blob: 3055651d91e13c37258627ef35001c14a5ec5004 [file] [log] [blame]
#-------------------------------------------------------------
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
#
#-------------------------------------------------------------
source("./scripts/staging/pipelines/utils.dml") as utils;
# The below functions will generate the all possible
# physical pipelines for a given logical pipeline
###################################################
getPermutations = function(Frame[String] opt)
return(Frame[String] output)
{
idx = seq(1, ncol(opt))
# get the indexes of columns for recode transformation
index = utils::vectorToCsv(idx)
# recode logical pipelines for easy handling
jspecR = "{ids:true, recode:["+index+"]}";
[X, M] = transformencode(target=opt, spec=jspecR);
# initialize output matrix
n = nrow(opt)
d = ncol(opt)
outC = matrix(0, n^d, d)
parfor(i in 1 : d) {
# matrix for storing rows of ith columns
outR = matrix(0, 0, 1)
j = n^i
rowIdx = 1
for(k in 1:j) {
valDup = matrix(as.scalar(X[rowIdx, i]), n^(d-i), 1)
outR = rbind(outR, valDup)
rowIdx = rowIdx + 1
rowIdx = ifelse(((rowIdx)%%(n+1)) == 0, 1, rowIdx)
}
outC[,i] = outR
}
output = transformdecode(target=outC, spec=jspecR, meta=M);
}