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我有一个针对数据集运行多个测试的 spark 应用程序,测试是包含 groupBy、filter 等 spark sql 查询的函数......
Dataset<Row> dataset = loadDataset();
test1(dataset);
test2(dataset);
test3(dataset);
此时一切正常,但我可以看到集群使用了大约 30%,因此为了优化这一点,我考虑将测试并行化以同时运行,为此我在一个线程中启动了每个测试:
Dataset<Row> dataset = loadDataset();
Thread thread1 = new Thread(()-> test3(dataset));
thread1.start();
Thread thread2 = new Thread(()-> test2(dataset));
thread2.start();
Thread thread3 = new Thread(()-> test1(dataset));
thread3.start();
但是这似乎不起作用,因为我遇到了一些奇怪的错误:
The currently active SparkContext was created at:
org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:914)
com.test.spark.Loader.loadDataset(Loader.java:96)
com.test.spark.Loader.run(Loader.java:29)
com.test.spark.Main.main(Main.java:15)
sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
java.lang.reflect.Method.invoke(Method.java:498)
org.apache.spark.deploy.yarn.ApplicationMaster$$anon$3.run(ApplicationMaster.scala:646)
at org.apache.spark.SparkContext.assertNotStopped(SparkContext.scala:100)
at org.apache.spark.SparkContext.broadcast(SparkContext.scala:1485)
at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat.buildReader(CSVFileFormat.scala:96)
at org.apache.spark.sql.execution.datasources.FileFormat$class.buildReaderWithPartitionValues(FileFormat.scala:117)
at org.apache.spark.sql.execution.datasources.TextBasedFileFormat.buildReaderWithPartitionValues(FileFormat.scala:148)
at org.apache.spark.sql.execution.FileSourceScanExec.inputRDD$lzycompute(DataSourceScanExec.scala:291)
at org.apache.spark.sql.execution.FileSourceScanExec.inputRDD(DataSourceScanExec.scala:289)
at org.apache.spark.sql.execution.FileSourceScanExec.inputRDDs(DataSourceScanExec.scala:309)
at org.apache.spark.sql.execution.FilterExec.inputRDDs(basicPhysicalOperators.scala:124)
at org.apache.spark.sql.execution.ProjectExec.inputRDDs(basicPhysicalOperators.scala:42)
at org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:386)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:138)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:135)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:116)
at org.apache.spark.sql.execution.columnar.InMemoryRelation.buildBuffers(InMemoryRelation.scala:91)
at org.apache.spark.sql.execution.columnar.InMemoryRelation.<init>(InMemoryRelation.scala:86)
at org.apache.spark.sql.execution.columnar.InMemoryRelation$.apply(InMemoryRelation.scala:42)
at org.apache.spark.sql.execution.CacheManager$$anonfun$cacheQuery$1.apply(CacheManager.scala:100)
at org.apache.spark.sql.execution.CacheManager.writeLock(CacheManager.scala:68)
at org.apache.spark.sql.execution.CacheManager.cacheQuery(CacheManager.scala:92)
at org.apache.spark.sql.Dataset.persist(Dataset.scala:2514)
at com.test.spark.Loader.test3(Loader.java:45)
at com.test.spark.Loader.lambda$run$0(Loader.java:32)
at java.lang.Thread.run(Thread.java:748)
19/07/13 22:05:08 INFO FileSourceStrategy: Pruning directories with:
19/07/13 22:05:08 INFO FileSourceStrategy: Post-Scan Filters: isnotnull(Sens#29),(Sens#29 = C)
19/07/13 22:05:08 INFO FileSourceStrategy: Output Data Schema: struct<JournalCode: string, JournalLib: string, EcritureNum: string, EcritureDate: string, CompteNum: string ... 16 more fields>
19/07/13 22:05:08 INFO FileSourceScanExec: Pushed Filters: IsNotNull(Sens),EqualTo(Sens,C)
19/07/13 22:05:08 INFO CodeGenerator: Code generated in 21.213109 ms
Exception in thread "Thread-29" java.lang.IllegalStateException: Cannot call methods on a stopped SparkContext.
