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Posted to issues@spark.apache.org by "Xiangrui Meng (JIRA)" <ji...@apache.org> on 2014/11/18 01:39:33 UTC

[jira] [Comment Edited] (SPARK-4127) Streaming Linear Regression- Python bindings

    [ https://issues.apache.org/jira/browse/SPARK-4127?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14215489#comment-14215489 ] 

Xiangrui Meng edited comment on SPARK-4127 at 11/18/14 12:38 AM:
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[~slcclimber] I think you need to call `_convert_to_vector` at https://github.com/anantasty/spark/compare/SPARK-4127#diff-66c3b8d150a095b53b5fa5cfad009717R290 . There are examples in MLlib, e.g., https://github.com/apache/spark/blob/master/python/pyspark/mllib/regression.py#L57 .

Maybe I missed some lines. But I think when you send a Vector on the Python side, you should get a vector on the Scala side. It is not necessary to go through the bytearray explicitly, for example:

https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala#L205


was (Author: mengxr):
[~slcclimber] I think you need to call `_convert_to_vector` at https://github.com/anantasty/spark/compare/SPARK-4127#diff-66c3b8d150a095b53b5fa5cfad009717R290 . There are examples in MLlib, e.g., https://github.com/apache/spark/blob/master/python/pyspark/mllib/regression.py#L57 .

> Streaming Linear Regression- Python bindings
> --------------------------------------------
>
>                 Key: SPARK-4127
>                 URL: https://issues.apache.org/jira/browse/SPARK-4127
>             Project: Spark
>          Issue Type: Improvement
>          Components: MLlib, PySpark
>            Reporter: Anant Daksh Asthana
>            Priority: Minor
>
> Create python bindings for Streaming Linear Regression (MLlib).
> The Mllib file relevant to this issue can be found at : https://github.com/apache/spark/blob/master/examples/src/main/scala/org/apache/spark/examples/mllib/StreamingLinearRegression.scala



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