Spark Scala 从 rdd.foreachPartition 取回数据

Question

I have some code like this:

      println("\nBEGIN Last Revs Class: "+ distinctFileGidsRDD.getClass)
      val lastRevs = distinctFileGidsRDD.
        foreachPartition(iter => {
          SetupJDBC(jdbcDriver, jdbcUrl, jdbcUser, jdbcPassword)
          while(iter.hasNext) {
            val item = iter.next()
            //println(item(0))
            println("String: "+item(0).toString())
            val jsonStr = DB.readOnly { implicit session =>
              sql"SELECT jsonStr FROM lasttail WHERE fileGId = ${item(0)}::varchar".
                map { resultSet => resultSet.string(1) }.single.apply()
            }
            println("\nJSON: "+jsonStr)
          }
        })
      println("\nEND Last Revs Class: "+ lastRevs.getClass)

The code outputs (with heavy edits) something like:

BEGIN Last Revs Class: class org.apache.spark.rdd.MapPartitionsRDD
String: 1fqhSXPE3GwrJ6SZzC65gJnBaB5_b7j3pWNSfqzU5FoM
JSON: Some({"Struct":{"fileGid":"1fqhSXPE3GwrJ6SZzC65gJnBaB5_b7j3pWNSfqzU5FoM",... )
String: 1eY2wxoVq17KGMUBzCZZ34J9gSNzF038grf5RP38DUxw
JSON: Some({"Struct":{"fileGid":"1fqhSXPE3GwrJ6SZzC65gJnBaB5_b7j3pWNSfqzU5FoM",... )
...
JSON: None()
END Last Revs Class: void

QUESTION 1: How can I get the lastRevs value to be in a useful format like the JSON string/null or an option like Some / None?

QUESTION 2: My preference: IS there another way get at partitions data that an RDD-like format (rather than the iterator format)?

dstream.foreachRDD { (rdd, time) =>
  rdd.foreachPartition { partitionIterator =>
    val partitionId = TaskContext.get.partitionId()
    val uniqueId = generateUniqueId(time.milliseconds, partitionId)
    // use this uniqueId to transactionally commit the data in partitionIterator
  } 
}

from http://spark.apache.org/docs/latest/streaming-programming-guide.html#performance-tuning

QUESTION 3: Is the method of getting data that I am using a sane method (given I am following the link above)? (Put aside the fact that this is a scalikejdbc system JDBC right now. This is going to be a key, value store of some type other than this prototype.)

Answer 1

To create a transformation that uses resources local to the executor (such as a DB or network connection), you should use rdd.mapPartitions . It allows to initialize some code locally to the executor and use those local resources to process the data in the partition.

The code should look like:

 val lastRevs = distinctFileGidsRDD.
        mapPartitions{iter => 
          SetupJDBC(jdbcDriver, jdbcUrl, jdbcUser, jdbcPassword)
          iter.map{ element => 
            DB.readOnly { implicit session =>
              sql"SELECT jsonStr FROM lasttail WHERE fileGId = ${element(0)}::varchar"
              .map { resultSet => resultSet.string(1) }.single.apply()
            }
          }
        }