内容简介：求助KMeans算法关于转换矩阵Vectors问题
遇到的问题，KMeans算法中，通过map算子，两种处理方法，结果不一样，第一种莫名的增加了很多列？
1.数据内容如下 test1.csv
2.完整代码如下
val rawData = sc.textFile("E:\\test1.csv")
println("----11122221-----")
rawData.foreach(println )
val labelsAndData = rawData.map{ line =>
val label = line.split(',').toString
println("lable:...."+label)
val vector = Vectors.dense(label.map(_.toDouble).toArray)
println("vector11111:......"+vector)
(label,vector)
/**
* 或者这样写
*/
val label2 = line.split(',')
val aa2 = label2.map(_.toDouble)
val vector2 = Vectors.dense(label2.map(_.toDouble))
println("vector22222:...."+vector2)
(label2,vector2)
}
labelsAndData.foreach(println )
val data = labelsAndData.values
println("---------******---------")
println("data:"+data)
data.foreach(println )
val dataAsArray = data.map(_.toArray)
println("dataAsArray:"+dataAsArray)
dataAsArray.foreach(println )
val sums = dataAsArray.reduce(
(a,b) => a.zip(b).map( t => t._1 + t._2)
)
for(ele <- sums) println(ele)
println("sums 数量："+sums.length)
输出结果如下：
17/06/01 13:29:48 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on localhost:60540 (size: 9.8 KB, free: 1132.5 MB) 17/06/01 13:29:48 INFO SparkContext: Created broadcast 0 from textFile at zip.scala:72 ----11122221----- 17/06/01 13:29:48 INFO FileInputFormat: Total input paths to process : 1 17/06/01 13:29:48 INFO SparkContext: Starting job: foreach at zip.scala:74 17/06/01 13:29:48 INFO DAGScheduler: Got job 0 (foreach at zip.scala:74) with 1 output partitions 17/06/01 13:29:48 INFO DAGScheduler: Final stage: ResultStage 0 (foreach at zip.scala:74) 17/06/01 13:29:48 INFO DAGScheduler: Parents of final stage: List() 17/06/01 13:29:48 INFO DAGScheduler: Missing parents: List() 17/06/01 13:29:48 INFO DAGScheduler: Submitting ResultStage 0 (E:\test1.csv MapPartitionsRDD[1] at textFile at zip.scala:72), which has no missing parents 17/06/01 13:29:48 INFO MemoryStore: Block broadcast_1 stored as values in memory (estimated size 3.0 KB, free 120.5 KB) 17/06/01 13:29:48 INFO MemoryStore: Block broadcast_1_piece0 stored as bytes in memory (estimated size 1799.0 B, free 122.2 KB) 17/06/01 13:29:48 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on localhost:60540 (size: 1799.0 B, free: 1132.5 MB) 17/06/01 13:29:48 INFO SparkContext: Created broadcast 1 from broadcast at DAGScheduler.scala:1006 17/06/01 13:29:48 INFO DAGScheduler: Submitting 1 missing tasks from ResultStage 0 (E:\test1.csv MapPartitionsRDD[1] at textFile at zip.scala:72) 17/06/01 13:29:48 INFO TaskSchedulerImpl: Adding task set 0.0 with 1 tasks 17/06/01 13:29:48 INFO TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0, localhost, partition 0,PROCESS_LOCAL, 2120 bytes) 17/06/01 13:29:48 INFO Executor: Running task 0.0 in stage 0.0 (TID 0) 17/06/01 13:29:48 INFO HadoopRDD: Input split: