解决了记录器依赖性之后，我终于使用通常的“ java -jar”命令成功启动了Spring Boot应用程序。
应用程序中有一个REST服务，在其中使用Spark将其从Oracle和MongoDB中提取数据。 当我调用此REST服务时，出现了以下异常：
Driver stacktrace:
Job 0 failed: treeAggregate at MongoInferSchema.scala:80, took 0.233175 s
Servlet.service() for servlet [dispatcherServlet] in context with path [] threw exception [Request processing failed; nested exception is org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3, 172.16.212.49, executor 0): java.lang.ClassNotFoundException: com.mongodb.spark.rdd.partitioner.MongoPartition
at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
at java.lang.Class.forName0(Native Method)
at java.lang.Class.forName(Class.java:348)
at org.apache.spark.serializer.JavaDeserializationStream$$anon$1.resolveClass(JavaSerializer.scala:67)
at java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1866)
at java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1749)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:2040)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1571)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2285)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:2209)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:2067)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1571)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:431)
at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:75)
at org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:114)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:313)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Driver stacktrace:] with root cause
java.lang.ClassNotFoundException: com.mongodb.spark.rdd.partitioner.MongoPartition
at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
at java.lang.Class.forName0(Native Method)
at java.lang.Class.forName(Class.java:348)
at org.apache.spark.serializer.JavaDeserializationStream$$anon$1.resolveClass(JavaSerializer.scala:67)
at java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1866)
at java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1749)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:2040)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1571)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2285)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:2209)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:2067)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1571)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:431)
at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:75)
at org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:114)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:313)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Closing MongoClient: [127.0.0.1:27017]
pom.xml包含mongodb依赖项：
<dependency>
<groupId>org.mongodb.spark</groupId>
<artifactId>mongo-spark-connector_2.11</artifactId>
<version>2.3.0</version>
</dependency>
并且已编译的Jar包含mongodb库：
....
825351 Mon Jul 30 14:42:22 CEST 2018 BOOT-INF/lib/mongo-spark-connector_2.11-2.3.0.jar
1897919 Mon May 28 23:33:28 CEST 2018 BOOT-INF/lib/mongo-java-driver-3.6.4.jar
....
我也尝试将库添加到类路径中，但没有结果。
有人知道如何让Spark看到需要的罐子吗？
编辑：
根据@Ramdev的建议，我将这部分代码添加到了我的代码中：
JavaSparkContext context = new JavaSparkContext(sparkSession.sparkContext());
context.addJar("/home/user/.m3/repository/org/mongodb/spark/mongo-spark-connector_2.11/2.3.0/mongo-spark-connector_2.11-2.3.0.jar");
context.addJar("/home/user/.m3/repository/org/mongodb/mongo-java-driver/3.8.1/mongo-java-driver-3.8.1.jar");
结果是Spark现在看到了jar，但是似乎与applicacation jar中的jar冲突：
018-09-25 11:39:51 ERROR [dispatcherServlet]:182 - Servlet.service() for servlet [dispatcherServlet] in context with path [] threw exception [Handler dispatch failed; nested exception is java.lang.NoSuchMethodError: com.mongodb.client.MongoCollection.countDocuments(Lorg/bson/conversions/Bson;)J] with root cause
java.lang.NoSuchMethodError: com.mongodb.client.MongoCollection.countDocuments(Lorg/bson/conversions/Bson;)J
at com.mongodb.spark.rdd.partitioner.MongoSamplePartitioner$$anonfun$7.apply(MongoSamplePartitioner.scala:88)
at com.mongodb.spark.rdd.partitioner.MongoSamplePartitioner$$anonfun$7.apply(MongoSamplePartitioner.scala:88)
at com.mongodb.spark.MongoConnector$$anonfun$withCollectionDo$1.apply(MongoConnector.scala:186)
at com.mongodb.spark.MongoConnector$$anonfun$withCollectionDo$1.apply(MongoConnector.scala:184)
at com.mongodb.spark.MongoConnector$$anonfun$withDatabaseDo$1.apply(MongoConnector.scala:171)
at com.mongodb.spark.MongoConnector$$anonfun$withDatabaseDo$1.apply(MongoConnector.scala:171)
