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nebula 版本：（2.0.1）
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部署方式（分布式）：
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是否为线上版本：Y
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问题的具体描述
当使用pagerank时，报如下错误
Caused by: java.lang.NumberFormatException: For input string: "player105"
at java.lang.NumberFormatException.forInputString(NumberFormatException.java:65)
at java.lang.Long.parseLong(Long.java:589)
at java.lang.Long.parseLong(Long.java:631)
at scala.collection.immutable.StringLike$class.toLong(StringLike.scala:277)
at scala.collection.immutable.StringOps.toLong(StringOps.scala:29)
at com.vesoft.nebula.algorithm.utils.NebulaUtil$$anonfun$1.apply(NebulaUtil.scala:30)
at com.vesoft.nebula.algorithm.utils.NebulaUtil$$anonfun$1.apply(NebulaUtil.scala:26)
at org.apache.spark.sql.execution.MapElementsExec$$anonfun$7$$anonfun$apply$1.apply(objects.scala:236)
at org.apache.spark.sql.execution.MapElementsExec$$anonfun$7$$anonfun$apply$1.apply(objects.scala:236)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:410)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:410)
at scala.collection.Iterator$class.foreach(Iterator.scala:891)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1334)
at org.apache.spark.graphx.EdgeRDD$$anonfun$1.apply(EdgeRDD.scala:107)
at org.apache.spark.graphx.EdgeRDD$$anonfun$1.apply(EdgeRDD.scala:105)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndex$1$$anonfun$apply$25.apply(RDD.scala:853)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndex$1$$anonfun$apply$25.apply(RDD.scala:853)
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$$anonfun$7.apply(RDD.scala:337)
at org.apache.spark.rdd.RDD$$anonfun$7.apply(RDD.scala:335)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1165)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1156)
at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:1091)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:1156)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:882)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:335)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:286)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55)
at org.apache.spark.scheduler.Task.run(Task.scala:123)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
pagerank配置：
read: {
# Nebula metad server address, multiple addresses are split by English comma
metaAddress: "192.168.5.180:9559,192.168.5.181:9559,192.168.5.182:9559"
# Nebula space
space: basketballplayer
# Nebula edge types, multiple labels means that data from multiple edges will union together
labels: ["serve"]
# Nebula edge property name for each edge type, this property will be as weight col for algorithm.
# Make sure the weightCols are corresponding to labels.
weightCols: ["start_year"]
}
使用Pagerank时，vid不能是string类型吗、
这个和你的设置有关系的