file:/E:/test1.csv:0+21 17/06/01 13:29:48 INFO deprecation: mapred.tip.id is deprecated. Instead, use mapreduce.task.id 17/06/01 13:29:48 INFO deprecation: mapred.task.id is deprecated. Instead, use mapreduce.task.attempt.id 17/06/01 13:29:48 INFO deprecation: mapred.task.is.map is deprecated. Instead, use mapreduce.task.ismap 17/06/01 13:29:48 INFO deprecation: mapred.task.partition is deprecated. Instead, use mapreduce.task.partition 17/06/01 13:29:48 INFO deprecation: mapred.job.id is deprecated. Instead, use mapreduce.job.id 1,2,3 4,5,6 7,8,9 17/06/01 13:29:48 INFO Executor: Finished task 0.0 in stage 0.0 (TID 0). 2044 bytes result sent to driver 17/06/01 13:29:48 INFO TaskSetManager: Finished task 0.0 in stage 0.0 (TID 0) in 60 ms on localhost (1/1) 17/06/01 13:29:48 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool 17/06/01 13:29:48 INFO DAGScheduler: ResultStage 0 (foreach at zip.scala:74) finished in 0.070 s 17/06/01 13:29:48 INFO DAGScheduler: Job 0 finished: foreach at zip.scala:74, took 0.136096 s 17/06/01 13:29:48 INFO SparkContext: Starting job: foreach at zip.scala:94 17/06/01 13:29:48 INFO DAGScheduler: Got job 1 (foreach at zip.scala:94) with 1 output partitions 17/06/01 13:29:48 INFO DAGScheduler: Final stage: ResultStage 1 (foreach at zip.scala:94) 17/06/01 13:29:48 INFO DAGScheduler: Parents of final stage: List() 17/06/01 13:29:48 INFO DAGScheduler: Missing parents: List() 17/06/01 13:29:48 INFO DAGScheduler: Submitting ResultStage 1 (MapPartitionsRDD[2] at map at zip.scala:75), which has no missing parents 17/06/01 13:29:48 INFO MemoryStore: Block broadcast_2 stored as values in memory (estimated size 3.1 KB, free 125.3 KB) 17/06/01 13:29:48 INFO MemoryStore: Block broadcast_2_piece0 stored as bytes in memory (estimated size 1865.0 B, free 127.1 KB) 17/06/01 13:29:48 INFO BlockManagerInfo: Added broadcast_2_piece0 in memory on localhost:60540 (size: 1865.0 B, free: 1132.5 MB) 17/06/01 13:29:48 INFO SparkContext: Created broadcast 2 from broadcast at DAGScheduler.scala:1006 17/06/01 13:29:48 INFO DAGScheduler: Submitting 1 missing tasks from ResultStage 1 (MapPartitionsRDD[2] at map at zip.scala:75) 17/06/01 13:29:48 INFO TaskSchedulerImpl: Adding task set 1.0 with 1 tasks 17/06/01 13:29:48 INFO TaskSetManager: Starting task 0.0 in stage 1.0 (TID 1, localhost, partition 0,PROCESS_LOCAL, 2120 bytes) lable:....[Ljava.lang.String;@3d38491e 17/06/01 13:29:48 INFO Executor: Running task 0.0 in stage 1.0 (TID 1) 17/06/01 13:29:48 INFO HadoopRDD: Input split: file:/E:/test1.csv:0+21 vector11111:......[91.0,76.0,106.0,97.0,118.0,97.0,46.0,108.0,97.0,110.0,103.0,46.0,83.0,116.0,114.0,105.0,110.0,103.0,59.0,64.0,51.0,100.0,51.0,56.0,52.0,57.0,49.0,101.0] vector22222:....[1.0,2.0,3.0] ([Ljava.lang.String;@751013ad,[1.0,2.0,3.0]) lable:....