提问参考模版:
- nebula 版本:3.2.1
- 部署方式:分布式
- 安装方式:RPM
- 是否为线上版本: N
- 问题的具体描述: nebula-exchange 导入 neo4j提示有精度缺失问题,exchange 是否有配置跳过此类异常或者应该如果配置nebula graph类型
org.neo4j.driver.exceptions.value.LossyCoercion: Cannot coerce INTEGER to Java int without losing precision
at org.neo4j.driver.internal.value.IntegerValue.asInt(IntegerValue.java:57)
at com.vesoft.nebula.exchange.utils.Neo4jUtils$.convertNeo4jData(Neo4jUtils.scala:21)
at com.vesoft.nebula.exchange.reader.Neo4JReader$$anonfun$1$$anonfun$apply$2$$anonfun$apply$1.apply$mcVI$sp(ServerBaseReader.scala:194)
at scala.collection.immutable.Range.foreach$mVc$sp(Range.scala:160)
at com.vesoft.nebula.exchange.reader.Neo4JReader$$anonfun$1$$anonfun$apply$2.apply(ServerBaseReader.scala:193)
at com.vesoft.nebula.exchange.reader.Neo4JReader$$anonfun$1$$anonfun$apply$2.apply(ServerBaseReader.scala:191)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:410)
at scala.collection.Iterator$$anon$12.next(Iterator.scala:445)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:394)
at scala.collection.Iterator$class.foreach(Iterator.scala:891)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1334)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
at scala.collection.AbstractIterator.to(Iterator.scala:1334)
at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1334)
at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
at scala.collection.AbstractIterator.toArray(Iterator.scala:1334)
at org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$29.apply(RDD.scala:1364)
at org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$29.apply(RDD.scala:1364)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2101)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2101)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:121)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:750)