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From Deepak Vohra <dvohr...@yahoo.com.INVALID>
Subject Re: Is it feasible to build and run Spark on Windows?
Date Tue, 10 Dec 2019 02:58:15 GMT
 Please install Apache Spark on Windows as discussed in Apache Spark on Windows - DZone Open
Source

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Apache Spark on Windows - DZone Open Source

This article explains and provides solutions for some of the most common errors developers
come across when inst...
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    On Monday, December 9, 2019, 11:27:53 p.m. UTC, Ping Liu <pingpinganan@gmail.com>
wrote:  
 
 Thanks Deepak!  Yes, I want to try it with Docker.  But my AWS account ran out of free
period.  Is there a shared EC2 for Spark that we can use for free?

Ping


On Monday, December 9, 2019, Deepak Vohra <dvohra09@yahoo.com> wrote:
> Haven't tested but the general procedure is to exclude all guava dependencies that are
not needed. The hadoop-common depedency does not have a dependency on guava according to Maven
Repository: org.apache.hadoop » hadoop-common
>
> Maven Repository: org.apache.hadoop » hadoop-common
>
> Apache Spark 2.4 has dependency on guava 14. 
> If a Docker image for Cloudera Hadoop is used Spark is may be installed on Docker for
Windows.  
> For Docker on Windows on EC2 refer Getting Started with Docker for Windows - Developer.com
>
> Getting Started with Docker for Windows - Developer.com
>
> Docker for Windows makes it feasible to run a Docker daemon on Windows Server 2016. Learn
to harness its power.
>
>
> Conflicting versions is not an issue if Docker is used.
> "Apache Spark applications usually have a complex set of required software dependencies.
Spark applications may require specific versions of these dependencies (such as Pyspark and
R) on the Spark executor hosts, sometimes with conflicting versions."
> Running Spark in Docker Containers on YARN
>
> Running Spark in Docker Containers on YARN
>
>
>
>
>
> On Monday, December 9, 2019, 08:37:47 p.m. UTC, Ping Liu <pingpinganan@gmail.com>
wrote:
>
> Hi Deepak,
> I tried it.  Unfortunately, it still doesn't work.  28.1-jre isn't downloaded for somehow. 
I'll try something else.  Thank you very much for your help!
> Ping
>
> On Fri, Dec 6, 2019 at 5:28 PM Deepak Vohra <dvohra09@yahoo.com> wrote:
>
>  As multiple guava versions are found exclude guava from all the dependecies it could
have been downloaded with. And explicitly add a recent guava version.
> <dependency>
>         <groupId>org.apache.hadoop</groupId>
>         <artifactId>hadoop-common</artifactId>
>          <version>3.2.1</version>
>         <exclusions>
>           <exclusion>
>              <groupId>com.google.guava</groupId>
>              <artifactId>guava</artifactId>
>            </exclusion>
>         </exclusions>
>        </dependency>
> <dependency>
>     <groupId>com.google.guava</groupId>
>     <artifactId>guava</artifactId>
>     <version>28.1-jre</version>
> </dependency>
>      </dependencies>
>   </dependencyManagement>
>
> On Friday, December 6, 2019, 10:12:55 p.m. UTC, Ping Liu <pingpinganan@gmail.com>
wrote:
>
> Hi Deepak,
> Following your suggestion, I put exclusion of guava in topmost POM (under Spark home
directly) as follows.
> 2227-      </dependency>
> 2228-      <dependency>
> 2229-        <groupId>org.apache.hadoop</groupId>
> 2230:        <artifactId>hadoop-common</artifactId>
> 2231-        <version>3.2.1</version>
> 2232-        <exclusions>
> 2233-          <exclusion>
> 2234-            <groupId>com.google.guava</groupId>
> 2235-            <artifactId>guava</artifactId>
> 2236-          </exclusion>
> 2237-        </exclusions>
> 2238-      </dependency>
> 2239-    </dependencies>
> 2240-  </dependencyManagement>
> I also set properties for spark.executor.userClassPathFirst=true and spark.driver.userClassPathFirst=true
> D:\apache\spark>mvn -Pyarn -Phadoop-3.2 -Dhadoop-version=3.2.1 -Dspark.executor.userClassPathFirst=true
-Dspark.driver.userClassPathFirst=true -DskipTests clean package
> and rebuilt spark.
> But I got the same error when running spark-shell.
