i'm trying to learn a big data online course and came across the problem while installing apache spark.
i've done everything correctly but when i try to run spark-submit it seems that there is an issue with java i guess.
when i run this:
(base) C:\SparkCourse>spark-submit ratings-counter.py
i get this error:
Exception in thread "main" java.lang.ExceptionInInitializerError
at org.apache.spark.unsafe.array.ByteArrayMethods.<clinit>(ByteArrayMethods.java:54)
at org.apache.spark.internal.config.package$.<init>(package.scala:1095)
at org.apache.spark.internal.config.package$.<clinit>(package.scala)
at org.apache.spark.deploy.SparkSubmitArguments.$anonfun$loadEnvironmentArguments$3(SparkSubmitArguments.scala:157)
at scala.Option.orElse(Option.scala:447)
at org.apache.spark.deploy.SparkSubmitArguments.loadEnvironmentArguments(SparkSubmitArguments.scala:157)
at org.apache.spark.deploy.SparkSubmitArguments.<init>(SparkSubmitArguments.scala:115)
at org.apache.spark.deploy.SparkSubmit$$anon$2$$anon$3.<init>(SparkSubmit.scala:1022)
at org.apache.spark.deploy.SparkSubmit$$anon$2.parseArguments(SparkSubmit.scala:1022)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:85)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:1039)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:1048)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.reflect.InaccessibleObjectException: Unable to make private java.nio.DirectByteBuffer(long,int) accessible: module java.base does not "opens java.nio" to unnamed module #5b94b04d
at java.base/java.lang.reflect.AccessibleObject.checkCanSetAccessible(AccessibleObject.java:354)
at java.base/java.lang.reflect.AccessibleObject.checkCanSetAccessible(AccessibleObject.java:297)
at java.base/java.lang.reflect.Constructor.checkCanSetAccessible(Constructor.java:188)
at java.base/java.lang.reflect.Constructor.setAccessible(Constructor.java:181)
at org.apache.spark.unsafe.Platform.<clinit>(Platform.java:56)
... 13 more
any ideas?
Cheers!
I reinstalled windows and started everything from scratch.
Installed jdk version 8, and this version of spark "spark-3.0.3-bin-hadoop2.7.tgz". Indicated all the paths correctly and. It worked as i can open pyspark shell and do spark-submit for example, but there still is a lot of text in the cmd that i can't get rid of.
Related
Downloaded the latest Spark version because of the fix for
ERROR AsyncEventQueue:70 - Dropping event from queue appStatus.
After setting environment variables and running the same code in PyCharm, I'm getting this error, which I can't find a solution of.
Exception in thread "main" java.util.NoSuchElementException: key not found: _PYSPARK_DRIVER_CONN_INFO_PATH
at scala.collection.MapLike$class.default(MapLike.scala:228)
at scala.collection.AbstractMap.default(Map.scala:59)
at scala.collection.MapLike$class.apply(MapLike.scala:141)
at scala.collection.AbstractMap.apply(Map.scala:59)
at org.apache.spark.api.python.PythonGatewayServer$.main(PythonGatewayServer.scala:64)
at org.apache.spark.api.python.PythonGatewayServer.main(PythonGatewayServer.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:894)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:198)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:228)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:137)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Any help?
i met this question too. The next is what i do, hoping to help you:
1 . find your spark version, my spark's version is 2.4.3;
2 . find your pyspark version, my pyspark,version is 2.2.0;
3 . reinstall your pyspark as same as the spark's version
pip install pyspark==2.4.3
Then everything is ok. Hope to help you.
I am using Pyspark 2.3.1 with pycharm 2018.1.4 and facing similar issue on my windows machine.
When I run this python file using spark-submit, it get executed successfully.
I have followed below steps
Created a new project in pycharm, lets call it Demo
Goto Settings->Project:Demo->Project Interpreter. Make sure project interpreter is python 2.7
Goto Settings->Project:Demo->Project Structure. Add Content Root.
I have added two content root one pointing to directory where content of apache spark is present and the other location is of py4j-0.10.7.src.zip
In my case these locations are
C:\apache-spark
and
C:\apache-spark\python\lib\py4j-0.10.7-src.zip
Created new python file(Demo1.py) and pasted below content inside it.
from pyspark import SparkContext
sc = SparkContext(master="local", appName="Spark Demo")
rdd = sc.textFile("C:/apache-spark/README.md")
wordsRDD = rdd.flatMap(lambda words: words.split(" "))
wordsRDD = wordsRDD.map(lambda word: (word, 1))
wordsCount = wordsRDD.reduceByKey(lambda x, y: x+y)
print wordsCount.collect()
Running this python file on pycharm gives below error
Exception in thread "main" java.util.NoSuchElementException: key not
found: _PYSPARK_DRIVER_CONN_INFO_PATH
Where as same program when executed from command prompt yields correct result.