[Ljava.lang.String;@7607112c vector11111:......[91.0,76.0,106.0,97.0,118.0,97.0,46.0,108.0,97.0,110.0,103.0,46.0,83.0,116.0,114.0,105.0,110.0,103.0,59.0,64.0,55.0,54.0,48.0,55.0,49.0,49.0,50.0,99.0] vector22222:....[4.0,5.0,6.0] ([Ljava.lang.String;@5884de0f,[4.0,5.0,6.0]) lable:....[Ljava.lang.String;@385daf7b vector11111:......[91.0,76.0,106.0,97.0,118.0,97.0,46.0,108.0,97.0,110.0,103.0,46.0,83.0,116.0,114.0,105.0,110.0,103.0,59.0,64.0,51.0,56.0,53.0,100.0,97.0,102.0,55.0,98.0] vector22222:....[7.0,8.0,9.0] ([Ljava.lang.String;@4da54ea6,[7.0,8.0,9.0]) 17/06/01 13:29:48 INFO Executor: Finished task 0.0 in stage 1.0 (TID 1). 2044 bytes result sent to driver 17/06/01 13:29:48 INFO TaskSetManager: Finished task 0.0 in stage 1.0 (TID 1) in 12 ms on localhost (1/1) 17/06/01 13:29:48 INFO TaskSchedulerImpl: Removed TaskSet 1.0, whose tasks have all completed, from pool 17/06/01 13:29:48 INFO DAGScheduler: ResultStage 1 (foreach at zip.scala:94) finished in 0.013 s 17/06/01 13:29:48 INFO DAGScheduler: Job 1 finished: foreach at zip.scala:94, took 0.033489 s ---------******--------- data:MapPartitionsRDD[3] at values at zip.scala:95 17/06/01 13:29:48 INFO SparkContext: Starting job: foreach at zip.scala:98 17/06/01 13:29:48 INFO DAGScheduler: Got job 2 (foreach at zip.scala:98) with 1 output partitions 17/06/01 13:29:48 INFO DAGScheduler: Final stage: ResultStage 2 (foreach at zip.scala:98) 17/06/01 13:29:48 INFO DAGScheduler: Parents of final stage: List() 17/06/01 13:29:48 INFO DAGScheduler: Missing parents: List() 17/06/01 13:29:48 INFO DAGScheduler: Submitting ResultStage 2 (MapPartitionsRDD[3] at values at zip.scala:95), which has no missing parents 17/06/01 13:29:48 INFO MemoryStore: Block broadcast_3 stored as values in memory (estimated size 3.3 KB, free 130.4 KB) lable:....[Ljava.lang.String;@4f707786 vector11111:......[91.0,76.0,106.0,97.0,118.0,97.0,46.0,108.0,97.0,110.0,103.0,46.0,83.0,116.0,114.0,105.0,110.0,103.0,59.0,64.0,52.0,102.0,55.0,48.0,55.0,55.0,56.0,54.0] vector22222:....[1.0,2.0,3.0] [1.0,2.0,3.0] lable:....[Ljava.lang.String;@57978dea vector11111:......[91.0,76.0,106.0,97.0,118.0,97.0,46.0,108.0,97.0,110.0,103.0,46.0,83.0,116.0,114.0,105.0,110.0,103.0,59.0,64.0,53.0,55.0,57.0,55.0,56.0,100.0,101.0,97.0] vector22222:....[4.0,5.0,6.0] [4.0,5.0,6.0] lable:....[Ljava.lang.String;@20028443 vector11111:......[91.0,76.0,106.0,97.0,118.0,97.0,46.0,108.0,97.0,110.0,103.0,46.0,83.0,116.0,114.0,105.0,110.0,103.0,59.0,64.0,50.0,48.0,48.0,50.0,56.0,52.0,52.0,51.0] vector22222:....