Re: Is it feasible to build and run Spark on Windows?

[Ping Liu]

I am new and plan to be an individual contributor for bug fix.  I assume I
need building the project if I'll be working on source code based on master
branch that the binaries are behind.  Do you think this makes sense?
Please let me know if, in this case, I can still use binary instead of
building the project.

On Tue, Dec 10, 2019 at 7:00 AM Deepak Vohra  wrote:

> The initial question was to build from source. Any reason to build when
> binaries are available at https://spark.apache.org/downloads.html
>
> On Tuesday, December 10, 2019, 03:05:44 AM UTC, Ping Liu <
> pingpinga...@gmail.com> wrote:
>
>
> Super.  Thanks Deepak!
>
> On Mon, Dec 9, 2019 at 6:58 PM Deepak Vohra  wrote:
>
> Please install Apache Spark on Windows as discussed in Apache Spark on
> Windows - DZone Open Source
> 
>
> 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...
> 
>
>
>
> On Monday, December 9, 2019, 11:27:53 p.m. UTC, Ping Liu <
> pingpinga...@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  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 <
> pingpinga...@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  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.
> > 
> > org.apache.hadoop
> > hadoop-common
> >  3.2.1
> > 
> >   
> >  com.google.guava
> >  guava
> >
> > 
> >
> > 
> > com.google.guava
> > guava
> > 28.1-jre
> > 
> >  
> >   
> >
> > On Friday, December 6, 2019, 10:12:55 p.m. UTC, Ping Liu <
> pingpinga...@gmail.com> wrote:
> >
> > Hi Deepak,
> > Following your suggestion, I put exclusion of guava in topmost POM
> (under Spark home directly) as follows.
> > 2227-  
> > 2228-  
> > 2229-org.apache.hadoop
> > 2230:hadoop-common
> > 2231-3.2.1
> > 2232-
> > 2233-  
> > 2234-com.google.guava
> > 2235-guava
> > 2236-  
> > 2237-
> > 2238-  
> > 2239-
> > 2240-  
> > 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 [
> 

Re: Is it feasible to build and run Spark on Windows?

[Ping Liu]

Super.  Thanks Deepak!

On Mon, Dec 9, 2019 at 6:58 PM Deepak Vohra  wrote:

> Please install Apache Spark on Windows as discussed in Apache Spark on
> Windows - DZone Open Source
> 
>
> 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...
> 
>
>
>
> On Monday, December 9, 2019, 11:27:53 p.m. UTC, Ping Liu <
> pingpinga...@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  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 <
> pingpinga...@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  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.
> > 
> > org.apache.hadoop
> > hadoop-common
> >  3.2.1
> > 
> >   
> >  com.google.guava
> >  guava
> >
> > 
> >
> > 
> > com.google.guava
> > guava
> > 28.1-jre
> > 
> >  
> >   
> >
> > On Friday, December 6, 2019, 10:12:55 p.m. UTC, Ping Liu <
> pingpinga...@gmail.com> wrote:
> >
> > Hi Deepak,
> > Following your suggestion, I put exclusion of guava in topmost POM
> (under Spark home directly) as follows.
> > 2227-  
> > 2228-  
> > 2229-org.apache.hadoop
> > 2230:hadoop-common
> > 2231-3.2.1
> > 2232-
> > 2233-  
> > 2234-com.google.guava
> > 2235-guava
> > 2236-  
> > 2237-
> > 2238-  
> > 2239-
> > 2240-  
> > 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]
> > 

Re: Is it feasible to build and run Spark on Windows?

[Ping Liu]

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  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 <
pingpinga...@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  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.
> 
> org.apache.hadoop
> hadoop-common
>  3.2.1
> 
>   
>  com.google.guava
>  guava
>
> 
>
> 
> com.google.guava
> guava
> 28.1-jre
> 
>  
>   
>
> On Friday, December 6, 2019, 10:12:55 p.m. UTC, Ping Liu <
pingpinga...@gmail.com> wrote:
>
> Hi Deepak,
> Following your suggestion, I put exclusion of guava in topmost POM (under
Spark home directly) as follows.
> 2227-  
> 2228-  
> 2229-org.apache.hadoop
> 2230:hadoop-common
> 2231-3.2.1
> 2232-
> 2233-  
> 2234-com.google.guava
> 2235-guava
> 2236-  
> 2237-
> 2238-  
> 2239-
> 2240-  
> 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 

Re: Is it feasible to build and run Spark on Windows?