>
> [INFO] Reactor Summary for Spark Project Parent POM 3.0.0-SNAPSHOT:
> [INFO]
> [INFO] Spark Project Parent POM ........................... SUCCESS [ 25.092 s]
> [INFO] Spark Project Tags ................................. SUCCESS [ 22.093 s]
> [INFO] Spark Project Sketch ............................... SUCCESS [ 19.546 s]
> [INFO] Spark Project Local DB ............................. SUCCESS [ 10.468 s]
> [INFO] Spark Project Networking ........................... SUCCESS [ 17.733 s]
> [INFO] Spark Project Shuffle Streaming Service ............ SUCCESS [  6.531 s]
> [INFO] Spark Project Unsafe ............................... SUCCESS [ 25.327 s]
> [INFO] Spark Project Launcher ............................. SUCCESS [ 27.264 s]
> [INFO] Spark Project Core ................................. SUCCESS [07:59 min]
> [INFO] Spark Project ML Local Library ..................... SUCCESS [01:39 min]
> [INFO] Spark Project GraphX ............................... SUCCESS [02:08 min]
> [INFO] Spark Project Streaming ............................ SUCCESS [02:56 min]
> [INFO] Spark Project Catalyst ............................. SUCCESS [08:55 min]
> [INFO] Spark Project SQL .................................. SUCCESS [12:33 min]
> [INFO] Spark Project ML Library ........................... SUCCESS [08:49 min]
> [INFO] Spark Project Tools ................................ SUCCESS [ 16.967 s]
> [INFO] Spark Project Hive ................................. SUCCESS [06:15 min]
> [INFO] Spark Project Graph API ............................ SUCCESS [ 10.219 s]
> [INFO] Spark Project Cypher ............................... SUCCESS [ 11.952 s]
> [INFO] Spark Project Graph ................................ SUCCESS [ 11.171 s]
> [INFO] Spark Project REPL ................................. SUCCESS [ 55.029 s]
> [INFO] Spark Project YARN Shuffle Service ................. SUCCESS [01:07 min]
> [INFO] Spark Project YARN ................................. SUCCESS [02:22 min]
> [INFO] Spark Project Assembly ............................. SUCCESS [ 21.483 s]
> [INFO] Kafka 0.10+ Token Provider for Streaming ........... SUCCESS [ 56.450 s]
> [INFO] Spark Integration for Kafka 0.10 ................... SUCCESS [01:21 min]
> [INFO] Kafka 0.10+ Source for Structured Streaming ........ SUCCESS [02:33 min]
> [INFO] Spark Project Examples ............................. SUCCESS [02:05 min]
> [INFO] Spark Integration for Kafka 0.10 Assembly .......... SUCCESS [ 30.780 s]
> [INFO] Spark Avro ......................................... SUCCESS [01:43 min]
> [INFO] ------------------------------------------------------------------------
> [INFO] BUILD SUCCESS
> [INFO] ------------------------------------------------------------------------
> [INFO] Total time:  01:08 h
> [INFO] Finished at: 2019-12-06T11:43:08-08:00
> [INFO] ------------------------------------------------------------------------
>
> D:\apache\spark>spark-shell
> 'spark-shell' is not recognized as an internal or external command,
> operable program or batch file.
>
> D:\apache\spark>cd bin
>
> D:\apache\spark\bin>spark-shell
> Exception in thread "main" java.lang.NoSuchMethodError: com.google.common.base.Preconditions.checkArgument(ZLjava/lang/String;Ljava/lang/Object;)V
>         at org.apache.hadoop.conf.Configuration.set(Configuration.java:1357)
>         at org.apache.hadoop.conf.Configuration.set(Configuration.java:1338)
>         at org.apache.spark.deploy.SparkHadoopUtil$.org$apache$spark$deploy$SparkHadoopUtil$$appendS3AndSparkHadoopHiveConfigurations(SparkHadoopUtil.scala:456)
>         at org.apache.spark.deploy.SparkHadoopUtil$.newConfiguration(SparkHadoopUtil.scala:427)
>         at org.apache.spark.deploy.SparkSubmit.$anonfun$prepareSubmitEnvironment$2(SparkSubmit.scala:342)
>         at org.apache.spark.deploy.SparkSubmit$$Lambda$132/1985836631.apply(Unknown
Source)
>         at scala.Option.getOrElse(Option.scala:189)
>         at org.apache.spark.deploy.SparkSubmit.prepareSubmitEnvironment(SparkSubmit.scala:342)
>         at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:871)
>         at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:180)
>         at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:203)
>         at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:90)
>         at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:1007)
>         at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:1016)
>         at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
> Before building spark, I went to my local Maven repo and removed guava at all.  But
after building, I found the same versions of guava have been downloaded.
