I am using MRjob to run Hadoop Streaming jobs over our HBase instance. For the life of me I cannot figure out how to pass a parameter to my reducer. I have two parameters that I want to pass to my reducer from when I run the job: startDate and endDate. Here's what my current reducer looks like:
def reducer(self, groupId, meterList):
"""
Print bucket.
"""
sys.stderr.write("Working on group = " + str(groupId) + "\n")
#print "Opening connection..."
conn = open_connection(hostname)
#print "Getting table..."
table = get_table(conn, tableName)
compositeDf = DataFrame()
for meterId in meterList:
sys.stderr.write("Querying: " + str(meterId) + "\n")
df = extract_meter_data(table, meterId, startDate, endDate)
I cannot seem to pass startDate and endDate as parameters to my reducer. The only way I can get the job to pick up the parameters is through a global variable at the top of the class.
startDate = datetime.datetime(2012, 6, 10)
endDate = datetime.datetime(2012, 6, 11)
class MRDataQuality(MRJob):
"""
MapReduce job that does a data quality check on the meter data in HBase.
"""
But that is dirty. I want to pass it in from calling the job. I've tried many methods. Setting it as an instance variable, setting it as a static class variable, creating an overloaded constructor for MRDataQualityJob.... nothing seems to work. I am calling it from my top-level script programmatically like so:
if args.hadoop:
mrdq_job = MRDataQuality(args=['-r', 'hadoop', '--conf-path', 'mrjob.conf', '--jobconf', 'mapred.reduce.tasks=42', meterFile])
else:
mrdq_job = MRDataQuality(args=[meterFile])
with mrdq_job.make_runner() as runner:
runner.run()
No matter what I do to the mrdq_job instance it seems like the runner.run() is using a fresh new instance of the class which doesn't have the instance or static variables defined. How can i pass my parameters to the reducer???? I can do it in regular Hadoop Streaming by passing a string: "--reducer reducer.py arg1 arg2". Is there any equivalent for MRjob?
How about passing your parameters to job config and then reading them with get_jobconf_value?
Something like this:
from mrjob.compat import get_jobconf_value
class MRDataQuality(MRJob):
def reducer(self, groupId, meterList):
...
startDate = get_jobconf_value("my.job.settings.startdate")
endDate = get_jobconf_value("my.job.settings.enddate")
for meterId in meterList:
sys.stderr.write("Querying: " + str(meterId) + "\n")
df = extract_meter_data(table, meterId, startDate, endDate)
And then set the parameters in code like you did above
mrdq_job = MRDataQuality(args=['-r', 'hadoop', '--conf-path', 'mrjob.conf', '--jobconf', 'mapred.reduce.tasks=42', '--jobconf', 'my.job.settings.startdate=2013-06-10', '--jobconf', 'my.job.settings.enddate=2013-06-11', meterFile])
How about passing your parameters to job config and then reading them with get_jobconf_value inside of the reducer_init? This way you only have to read the parameters in once.
Something like this:
from mrjob.compat import get_jobconf_value
class MRDataQuality(MRJob):
def reducer_init(self):
...
self.startDate = get_jobconf_value("my.job.settings.startdate")
self.endDate = get_jobconf_value("my.job.settings.enddate")
def reducer(self, groupId, meterList):
for meterId in meterList:
sys.stderr.write("Querying: " + str(meterId) + "\n")
df = extract_meter_data(table, meterId, self.startDate, self.endDate)
And then set the parameters in code like you did above
mrdq_job = MRDataQuality(args=['-r', 'hadoop', '--conf-path', 'mrjob.conf', '--jobconf', 'mapred.reduce.tasks=42', '--jobconf', 'my.job.settings.startdate=2013-06-10', '--jobconf', 'my.job.settings.enddate=2013-06-11', meterFile])
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