Multiple Guava versions could be in the classpath inherited from Hadoop. Use
the Guava version supported by Spark, and exclude other Guava. Also add
spark.executor.userClassPathFirst=true and spark.driver.userClassPathFirst=true
in properties.
On Thursday, December 5, 2019, 11:35:27 PM UTC, Ping Liu
<[email protected]> wrote:
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(
1132 name != null,
1133 "Property name must not be null");
1134 Preconditions.checkArgument(
1135 value != 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 <[email protected]> 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 <[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
>> >