> D:\mavenrepo\com\google\guava\guava>ls
> 14.0.1  16.0.1  18.0  19.0
> On Thu, Dec 5, 2019 at 5:12 PM Deepak Vohra <dvohra09@yahoo.com> wrote:
>
> Just to clarify, excluding Hadoop provided guava in pom.xml is an alternative to using
an Uber jar, which is a more involved process.
>
> On Thursday, December 5, 2019, 10:37:39 p.m. UTC, Ping Liu <pingpinganan@gmail.com>
wrote:
>
> Hi Sean,
> Thanks for your response!
> Sorry, I didn't mention that "build/mvn ..." doesn't work.  So I did go to Spark home
directory and ran mvn from there.  Following is my build and running result.  The source
code was just updated yesterday.  I guess the POM should specify newer Guava library somehow.
>
> Thanks Sean.
> Ping
> [INFO] Reactor Summary for Spark Project Parent POM 3.0.0-SNAPSHOT:
> [INFO]
> [INFO] Spark Project Parent POM ........................... SUCCESS [ 14.794 s]
> [INFO] Spark Project Tags ................................. SUCCESS [ 18.233 s]
> [INFO] Spark Project Sketch ............................... SUCCESS [ 20.077 s]
> [INFO] Spark Project Local DB ............................. SUCCESS [  7.846 s]
> [INFO] Spark Project Networking ........................... SUCCESS [ 14.906 s]
> [INFO] Spark Project Shuffle Streaming Service ............ SUCCESS [  6.267 s]
> [INFO] Spark Project Unsafe ............................... SUCCESS [ 31.710 s]
> [INFO] Spark Project Launcher ............................. SUCCESS [ 10.227 s]
> [INFO] Spark Project Core ................................. SUCCESS [08:03 min]
> [INFO] Spark Project ML Local Library ..................... SUCCESS [01:51 min]
> [INFO] Spark Project GraphX ............................... SUCCESS [02:20 min]
> [INFO] Spark Project Streaming ............................ SUCCESS [03:16 min]
> [INFO] Spark Project Catalyst ............................. SUCCESS [08:45 min]
> [INFO] Spark Project SQL .................................. SUCCESS [12:12 min]
> [INFO] Spark Project ML Library ........................... SUCCESS [  16:28 h]
> [INFO] Spark Project Tools ................................ SUCCESS [ 23.602 s]
> [INFO] Spark Project Hive ................................. SUCCESS [07:50 min]
> [INFO] Spark Project Graph API ............................ SUCCESS [  8.734 s]
> [INFO] Spark Project Cypher ............................... SUCCESS [ 12.420 s]
> [INFO] Spark Project Graph ................................ SUCCESS [ 10.186 s]
> [INFO] Spark Project REPL ................................. SUCCESS [01:03 min]
> [INFO] Spark Project YARN Shuffle Service ................. SUCCESS [01:19 min]
> [INFO] Spark Project YARN ................................. SUCCESS [02:19 min]
> [INFO] Spark Project Assembly ............................. SUCCESS [ 18.912 s]
> [INFO] Kafka 0.10+ Token Provider for Streaming ........... SUCCESS [ 57.925 s]
> [INFO] Spark Integration for Kafka 0.10 ................... SUCCESS [01:20 min]
> [INFO] Kafka 0.10+ Source for Structured Streaming ........ SUCCESS [02:26 min]
> [INFO] Spark Project Examples ............................. SUCCESS [02:00 min]
> [INFO] Spark Integration for Kafka 0.10 Assembly .......... SUCCESS [ 28.354 s]
> [INFO] Spark Avro ......................................... SUCCESS [01:44 min]
> [INFO] ------------------------------------------------------------------------
> [INFO] BUILD SUCCESS
> [INFO] ------------------------------------------------------------------------
> [INFO] Total time:  17:30 h
> [INFO] Finished at: 2019-12-05T12:20:01-08:00
> [INFO] ------------------------------------------------------------------------
>
> D:\apache\spark>cd bin
>
> D:\apache\spark\bin>ls
> beeline               load-spark-env.cmd  run-example       spark-shell  
    spark-sql2.cmd     sparkR.cmd
> beeline.cmd           load-spark-env.sh   run-example.cmd   spark-shell.cmd  
spark-submit       sparkR2.cmd
> docker-image-tool.sh  pyspark             spark-class       spark-shell2.cmd
 spark-submit.cmd
> find-spark-home       pyspark.cmd         spark-class.cmd   spark-sql      
  spark-submit2.cmd
> find-spark-home.cmd   pyspark2.cmd        spark-class2.cmd  spark-sql.cmd    
sparkR
>
> D:\apache\spark\bin>spark-shell
> Exception in thread "main" java.lang.NoSuchMethodError: com.google.common.base.Preconditions.checkArgument(ZLjava/lang/String;Ljava/lang/Object;)V
