数据库数据量较大时,查询失败,请问如何解决

读取数据的代码
val config =
NebulaConnectionConfig
.builder()
.withMetaAddress(address)
.withTimeout(6000)
.withConenctionRetry(2)
.build()
val nebulaReadEdgeConfig: ReadNebulaConfig = ReadNebulaConfig
.builder()
.withSpace(space ) // 数据库Space
.withLabel(label) // c2a07aa701474c81a7c9fec9bc4dc8a3
.withNoColumn(true)
.withLimit(2000)
.withPartitionNum(5)
.build()

报错:
WARN [driver-heartbeater] - Issue communicating with driver in heartbeater
org.apache.spark.rpc.RpcTimeoutException: Futures timed out after [10000 milliseconds]. This timeout is controlled by spark.executor.heartbeatInterval
at org.apache.spark.rpc.RpcTimeout.org$apache$spark$rpc$RpcTimeout$$createRpcTimeoutException(RpcTimeout.scala:47)
at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:62)
at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:58)
at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:36)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:76)
at org.apache.spark.rpc.RpcEndpointRef.askSync(RpcEndpointRef.scala:92)
at org.apache.spark.executor.Executor.org$apache$spark$executor$Executor$$reportHeartBeat(Executor.scala:841)
at org.apache.spark.executor.Executor$$anon$2$$anonfun$run$1.apply$mcV$sp(Executor.scala:870)
at org.apache.spark.executor.Executor$$anon$2$$anonfun$run$1.apply(Executor.scala:870)
at org.apache.spark.executor.Executor$$anon$2$$anonfun$run$1.apply(Executor.scala:870)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1945)
at org.apache.spark.executor.Executor$$anon$2.run(Executor.scala:870)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:308)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:180)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:294)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.util.concurrent.TimeoutException: Futures timed out after [10000 milliseconds]
at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:223)
at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:227)
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:220)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
… 14 more
WARN [dispatcher-event-loop-0] - Removing executor driver with no recent heartbeats: 200634 ms exceeds timeout 120000 ms
WARN [driver-heartbeater] - Issue communicating with driver in heartbeater
org.apache.spark.rpc.RpcTimeoutException: Futures timed out after [10000 milliseconds]. This timeout is controlled by spark.executor.heartbeatInterval
at org.apache.spark.rpc.RpcTimeout.org$apache$spark$rpc$RpcTimeout$$createRpcTimeoutException(RpcTimeout.scala:47)
at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:62)
at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:58)
at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:36)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:76)
at org.apache.spark.rpc.RpcEndpointRef.askSync(RpcEndpointRef.scala:92)
at org.apache.spark.executor.Executor.org$apache$spark$executor$Executor$$reportHeartBeat(Executor.scala:841)
at org.apache.spark.executor.Executor$$anon$2$$anonfun$run$1.apply$mcV$sp(Executor.scala:870)
at org.apache.spark.executor.Executor$$anon$2$$anonfun$run$1.apply(Executor.scala:870)
at org.apache.spark.executor.Executor$$anon$2$$anonfun$run$1.apply(Executor.scala:870)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1945)
at org.apache.spark.executor.Executor$$anon$2.run(Executor.scala:870)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:308)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:180)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:294)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.util.concurrent.TimeoutException: Futures timed out after [10000 milliseconds]
at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:223)
at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:227)
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:220)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
… 14 more
WARN [driver-heartbeater] - Issue communicating with driver in heartbeater
org.apache.spark.rpc.RpcTimeoutException: Futures timed out after [10000 milliseconds]. This timeout is controlled by spark.executor.heartbeatInterval
at org.apache.spark.rpc.RpcTimeout.org$apache$spark$rpc$RpcTimeout$$createRpcTimeoutException(RpcTimeout.scala:47)
