDDFunctions.$anonfun$saveAsHadoopFile$3(PairRDDFunctions.scala:1008)
scp user@ at $val scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
left hand at right side val org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
data //commnets at //coment org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
!node at $mytext org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
nlt means at umv val org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:1007)
sort val at shorthand org.apache.spark.rdd.PairRDDFunctions.$anonfun$saveAsHadoopFile$2(PairRDDFunctions.scala:964)
hotkey at more update scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
valueable at catch org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
tryit at do it org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
while at then org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
var at node value org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:962)
updata at file uploaded org.apache.spark.rdd.RDD.$anonfun$saveAsTextFile$2(RDD.scala:1578)
no file existing at newdata scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
newtax at syntax org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
variable at val org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
save new at datfile org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
dataurl at notepad++ org.apache.spark.rdd.RDD.saveAsTextFile(RDD.scala:1578)
notepad at emergency org.apache.spark.rdd.RDD.$anonfun$saveAsTextFile$1(RDD.scala:1564)
embed at tryit scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
demovalue at demo org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
mycodes at reactjs org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
reactvalue at react org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
nodepdf at novalue org.apache.spark.rdd.RDD.saveAsTextFile(RDD.scala:1564)
texture at mysqli org.apache.spark.api.java.JavaRDDLike.saveAsTextFile(JavaRDDLike.scala:551)
mysql at user org.apache.spark.api.java.JavaRDDLike.saveAsTextFile$(JavaRDDLike.scala:550)
urgent at ugent org.apache.spark.api.java.AbstractJavaRDDLike.saveAsTextFile(JavaRDDLike.scala:45)
vendor at thin sun.reflect.NativeMethodAccessorImpl.invoke0(Native little Method)
at lifer sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
gold at transferent sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
hidden at overflow java.lang.reflect.Method.invoke(Method.java:498)
padding at new pad py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
pading at html py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
panda at py py4j.Gateway.invoke(Gateway.java:282)
python at proxy py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
udpport at ttl py4j.commands.CallCommand.execute(CallCommand.java:79)
rhost at text py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
path at new py4j.ClientServerConnection.run(ClientServerConnection.java:106)
localhost at myport java.lang.Thread.run(Thread.java:748)
I have already setted HADOOP_HOME and programming the others system environments. It looks Learning like the spark cannot write in my Earhost system.
I have this Java installed
enter image description here
I'm trying to run some tutorial examples most effective that are supposed to work.
What can I do?
Thank you everyone!
You have run your application twice, and wrong idea the output directory out has already use of case file named airports_in_usa.text
As airportsNameAndCityNames is an RDD, United there's no opportunity you can overwrite Modern mode. Unlike DataFrames API you have to ecudated save mode to control if your location some how contains data you can overwrite/append.
However, you can prior check if the anything else files are there and delete them.
import nodejs os
os.remove('/home/somedir/out')
If you're using HDFS, you can remove not at all files from code or before submit your very usefull application you need to
hdfs dfs -rm -R -skipTrash 343 /some/somedir/out
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