我尝试在azure的hdinsight sparkrunner上运行一个beam管道。我首先尝试了一个基于spark2.3.0/hadoop2.7(hdi3.6)和2.3.1/hadoop3.0(hdi4.0预览版)的集群。我尝试使用ApacheBeam2.2.0和Next2.10.0-snapshot。
spark submit命令是(对于beam 2.10.0):
JARS="wasbs:///dependency/hadoop-azure-3.1.1.3.0.2.0-50.jar,wasbs:///dependency/azure-storage-7.0.0.jar,wasbs:///dependency/beam-model-fn-execution-2.10.0-SNAPSHOT.jar,wasbs:///dependency/beam-model-job-management-2.10.0-SNAPSHOT.jar,wasbs:///dependency/beam-model-pipeline-2.10.0-SNAPSHOT.jar,wasbs:///dependency/beam-runners-core-construction-java-2.10.0-SNAPSHOT.jar,wasbs:///dependency/beam-runners-core-java-2.10.0-SNAPSHOT.jar,wasbs:///dependency/beam-runners-direct-java-2.10.0-SNAPSHOT.jar,wasbs:///dependency/beam-runners-spark-2.10.0-SNAPSHOT.jar,wasbs:///dependency/beam-sdks-java-core-2.10.0-SNAPSHOT.jar,wasbs:///dependency/beam-sdks-java-fn-execution-2.10.0-SNAPSHOT.jar,wasbs:///dependency/beam-sdks-java-io-hadoop-file-system-2.10.0-SNAPSHOT.jar,wasbs:///dependency/beam-vendor-grpc-1_13_1-0.1.jar"
spark-submit --conf spark.yarn.maxAppAttempts=1 --deploy-mode cluster --master yarn --jars $JARS --class example.MinimalWordCountJava8 wasbs:///mavenproject1-1.0-SNAPSHOT.jar --runner=SparkRunner
(最初,没有给jars提供hadoopazure和azure存储jar,但这没有任何区别)。
这个 main()
看起来像这样:
public static void main(String[] args) {
JavaSparkContext ct = new JavaSparkContext();
Configuration config = ct.hadoopConfiguration();
config.set("fs.wasbs.impl", "org.apache.hadoop.fs.azure.NativeAzureFileSystem");
config.set("fs.wasb.impl", "org.apache.hadoop.fs.azure.NativeAzureFileSystem");
config.set("fs.AbstractFileSystem.wasb.impl", "org.apache.hadoop.fs.azure.Wasb");
config.set("fs.AbstractFileSystem.wasb.impl", "org.apache.hadoop.fs.azure.Wasbs");
config.set("fs.azure", "org.apache.hadoop.fs.azure.NativeAzureFileSystem");
config.set("fs.azure.account.key." + account + ".blob.core.windows.net", key);
config.set("fs.defaultFS", "wasb://" + container + "@" + account + ".blob.core.windows.net");
System.out.println("### hello.txt content:");
JavaRDD<String> content = ct.textFile("wasbs:///hello.txt");
System.out.println(content.toString());
System.out.println("### MinimalWordCountJava8");
PipelineOptions options = PipelineOptionsFactory.create();
SparkContextOptions sparkContextOptions = options.as(SparkContextOptions.class);
sparkContextOptions.setUsesProvidedSparkContext(true);
sparkContextOptions.setProvidedSparkContext(ct);
sparkContextOptions.setRunner(SparkRunner.class);
Pipeline p = Pipeline.create(sparkContextOptions);
p.apply(TextIO.read().from("hello.txt"))
.apply(FlatMapElements
.into(TypeDescriptors.strings())
.via((String word) -> Arrays.asList(word.split("[^\\p{L}]+"))))
.apply(Filter.by((String word) -> !word.isEmpty()))
.apply(Count.<String>perElement())
.apply(MapElements
.into(TypeDescriptors.strings())
.via((KV<String, Long> wordCount) -> wordCount.getKey() + ": " + wordCount.getValue()))
// CHANGE 3/3: The Google Cloud Storage path is required for outputting the results to.
