Sebastian Alfers created SPARK-7594:
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Summary: Increase maximum amount of columns for covariance matrix
for principal components
Key: SPARK-7594
URL: https://issues.apache.org/jira/browse/SPARK-7594
Project: Spark
Issue Type: Improvement
Components: MLlib
Reporter: Sebastian Alfers
Priority: Minor
In order to compute a huge dataset, the amount of columns to calculate the
covariance matrix is limited:
https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala#L129
What is the reason behind this limitation and can it be extended?
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