Pyspark-WARN bisetingkmeans：输入RDD不是直接缓存的
我把kmeans一分为二Pyspark-WARN bisetingkmeans：输入RDD不是直接缓存的,pyspark,spark-dataframe,apache-spark-mllib,apache-spark-ml,Pyspark,Spark Dataframe,Apache Spark Mllib,Apache Spark Ml,我把kmeans一分为二 bkm_test=BisectingKMeans().setK(5).setSeed(1) rdf.cache() assembled.cache() model_test=bkm_test.fit(assembled) 我缓存了这两个数据帧，因为我不断得到错误，但这没有什么区别，我发现这与kmeans相似。 但我也得到了下面的警告执行器错误。这只是算法中我无法修复的部分吗 17/08/14 21:53:17 WARN BisectingKMeans: The in
bkm_test=BisectingKMeans().setK(5).setSeed(1)
rdf.cache()
assembled.cache()
model_test=bkm_test.fit(assembled)
17/08/14 21:53:17 WARN BisectingKMeans: The input RDD 306 is not directly cached, which may hurt performance if its parent RDDs are also not cached.
17/08/14 21:53:17 WARN Executor: 1 block locks were not released by TID = 132:
[rdd_302_0]