H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
Restore functionality of matches for R client. Further, expand the behavior to work on String columns as well.
The Java implementation is:
class ASTMatch in h2o-core/src/main/java/water/rapids/ASTUniOp.java
The R client code is at: h2o.match <- function(x, table, nomatch = 0, incomparables = NULL) in h2o-r/h2o-package/R/frame.R
The original R unit test is h2o-r/tests/testdir_munging/slice/runit_NOPASS_match.R
The python client implementation is def match(self, table, nomatch=0) in h2o-py/h2o/frame.py
I believe a python test is still needed. For a look at other string related methods in Java see:
h2o-core/src/main/java/water/ASTStrOp.java and then h2o-core/src/main/java/water/fvec/CStrChunk.java for accelerated versions of methods when the string column is pure ASCII.
Restore functionality of matches for R client. Further, expand the behavior to work on String columns as well.
The Java implementation is: class ASTMatch in h2o-core/src/main/java/water/rapids/ASTUniOp.java
The R client code is at: h2o.match <- function(x, table, nomatch = 0, incomparables = NULL) in h2o-r/h2o-package/R/frame.R
The original R unit test is h2o-r/tests/testdir_munging/slice/runit_NOPASS_match.R
The python client implementation is def match(self, table, nomatch=0) in h2o-py/h2o/frame.py
I believe a python test is still needed. For a look at other string related methods in Java see: h2o-core/src/main/java/water/ASTStrOp.java and then h2o-core/src/main/java/water/fvec/CStrChunk.java for accelerated versions of methods when the string column is pure ASCII.