>         at org.apache.hadoop.conf.Configuration.set(Configuration.java:1357)
>         at org.apache.hadoop.conf.Configuration.set(Configuration.java:1338)
>         at org.apache.spark.deploy.SparkHadoopUtil$.org$apache$spark$deploy$SparkHadoopUtil$$appendS3AndSparkHadoopHiveConfigurations(SparkHadoopUtil.scala:456)
>         at org.apache.spark.deploy.SparkHadoopUtil$.newConfiguration(SparkHadoopUtil.scala:427)
>         at org.apache.spark.deploy.SparkSubmit.$anonfun$prepareSubmitEnvironment$2(SparkSubmit.scala:342)
>         at org.apache.spark.deploy.SparkSubmit$$Lambda$132/817978763.apply(Unknown
Source)
>         at scala.Option.getOrElse(Option.scala:189)
>         at org.apache.spark.deploy.SparkSubmit.prepareSubmitEnvironment(SparkSubmit.scala:342)
>         at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:871)
>         at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:180)
>         at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:203)
>         at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:90)
>         at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:1007)
>         at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:1016)
>         at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
>
> D:\apache\spark\bin>
> On Thu, Dec 5, 2019 at 1:33 PM Sean Owen <srowen@gmail.com> wrote:
>
> What was the build error? you didn't say. Are you sure it succeeded?
> Try running from the Spark home dir, not bin.
> I know we do run Windows tests and it appears to pass tests, etc.
>
> On Thu, Dec 5, 2019 at 3:28 PM Ping Liu <pingpinganan@gmail.com> wrote:
>>
>> Hello,
>>
>> I understand Spark is preferably built on Linux.  But I have a Windows machine with
a slow Virtual Box for Linux.  So I wish I am able to build and run Spark code on Windows
environment.
>>
>> Unfortunately,
>>
>> # Apache Hadoop 2.6.X
>> ./build/mvn -Pyarn -DskipTests clean package
>>
>> # Apache Hadoop 2.7.X and later
>> ./build/mvn -Pyarn -Phadoop-2.7 -Dhadoop.version=2.7.3 -DskipTests clean package
>>
>>
>> Both are listed on http://spark.apache.org/docs/latest/building-spark.html#specifying-the-hadoop-version-and-enabling-yarn
>>
>> But neither works for me (I stay directly under spark root directory and run "mvn
-Pyarn -Phadoop-2.7 -Dhadoop.version=2.7.3 -DskipTests clean package"
>>
>> and
>>
>> Then I tried "mvn -Pyarn -Phadoop-3.2 -Dhadoop.version=3.2.1 -DskipTests clean package"
>>
>> Now build works.  But when I run spark-shell.  I got the following error.
>>
>> D:\apache\spark\bin>spark-shell
>> Exception in thread "main" java.lang.NoSuchMethodError: com.google.common.base.Preconditions.checkArgument(ZLjava/lang/String;Ljava/lang/Object;)V
>>         at org.apache.hadoop.conf.Configuration.set(Configuration.java:1357)
>>         at org.apache.hadoop.conf.Configuration.set(Configuration.java:1338)
>>         at org.apache.spark.deploy.SparkHadoopUtil$.org$apache$spark$deploy$SparkHadoopUtil$$appendS3AndSparkHadoopHiveConfigurations(SparkHadoopUtil.scala:456)
>>         at org.apache.spark.deploy.SparkHadoopUtil$.newConfiguration(SparkHadoopUtil.scala:427)
>>         at org.apache.spark.deploy.SparkSubmit.$anonfun$prepareSubmitEnvironment$2(SparkSubmit.scala:342)
>>         at org.apache.spark.deploy.SparkSubmit$$Lambda$132/817978763.apply(Unknown
Source)
>>         at scala.Option.getOrElse(Option.scala:189)
>>         at org.apache.spark.deploy.SparkSubmit.prepareSubmitEnvironment(SparkSubmit.scala:342)
>>         at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:871)
>>         at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:180)
>>         at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:203)
>>         at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:90)
>>         at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:1007)
>>         at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:1016)
>>         at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
>>
>>
>> Has anyone experienced building and running Spark source code successfully on Windows? 
Could you please share your experience?
>>
>> Thanks a lot!
>>
>> Ping
>>
>  
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