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 <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 <pingpinga...@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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