at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:62)
at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:58)
at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:36)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:76)
at org.apache.spark.rpc.RpcEndpointRef.askSync(RpcEndpointRef.scala:92)
at org.apache.spark.executor.Executor.org$apache$spark$executor$Executor$$reportHeartBeat(Executor.scala:841)
at org.apache.spark.executor.Executor$$anon$2$$anonfun$run$1.apply$mcV$sp(Executor.scala:870)
at org.apache.spark.executor.Executor$$anon$2$$anonfun$run$1.apply(Executor.scala:870)
at org.apache.spark.executor.Executor$$anon$2$$anonfun$run$1.apply(Executor.scala:870)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1945)
at org.apache.spark.executor.Executor$$anon$2.run(Executor.scala:870)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:308)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:180)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:294)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.util.concurrent.TimeoutException: Futures timed out after [10000 milliseconds]
at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:223)
at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:227)
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:220)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
… 14 more
ERROR [dispatcher-event-loop-0] - Lost executor driver on localhost: Executor heartbeat timed out after 200634 ms
WARN [driver-heartbeater] - Issue communicating with driver in heartbeater
org.apache.spark.rpc.RpcTimeoutException: Futures timed out after [10000 milliseconds]. This timeout is controlled by spark.executor.heartbeatInterval
at org.apache.spark.rpc.RpcTimeout.org$apache$spark$rpc$RpcTimeout$$createRpcTimeoutException(RpcTimeout.scala:47)
at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:62)
at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:58)
at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:36)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:76)
at org.apache.spark.rpc.RpcEndpointRef.askSync(RpcEndpointRef.scala:92)
at org.apache.spark.executor.Executor.org$apache$spark$executor$Executor$$reportHeartBeat(Executor.scala:841)
at org.apache.spark.executor.Executor$$anon$2$$anonfun$run$1.apply$mcV$sp(Executor.scala:870)
at org.apache.spark.executor.Executor$$anon$2$$anonfun$run$1.apply(Executor.scala:870)
at org.apache.spark.executor.Executor$$anon$2$$anonfun$run$1.apply(Executor.scala:870)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1945)
at org.apache.spark.executor.Executor$$anon$2.run(Executor.scala:870)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:308)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:180)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:294)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.util.concurrent.TimeoutException: Futures timed out after [10000 milliseconds]
at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:223)
at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:227)
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:220)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
… 14 more
WARN [driver-heartbeater] - Issue communicating with driver in heartbeater
Exception in thread “dispatcher-event-loop-0” java.lang.OutOfMemoryError: Java heap space
WARN [dispatcher-event-loop-0] - Ignored failure: java.lang.OutOfMemoryError: Java heap space
at java.lang.String.toCharArray(String.java:2899)
at sun.net.www.ParseUtil.encodePath(ParseUtil.java:107)
at sun.misc.URLClassPath$JarLoader.checkResource(URLClassPath.java:959)
at sun.misc.URLClassPath$JarLoader.getResource(URLClassPath.java:1044)
at sun.misc.URLClassPath.getResource(URLClassPath.java:239)
at java.net.URLClassLoader$1.run(URLClassLoader.java:365)
at java.net.URLClassLoader$1.run(URLClassLoader.java:362)
at java.security.AccessController.doPrivileged(Native Method)
at java.net.URLClassLoader.findClass(URLClassLoader.java:361)
at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:338)
at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
at org.apache.spark.scheduler.Pool.executorLost(Pool.scala:88)
at org.apache.spark.scheduler.TaskSchedulerImpl.removeExecutor(TaskSchedulerImpl.scala:770)