C:\Users\manish>spark-submit C:\Demo\demo1.py
Any suggestions to solve this problem?
I have had a similar exception. My problem was running jupyter and spark with different users. When I run them with the same user problem is solved.
Details;
When I updated spark from v2.2.0 to v2.3.1 then run the Jupyter notebook, the error log was as follows;
Exception in thread "main" java.util.NoSuchElementException: key not found: _PYSPARK_DRIVER_CONN_INFO_PATH
at scala.collection.MapLike$class.default(MapLike.scala:228)
at scala.collection.AbstractMap.default(Map.scala:59)
at scala.collection.MapLike$class.apply(MapLike.scala:141)
at scala.collection.AbstractMap.apply(Map.scala:59)
at org.apache.spark.api.python.PythonGatewayServer$.main(PythonGatewayServer.scala:64)
at org.apache.spark.api.python.PythonGatewayServer.main(PythonGatewayServer.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 org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:894)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:198)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:228)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:137)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
When I googling I encountered the following link;
spark-commits mailing list archives
In the code
/core/src/main/scala/org/apache/spark/api/python/PythonGatewayServer.scala
there is a change
+ // Communicate the connection information back to the python process by writing the
+ // information in the requested file. This needs to match the read side in java_gateway.py.
+ val connectionInfoPath = new File(sys.env("_PYSPARK_DRIVER_CONN_INFO_PATH"))
+ val tmpPath = Files.createTempFile(connectionInfoPath.getParentFile().toPath(),
+ "connection", ".info").toFile()
According to this change it is created a temp dir and a file in it. My problem was running jupyter and spark with different users. Because of this I think the process could not created the temp file. When I run them with the same user problem solved. I hope it helps.
I had this problem too, and it ended up being the pyspark code I was importing/running from PyCharm was still the spark 2.2 install instead of the spark 2.3 installation that I had updated SPARK_HOME to point to.
Specifically, I added spark-2.2 to my PyCharm project structure and then marked it's python folder a "Sources" so PyCharm would recognize all it's symbols. So the PyCharm code was importing from there, instead of spark-2.3, and the older code didn't set the _PYSPARK_DRIVER_CONN_INFO_PATH environment variable.
If Vezir's answer didn't fix your case, try tracing into the creation SparkContext and compare carefully the path that is being read from as opposed to path of your spark install. Similarly, if you installed pyspark into your python project via pip, make sure you installed 2.3.1 to match your installed spark version.
This can happen when you are running spark 2.3.1 jars with an older version of pyspark (eg: 2.3.0)
The class edu.mit.csail.sdg.alloy4whole.ExampleUsingTheCompiler provides an example of how to execute Alloy commands from the command-line. The backend solver used in this example is Sat4J. I would love to change the solver to one of the faster ones like Plingeling. Unfortunately I can't work out how to achieve this. Simply changing the line
options.solver = A4Options.SatSolver.SAT4J;
into
options.solver = A4Options.SatSolver.PLingelingJNI;
doesn't work; I get the following error message:
Exception in thread "main" Fatal error:
Unknown exception occurred: kodkod.engine.AbortedException: kodkod.engine.satlab.SATAbortedException: java.io.IOException: Cannot run program "plingeling": error=2, No such file or directory
at edu.mit.csail.sdg.alloy4compiler.translator.TranslateAlloyToKodkod.executeCommand(TranslateAlloyToKodkod.java:1079)
at edu.mit.csail.sdg.alloy4compiler.translator.TranslateAlloyToKodkod.executeCommand(TranslateAlloyToKodkod.java:1065)
at edu.mit.csail.sdg.alloy4compiler.translator.TranslateAlloyToKodkod.execute_command(TranslateAlloyToKodkod.java:381)
at edu.mit.csail.sdg.alloy4whole.ExampleUsingTheCompiler.main(ExampleUsingTheCompiler.java:72)
Caused by: kodkod.engine.AbortedException: kodkod.engine.satlab.SATAbortedException: java.io.IOException: Cannot run program "plingeling": error=2, No such file or directory
at kodkod.engine.Solver.solve(Solver.java:147)
at edu.mit.csail.sdg.alloy4compiler.translator.A4Solution.solve(A4Solution.java:1058)
at edu.mit.csail.sdg.alloy4compiler.translator.TranslateAlloyToKodkod.executeCommand(TranslateAlloyToKodkod.java:1070)
... 3 more
Caused by: kodkod.engine.satlab.SATAbortedException: java.io.IOException: Cannot run program "plingeling": error=2, No such file or directory
at kodkod.engine.satlab.ExternalSolver.solve(ExternalSolver.java:255)
at kodkod.engine.Solver.solve(Solver.java:140)
... 5 more
Caused by: java.io.IOException: Cannot run program "plingeling": error=2, No such file or directory
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1048)
at java.lang.Runtime.exec(Runtime.java:620)
at java.lang.Runtime.exec(Runtime.java:485)
at kodkod.engine.satlab.ExternalSolver.solve(ExternalSolver.java:221)
... 6 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:248)
at java.lang.ProcessImpl.start(ProcessImpl.java:134)
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1029)
... 9 more
The Alloy GUI seems to get around this problem by copying some files (including the plingeling executable) into the right place before it runs.
