0
使用MLlib功能ALS我已經從文件中讀取這樣的:錯誤在星火
val ratingText = sc.textFile("/home/cloudera/rec_data/processed_data/ratings/000000_0")
使用下面的函數來分析這樣的數據:
def parseRating(str: String): Rating= {
val fields = str.split(",")
Rating(fields(0).toInt, fields(1).trim.toInt, fields(2).trim.toDouble)
}
而且創造了一個RDD,這是然後分裂成不同的RDDS
val ratingsRDD = ratingText.map(x=>parseRating(x)).cache()
val splits = ratingsRDD.randomSplit(Array(0.8, 0.2), 0L)
val trainingRatingsRDD = splits(0).cache()
使用的訓練RDD創建模型如下:
val model = (new ALS().setRank(20).setIterations(10) .run(trainingRatingsRDD))
我得到以下錯誤在最後的命令
16/10/28 01:03:44 WARN BLAS: Failed to load implementation from: com.github.fommil.netlib.NativeSystemBLAS
16/10/28 01:03:44 WARN BLAS: Failed to load implementation from: com.github.fommil.netlib.NativeRefBLAS
16/10/28 01:03:46 WARN LAPACK: Failed to load implementation from: com.github.fommil.netlib.NativeSystemLAPACK
16/10/28 01:03:46 WARN LAPACK: Failed to load implementation from: com.github.fommil.netlib.NativeRefLAPACK
編輯:T. Gaweda的建議,幫助在消除錯誤,但我仍然得到以下警告:
16/10/28 01:53:59 WARN Executor: 1 block locks were not released by TID = 60:
[rdd_420_0]
16/10/28 01:54:00 WARN Executor: 1 block locks were not released by TID = 61:
[rdd_421_0]
我認爲這導致了一個空的模型,因爲下一步導致以下錯誤:
VAL topRecsForUser = model.recommendProducts(4276736,3)
錯誤是:
java.util.NoSuchElementException: next on empty iterator at scala.collection.Iterator$$anon$2.next(Iterator.scala:39)
請幫幫忙!
感謝@T。 Gaweda,在刪除警告方面效果很好,但以下錯誤持續存在。你可以請看一看::val model =(new ALS()。setRank(20).setIterations(10).run(trainingRatingsRDD)) 16/10/28 01:53:59 WARN Executor:1 block locks were不是由TID = 60發佈: [rdd_420_0] 16/10/28 01:54:00警告執行程序:1個塊鎖不是由TID = 61發佈的: [rdd_421_0] model:org.apache.spark.mllib .recommendation.MatrixFactorizationModel = [email protected]a853a7d – Kuwali
另外,在此之後,當我使用val topRecsForUser = model.recommendProducts(4276736,3)時,我得到一個錯誤,說java.util.NoSuchElementException:next在空迭代器 在scala.collection.Iterator $$ anon $ 2.next(Iterator.scala:39) 這是否意味着該模型是空的?請幫忙! – Kuwali
這是你的代碼有問題 - 你試圖用用戶標識預測模型中不存在 - http://stackoverflow.com/questions/32488328/mllib-matrixfactorizationmodel-recommendproductsuser-num-failing-on-some-user –