Author: jbellis
Date: Thu Sep 23 21:46:00 2010
New Revision: 1000641

URL: http://svn.apache.org/viewvc?rev=1000641&view=rev
Log:
r/m clock struct from Streaming example.  patch by Jeremy Hanna; reviewed by 
jbellis for CASSANDRA-1342

Modified:
    cassandra/trunk/contrib/hadoop_streaming_output/bin/reducer.py
    cassandra/trunk/contrib/py_stress/avro_stress.py

Modified: cassandra/trunk/contrib/hadoop_streaming_output/bin/reducer.py
URL: 
http://svn.apache.org/viewvc/cassandra/trunk/contrib/hadoop_streaming_output/bin/reducer.py?rev=1000641&r1=1000640&r2=1000641&view=diff
==============================================================================
--- cassandra/trunk/contrib/hadoop_streaming_output/bin/reducer.py (original)
+++ cassandra/trunk/contrib/hadoop_streaming_output/bin/reducer.py Thu Sep 23 
21:46:00 2010
@@ -49,7 +49,7 @@ def new_column(name, value):
     column = dict()
     column['name'] = '%s' % name
     column['value'] = '%s' % value
-    column['clock'] = {'timestamp': long(time.time() * 1e6)}
+    column['timestamp'] = long(time.time() * 1e6)
     column['ttl'] = 0
     return column
 

Modified: cassandra/trunk/contrib/py_stress/avro_stress.py
URL: 
http://svn.apache.org/viewvc/cassandra/trunk/contrib/py_stress/avro_stress.py?rev=1000641&r1=1000640&r2=1000641&view=diff
==============================================================================
--- cassandra/trunk/contrib/py_stress/avro_stress.py (original)
+++ cassandra/trunk/contrib/py_stress/avro_stress.py Thu Sep 23 21:46:00 2010
@@ -175,7 +175,7 @@ class Operation(Thread):
 class Inserter(Operation):
     def run(self):
         data = md5(str(get_ident())).hexdigest()
-        columns = [{'name': 'C' + str(j), 'value': data, 'clock': 
{'timestamp': int(time.time() * 1000000)}} for j in xrange(columns_per_key)]
+        columns = [{'name': 'C' + str(j), 'value': data, 'timestamp': 
int(time.time() * 1000000)} for j in xrange(columns_per_key)]
         fmt = '%0' + str(len(str(total_keys))) + 'd'
         if 'super' == options.cftype:
             supers = [{'name': 'S' + str(j), 'columns': columns} for j in 
xrange(supers_per_key)]


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