def multiply(self, m1, m2):
'''Perform matrix multiplication between m1 and m2 using MapReduce'''
product = []
for row in range(1, self.dim+1):
for col in range(1, self.dim+1):
#TODO: better ways to implement the multiplication op?
map_fun = Code('''function() {
for (i=0;i < this.elements.length; i++) {
if((this.elements[i][0]== %s && this.key == '%s')|(this.elements[i][1]== %s && this.key=='%s')) {
emit(null, this.elements[i]);
}
}
}''' % (str(row), m1['key'], str(col), m2['key']) )
#assumes there is an order (is that okay?)
red = Code('''function(key, values) {
var total = 0;
var dim = %s
for(i=0; i < dim; i++) {
total += values[i][2] * values[i+dim][2];
}
return total;
}''' % self.dim)
result = self.matrix_coll.map_reduce(map_fun,red,'myresults')
for doc in result.find():
product.append([row, col, int(doc['value'])])
print m1['key'], 'X', m2['key']
print_matrix(product)
def multiply(self, m1, m2):
'''Perform matrix multiplication between m1 and m2 using MapReduce'''
product = []
for row in range(1, self.dim+1):
for col in range(1, self.dim+1):
#TODO:how does the efficiency of this mapreduce compare??
query = self.client.add('matrices')
query.map('''function(v) {
var doc = JSON.parse(v.values[0].data);
var matrix = new Array();
for (i=0; i < doc.elements.length; i++) {
if((doc.elements[i][0] == %s && doc.key == '%s') | (doc.elements[i][1] == %s && doc.key == '%s')){
var match = {};
match[doc.key] = doc.elements[i];
matrix.push(match);
}
}
return matrix;
}''' % (str(row), m1['key'], str(col), m2['key']))
query.reduce('''function(data) {
var m1 = new Array();
var m2 = new Array();
var m1_key = '%s';
var m2_key = '%s';
for (i=0;i<data.length;i++) {
for(var key in data[i]) {
if(key == m1_key) {
m1.push(data[i]);
}
else {
m2.push(data[i]);
}
}
}
var total = 0;
for (i=0;i<m1.length;i++) {
var val1 = m1[i][m1_key][2];
var val2 = m2[i][m2_key][2];
total += val1 * val2;
}
return [total];
}''' % (m1['key'],m2['key']))
#print row, m1['key'], col, m2['key']
for result in query.run():
product.append([row, col, result])
#print result
print m1['key'], 'X', m2['key']
print_matrix(product)
def multiply(self, m1, m2):
'''Perform matrix multiplication between m1 and m2 using MapReduce'''
product = []
for row in range(1, self.dim+1):
for col in range(1, self.dim+1):
#maps proper row and column of m1 and m2
map_fun = ('''function(doc) {
for (i=0;i < doc.elements.length; i++) {
if((doc.elements[i][0]== %s && doc._id == '%s')|(doc.elements[i][1]== %s && doc._id=='%s')) {
emit(null, doc.elements[i]);
}
}
}''' % (str(row), m1.id, str(col), m2.id) )
#calculates dot product of the row and column
red = ('''function(key, data) {
var total = 0;
var dim = %s
for(i=0; i < dim; i++) {
total += data[i][2] * data[i+dim][2];
}
return total;
}''' % self.dim)
#creates a permanent view in Couch
view = ViewDefinition('oper','multiply',map_fun,reduce_fun=red)
view.sync(self.matrix_db)
design = "_design/oper/_view/multiply"
for result in self.matrix_db.view(design):
product.append([row, col, result.value])
#prints the result
print m1.id, 'X', m2.id
print_matrix(product)
import pstats
from riak_numbers import TestRiakNum
from databases.print_matrix import print_matrix
if __name__ == "__main__":
for j in range(1, 4):
riak_test = TestRiakNum()
cProfile.run("riak_test.store_data()", "store{0}.profile".format(j))
cProfile.run("riak_test.test_retrieve()", "retrieve{0}.profile".format(j))
matrices = riak_test.test_retrieve()
for i in range(0, len(matrices)):
key = "matrix%s" % str(i + 1)
for matrix in matrices:
if matrix["key"] == key:
print "Matrix %s:" % str(i + 1)
print_matrix(matrix["elements"])
# cProfile.run('riak_test.test_analysis()','analysis{0}.profile'.format(j))
riak_test.remove_data()
store = pstats.Stats("store1.profile")
retr = pstats.Stats("retrieve1.profile")
# analy = pstats.Stats('analysis1.profile')
for i in range(2, 4):
store.add("store{0}.profile".format(i))
retr.add("retrieve{0}.profile".format(i))
# analy.add('analysis{0}.profile'.format(i))
store.print_stats(5)
retr.print_stats(5)
# analy.print_stats(5)
import cProfile
import pstats
from redis_numbers import TestRedisNum
from databases.print_matrix import print_matrix
if __name__ == "__main__":
"""
Runs one cProfile test of couch, prints results.
Results saved into file called <test_name>.profile (e.g. analysis.profile)
"""
redis_test = TestRedisNum()
cProfile.run('redis_test.store_data()','store.profile')
cProfile.run('redis_test.test_retrieve()','retrieve.profile')
matrices = redis_test.test_retrieve()
for i in range(0, len(matrices)):
key = 'matrix%s' % str(i+1)
for matrix in matrices:
if matrix['key'] == key:
print 'Matrix %s:' % str(i+1)
print_matrix(matrix['elements'])
cProfile.run('redis_test.remove_data()','remove.profile')
store = pstats.Stats('store.profile')
store.sort_stats('time').print_stats(5)
retr = pstats.Stats('retrieve.profile')
retr.sort_stats('time').print_stats(5)