This stopped SparkContext was created at:
org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:914)
com.test.spark.Loader.loadDataset(Loader.java:96)
com.test.spark.Loader.run(Loader.java:29)
com.test.spark.Main.main(Main.java:15)
sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
java.lang.reflect.Method.invoke(Method.java:498)
org.apache.spark.deploy.yarn.ApplicationMaster$$anon$3.run(ApplicationMaster.scala:646)
The currently active SparkContext was created at:
org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:914)
com.test.spark.Loader.loadDataset(Loader.java:96)
com.test.spark.Loader.run(Loader.java:29)
com.test.spark.Main.main(Main.java:15)
sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
java.lang.reflect.Method.invoke(Method.java:498)
org.apache.spark.deploy.yarn.ApplicationMaster$$anon$3.run(ApplicationMaster.scala:646)
at org.apache.spark.SparkContext.assertNotStopped(SparkContext.scala:100)
at org.apache.spark.SparkContext.broadcast(SparkContext.scala:1485)
at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat.buildReader(CSVFileFormat.scala:96)
at org.apache.spark.sql.execution.datasources.FileFormat$class.buildReaderWithPartitionValues(FileFormat.scala:117)
at org.apache.spark.sql.execution.datasources.TextBasedFileFormat.buildReaderWithPartitionValues(FileFormat.scala:148)
at org.apache.spark.sql.execution.FileSourceScanExec.inputRDD$lzycompute(DataSourceScanExec.scala:291)
at org.apache.spark.sql.execution.FileSourceScanExec.inputRDD(DataSourceScanExec.scala:289)
at org.apache.spark.sql.execution.FileSourceScanExec.inputRDDs(DataSourceScanExec.scala:309)
at org.apache.spark.sql.execution.FilterExec.inputRDDs(basicPhysicalOperators.scala:124)
at org.apache.spark.sql.execution.ProjectExec.inputRDDs(basicPhysicalOperators.scala:42)
at org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:386)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:138)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:135)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:116)
at org.apache.spark.sql.execution.columnar.InMemoryRelation.buildBuffers(InMemoryRelation.scala:91)
at org.apache.spark.sql.execution.columnar.InMemoryRelation.<init>(InMemoryRelation.scala:86)
at org.apache.spark.sql.execution.columnar.InMemoryRelation$.apply(InMemoryRelation.scala:42)
at org.apache.spark.sql.execution.CacheManager$$anonfun$cacheQuery$1.apply(CacheManager.scala:100)
at org.apache.spark.sql.execution.CacheManager.writeLock(CacheManager.scala:68)
at org.apache.spark.sql.execution.CacheManager.cacheQuery(CacheManager.scala:92)
at org.apache.spark.sql.Dataset.persist(Dataset.scala:2514)
at com.test.spark.Loader.test1(Loader.java:67)
at com.test.spark.Loader.lambda$run$2(Loader.java:36)
at java.lang.Thread.run(Thread.java:748)
19/07/13 22:05:08 INFO FileSourceStrategy: Pruning directories with:
19/07/13 22:05:08 INFO FileSourceStrategy: Post-Scan Filters:
19/07/13 22:05:08 INFO FileSourceStrategy: Output Data Schema: struct<CompteNum: string>
19/07/13 22:05:08 INFO FileSourceScanExec: Pushed Filters:
19/07/13 22:05:08 INFO HashAggregateExec: spark.sql.codegen.aggregate.map.twolevel.enable is set to true, but current version of codegened fast hashmap does not support this aggregate.
19/07/13 22:05:08 INFO CodeGenerator: Code generated in 29.090949 ms
19/07/13 22:05:08 INFO HashAggregateExec: spark.sql.codegen.aggregate.map.twolevel.enable is set to true, but current version of codegened fast hashmap does not support this aggregate.
19/07/13 22:05:08 INFO CodeGenerator: Code generated in 20.861207 ms
Exception in thread "Thread-28" org.apache.spark.sql.catalyst.errors.package$TreeNodeException: execute, tree:
Exchange SinglePartition
+- *HashAggregate(keys=[], functions=[partial_count(1)], output=[count#297L])
+- *HashAggregate(keys=[CompteNum#21], functions=[], output=[])
+- Exchange hashpartitioning(CompteNum#21, 10)
+- *HashAggregate(keys=[CompteNum#21], functions=[], output=[CompteNum#21])
+- *FileScan csv [CompteNum#21] Batched: false, Format: CSV, Location: InMemoryFileIndex[adl://home/home/azhdipaasssh/fecs/Abdennacer/9-5Gb/2019-01-07/FEC/2019-01-07-16..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<CompteNum:string>
at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:56)
at org.apache.spark.sql.execution.exchange.ShuffleExchange.doExecute(ShuffleExchange.scala:115)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:138)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:135)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:116)
at org.apache.spark.sql.execution.InputAdapter.inputRDDs(WholeStageCodegenExec.scala:252)
at org.apache.spark.sql.execution.aggregate.HashAggregateExec.inputRDDs(HashAggregateExec.scala:141)
at org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:386)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:138)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:135)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:116)
at org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:228)
at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:275)
at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2431)
