[jira] [Created] (SYSTEMML-1379) Investigate script metadata to simplify MLContext script interaction

["Deron Eriksson (JIRA)" <ji...@apache.org>]

Deron Eriksson created SYSTEMML-1379:
----------------------------------------

             Summary: Investigate script metadata to simplify MLContext script interaction
                 Key: SYSTEMML-1379
                 URL: https://issues.apache.org/jira/browse/SYSTEMML-1379
             Project: SystemML
          Issue Type: Improvement
          Components: Algorithms, APIs
            Reporter: Deron Eriksson
            Assignee: Deron Eriksson


Currently many scripts contain usage comments such as the following:
{code}
# THIS SCRIPT COMPUTES AN APPROXIMATE FACTORIZATIONOF A LOW-RANK MATRIX X INTO TWO MATRICES U AND V 
# USING ALTERNATING-LEAST-SQUARES (ALS) ALGORITHM WITH CONJUGATE GRADIENT 
# MATRICES U AND V ARE COMPUTED BY MINIMIZING A LOSS FUNCTION (WITH REGULARIZATION)
#
# INPUT   PARAMETERS:
# ---------------------------------------------------------------------------------------------
# NAME    TYPE     DEFAULT  MEANING
# ---------------------------------------------------------------------------------------------
# X       String   ---      Location to read the input matrix X to be factorized
# U       String   ---      Location to write the factor matrix U
# V       String   ---      Location to write the factor matrix V
# rank    Int      10       Rank of the factorization
# reg     String   "L2"	    Regularization: 
#                           "L2" = L2 regularization;
#                           "wL2" = weighted L2 regularization
# lambda  Double   0.000001 Regularization parameter, no regularization if 0.0
# maxi    Int      50       Maximum number of iterations
# check   Boolean  FALSE    Check for convergence after every iteration, i.e., updating U and V once
# thr     Double   0.0001   Assuming check is set to TRUE, the algorithm stops and convergence is declared 
#                           if the decrease in loss in any two consecutive iterations falls below this threshold; 
#                           if check is FALSE thr is ignored
# fmt     String   "text"   The output format of the factor matrices L and R, such as "text" or "csv"
# ---------------------------------------------------------------------------------------------
# OUTPUT: 
# 1- An m x r matrix U, where r is the factorization rank 
# 2- An r x n matrix V
#
# HOW TO INVOKE THIS SCRIPT - EXAMPLE:
# hadoop jar SystemML.jar -f ALS-CG.dml -nvargs X=INPUT_DIR/X U=OUTPUT_DIR/U V=OUTPUT_DIR/V rank=10 reg="L2" lambda=0.0001 fmt=csv
{code}

Comments such as these are difficult to refer to from a programmatic interactive environment such as the Spark Shell. If similar information is provided in a parseable format, such as JSON or XML, it can potentially be parsed and used to provide such information programmatically, such as through the MLContext API in the Spark Shell.




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