at org.apache.spark.scheduler.TaskSchedulerImpl.executorLost(TaskSchedulerImpl.scala:685)
at org.apache.spark.HeartbeatReceiver$$anonfun$org$apache$spark$HeartbeatReceiver$$expireDeadHosts$3.apply(HeartbeatReceiver.scala:199)
at org.apache.spark.HeartbeatReceiver$$anonfun$org$apache$spark$HeartbeatReceiver$$expireDeadHosts$3.apply(HeartbeatReceiver.scala:195)
at scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:733)
at scala.collection.mutable.HashMap$$anonfun$foreach$1.apply(HashMap.scala:130)
at scala.collection.mutable.HashMap$$anonfun$foreach$1.apply(HashMap.scala:130)
at scala.collection.mutable.HashTable$class.foreachEntry(HashTable.scala:236)
at scala.collection.mutable.HashMap.foreachEntry(HashMap.scala:40)
at scala.collection.mutable.HashMap.foreach(HashMap.scala:130)
at scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:732)
at org.apache.spark.HeartbeatReceiver.org$apache$spark$HeartbeatReceiver$$expireDeadHosts(HeartbeatReceiver.scala:195)
at org.apache.spark.HeartbeatReceiver$$anonfun$receiveAndReply$1.applyOrElse(HeartbeatReceiver.scala:118)
at org.apache.spark.rpc.netty.Inbox$$anonfun$process$1.apply$mcV$sp(Inbox.scala:105)
at org.apache.spark.rpc.netty.Inbox.safelyCall(Inbox.scala:205)
at org.apache.spark.rpc.netty.Inbox.process(Inbox.scala:101)
at org.apache.spark.rpc.netty.Dispatcher$MessageLoop.run(Dispatcher.scala:221)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
ERROR [Executor task launch worker for task 0] - Exception in task 0.0 in stage 0.0 (TID 0)
java.lang.OutOfMemoryError: Java heap space
at com.vesoft.nebula.meta.ListEdgesResp.read(ListEdgesResp.java:359)
at com.vesoft.nebula.meta.MetaService$listEdges_result.read(MetaService.java:16086)
at com.vesoft.nebula.meta.MetaService$Client.recv_listEdges(MetaService.java:1131)
at com.vesoft.nebula.meta.MetaService$Client.listEdges(MetaService.java:1101)
at com.vesoft.nebula.client.meta.MetaClient.getEdges(MetaClient.java:338)
at com.vesoft.nebula.client.meta.MetaManager.fillMetaInfo(MetaManager.java:106)
at com.vesoft.nebula.client.meta.MetaManager.(MetaManager.java:74)
at com.vesoft.nebula.client.storage.StorageClient.connect(StorageClient.java:105)
at com.vesoft.nebula.connector.reader.NebulaPartitionReader.(NebulaPartitionReader.scala:98)
at com.vesoft.nebula.connector.reader.NebulaEdgePartitionReader.(NebulaEdgePartitionReader.scala:15)
at com.vesoft.nebula.connector.reader.NebulaEdgePartition.createPartitionReader(NebulaPartition.scala:22)
at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD.compute(DataSourceRDD.scala:42)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.UnionRDD.compute(UnionRDD.scala:105)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:123)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
ERROR [Executor task launch worker for task 0] - Uncaught exception in thread Thread[Executor task launch worker for task 0,5,main]
java.lang.OutOfMemoryError: Java heap space
at com.vesoft.nebula.meta.ListEdgesResp.read(ListEdgesResp.java:359)
at com.vesoft.nebula.meta.MetaService$listEdges_result.read(MetaService.java:16086)
at com.vesoft.nebula.meta.MetaService$Client.recv_listEdges(MetaService.java:1131)
at com.vesoft.nebula.meta.MetaService$Client.listEdges(MetaService.java:1101)
at com.vesoft.nebula.client.meta.MetaClient.getEdges(MetaClient.java:338)
at com.vesoft.nebula.client.meta.MetaManager.fillMetaInfo(MetaManager.java:106)
at com.vesoft.nebula.client.meta.MetaManager.(MetaManager.java:74)
at com.vesoft.nebula.client.storage.StorageClient.connect(StorageClient.java:105)
at com.vesoft.nebula.connector.reader.NebulaPartitionReader.(NebulaPartitionReader.scala:98)
at com.vesoft.nebula.connector.reader.NebulaEdgePartitionReader.(NebulaEdgePartitionReader.scala:15)
at com.vesoft.nebula.connector.reader.NebulaEdgePartition.createPartitionReader(NebulaPartition.scala:22)
at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD.compute(DataSourceRDD.scala:42)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.UnionRDD.compute(UnionRDD.scala:105)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:123)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