.apply(TextIO.write().to("output"));
p.run().waitUntilFinish();
调用时失败 Pipeline.create(options);
对于此异常跟踪:
18/12/09 14:47:10 ERROR ApplicationMaster: User class threw exception: java.lang.IllegalArgumentException: Failed to construct Hadoop filesystem with configuration Configuration: /usr/hdp/3.0.2.0-50/hadoop/conf/core-site.xml, /usr/hdp/3.0.2.0-50/hadoop/conf/hdfs-site.xml
java.lang.IllegalArgumentException: Failed to construct Hadoop filesystem with configuration Configuration: /usr/hdp/3.0.2.0-50/hadoop/conf/core-site.xml, /usr/hdp/3.0.2.0-50/hadoop/conf/hdfs-site.xml
at org.apache.beam.sdk.io.hdfs.HadoopFileSystemRegistrar.fromOptions(HadoopFileSystemRegistrar.java:59)
at org.apache.beam.sdk.io.FileSystems.verifySchemesAreUnique(FileSystems.java:489)
at org.apache.beam.sdk.io.FileSystems.setDefaultPipelineOptions(FileSystems.java:479)
at org.apache.beam.sdk.PipelineRunner.fromOptions(PipelineRunner.java:47)
at org.apache.beam.sdk.Pipeline.create(Pipeline.java:145)
at io.aptly.mavenproject1.MinimalWordCountJava8.main(MinimalWordCountJava8.java:88)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$4.run(ApplicationMaster.scala:721)
Caused by: org.apache.hadoop.fs.UnsupportedFileSystemException: No FileSystem for scheme "wasbs"
at org.apache.hadoop.fs.FileSystem.getFileSystemClass(FileSystem.java:3332)
at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:3352)
at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:124)
at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:3403)
at org.apache.hadoop.fs.FileSystem$Cache.getUnique(FileSystem.java:3377)
at org.apache.hadoop.fs.FileSystem.newInstance(FileSystem.java:530)
at org.apache.hadoop.fs.FileSystem.newInstance(FileSystem.java:542)
at org.apache.beam.sdk.io.hdfs.HadoopFileSystem.<init>(HadoopFileSystem.java:82)
at org.apache.beam.sdk.io.hdfs.HadoopFileSystemRegistrar.fromOptions(HadoopFileSystemRegistrar.java:56)
... 10 more
18/12/09 14:47:10 INFO ApplicationMaster: Final app status: FAILED, exitCode: 15, (reason: User class threw exception: java.lang.IllegalArgumentException: Failed to construct Hadoop filesystem with configuration Configuration: /usr/hdp/3.0.2.0-50/hadoop/conf/core-site.xml, /usr/hdp/3.0.2.0-50/hadoop/conf/hdfs-site.xml
at org.apache.beam.sdk.io.hdfs.HadoopFileSystemRegistrar.fromOptions(HadoopFileSystemRegistrar.java:59)
at org.apache.beam.sdk.io.FileSystems.verifySchemesAreUnique(FileSystems.java:489)
at org.apache.beam.sdk.io.FileSystems.setDefaultPipelineOptions(FileSystems.java:479)
at org.apache.beam.sdk.PipelineRunner.fromOptions(PipelineRunner.java:47)
at org.apache.beam.sdk.Pipeline.create(Pipeline.java:145)
at io.aptly.mavenproject1.MinimalWordCountJava8.main(MinimalWordCountJava8.java:88)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$4.run(ApplicationMaster.scala:721)
Caused by: org.apache.hadoop.fs.UnsupportedFileSystemException: No FileSystem for scheme "wasbs"
at org.apache.hadoop.fs.FileSystem.getFileSystemClass(FileSystem.java:3332)
at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:3352)
at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:124)
at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:3403)
at org.apache.hadoop.fs.FileSystem$Cache.getUnique(FileSystem.java:3377)
at org.apache.hadoop.fs.FileSystem.newInstance(FileSystem.java:530)
at org.apache.hadoop.fs.FileSystem.newInstance(FileSystem.java:542)
at org.apache.beam.sdk.io.hdfs.HadoopFileSystem.<init>(HadoopFileSystem.java:82)
at org.apache.beam.sdk.io.hdfs.HadoopFileSystemRegistrar.fromOptions(HadoopFileSystemRegistrar.java:56)
提交工程(the submit works) wasps://
是公认的)和阅读的小 wasps:///hello.txt
不会失败。这些案例表明 wasps://
在那之前一切都很好。
这是早期内梁,它似乎失败了。
因此我通过了考试 JavaSparkContext
与 PipelineOptions
(使用其他so问题/答案建议的动态hadoop配置)。但这对我来说没什么不同。
有谁能指导如何绕过这个问题?
1条答案
按热度按时间kq0g1dla1#
从快速挖掘代码和bug跟踪器来看,从hadoop3.2.0(代码,jira)开始,azure似乎作为hadoop文件系统得到了支持。当前梁固定到版本2.7.3。这就解释了梁的失效
HadoopFilesystem
.可能是这样的
spark-submit
成功是因为wasbs://
通过与hadoop库不同的机制或使用捆绑的更新版本的hadoop来支持。