[7.0,8.0,9.0] [7.0,8.0,9.0] 17/06/01 13:29:48 INFO MemoryStore: Block broadcast_3_piece0 stored as bytes in memory (estimated size 1951.0 B, free 132.3 KB) 17/06/01 13:29:48 INFO BlockManagerInfo: Added broadcast_3_piece0 in memory on localhost:60540 (size: 1951.0 B, free: 1132.5 MB) 17/06/01 13:29:48 INFO SparkContext: Created broadcast 3 from broadcast at DAGScheduler.scala:1006 17/06/01 13:29:48 INFO DAGScheduler: Submitting 1 missing tasks from ResultStage 2 (MapPartitionsRDD[3] at values at zip.scala:95) 17/06/01 13:29:48 INFO TaskSchedulerImpl: Adding task set 2.0 with 1 tasks 17/06/01 13:29:48 INFO TaskSetManager: Starting task 0.0 in stage 2.0 (TID 2, localhost, partition 0,PROCESS_LOCAL, 2120 bytes) 17/06/01 13:29:48 INFO Executor: Running task 0.0 in stage 2.0 (TID 2) 17/06/01 13:29:48 INFO HadoopRDD: Input split: file:/E:/test1.csv:0+21 17/06/01 13:29:48 INFO Executor: Finished task 0.0 in stage 2.0 (TID 2). 2044 bytes result sent to driver dataAsArray:MapPartitionsRDD[4] at map at zip.scala:100 17/06/01 13:29:48 INFO TaskSetManager: Finished task 0.0 in stage 2.0 (TID 2) in 21 ms on localhost (1/1) 17/06/01 13:29:48 INFO TaskSchedulerImpl: Removed TaskSet 2.0, whose tasks have all completed, from pool 17/06/01 13:29:48 INFO DAGScheduler: ResultStage 2 (foreach at zip.scala:98) finished in 0.022 s 17/06/01 13:29:48 INFO DAGScheduler: Job 2 finished: foreach at zip.scala:98, took 0.016712 s 17/06/01 13:29:48 INFO SparkContext: Starting job: foreach at zip.scala:102 17/06/01 13:29:48 INFO DAGScheduler: Got job 3 (foreach at zip.scala:102) with 1 output partitions 17/06/01 13:29:48 INFO DAGScheduler: Final stage: ResultStage 3 (foreach at zip.scala:102) 17/06/01 13:29:48 INFO DAGScheduler: Parents of final stage: List() 17/06/01 13:29:48 INFO DAGScheduler: Missing parents: List() 17/06/01 13:29:48 INFO DAGScheduler: Submitting ResultStage 3 (MapPartitionsRDD[4] at map at zip.scala:100), which has no missing parents 17/06/01 13:29:48 INFO MemoryStore: Block broadcast_4 stored as values in memory (estimated size 3.4 KB, free 135.7 KB) 17/06/01 13:29:48 INFO MemoryStore: Block broadcast_4_piece0 stored as bytes in memory (estimated size 1988.0 B, free 137.7 KB) 17/06/01 13:29:48 INFO BlockManagerInfo: Added broadcast_4_piece0 in memory on localhost:60540 (size: 1988.0 B, free: 1132.5 MB) 17/06/01 13:29:48 INFO SparkContext: Created broadcast 4 from broadcast at DAGScheduler.scala:1006 17/06/01 13:29:48 INFO DAGScheduler: Submitting 1 missing tasks from ResultStage 3 (MapPartitionsRDD[4] at map at zip.scala:100) 17/06/01 13:29:48 INFO TaskSchedulerImpl: Adding task set 3.0 with 1 tasks 17/06/01 13:29:48 INFO TaskSetManager: Starting task 0.0 in stage 3.0 (TID 3, localhost, partition 0,PROCESS_LOCAL, 2120 bytes) 17/06/01 13:29:48 INFO Executor: Running task 0.0 in stage 3.0 (TID 3) lable:....[Ljava.lang.String;@4f304a06 vector11111:......[91.0,76.0,106.0,97.0,118.0,97.0,46.0,108.0,97.0,110.0,103.0,46.0,83.0,116.0,114.0,105.0,110.0,103.0,59.0,64.0,52.0,102.0,51.0,48.0,52.0,97.0,48.0,54.0] vector22222:....