ERROR [dispatcher-event-loop-1] - Ignoring update with state FAILED for TID 0 because its task set is gone (this is likely the result of receiving duplicate task finished status updates) or its executor has been marked as failed.
INFO [Thread-1] - Invoking stop() from shutdown hook
INFO [Thread-1] - Stopped Spark@1e5f4170{HTTP/1.1,[http/1.1]}{0.0.0.0:4040}
INFO [Thread-1] - Stopped Spark web UI at http://DESKTOP-EI4RA7I:4040
INFO [main] - Job 0 failed: show at NebulaExample.scala:52, took 1214.011873 s
INFO [Thread-1] - ResultStage 0 (show at NebulaExample.scala:52) failed in 1213.918 s due to Stage cancelled because SparkContext was shut down
Exception in thread “main” org.apache.spark.SparkException: Job 0 cancelled because SparkContext was shut down
at org.apache.spark.scheduler.DAGScheduler$$anonfun$cleanUpAfterSchedulerStop$1.apply(DAGScheduler.scala:932)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$cleanUpAfterSchedulerStop$1.apply(DAGScheduler.scala:930)
at scala.collection.mutable.HashSet.foreach(HashSet.scala:78)
at org.apache.spark.scheduler.DAGScheduler.cleanUpAfterSchedulerStop(DAGScheduler.scala:930)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onStop(DAGScheduler.scala:2128)
at org.apache.spark.util.EventLoop.stop(EventLoop.scala:84)
at org.apache.spark.scheduler.DAGScheduler.stop(DAGScheduler.scala:2041)
at org.apache.spark.SparkContext$$anonfun$stop$6.apply$mcV$sp(SparkContext.scala:1949)
at org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1340)
at org.apache.spark.SparkContext.stop(SparkContext.scala:1948)
at org.apache.spark.SparkContext$$anonfun$2.apply$mcV$sp(SparkContext.scala:575)
at org.apache.spark.util.SparkShutdownHook.run(ShutdownHookManager.scala:216)
at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ShutdownHookManager.scala:188)
at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1$$anonfun$apply$mcV$sp$1.apply(ShutdownHookManager.scala:188)
at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1$$anonfun$apply$mcV$sp$1.apply(ShutdownHookManager.scala:188)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1945)
at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1.apply$mcV$sp(ShutdownHookManager.scala:188)
at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1.apply(ShutdownHookManager.scala:188)
at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1.apply(ShutdownHookManager.scala:188)
at scala.util.Try$.apply(Try.scala:192)
at org.apache.spark.util.SparkShutdownHookManager.runAll(ShutdownHookManager.scala:188)
at org.apache.spark.util.SparkShutdownHookManager$$anon$2.run(ShutdownHookManager.scala:178)
at org.apache.hadoop.util.ShutdownHookManager$1.run(ShutdownHookManager.java:54)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2082)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2101)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:365)
at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3389)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2550)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2550)
at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3370)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3369)
at org.apache.spark.sql.Dataset.head(Dataset.scala:2550)
at org.apache.spark.sql.Dataset.take(Dataset.scala:2764)
at org.apache.spark.sql.Dataset.getRows(Dataset.scala:254)
at org.apache.spark.sql.Dataset.showString(Dataset.scala:291)
at org.apache.spark.sql.Dataset.show(Dataset.scala:751)
at org.apache.spark.sql.Dataset.show(Dataset.scala:710)
at org.apache.spark.sql.Dataset.show(Dataset.scala:719)
at com.vesoft.nebula.algorithm.NebulaExample$.main(NebulaExample.scala:52)
at com.vesoft.nebula.algorithm.NebulaExample.main(NebulaExample.scala)
INFO [dispatcher-event-loop-2] - MapOutputTrackerMasterEndpoint stopped!

现象:
我有一个开发库、一个测试库,开发库数据量较小、测试库数据量 应该是千万级别的。
但是,要查询的space数据量、数据字典、数据都是一样的。
开发库 能很快查出来, 测试库 就会报错。
请问这个是什么原因,如何解决?

我的目标是查询space下所有的边进行社区发现计算。
加载边数据的代码为
var df = spark.read.nebula(config, nebulaReadEdgeConfig).loadEdgesToDF()

请问这种加载边数据的方式,是在数据库中按照边ID进行数据过滤;还是把所有边加载到内存中,再根据边Id进行过滤呢?
怎么会 出现: java.lang.OutOfMemoryError: Java heap space 的内存泄露呢。 我的space里面 数据只有十几条,但是整个库的数据量 是千万级别的。

@nicole

你的spark connector去读取某一个edgetype的数据时 现在是不能在server端过滤的,会把当前edgetype的边都拉到内存。 你需要调大jvm 的内存配置

此话题已在最后回复的 30 天后被自动关闭。不再允许新回复。