Thanks to the questions linked from Tarciana's answer, I successfully got this working on my machine (a Mac).
In order to use solvers like Plingeling that are distributed as
executables, one should run
export PATH=<path_to_solver_binaries_and_libraries>:$PATH
before running java.
In order to use solvers like MiniSat that are distributed as
dynamic libraries, one should add the argument
-Djava.library.path=<path_to_solver_binaries_and_libraries>
when running java.
I was with the same problem than yours as shown in my question:
Execution Error when change the SATSolver from SAT4J to MiniSAT
The solution pointed by #Aleksandar in a previous question, see
Alloy API resulting in java.lang.UnsatisfiedLinkError
, works for me in an older ubuntu version (10.0.0) but it does not work in earlier ubuntu versions (such as 14.04 or 16.04).
When choosing another solvers such as zchaff or minisatprover i observe that the error changes, for instance:
"The required JNI library cannot be found: java.lang.UnsatisfiedLinkError: no zchaffx5 in java.library.path"
and for all the other solvers it seems that the library it is looking for (ex.: zchaffx5) is more updated than the existing one in the x86-linux folder (inside the alloy-4.2.jar): zchaffx1. I think the existing libraries for the other solvers are outdated. If you achieve to find a solution for this problem, please let us know.
I've downloaded a prebuilt version of Spark on my mac (OS Mavericks), but when I try to open an interactive shell, typing bin/pyspark, I get the following error:
Exception in thread "main" java.lang.NoClassDefFoundError: org/apache/spark/launcher/Main
Caused by: java.lang.ClassNotFoundException: org.apache.spark.launcher.Main
at java.net.URLClassLoader$1.run(URLClassLoader.java:202)
at java.security.AccessController.doPrivileged(Native Method)
at java.net.URLClassLoader.findClass(URLClassLoader.java:190)
at java.lang.ClassLoader.loadClass(ClassLoader.java:306)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:301)
at java.lang.ClassLoader.loadClass(ClassLoader.java:247)
I have googled every part of the error and checkout out some other stack overflow threads, but I can't find anything that addresses this error. Any idea what's going on/how to fix it?
One idea I have is that scala is a dependency that I need to download separately...but I really don't know.
I had the same issue before, and it turned out to be a permission issue and I'm under user who has no access to the spark files (root downloaded spark).
Another possibility is, you downloaded the source code and did not build the project from source code :P
Hope it helps.
I've downloaded the prebuild version of spark 1.4.0 without hadoop (with user-provided Haddop). When I ran the spark-shell command, I got this error:
> Exception in thread "main" java.lang.NoClassDefFoundError: org/apache/hadoop/fs/
FSDataInputStream
at org.apache.spark.deploy.SparkSubmitArguments$$anonfun$mergeDefaultSpa
rkProperties$1.apply(SparkSubmitArguments.scala:111)
at org.apache.spark.deploy.SparkSubmitArguments$$anonfun$mergeDefaultSpa
rkProperties$1.apply(SparkSubmitArguments.scala:111)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.deploy.SparkSubmitArguments.mergeDefaultSparkPropert
ies(SparkSubmitArguments.scala:111)
at org.apache.spark.deploy.SparkSubmitArguments.<init>(SparkSubmitArgume
nts.scala:97)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:106)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.ClassNotFoundException: org.apache.hadoop.fs.FSDataInputStr
eam
at java.net.URLClassLoader$1.run(URLClassLoader.java:366)
at java.net.URLClassLoader$1.run(URLClassLoader.java:355)
at java.security.AccessController.doPrivileged(Native Method)
at java.net.URLClassLoader.findClass(URLClassLoader.java:354)
at java.lang.ClassLoader.loadClass(ClassLoader.java:425)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:308)
at java.lang.ClassLoader.loadClass(ClassLoader.java:358)
... 7 more
I've searched on Internet, it is said that HADOOP_HOME has not been set yet in spark-env.cmd. But I cannot find spark-env.cmd in the spark installation folder.