at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2430)
at org.apache.spark.sql.Dataset$$anonfun$55.apply(Dataset.scala:2838)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:65)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:2837)
at org.apache.spark.sql.Dataset.count(Dataset.scala:2430)
at com.test.spark.Loader.test2(Loader.java:60)
at com.test.spark.Loader.lambda$run$1(Loader.java:34)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.spark.sql.catalyst.errors.package$TreeNodeException: execute, tree:
Exchange hashpartitioning(CompteNum#21, 10)
+- *HashAggregate(keys=[CompteNum#21], functions=[], output=[CompteNum#21])
+- *FileScan csv [CompteNum#21] Batched: false, Format: CSV, Location: InMemoryFileIndex[adl://home/home/azhdipaasssh/fecs/Abdennacer/9-5Gb/2019-01-07/FEC/2019-01-07-16..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<CompteNum:string>
at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:56)
at org.apache.spark.sql.execution.exchange.ShuffleExchange.doExecute(ShuffleExchange.scala:115)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:138)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:135)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:116)
at org.apache.spark.sql.execution.InputAdapter.inputRDDs(WholeStageCodegenExec.scala:252)
at org.apache.spark.sql.execution.aggregate.HashAggregateExec.inputRDDs(HashAggregateExec.scala:141)
at org.apache.spark.sql.execution.aggregate.HashAggregateExec.inputRDDs(HashAggregateExec.scala:141)
at org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:386)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:138)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:135)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:116)
at org.apache.spark.sql.execution.exchange.ShuffleExchange.prepareShuffleDependency(ShuffleExchange.scala:88)
at org.apache.spark.sql.execution.exchange.ShuffleExchange$$anonfun$doExecute$1.apply(ShuffleExchange.scala:124)
at org.apache.spark.sql.execution.exchange.ShuffleExchange$$anonfun$doExecute$1.apply(ShuffleExchange.scala:115)
at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:52)
... 27 more
Caused by: java.lang.IllegalStateException: Cannot call methods on a stopped SparkContext.
This stopped SparkContext was created at:
org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:914)
com.test.spark.Loader.loadDataset(Loader.java:96)
com.test.spark.Loader.run(Loader.java:29)
com.test.spark.Main.main(Main.java:15)
sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
java.lang.reflect.Method.invoke(Method.java:498)
org.apache.spark.deploy.yarn.ApplicationMaster$$anon$3.run(ApplicationMaster.scala:646)
The currently active SparkContext was created at:
org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:914)
com.test.spark.Loader.loadDataset(Loader.java:96)
com.test.spark.Loader.run(Loader.java:29)
com.test.spark.Main.main(Main.java:15)
sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
java.lang.reflect.Method.invoke(Method.java:498)
org.apache.spark.deploy.yarn.ApplicationMaster$$anon$3.run(ApplicationMaster.scala:646)
at org.apache.spark.SparkContext.assertNotStopped(SparkContext.scala:100)
at org.apache.spark.SparkContext.broadcast(SparkContext.scala:1485)
at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat.buildReader(CSVFileFormat.scala:96)
at org.apache.spark.sql.execution.datasources.FileFormat$class.buildReaderWithPartitionValues(FileFormat.scala:117)
at org.apache.spark.sql.execution.datasources.TextBasedFileFormat.buildReaderWithPartitionValues(FileFormat.scala:148)
at org.apache.spark.sql.execution.FileSourceScanExec.inputRDD$lzycompute(DataSourceScanExec.scala:291)
at org.apache.spark.sql.execution.FileSourceScanExec.inputRDD(DataSourceScanExec.scala:289)
at org.apache.spark.sql.execution.FileSourceScanExec.inputRDDs(DataSourceScanExec.scala:309)
at org.apache.spark.sql.execution.aggregate.HashAggregateExec.inputRDDs(HashAggregateExec.scala:141)
at org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:386)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:138)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:135)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:116)
at org.apache.spark.sql.execution.exchange.ShuffleExchange.prepareShuffleDependency(ShuffleExchange.scala:88)
at org.apache.spark.sql.execution.exchange.ShuffleExchange$$anonfun$doExecute$1.apply(ShuffleExchange.scala:124)
at org.apache.spark.sql.execution.exchange.ShuffleExchange$$anonfun$doExecute$1.apply(ShuffleExchange.scala:115)
at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:52)
... 48 more
19/07/13 22:05:09 INFO YarnAllocator: Driver requested a total number of 0 executor(s).
日志没有提供太多信息,有没有人有同样的错误?
更新
这是 loadDataset(),但我认为它不会增加太多:
private Dataset<Row> loadDataset() {
SparkSession session = SparkSession.builder().getOrCreate();
String path = "/home/user/files/file.txt";
return session.read().option("header", "true").option("delimiter", "|").csv(path);
}
最佳答案
SparkEnv.set(SparkEnv.get)
此代码应在使用 spark 上下文/ session 的每个线程中执行。
请尝试并分享您的结果。
关于java - 多线程 spark sql 作业总是失败,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/57031531/
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