[1.0,2.0,3.0] [D@508a86c7 lable:....[Ljava.lang.String;@d158d30 vector11111:......[91.0,76.0,106.0,97.0,118.0,97.0,46.0,108.0,97.0,110.0,103.0,46.0,83.0,116.0,114.0,105.0,110.0,103.0,59.0,64.0,100.0,49.0,53.0,56.0,100.0,51.0,48.0] vector22222:....[4.0,5.0,6.0] [D@54314d3d lable:....[Ljava.lang.String;@199c4dc7 vector11111:......[91.0,76.0,106.0,97.0,118.0,97.0,46.0,108.0,97.0,110.0,103.0,46.0,83.0,116.0,114.0,105.0,110.0,103.0,59.0,64.0,49.0,57.0,57.0,99.0,52.0,100.0,99.0,55.0] vector22222:....[7.0,8.0,9.0] [D@1d244c8d 17/06/01 13:29:49 INFO HadoopRDD: Input split: file:/E:/test1.csv:0+21 17/06/01 13:29:49 INFO Executor: Finished task 0.0 in stage 3.0 (TID 3). 2044 bytes result sent to driver 17/06/01 13:29:49 INFO TaskSetManager: Finished task 0.0 in stage 3.0 (TID 3) in 20 ms on localhost (1/1) 17/06/01 13:29:49 INFO TaskSchedulerImpl: Removed TaskSet 3.0, whose tasks have all completed, from pool 17/06/01 13:29:49 INFO DAGScheduler: ResultStage 3 (foreach at zip.scala:102) finished in 0.020 s 17/06/01 13:29:49 INFO DAGScheduler: Job 3 finished: foreach at zip.scala:102, took 0.031459 s 17/06/01 13:29:49 INFO BlockManagerInfo: Removed broadcast_3_piece0 on localhost:60540 in memory (size: 1951.0 B, free: 1132.5 MB) 17/06/01 13:29:49 INFO SparkContext: Starting job: reduce at zip.scala:103 17/06/01 13:29:49 INFO DAGScheduler: Got job 4 (reduce at zip.scala:103) with 1 output partitions 17/06/01 13:29:49 INFO DAGScheduler: Final stage: ResultStage 4 (reduce at zip.scala:103) 17/06/01 13:29:49 INFO DAGScheduler: Parents of final stage: List() 17/06/01 13:29:49 INFO DAGScheduler: Missing parents: List() 17/06/01 13:29:49 INFO DAGScheduler: Submitting ResultStage 4 (MapPartitionsRDD[4] at map at zip.scala:100), which has no missing parents 17/06/01 13:29:49 INFO MemoryStore: Block broadcast_5 stored as values in memory (estimated size 3.4 KB, free 135.9 KB) 17/06/01 13:29:49 INFO MemoryStore: Block broadcast_5_piece0 stored as bytes in memory (estimated size 1982.0 B, free 137.8 KB) lable:....[Ljava.lang.String;@4f867a2b vector11111:......[91.0,76.0,106.0,97.0,118.0,97.0,46.0,108.0,97.0,110.0,103.0,46.0,83.0,116.0,114.0,105.0,110.0,103.0,59.0,64.0,52.0,102.0,56.0,54.0,55.0,97.0,50.0,98.0] vector22222:....[1.0,2.0,3.0] lable:....[Ljava.lang.String;@4d6c48b7 vector11111:......[91.0,76.0,106.0,97.0,118.0,97.0,46.0,108.0,97.0,110.0,103.0,46.0,83.0,116.0,114.0,105.0,110.0,103.0,59.0,64.0,52.0,100.0,54.0,99.0,52.0,56.0,98.0,55.0] vector22222:....[4.0,5.0,6.0] lable:....