[Ping Liu]

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  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.
>
> 
> org.apache.hadoop
> hadoop-common
>  3.2.1
> 
>   
>  com.google.guava
>  guava
>
> 
>
> 
> com.google.guava
> guava
> 28.1-jre
> 
>  
>   
>
>
> On Friday, December 6, 2019, 10:12:55 p.m. UTC, Ping Liu <
> pingpinga...@gmail.com> wrote:
>
>
> Hi Deepak,
>
> Following your suggestion, I put exclusion of guava in topmost POM (under
> Spark home directly) as follows.
>
> 2227-  
> 2228-  
> 2229-org.apache.hadoop
> 2230:hadoop-common
> 2231-3.2.1
> 2232-
> 2233-  
> 2234-com.google.guava
> 2235-guava
> 2236-  
> 2237-
> 2238-  
> 2239-
> 2240-  
>
> 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
> 

Re: Is it feasible to build and run Spark on Windows?

[Ping Liu]

Hi Deepak,

Following your suggestion, I put exclusion of guava in topmost POM (under
Spark home directly) as follows.

2227-  
2228-  
2229-org.apache.hadoop
2230:hadoop-common
2231-3.2.1
2232-
2233-  
2234-com.google.guava
2235-guava
2236-  
2237-
2238-  
2239-
2240-  

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

Re: Is it feasible to build and run Spark on Windows?

[Ping Liu]

Thanks Deepak!  I'll try it.

On Thu, Dec 5, 2019 at 4:13 PM Deepak Vohra  wrote:

> The Guava issue could be fixed in one of two ways:
>
> - Use Hadoop v3
> - Create an Uber jar, refer
>
> https://gite.lirmm.fr/yagoubi/spark/commit/c9f743957fa963bc1dbed7a44a346ffce1a45cf2
>   Managing Java dependencies for Apache Spark applications on Cloud
> Dataproc | Google Cloud Blog
> 
>
> Managing Java dependencies for Apache Spark applications on Cloud Datapr...
>
> Learn how to set up Java imported packages for Apache Spark on Cloud
> Dataproc to avoid conflicts.
>
> 
>
>
>
> On Thursday, December 5, 2019, 11:49:47 PM UTC, Ping Liu <
> pingpinga...@gmail.com> wrote:
>
>
> Hi Deepak,
>
> For Spark, I am using master branch and just have code updated yesterday.
>
> For Guava, I actually deleted my old versions from the local Maven repo.
> The build process of Spark automatically downloaded a few versions.  The
> oldest version is 14.0.1.
>
> But even in 14.0,1 (
> https://guava.dev/releases/14.0.1/api/docs/com/google/common/base/Preconditions.html)
> Preconditions already requires boolean as first parameter.
>
> static void *checkArgument
> *(boolean
>  expression,
> String
> 
>  errorMessageTemplate,
> Object
> 
> ... errorMessageArgs)
>
> The newer Guava version, checkArgument() all require boolean as first
> parameter.
>
> For Docker, using EC2 is a good idea.  Is there a document or guidance for
> it?
>
> Thanks.
>
> Ping
>
>
>
> On Thu, Dec 5, 2019 at 3:30 PM Deepak Vohra  wrote:
>
> Such type exception could occur if a dependency (most likely Guava)
> version is not supported by the Spark version. What is the Spark and Guava
> versions? Use a more recent Guava version dependency in Maven pom.xml.
>
> Regarding Docker, a cloud platform instance such as EC2 could be used with
> Hyper-V support.
>
> On Thursday, December 5, 2019, 10:51:59 PM UTC, Ping Liu <
> pingpinga...@gmail.com> wrote:
>
>
> Hi Deepak,
>
> Yes, I did use Maven. I even have the build pass successfully when setting
> Hadoop version to 3.2.  Please see my response to Sean's email.
>
> Unfortunately, I only have Docker Toolbox as my Windows doesn't have
> Microsoft Hyper-V.  So I want to avoid using Docker to do major work if
> possible.
>
> Thanks!
>
> Ping
>
>
> On Thu, Dec 5, 2019 at 2:24 PM Deepak Vohra  wrote:
>
> Several alternatives are available:
>
> - Use Maven to build Spark on Windows.
> http://spark.apache.org/docs/latest/building-spark.html#apache-maven
>
> - Use Docker image for  CDH on Windows
> Docker Hub 
>
> Docker Hub
>
> 
>
>
>
>
> On Thursday, December 5, 2019, 09:33:43 p.m. UTC, Sean Owen <
> sro...@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  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)
> >

Re: Is it feasible to build and run Spark on Windows?

[Ping Liu]

Hi Deepak,

For Spark, I am using master branch and just have code updated yesterday.

For Guava, I actually deleted my old versions from the local Maven repo.
The build process of Spark automatically downloaded a few versions.  The
oldest version is 14.0.1.

But even in 14.0,1 (
https://guava.dev/releases/14.0.1/api/docs/com/google/common/base/Preconditions.html)
Preconditions already requires boolean as first parameter.

static void *checkArgument
*(boolean expression, String

errorMessageTemplate,
Object

... errorMessageArgs)

The newer Guava version, checkArgument() all require boolean as first
parameter.

