See http://people.csail.mit.edu/matei/spark-unified-docs/ for a more recent
build of the docs; if you spot any problems in those, let us know.
Matei
On Apr 23, 2014, at 9:49 AM, Xiangrui Meng <men...@gmail.com> wrote:
> The doc is for 0.9.1. You are running a later snapshot, which added
> sparse vectors. Try LabeledPoint(parts(0).toDouble,
> Vectors.dense(parts(1).split(' ').map(x => x.toDouble)). The examples
> are updated in the master branch. You can also check the examples
> there. -Xiangrui
>
> On Wed, Apr 23, 2014 at 9:34 AM, Mohit Jaggi <mohitja...@gmail.com> wrote:
>>
>> sorry...added a subject now
>>
>> On Wed, Apr 23, 2014 at 9:32 AM, Mohit Jaggi <mohitja...@gmail.com> wrote:
>>>
>>> I am trying to run the example linear regression code from
>>>
>>> http://spark.apache.org/docs/latest/mllib-guide.html
>>>
>>> But I am getting the following error...am I missing an import?
>>>
>>> ----code----
>>>
>>> import org.apache.spark._
>>>
>>> import org.apache.spark.mllib.regression.LinearRegressionWithSGD
>>>
>>> import org.apache.spark.mllib.regression.LabeledPoint
>>>
>>>
>>> object ModelLR {
>>>
>>> def main(args: Array[String]) {
>>>
>>> val sc = new SparkContext(args(0), "SparkLR",
>>>
>>> System.getenv("SPARK_HOME"),
>>> SparkContext.jarOfClass(this.getClass).toSeq)
>>>
>>> // Load and parse the data
>>>
>>> val data = sc.textFile("mllib/data/ridge-data/lpsa.data")
>>>
>>> val parsedData = data.map { line =>
>>>
>>> val parts = line.split(',')
>>>
>>> LabeledPoint(parts(0).toDouble, parts(1).split(' ').map(x =>
>>> x.toDouble).toArray)
>>>
>>> }
>>>
>>> ...<snip>...
>>>
>>> }
>>>
>>> ----error----
>>>
>>> - polymorphic expression cannot be instantiated to expected type; found :
>>> [U >: Double]Array[U] required:
>>>
>>> org.apache.spark.mllib.linalg.Vector
>>>
>>> - polymorphic expression cannot be instantiated to expected type; found :
>>> [U >: Double]Array[U] required:
>>>
>>> org.apache.spark.mllib.linalg.Vector
>>
>>
