算子：sample(false, 0.1)抽样数据

抽样示例操作：

scala> import org.apache.spark.sql.hive.HiveContext
import org.apache.spark.sql.hive.HiveContext

scala> val hiveContext = new HiveContext(sc)
17/11/07 17:19:36 WARN SessionState: load mapred-default.xml, HIVE_CONF_DIR env not found!
17/11/07 17:19:37 WARN SessionState: load mapred-default.xml, HIVE_CONF_DIR env not found!
hiveContext: org.apache.spark.sql.hive.HiveContext = org.apache.spark.sql.hive.HiveContext@14cc2fdd

scala> hiveContext.sql("use my_hive_db")
17/11/07 17:19:40 WARN SessionState: METASTORE_FILTER_HOOK will be ignored, since hive.security.authorization.manager is set to instance of HiveAuthorizerFactory.
17/11/07 17:19:40 WARN UserGroupInformation: No groups available for user acount_rc
res20: org.apache.spark.sql.DataFrame = [result: string]

scala> val sampledPairs = hiveContext.sql("select objectid from myobjectid")
    .map(s=>(s.getAs[String]("objectid"),1))
    .sample(false, 0.1)
17/11/07 17:19:40 WARN UserGroupInformation: No groups available for user acount_rc
17/11/07 17:19:40 WARN UserGroupInformation: No groups available for user acount_rc
sampledPairs: org.apache.spark.rdd.RDD[(String, Int)] = PartitionwiseSampledRDD[1059] at sample at <console>:32

scala> val sampledWordCounts = sampledPairs.countByKey
sampledWordCounts: scala.collection.Map[String,Long] = Map(193700355 -> 32348, 101549569 -> 81388, 100890370 -> 66425, 184703237 -> 60943, 
184563457 -> 77401, 100692995 -> 55021, 184756482 -> 88707, 193611009 -> 1588, 185257985 -> 16457, 190035714 -> 14209, 153225089 -> 41515, 
100811782 -> 115963, 100782849 -> 54729, 184581890 -> 70271, 185388291 -> 76225, 185278978 -> 40917, 80085891 -> 66957, 184957442 -> 59129, 
153127554 -> 146, 101362179 -> 18600, 193658626 -> 48758, 79805058 -> 17477, 101623810 -> 263451, 184637699 -> 23640, 185363457 -> 24341, 
153561730 -> 19010, 184722690 -> 2516, 79906177 -> 21106, 193805313 -> 78224, 184739585 -> 34405, 101342210 -> 60860, 193511427 -> 77125, 
101244675 -> 624, 80425606 -> 12167, 189870594 -> 6944, 101441025 -> 39970, 185549825 -> 322, 101125633...
scala> sampledWordCounts.foreach(println(_))
(193700355,32348)
(101549569,81388)
(100890370,66425)
(184703237,60943)
(184563457,77401)
(100692995,55021)
(184756482,88707)
(193611009,1588)
(185257985,16457)
(190035714,14209)
(153225089,41515)
(100811782,115963)
(100782849,54729)
(184581890,70271)