4
我想我的載體轉移到陣列,所以我用對於Spark矢量使用.toArray()後應該是什麼類型?
get_array = udf(lambda x: x.toArray(),ArrayType(DoubleType()))
result3 = result2.withColumn('list',get_array('features'))
result3.show()
其中列features
是矢量D型。但是星火告訴我,
net.razorvine.pickle.PickleException: expected zero arguments for construction of ClassDict (for numpy.core.multiarray._reconstruct)
我知道原因一定是我在使用UDF的類型,所以我嘗試get_array = udf(lambda x: x.toArray(),ArrayType(FloatType()))
,這也不能幹活知道它是轉讓後numpy.narray,但我怎麼能顯示它正確嗎?
這裏是我的代碼是如何得到我的數據框RESULT2:
df4 = indexed.groupBy('uuid').pivot('name').sum('fre')
df4 = df4.fillna(0)
from pyspark.ml.feature import VectorAssembler
assembler = VectorAssembler(
inputCols=df4.columns[1:],
outputCol="features")
dataset = assembler.transform(df4)
bk = BisectingKMeans(k=8, seed=2, featuresCol="features")
result2 = bk.fit(dataset).transform(dataset)
這裏是收錄的樣子:
+------------------+------------+---------+-------------+------------+----------+--------+----+
| uuid| category| code| servertime| cat| fre|catIndex|name|
+------------------+------------+---------+-------------+------------+----------+--------+----+
| 351667085527886| 398| null|1503084585000| 398|0.37951264| 2.0| a2|
| 352279079643619| 403| null|1503105476000| 403| 0.3938634| 3.0| a3|
| 352279071621894| 398| null|1503085396000| 398|0.38005984| 2.0| a2|
| 357653074851887| 398| null|1503085552000| 398| 0.3801652| 2.0| a2|
| 354287077780760| 407| null|1503085603000| 407|0.38019964| 5.0| a5|
|0_8f394ebf3f67597c| 403| null|1503084183000| 403|0.37924168| 3.0| a3|
| 353528084062994| 403| null|1503084234000| 403|0.37927604| 3.0| a3|
| 356626072993852| 100000504|100000504|1503104781000| 100000504| 0.3933774| 0.0| a0|
| 351667081062615| 100000448| 398|1503083901000| 398|0.37905172| 2.0| a2|
| 354330089551058|1.00000444E8| null|1503084004000|1.00000444E8|0.37912107| 34.0| a34|
+------------------+------------+---------+-------------+------------+----------+--------+----+
在result2
,我有double
類型的某些列,然後我使用VectorAssembler
將這些雙列組裝成一個向量features
,這是我想要傳輸到數組的列。
我有文章,請檢查它。 –