[Ljava.lang.String;@5ad75e7 17/06/01 13:29:49 INFO BlockManagerInfo: Added broadcast_5_piece0 in memory on localhost:60540 (size: 1982.0 B, free: 1132.5 MB) 17/06/01 13:29:49 INFO SparkContext: Created broadcast 5 from broadcast at DAGScheduler.scala:1006 17/06/01 13:29:49 INFO DAGScheduler: Submitting 1 missing tasks from ResultStage 4 (MapPartitionsRDD[4] at map at zip.scala:100) 17/06/01 13:29:49 INFO TaskSchedulerImpl: Adding task set 4.0 with 1 tasks 17/06/01 13:29:49 INFO TaskSetManager: Starting task 0.0 in stage 4.0 (TID 4, localhost, partition 0,PROCESS_LOCAL, 2120 bytes) 17/06/01 13:29:49 INFO Executor: Running task 0.0 in stage 4.0 (TID 4) 17/06/01 13:29:49 INFO HadoopRDD: Input split: file:/E:/test1.csv:0+21 17/06/01 13:29:49 INFO Executor: Finished task 0.0 in stage 4.0 (TID 4). 2130 bytes result sent to driver vector11111:......[91.0,76.0,106.0,97.0,118.0,97.0,46.0,108.0,97.0,110.0,103.0,46.0,83.0,116.0,114.0,105.0,110.0,103.0,59.0,64.0,53.0,97.0,100.0,55.0,53.0,101.0,55.0] vector22222:....[7.0,8.0,9.0] 12.0 15.0 18.0 sums 数量：3 17/06/01 13:29:49 INFO TaskSetManager: Finished task 0.0 in stage 4.0 (TID 4) in 10 ms on localhost (1/1)
注意到数据内容为：
vector11111:......[91.0,76.0,106.0,97.0,118.0,97.0,46.0,108.0,97.0,110.0,103.0,46.0,83.0,116.0,114.0,105.0,110.0,103.0,59.0,64.0,51.0,100.0,51.0,56.0,52.0,57.0,49.0,101.0] vector22222:....[1.0,2.0,3.0] ([Ljava.lang.String;@751013ad,[1.0,2.0,3.0]) lable:....[Ljava.lang.String;@7607112c vector11111:......[91.0,76.0,106.0,97.0,118.0,97.0,46.0,108.0,97.0,110.0,103.0,46.0,83.0,116.0,114.0,105.0,110.0,103.0,59.0,64.0,55.0,54.0,48.0,55.0,49.0,49.0,50.0,99.0] vector22222:....[4.0,5.0,6.0] ([Ljava.lang.String;@5884de0f,[4.0,5.0,6.0]) lable:....[Ljava.lang.String;@385daf7b vector11111:......[91.0,76.0,106.0,97.0,118.0,97.0,46.0,108.0,97.0,110.0,103.0,46.0,83.0,116.0,114.0,105.0,110.0,103.0,59.0,64.0,51.0,56.0,53.0,100.0,97.0,102.0,55.0,98.0] vector22222:....[7.0,8.0,9.0] ([Ljava.lang.String;@4da54ea6,[7.0,8.0,9.0])
看到 第一次处理的结果多了很多列，第二种处理方式转换成的矩阵是正确的。
分析：
第一种处理方式：
val labelsAndData = rawData.map{ line =>
val label = line.split(',').toString
println("lable:...."+label)
val vector = Vectors.dense(label.map(_.toDouble).toArray)
println("vector11111:......"+vector)
因为Vectors要求的是 Array[Double]，如下图所示，如果在
val vector = Vectors.dense(label.map(_.toDouble))
没有转换成Array报错，第一种方法就是先通过split函数分隔，然后转换成 String类型，然后转成Vectors的时候再转换成Array，但是结果出错了。
第二种方法，开始直接通过split函数切分数据集，然后直接在转换成Vecotrs 的时候也不需要转换成Array。
查看各函数类型：
类型就是一样的，为什么结果不一样？第二种结果是正确的，第一种为什么多了很多列？
以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持 码农网
猜你喜欢:
- 机器学习 | SVD矩阵分解算法，对矩阵做拆分，然后呢？
- golang 算法-矩阵
- 基于矩阵分解的推荐算法
- 蓝桥杯 ADV-61 算法提高 矩阵乘方
- 蓝桥杯 ALGO-86 算法训练 矩阵乘法
- 如何计算Hill Cipher算法中的反密钥矩阵？
本站部分资源来源于网络，本站转载出于传递更多信息之目的，版权归原作者或者来源机构所有，如转载稿涉及版权问题，请联系我们。
Effective C++
梅耶 (Scott Meyers) / 侯捷 / 电子工业出版社 / 2011-1-1 / 65.00元
《Effective C++:改善程序与设计的55个具体做法(第3版)(中文版)(双色)》内容简介：有人说C++程序员可以分为两类，读过Effective C++的和没读过的。世界项级C++大师scott Meyers成名之作的第三版的确当得起这样的评价。当您读过《Effective C++:改善程序与设计的55个具体做法(第3版)(中文版)(双色)》之后，就获得了迅速提升自己C++功力的一个契机......一起来看看 《Effective C++》 这本书的介绍吧!
