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https://issues.apache.org/jira/browse/SDAP-40?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16397947#comment-16397947
 ] 

ASF GitHub Bot commented on SDAP-40:
------------------------------------

fgreg commented on a change in pull request #8: SDAP-40 Update Spark Time 
Series algorithm to handle multiple time steps per tile
URL: https://github.com/apache/incubator-sdap-nexus/pull/8#discussion_r174330935
 
 

 ##########
 File path: analysis/webservice/algorithms_spark/TimeSeriesSpark.py
 ##########
 @@ -178,27 +178,10 @@ def calc(self, request, **args):
         for shortName in ds:
 
             the_time = datetime.now()
-            daysinrange = 
self._tile_service.find_days_in_range_asc(bounding_polygon.bounds[1],
-                                                                    
bounding_polygon.bounds[3],
-                                                                    
bounding_polygon.bounds[0],
-                                                                    
bounding_polygon.bounds[2],
-                                                                    shortName,
-                                                                    
start_seconds_from_epoch,
-                                                                    
end_seconds_from_epoch)
-            self.log.info("Finding days in range took %s for dataset %s" % 
(str(datetime.now() - the_time), shortName))
-
-            ndays = len(daysinrange)
-            if ndays == 0:
-                raise NoDataException(reason="No data found for selected 
timeframe")
-
-            self.log.debug('Found {0} days in range'.format(ndays))
-            for i, d in enumerate(daysinrange):
-                self.log.debug('{0}, {1}'.format(i, 
datetime.utcfromtimestamp(d)))
-            spark_nparts_needed = min(spark_nparts, ndays)
-
-            the_time = datetime.now()
-            results, meta = spark_driver(daysinrange, bounding_polygon, 
shortName,
-                                         
spark_nparts_needed=spark_nparts_needed, sc=self._sc)
+            results, meta = spark_driver(start_seconds_from_epoch,
 
 Review comment:
   This is good, but I'm thinking we should run a sanity check query to make 
sure there are at least some tiles in the search domain before passing off to 
Spark. Otherwise we incur the cost of spinning up a bunch of spark tasks for no 
reason.

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> Update Spark Time Series algorithm to handle multiple time steps per tile
> -------------------------------------------------------------------------
>
>                 Key: SDAP-40
>                 URL: https://issues.apache.org/jira/browse/SDAP-40
>             Project: Apache Science Data Analytics Platform
>          Issue Type: Improvement
>            Reporter: Joseph Jacob
>            Assignee: Joseph Jacob
>            Priority: Major
>
> To date, NEXUS has partitioned data to have 1 time step per tile.  For SWOT 
> we want to have multiple time steps per tile for efficiency of the 
> computations.
>  



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