How to close connection in mapPartitions?

[Bin Wang]

I use mapPartitions to open connections to Redis, I write it like this:

    val seqs = lines.mapPartitions { lines =>
      val cache = new RedisCache(redisUrl, redisPort)
      val result = lines.map(line => Parser.parseBody(line, cache))
      cache.redisPool.close
      result
    }

But it seems the pool is closed before I use it. Am I doing anything wrong?
Here is the error:

java.lang.IllegalStateException: Pool not open
        at 
org.apache.commons.pool.BaseObjectPool.assertOpen(BaseObjectPool.java:140)
        at 
org.apache.commons.pool.impl.StackObjectPool.borrowObject(StackObjectPool.java:166)
        at com.redis.RedisClientPool.withClient(Pool.scala:34)
        at com.appadhoc.data.cache.RedisCache.getExpId(RedisCache.scala:17)
        at 
com.appadhoc.data.parser.Parser$$anonfun$parseBody$1.apply(Parser.scala:29)
        at 
com.appadhoc.data.parser.Parser$$anonfun$parseBody$1.apply(Parser.scala:26)
        at 
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
        at 
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
        at scala.collection.immutable.List.foreach(List.scala:318)
        at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
        at scala.collection.AbstractTraversable.map(Traversable.scala:105)
        at com.appadhoc.data.parser.Parser$.parseBody(Parser.scala:26)
        at 
com.appadhoc.data.main.StatCounter$$anonfun$2$$anonfun$3.apply(StatCounter.scala:33)
        at 
com.appadhoc.data.main.StatCounter$$anonfun$2$$anonfun$3.apply(StatCounter.scala:33)
        at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
        at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
        at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
        at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
        at 
org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:209)
        at 
org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:73)
        at 
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
        at 
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
        at org.apache.spark.scheduler.Task.run(Task.scala:88)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
        at 
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
        at 
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
        at java.lang.Thread.run(Thread.java:745)