[GitHub] spark pull request: [MLlib]Vectors.sparse() add support to unsorte...
Github user asfgit closed the pull request at: https://github.com/apache/spark/pull/3791 --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [MLlib]Vectors.sparse() add support to unsorte...
Github user mengxr commented on the pull request: https://github.com/apache/spark/pull/3791#issuecomment-68279740 @hzlyx As @srowen mentioned, this is a contract to avoid the expensive check. You can use https://github.com/hzlyx/spark/blob/master/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala#L191 if the indices are not ordered. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [MLlib]Vectors.sparse() add support to unsorte...
Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/3791#discussion_r22257875
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala
---
@@ -173,11 +173,13 @@ object Vectors {
* Creates a sparse vector providing its index array and value array.
*
* @param size vector size.
- * @param indices index array, must be strictly increasing.
- * @param values value array, must have the same length as indices.
+ * @param indices index array.
+ * @param values value array.
*/
- def sparse(size: Int, indices: Array[Int], values: Array[Double]):
Vector =
-new SparseVector(size, indices, values)
+ def sparse(size: Int, indices: Array[Int], values: Array[Double]):
Vector = {
+val (newIndices, newValues) = indices.zip(values).sortBy(_._1).unzip
--- End diff --
This is non-trivial overhead to introduce every time a vector is made, when
the common case is that the indices are sorted, and the other cases are really
caller error. I'd still suggest merely checking the sorting. There are lots of
one-liners but this may be among the most efficient `require((1 until
indices.length).forall(i = indices(i-1) = indices(i)))`
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[GitHub] spark pull request: [MLlib]Vectors.sparse() add support to unsorte...
Github user AmplabJenkins commented on the pull request: https://github.com/apache/spark/pull/3791#issuecomment-68057633 Can one of the admins verify this patch? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [MLlib]Vectors.sparse() add support to unsorte...
Github user hzlyx commented on a diff in the pull request:
https://github.com/apache/spark/pull/3791#discussion_r22268406
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala
---
@@ -173,11 +173,13 @@ object Vectors {
* Creates a sparse vector providing its index array and value array.
*
* @param size vector size.
- * @param indices index array, must be strictly increasing.
- * @param values value array, must have the same length as indices.
+ * @param indices index array.
+ * @param values value array.
*/
- def sparse(size: Int, indices: Array[Int], values: Array[Double]):
Vector =
-new SparseVector(size, indices, values)
+ def sparse(size: Int, indices: Array[Int], values: Array[Double]):
Vector = {
+val (newIndices, newValues) = indices.zip(values).sortBy(_._1).unzip
--- End diff --
I agree with your method. At least a error should be reported, otherwise
it's hard to locate problems in applications.
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