[GitHub] spark issue #18288: [SPARK-21066][ML] LibSVM load just one input file

2017-06-23 Thread facaiy
Github user facaiy commented on the issue:

https://github.com/apache/spark/pull/18288
  
Yes.

an example code:
```scala
val df = spark.read.format("libsvm")
  .option("numFeatures", "780")
  .load("data/mllib/sample_libsvm_data.txt")
```


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[GitHub] spark issue #18288: [SPARK-21066][ML] LibSVM load just one input file

2017-06-22 Thread darionyaphet
Github user darionyaphet commented on the issue:

https://github.com/apache/spark/pull/18288
  
So if I want to load a mulit file LibSVM input should specify the 
`numFeatures`  ? 


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[GitHub] spark issue #18288: [SPARK-21066][ML] LibSVM load just one input file

2017-06-22 Thread facaiy
Github user facaiy commented on the issue:

https://github.com/apache/spark/pull/18288
  
You might be mistaken. The aim of code here is to encourage user to specify 
`numFeatures` in any case, rather than encourage user to use only one file.


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[GitHub] spark issue #18288: [SPARK-21066][ML] LibSVM load just one input file

2017-06-22 Thread darionyaphet
Github user darionyaphet commented on the issue:

https://github.com/apache/spark/pull/18288
  
@srowen @facaiy `numFeatures` is the `number of features` 

I'm confuse about why features number could control the input path and if 
just only one input file have some advantage ?


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[GitHub] spark issue #18288: [SPARK-21066][ML] LibSVM load just one input file

2017-06-22 Thread facaiy
Github user facaiy commented on the issue:

https://github.com/apache/spark/pull/18288
  
In my opinion, `numFeatures` is vital for sparse data. 

Say our feature is 100-dim indeed, while in a small train data their 
maximum size is 990. It is dangerous (or wrong) to train a 990-dim model as it 
might fail in the coming test data.

Hence, in most cases, `numFeatures` should be given by user.


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[GitHub] spark issue #18288: [SPARK-21066][ML] LibSVM load just one input file

2017-06-22 Thread srowen
Github user srowen commented on the issue:

https://github.com/apache/spark/pull/18288
  
@darionyaphet what do you think?


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[GitHub] spark issue #18288: [SPARK-21066][ML] LibSVM load just one input file

2017-06-14 Thread darionyaphet
Github user darionyaphet commented on the issue:

https://github.com/apache/spark/pull/18288
  
@srowen I have update `LibSVMRelationSuite` to adapt libsvm mutli file 
input :) thanks for you review .


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[GitHub] spark issue #18288: [SPARK-21066][ML] LibSVM load just one input file

2017-06-14 Thread srowen
Github user srowen commented on the issue:

https://github.com/apache/spark/pull/18288
  
Is it easy to add a simple test for this case?


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[GitHub] spark issue #18288: [SPARK-21066][ML] LibSVM load just one input file

2017-06-13 Thread darionyaphet
Github user darionyaphet commented on the issue:

https://github.com/apache/spark/pull/18288
  
@srowen It seems OK. `FileInputFormat` will use a  comma-separated paths to 
be set as the list of inputs for the job.


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[GitHub] spark issue #18288: [SPARK-21066][ML] LibSVM load just one input file

2017-06-13 Thread srowen
Github user srowen commented on the issue:

https://github.com/apache/spark/pull/18288
  
Is that going to work as an argument to parseLibSVMFile ?
CC @liancheng


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[GitHub] spark issue #18288: [SPARK-21066][ML] LibSVM load just one input file

2017-06-13 Thread AmplabJenkins
Github user AmplabJenkins commented on the issue:

https://github.com/apache/spark/pull/18288
  
Can one of the admins verify this patch?


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