For Docker, using EC2 is a good idea.  Is there a document or guidance for
it?

Thanks.

Ping



On Thu, Dec 5, 2019 at 3:30 PM Deepak Vohra  wrote:

> Such type exception could occur if a dependency (most likely Guava)
> version is not supported by the Spark version. What is the Spark and Guava
> versions? Use a more recent Guava version dependency in Maven pom.xml.
>
> Regarding Docker, a cloud platform instance such as EC2 could be used with
> Hyper-V support.
>
> On Thursday, December 5, 2019, 10:51:59 PM UTC, Ping Liu <
> pingpinga...@gmail.com> wrote:
>
>
> Hi Deepak,
>
> Yes, I did use Maven. I even have the build pass successfully when setting
> Hadoop version to 3.2.  Please see my response to Sean's email.
>
> Unfortunately, I only have Docker Toolbox as my Windows doesn't have
> Microsoft Hyper-V.  So I want to avoid using Docker to do major work if
> possible.
>
> Thanks!
>
> Ping
>
>
> On Thu, Dec 5, 2019 at 2:24 PM Deepak Vohra  wrote:
>
> Several alternatives are available:
>
> - Use Maven to build Spark on Windows.
> http://spark.apache.org/docs/latest/building-spark.html#apache-maven
>
> - Use Docker image for  CDH on Windows
> Docker Hub 
>
> Docker Hub
>
> 
>
>
>
>
> On Thursday, December 5, 2019, 09:33:43 p.m. UTC, Sean Owen <
> sro...@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  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
> 

Re: Is it feasible to build and run Spark on Windows?

[Ping Liu]

Hi Sean,

Oh, sorry.  I just came back to Spark home.  However, the same error came
out.

D:\apache\spark\bin>cd ..

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>

The error shows com.google.common.base.Preconditions.checkArgument()
requires two parameters: String and Object.

But Guava version 19 Preconditions (
https://guava.dev/releases/19.0/api/docs/com/google/common/base/Preconditions.html)
shows an additinal boolean variable as first parameter.



static void *checkArgument
*(boolean expression, String

errorMessageTemplate,
Object

... errorMessageArgs)

>From Hadoop Configuration source code here (
https://hadoop.apache.org/docs/r2.7.1/api/src-html/org/apache/hadoop/conf/Configuration.html),


1130  public void set(String name, String value, String source) {1131
  Preconditions.checkArgument(1132name != null,1133
"Property name must not be null");1134
Preconditions.checkArgument(1135value != null,1136"The
value of property " + name + " must not be null");

My best guess was that maybe an old version of Hadoop is used somewhere
that might incorrectly call Preditions.checkArgument(String, Object) but
not Preditions.checkArgument(boolean, String, Object).  But this is just my
guess.

Thanks.

Ping





On Thu, Dec 5, 2019 at 2:38 PM Sean Owen  wrote:

> No, the build works fine, at least certainly on test machines. As I
> say, try running from the actual Spark home, not bin/. You are still
> running spark-shell there.
>
> On Thu, Dec 5, 2019 at 4:37 PM Ping Liu  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 

Re: Is it feasible to build and run Spark on Windows?

[Ping Liu]

Hi Deepak,

Yes, I did use Maven. I even have the build pass successfully when setting
Hadoop version to 3.2.  Please see my response to Sean's email.

Unfortunately, I only have Docker Toolbox as my Windows doesn't have
Microsoft Hyper-V.  So I want to avoid using Docker to do major work if
possible.

Thanks!

Ping


On Thu, Dec 5, 2019 at 2:24 PM Deepak Vohra  wrote:

> Several alternatives are available:
>
> - Use Maven to build Spark on Windows.
> http://spark.apache.org/docs/latest/building-spark.html#apache-maven
>
> - Use Docker image for  CDH on Windows
> Docker Hub 
>
> Docker Hub
>
> 
>
>
>
>
> On Thursday, December 5, 2019, 09:33:43 p.m. UTC, Sean Owen <
> sro...@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  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
>
> >
>
> -
> To unsubscribe e-mail: user-unsubscr...@spark.apache.org
>
>
>

Re: Is it feasible to build and run Spark on Windows?

[Sean Owen]

No, the build works fine, at least certainly on test machines. As I
say, try running from the actual Spark home, not bin/. You are still
running spark-shell there.

On Thu, Dec 5, 2019 at 4:37 PM Ping Liu  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.cmdspark-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 

Re: Is it feasible to build and run Spark on Windows?

[Ping Liu]

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.cmdspark-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

Re: Is it feasible to build and run Spark on Windows?

[Sean Owen]

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  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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Is it feasible to build and run Spark on Windows?

[Ping Liu]

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