Spark rdd.count()会产生不一致的结果

Question

我有点困惑.

一个简单的rdd.count()在多次运行时给出不同的结果.

这是我运行的代码:

val inputRdd = sc.newAPIHadoopRDD(inputConfig,
classOf[com.mongodb.hadoop.MongoInputFormat],
classOf[Long],
classOf[org.bson.BSONObject])

println(inputRdd.count())

它打开与MondoDb服务器的连接,并简单地计算对象.似乎很直接给我

根据MongoDb,有3,349,495个条目

这是我的火花输出,都运行相同的jar:

spark1 :    3.257.048  
spark2 :    3.303.272  
spark3 :    3.303.272  
spark4 :    3.303.272  
spark5 :    3.303.271   
spark6 :    3.303.271  
spark7 :    3.303.272  
spark8 :    3.303.272  
spark9 :    3.306.300  
spark10:    3.303.272  
spark11:    3.303.271  

Spark和MongoDb在同一个集群上运行.
我们正在运行:

Spark version 1.5.0-cdh5.6.1  
Scala version 2.10.4  
MongoDb version 2.6.12  

不幸的是我们无法更新这些

Spark不确定吗？
有没有人可以开导我？

提前致谢

编辑/更多信息
我刚刚注意到我们的mongod.log中有错误.这个错误会导致不一致的行为吗？

[rsBackgroundSync] replSet not trying to sync from hadoop04:27017, it is vetoed for 333 more seconds
[rsBackgroundSync] replSet syncing to: hadoop05:27017
[rsBackgroundSync] replSet not trying to sync from hadoop05:27017, it is vetoed for 600 more seconds
[rsBackgroundSync] replSet not trying to sync from hadoop04:27017, it is vetoed for 333 more seconds
[rsBackgroundSync] replSet not trying to sync from hadoop05:27017, it is vetoed for 600 more seconds
[rsBackgroundSync] replSet not trying to sync from hadoop04:27017, it is vetoed for 333 more seconds
[rsBackgroundSync] replSet error RS102 too stale to catch up, at least from hadoop05:27017
[rsBackgroundSync] replSet our last optime : Jul  2 10:19:44 57777920:111
[rsBackgroundSync] replSet oldest at hadoop05:27017 : Jul  5 15:17:58 577bb386:59
[rsBackgroundSync] replSet See http://dochub.mongodb.org/core/resyncingaverystalereplicasetmember
[rsBackgroundSync] replSet error RS102 too stale to catch up

Answer 1

正如您已经发现的，问题似乎不在于 Spark（或 scala），而在于 MongoDB。

这样，关于差异的问题似乎就得到了解决。

您仍然希望解决实际的 MongoDB 错误，提供的链接可以是一个很好的起点： http: //dochub.mongodb.org/core/resyncingaverystalereplicasetmember