I've traced the spark-shell command and it seems that there are no HADOOP_CONFIG in there. I've tried to add the HADOOP_HOME on environment variable but it still give the same exception.
Actually I don't really using the hadoop. I downloaded hadoop as a workaround as suggested in this question
I am using windows 8 and scala 2.10.
Any help will be appreciated. Thanks.
The "without Hadoop" in the Spark's build name is misleading: it means the build is not tied to a specific Hadoop distribution, not that it is meant to run without it: the user should indicate where to find Hadoop (see https://spark.apache.org/docs/latest/hadoop-provided.html)
One clean way to fix this issue is to:
Obtain Hadoop Windows binaries. Ideally build them, but this is painful (for some hints see: Hadoop on Windows Building/ Installation Error). Otherwise Google some up, for instance currently you can download 2.6.0 from here: http://www.barik.net/archive/2015/01/19/172716/
Create a spark-env.cmd file looking like this (modify Hadoop path to match your installation):
#echo off
set HADOOP_HOME=D:\Utils\hadoop-2.7.1
set PATH=%HADOOP_HOME%\bin;%PATH%
set SPARK_DIST_CLASSPATH=<paste here the output of %HADOOP_HOME%\bin\hadoop classpath>
Put this spark-env.cmd either in a conf folder located at the same level as your Spark base folder (which may look weird), or in a folder indicated by the SPARK_CONF_DIR environment variable.
I had the same problem, in fact it's mentioned on the Getting started page of Spark how to handle it:
### in conf/spark-env.sh ###
# If 'hadoop' binary is on your PATH
export SPARK_DIST_CLASSPATH=$(hadoop classpath)
# With explicit path to 'hadoop' binary
export SPARK_DIST_CLASSPATH=$(/path/to/hadoop/bin/hadoop classpath)
# Passing a Hadoop configuration directory
export SPARK_DIST_CLASSPATH=$(hadoop --config /path/to/configs classpath)
If you want to use your own hadoop follow one of the 3 options, copy and paste it into spark-env.sh file :
1- if you have the hadoop on your PATH
2- you want to show hadoop binary explicitly
3- you can also show hadoop configuration folder
http://spark.apache.org/docs/latest/hadoop-provided.html
I too had the issue,
export SPARK_DIST_CLASSPATH=`hadoop classpath`
resolved the issue.
I ran into the same error when trying to get familiar with spark. My understanding of the error message is that while spark doesn't need a hadoop cluster to run, it does need some of the hadoop classes. Since I was just playing around with spark and didn't care what version of hadoop libraries are used, I just downloaded a spark binary pre-built with a version of hadoop (2.6) and things started working fine.
linux
ENV SPARK_DIST_CLASSPATH="$HADOOP_HOME/etc/hadoop/*:$HADOOP_HOME/share/hadoop/common/lib/*:$HADOOP_HOME/share/hadoop/common/*:$HADOOP_HOME/share/hadoop/hdfs/*:$HADOOP_HOME/share/hadoop/hdfs/lib/*:$HADOOP_HOME/share/hadoop/hdfs/*:$HADOOP_HOME/share/hadoop/yarn/lib/*:$HADOOP_HOME/share/hadoop/yarn/*:$HADOOP_HOME/share/hadoop/mapreduce/lib/*:$HADOOP_HOME/share/hadoop/mapreduce/*:$HADOOP_HOME/share/hadoop/tools/lib/*"
windows
set SPARK_DIST_CLASSPATH=%HADOOP_HOME%\etc\hadoop\*;%HADOOP_HOME%\share\hadoop\common\lib\*;%HADOOP_HOME%\share\hadoop\common\*;%HADOOP_HOME%\share\hadoop\hdfs\*;%HADOOP_HOME%\share\hadoop\hdfs\lib\*;%HADOOP_HOME%\share\hadoop\hdfs\*;%HADOOP_HOME%\share\hadoop\yarn\lib\*;%HADOOP_HOME%\share\hadoop\yarn\*;%HADOOP_HOME%\share\hadoop\mapreduce\lib\*;%HADOOP_HOME%\share\hadoop\mapreduce\*;%HADOOP_HOME%\share\hadoop\tools\lib\*
Enter into SPARK_HOME -> conf
copy spark-env.sh.template file and rename it to spark-env.sh
Inside this file you can set the parameters for spark.
