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算子:sample(false, 0.1)抽樣數據

ssi info efault span 數據 ignore pac scala contex

抽樣示例操作:

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)

算子:sample(false, 0.1)抽樣數據