at com.mongodb.spark.MongoConnector.withMongoClientDo(MongoConnector.scala:154)
at com.mongodb.spark.MongoConnector.withDatabaseDo(MongoConnector.scala:171)
at com.mongodb.spark.MongoConnector.withCollectionDo(MongoConnector.scala:184)
at com.mongodb.spark.rdd.partitioner.MongoSamplePartitioner.partitions(MongoSamplePartitioner.scala:88)
at com.mongodb.spark.rdd.partitioner.DefaultMongoPartitioner.partitions(DefaultMongoPartitioner.scala:34)
at com.mongodb.spark.rdd.MongoRDD.getPartitions(MongoRDD.scala:139)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
at org.apache.spark.ShuffleDependency.<init>(Dependency.scala:91)
at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$.prepareShuffleDependency(ShuffleExchangeExec.scala:318)
at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.prepareShuffleDependency(ShuffleExchangeExec.scala:91)
at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$$anonfun$doExecute$1.apply(ShuffleExchangeExec.scala:128)
at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$$anonfun$doExecute$1.apply(ShuffleExchangeExec.scala:119)
at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:52)
at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.doExecute(ShuffleExchangeExec.scala:119)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at org.apache.spark.sql.execution.InputAdapter.inputRDDs(WholeStageCodegenExec.scala:371)
at org.apache.spark.sql.execution.SortExec.inputRDDs(SortExec.scala:121)
at org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:605)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at org.apache.spark.sql.execution.InputAdapter.doExecute(WholeStageCodegenExec.scala:363)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at org.apache.spark.sql.execution.joins.SortMergeJoinExec.inputRDDs(SortMergeJoinExec.scala:386)
at org.apache.spark.sql.execution.ProjectExec.inputRDDs(basicPhysicalOperators.scala:41)
at org.apache.spark.sql.execution.aggregate.HashAggregateExec.inputRDDs(HashAggregateExec.scala:150)
at org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:605)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.prepareShuffleDependency(ShuffleExchangeExec.scala:92)
at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$$anonfun$doExecute$1.apply(ShuffleExchangeExec.scala:128)
at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$$anonfun$doExecute$1.apply(ShuffleExchangeExec.scala:119)
at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:52)
at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.doExecute(ShuffleExchangeExec.scala:119)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at org.apache.spark.sql.execution.InputAdapter.inputRDDs(WholeStageCodegenExec.scala:371)
at org.apache.spark.sql.execution.aggregate.HashAggregateExec.inputRDDs(HashAggregateExec.scala:150)
at org.apache.spark.sql.execution.BaseLimitExec$class.inputRDDs(limit.scala:62)
at org.apache.spark.sql.execution.LocalLimitExec.inputRDDs(limit.scala:97)
at org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:605)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:247)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:337)
at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3273)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2484)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2484)
at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3254)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3253)
at org.apache.spark.sql.Dataset.head(Dataset.scala:2484)
at org.apache.spark.sql.Dataset.take(Dataset.scala:2698)
at org.apache.spark.sql.Dataset.showString(Dataset.scala:254)
at org.apache.spark.sql.Dataset.show(Dataset.scala:723)
at org.apache.spark.sql.Dataset.show(Dataset.scala:682)
at org.apache.spark.sql.Dataset.show(Dataset.scala:691)
at my.app.common.spark.SparkSpringBootHandler.querySpark(SparkSpringBootHandler.java:92)
SparkSpringBootHandler.java:85-92行
String queryJ = "select count(s.idlocalizator) "
+ "from installationOnBoard i join storicpos s on s.installation_uuid = i.uuid ";
result += sdf.format(new Date()) + " - ***************** QUERY ***************** Start...\n";
Dataset<Long> counter = sparkSession.sql(queryJ).as(Encoders.LONG());
counter.show();
答案 0 :(得分：1)
我不确定您如何集成Spark作业和Spring Boot。我正在根据我在一个项目中所做的事情分享自己的观点。
我们有一个单独的Spark / Scala项目，并使用sbt程序集构建了所有依赖项的胖子。
在Spring Boot项目方面，我们使用Apache Livy API调用Spark作业，并使用Apache Livy生成的批处理ID跟踪作业状态。
Apache Live可用于Spark 1.x和Spark 2.x
https://livy.incubator.apache.org/docs/latest/rest-api.html
我希望它可以在某些方面有所帮助。