我将在以下方面进行协作过滤建议：this link
我通过此代码连接到spark：
sc <- spark_connect(master="local" , method = c("shell"),
config=list(spark.driver.memory = "2g"),
app_name = "sparklyr",version="2.0.0",
extensions = sparklyr::registered_extensions(),
spark_home =
normalizePath(path.expand(path = "C:/spark"),
winslash = "\\", mustWork = NA)
)
jDF2 <- sdf_copy_to(sc,jDF, "spark_jester", overwrite=T)
implicit_model <- ml_als_factorization(jDF2,
rating.column = "rating",
user.column = "user",
item.column = "item",
iter.max = 5,
regularization.parameter = 0.01,
implicit.preferences = TRUE,
alpha = 1.0)
implicit_predictions <- implicit_model$.model %>%
invoke("transform", spark_dataframe(jDF2)) %>%
collect()
我的数据是：
> jDF
user item rating
1 3385 1 7.91
3315 3385 13 9.17
6963 3385 24 5.34
10301 3385 35 8.16
13443 3385 46 -8.74
18441 3385 57 7.14
22514 3385 68 8.88
27513 3385 79 -8.25
32513 3385 90 5.87
35686 3385 2 6.21
39743 3385 4 7.72
44096 3385 5 6.12
48574 3385 6 -0.73
运行代码后出现以下错误：
UseMethod中的错误（＆＃34;调用＆＃34;）：没有适用的方法来调用＆＃39; 应用于类＆＃34; NULL＆＃34;
的对象
当我检查模型时，我得到了这个：
> summary(implicit_model)
Length Class Mode
uid 1 -none- character
param_map 3 -none- list
rank 1 -none- numeric
recommend_for_all_items 1 -none- function
recommend_for_all_users 1 -none- function
item_factors 2 tbl_spark list
user_factors 2 tbl_spark list
user_col 1 -none- character
item_col 1 -none- character
prediction_col 1 -none- character
.jobj 2 spark_jobj environment
这里有什么错误吗？