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mapReduceCrimes.py
122 lines (100 loc) · 4.68 KB
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mapReduceCrimes.py
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import urllib.request
import json
import dml
import prov.model
import datetime
import uuid
from bson.code import Code
class mapReduceCrimes(dml.Algorithm):
contributor = 'jzhou94_katerin'
reads = ['jzhou94_katerin.crime_incident']
writes = ['jzhou94_katerin.crime']
@staticmethod
def execute(trial = False):
print("starting data retrieval")
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
print("repo: ", repo)
repo.authenticate('jzhou94_katerin', 'jzhou94_katerin')
map_function_crime = Code('''
function() {
district = this.reptdistrict
if(district == 'A1' || district == 'A15')
emit('02120', {crime:1});
else if(district == 'A7')
emit('02128', {crime:1});
else if(district == 'B2')
emit('02119', {crime:1});
else if(district == 'B3')
emit('02124', {crime:1});
else if(district == 'C6')
emit('02127', {crime:1});
else if(district == 'C11')
emit('02122', {crime:1});
else if(district == 'D4')
emit('02116', {crime:1});
else if(district == 'D14')
emit('02135', {crime:1});
else if(district == 'E5')
emit('02132', {crime:1});
else if(district == 'E13')
emit('02130', {crime:1});
else if(district == 'E18')
emit('02136', {crime:1});
}''')
reduce_function_crime = Code('''function(k, vs) {
var total = 0;
for (var i = 0; i < vs.length; i++)
total += vs[i].crime;
return {crime:total};
}''')
repo.dropPermanent('jzhou94_katerin.crime')
repo.createPermanent('jzhou94_katerin.crime')
if trial == True:
repo['jzhou94_katerin.crime'].insert(repo.jzhou94_katerin.crime_incident.find().limit(20))
repo.jzhou94_katerin.crime.map_reduce(map_function_crime, reduce_function_crime, 'jzhou94_katerin.crime');
else:
repo.jzhou94_katerin.crime_incident.map_reduce(map_function_crime, reduce_function_crime, 'jzhou94_katerin.crime');
repo.logout()
endTime = datetime.datetime.now()
return {"start":startTime, "end":endTime}
@staticmethod
def provenance(doc = prov.model.ProvDocument(), startTime = None, endTime = None):
'''
Create the provenance document describing everything happening
in this script. Each run of the script will generate a new
document describing that invocation event.
'''
# Set up the database connection.
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('jzhou94_katerin', 'jzhou94_katerin')
doc.add_namespace('alg', 'http://datamechanics.io/algorithm/jzhou94_katerin/') # The scripts are in <folder>#<filename> format.
doc.add_namespace('dat', 'http://datamechanics.io/data/jzhou94_katerin/') # The data sets are in <user>#<collection> format.
doc.add_namespace('ont', 'http://datamechanics.io/ontology#') # 'Extension', 'DataResource', 'DataSet', 'Retrieval', 'Query', or 'Computation'.
doc.add_namespace('log', 'http://datamechanics.io/log/') # The event log.
doc.add_namespace('bdp', 'https://data.cityofboston.gov/resource/')
this_script = doc.agent('alg:mapReduceCrimes', {prov.model.PROV_TYPE:prov.model.PROV['SoftwareAgent'], 'ont:Extension':'py'})
crime_incident = doc.entity('dat:crime_incident', {prov.model.PROV_LABEL:'Crime Incident', prov.model.PROV_TYPE:'ont:DataSet'})
get_crime = doc.activity('log:uuid'+str(uuid.uuid4()), startTime, endTime)
doc.wasAssociatedWith(get_crime, this_script)
doc.usage(get_crime, crime_incident, startTime, None,
{prov.model.PROV_TYPE:'ont:Computation',
'ont:Query':'?value'
}
)
crime = doc.entity('dat:crime', {prov.model.PROV_LABEL:'Crimes per Location', prov.model.PROV_TYPE:'ont:DataSet'})
doc.wasAttributedTo(crime, this_script)
doc.wasGeneratedBy(crime, get_crime, endTime)
doc.wasDerivedFrom(crime, crime_incident, get_crime, get_crime, get_crime)
repo.record(doc.serialize()) # Record the provenance document.
repo.logout()
return doc
mapReduceCrimes.execute()
print("mapReduceCrimes Algorithm Done")
doc = mapReduceCrimes.provenance()
print(doc.get_provn())
print(json.dumps(json.loads(doc.serialize()), indent=4))
print("mapReduceCrimes Provenance Done")
## eof