ally want to do this and can tolerate some approximation, I
think you want to do some kind of location sensitive hashing to bucket
the vectors and then evaluate similarity to only the other items in
the bucket.
On Fri, Apr 25, 2014 at 5:55 AM, Qin Wei <[hidden email]> wrote:
> Hi All
ally want to do this and can tolerate some approximation, I
think you want to do some kind of location sensitive hashing to bucket
the vectors and then evaluate similarity to only the other items in
the bucket.
On Fri, Apr 25, 2014 at 5:55 AM, Qin Wei <[hidden email]> wrote:
> Hi All
Hi All,
I have a problem with the Item-Based Collaborative Filtering Recommendation
Algorithms in spark.
The basic flow is as below:
(Item1, (User1 ,
Score1))
RDD1 ==>(Item2, (User2 , Score2))
Hi All,
I have a problem with the Item-Based Collaborative Filtering Recommendation
Algorithms in spark.
The basic flow is as below:
(Item1, (User1 ,
Score1))
RDD1 ==>(Item2, (User2 , Score2))
eAsTextFile("/home/deployer/sim")}
I ran the program through "java -jar myjar.jar", it crashed quickly, but it
succeed when the size of the data file is small.
Thanks for your help!
qinwei
From: Andre Bois-Crettez [via Apache Spark User List]Date: 2014-04-16 17:50To:
Qin WeiSubj
Hi, all
My spark program always gives me the error "java.lang.OutOfMemoryError: Java
heap space" in my standalone cluster, here is my code:
object SimCalcuTotal {
def main(args: Array[String]) {
val sc = new SparkContext("spark://192.168.2.184:7077", "Sim Calcu
Total", "/usr/local/spark
