Newbie question...
Can I use any of the main ML capabilities of MLlib in a Java-only
environment, without any native library dependencies?
According to the documentation, java-netlib provides a JVM fallback. This
suggests that native netlib libraries are not required.
It appears that such a fallback is not available for jblas. However, a quick
look at the MLlib source suggests that MLlib's dependencies on jblas are
rather isolated:
> grep -R jblas
main/scala/org/apache/spark/ml/recommendation/ALS.scala:import
org.jblas.DoubleMatrix
main/scala/org/apache/spark/mllib/optimization/NNLS.scala:import
org.jblas.{DoubleMatrix, SimpleBlas}
main/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.scala:import
org.jblas.DoubleMatrix
main/scala/org/apache/spark/mllib/util/LinearDataGenerator.scala:import
org.jblas.DoubleMatrix
main/scala/org/apache/spark/mllib/util/LinearDataGenerator.scala:
org.jblas.util.Random.seed(42)
main/scala/org/apache/spark/mllib/util/MFDataGenerator.scala:import
org.jblas.DoubleMatrix
main/scala/org/apache/spark/mllib/util/SVMDataGenerator.scala:import
org.jblas.DoubleMatrix
Is it true or false that many of MLlib's capabilities will work perfectly
fine without any native (non-Java) libraries installed at all?
Thanks for the help,
John
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