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
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Maven Repository: org.apache.hadoop » hadoop-common
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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
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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.
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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
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Running Spark in Docker Containers on YARN
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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 <dvohr...@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
<pingpinga...@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 <dvohr...@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
<pingpinga...@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 <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
>
