Please install Apache Spark on Windows as discussed in Apache Spark on Windows
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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
<[email protected]> 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 <[email protected]> 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
> <[email protected]> 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 <[email protected]> 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
> <[email protected]> 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 <[email protected]> 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
> <[email protected]> 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 <[email protected]> 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 <[email protected]> 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
>>
>
