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From "Fei Hu (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SYSTEMML-1762) Fix the sparse matrix reshape function for the Spark mode
Date Thu, 13 Jul 2017 00:21:00 GMT

     [ https://issues.apache.org/jira/browse/SYSTEMML-1762?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Fei Hu updated SYSTEMML-1762:
-----------------------------
    Description: 
When running the [distributed MNIST LeNet example | https://github.com/apache/systemml/blob/master/scripts/nn/examples/mnist_lenet_distrib_sgd.dml],
it works well in the hybrid mode. But in the Spark mode, there are some errors about
{{java.lang.NullPointerException}}  and {{java.lang.ArrayIndexOutOfBoundsException: 1000}}
when reshaping the sparse matrix. The involved function is {{org.apache.sysml.runtime.matrix.data.LibMatrixReorg#reshapeSparse}}
. The reason is that the output matrix index computed by {{org.apache.sysml.runtime.matrix.data.LibMatrixReorg#computeResultBlockIndex}}
does not match the keys in the {{HashMap<MatrixIndexes,MatrixBlock> rix}}. 

To reproduce the error, the attached scala file {{MNIST_Distrib_Sgd.scala}} could be used
to run the distributed MNIST example.  

In addition, if adding some codes to ignore the null output matrix block from {{MatrixBlock
out = rix.get(ixtmp)}},  the distributed MNIST example could run in the Spark mode, but the
result may not be right. 


  was:
When running the [distributed MNIST LeNet example | https://github.com/apache/systemml/blob/master/scripts/nn/examples/mnist_lenet_distrib_sgd.dml],
it works well in the hybrid mode. But in the Spark mode, there are some errors about
{{java.lang.NullPointerException}}  and {{java.lang.ArrayIndexOutOfBoundsException: 1000}}when
reshaping the sparse matrix. The involved function is {{org.apache.sysml.runtime.matrix.data.LibMatrixReorg#reshapeSparse}}
. The reason is that the output matrix index computed by {{org.apache.sysml.runtime.matrix.data.LibMatrixReorg#computeResultBlockIndex}}
does not match the keys in the {{HashMap<MatrixIndexes,MatrixBlock> rix}}. 

To reproduce the error, the attached scala file {{MNIST_Distrib_Sgd.scala}} could be used
to run the distributed MNIST example.  

In addition, if adding some codes to ignore the null output matrix block from {{MatrixBlock
out = rix.get(ixtmp)}},  the distributed MNIST example could run in the Spark mode, but the
result may not be right. 



> Fix the sparse matrix reshape function for the Spark mode
> ---------------------------------------------------------
>
>                 Key: SYSTEMML-1762
>                 URL: https://issues.apache.org/jira/browse/SYSTEMML-1762
>             Project: SystemML
>          Issue Type: Bug
>          Components: Algorithms, ParFor, Runtime
>            Reporter: Fei Hu
>            Assignee: Fei Hu
>         Attachments: MNIST_Distrib_Sgd.scala
>
>
> When running the [distributed MNIST LeNet example | https://github.com/apache/systemml/blob/master/scripts/nn/examples/mnist_lenet_distrib_sgd.dml],
it works well in the hybrid mode. But in the Spark mode, there are some errors about
> {{java.lang.NullPointerException}}  and {{java.lang.ArrayIndexOutOfBoundsException: 1000}}
when reshaping the sparse matrix. The involved function is {{org.apache.sysml.runtime.matrix.data.LibMatrixReorg#reshapeSparse}}
. The reason is that the output matrix index computed by {{org.apache.sysml.runtime.matrix.data.LibMatrixReorg#computeResultBlockIndex}}
does not match the keys in the {{HashMap<MatrixIndexes,MatrixBlock> rix}}. 
> To reproduce the error, the attached scala file {{MNIST_Distrib_Sgd.scala}} could be
used to run the distributed MNIST example.  
> In addition, if adding some codes to ignore the null output matrix block from {{MatrixBlock
out = rix.get(ixtmp)}},  the distributed MNIST example could run in the Spark mode, but the
result may not be right. 



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