Run below from your package dir just before running spark-submit -
export SPARK_DIST_CLASSPATH=`hadoop classpath`
I finally find a solution to remove the exception.
In spark-class2.cmd, add :
set HADOOP_CLASS1=%HADOOP_HOME%\share\hadoop\common\*
set HADOOP_CLASS2=%HADOOP_HOME%\share\hadoop\common\lib\*
set HADOOP_CLASS3=%HADOOP_HOME%\share\hadoop\mapreduce\*
set HADOOP_CLASS4=%HADOOP_HOME%\share\hadoop\mapreduce\lib\*
set HADOOP_CLASS5=%HADOOP_HOME%\share\hadoop\yarn\*
set HADOOP_CLASS6=%HADOOP_HOME%\share\hadoop\yarn\lib\*
set HADOOP_CLASS7=%HADOOP_HOME%\share\hadoop\hdfs\*
set HADOOP_CLASS8=%HADOOP_HOME%\share\hadoop\hdfs\lib\*
set CLASSPATH=%HADOOP_CLASS1%;%HADOOP_CLASS2%;%HADOOP_CLASS3%;%HADOOP_CLASS4%;%HADOOP_CLASS5%;%HADOOP_CLASS6%;%HADOOP_CLASS7%;%HADOOP_CLASS8%;%LAUNCH_CLASSPATH%
Then, change :
"%RUNNER%" -cp %CLASSPATH%;%LAUNCH_CLASSPATH% org.apache.spark.launcher.Main %* > %LAUNCHER_OUTPUT%
to :
"%RUNNER%" -Dhadoop.home.dir=*hadoop-installation-folder* -cp %CLASSPATH% %JAVA_OPTS% %*
It works fine with me, but I'm not sure this is the best solution.
You should add these jars in you code:
common-cli-1.2.jar
hadoop-common-2.7.2.jar
Thank you so much. That worked great, but I had to add the spark jars to the classpath as well:
;c:\spark\lib*
Also, the last line of the cmd file is missing the word "echo"; so it should say:
echo %SPARK_CMD%
I had the same issue ....Exception in thread "main" java.lang.NoClassDefFoundError: org/apache/hadoop/fs/
FSDataInputStream
at org.apache.spark.deploy.SparkSubmitArguments$$anonfun$mergeDefaultSpa
rkProperties$1.apply(SparkSubmitArguments.scala:111)...
Then I realized that I had installed the spark version without hadoop. I installed the "with-hadoop" version the problem went away.
for my case
running spark job locally differs from running it on cluster. on cluster you might have a different dependency/context to follow. so essentially in your pom.xml you might have dependencies declared as provided.
when running locally, you don't need these provided dependencies. just uncomment them and rebuild again.
I encountered the same error. I wanted to install spark on my windows PC and therefore downloaded the without hadoop version of spark, but turns out you need the hadoop libraries! so download any hadoop spark version and set the environment variables.
I got this error because the file was copied from Windows.
Resolve it using
dos2unix file_name
I think you need spark-core dependency of maven. It worked fine for me.
I used:
export SPARK_HOME=/opt/cloudera/parcels/SPARK2/lib/spark2
export HADOOP_MAPRED_HOME=/opt/cloudera/parcels/CDH/lib/hadoop-0.20-mapreduce
It's work for me!
I added hadoop-client-runtime-3.3.2.jar to my user library.
After installing CRF++ toolkit, I try to run the program "test.java" under CRF++-0.54/java folder. For this, I type :
java -cp /home/amira/CRF++-0.54/java/org/chasen/crfpp test
But, I have the following error:
Exception in thread "main" java.lang.NoClassDefFoundError: test
Caused by: java.lang.ClassNotFoundException: test
at java.net.URLClassLoader$1.run(URLClassLoader.java:217)
at java.security.AccessController.doPrivileged(Native Method)
at java.net.URLClassLoader.findClass(URLClassLoader.java:205)
at java.lang.ClassLoader.loadClass(ClassLoader.java:321)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:294)
at java.lang.ClassLoader.loadClass(ClassLoader.java:266)
Could not find the main class: test. Program will exit.
In the README file, there is the command java -classpath CRFPP.jar test -d ../dic. But, the problem is that I don't find the classpath of CRFPP.jar. Moreover, I don't understand what ../dic in the command refer to.
Make changes in the Makefile of the java directory as per your machine settings.
Give the correct Java path and the compiler you are using using.
Run make java in the swig directory.
Run make all in the java directory.
Before running make in the java directory, ensure that you have the model file in the proper location, otherwise it won't open the model file.
Run make test in the java directory.