Removed statistics_order from api.

gui/src/components/search/UploadersList.js

@@ -21,8 +21,7 @@ class UploadersList extends React.Component {
   static contextType = SearchContext.type
 
   componentDidMount() {
-    const {state: {query}, setQuery, setStatisticsToRefresh} = this.context
-    setQuery({...query, statistics_order: '_count'})
+    const {setStatisticsToRefresh} = this.context
     setStatisticsToRefresh('uploader')
   }
 

nomad/app/api/repo.py

@@ -113,8 +113,6 @@ _search_request_parser.add_argument(
         'Possible values are %s.' % ', '.join(search_extension.metrics.keys())))
 _search_request_parser.add_argument(
     'statistics', type=bool, help=('Return statistics.'))
-_search_request_parser.add_argument(
-    'statistics_order', type=str, help='Statistics order (can be _key or _count)')
 _search_request_parser.add_argument(
     'exclude', type=str, action='split', help='Excludes the given keys in the returned data.')
 for group_name in search_extension.groups:
@@ -203,7 +201,6 @@ class RepoCalcsResource(Resource):
 
             with_statistics = args.get('statistics', False) or \
                 any(args.get(group_name, False) for group_name in search_extension.groups)
-            statistics_order = args.get('statistics_order', '_key')
         except Exception as e:
             abort(400, message='bad parameters: %s' % str(e))
 
@@ -233,7 +230,7 @@ class RepoCalcsResource(Resource):
                 abort(400, message='there is no metric %s' % metric)
 
         if with_statistics:
-            search_request.default_statistics(metrics_to_use=metrics, statistics_order=statistics_order)
+            search_request.default_statistics(metrics_to_use=metrics)
 
             additional_metrics = [
                 group_quantity.metric_name

nomad/datamodel/datamodel.py

@@ -351,7 +351,8 @@ class EntryMetadata(metainfo.MSection):
                 description='Search uploader with exact names.',
                 metric_name='uploaders', metric='cardinality',
                 many_or='append', search_field='uploader.name.keyword',
-                default_statistic=True, statistic_size=10),
+                default_statistic=True, statistic_size=10,
+                statistic_order='_count'),
             Search(
                 name='uploader_id', search_field='uploader.user_id')
         ])

nomad/datamodel/dft.py

@@ -259,12 +259,16 @@ class DFTMetadata(MSection):
     labels_springer_compound_class = Quantity(
         type=str, shape=['0..*'],
         description='Springer compund classification.',
-        a_search=Search(many_and='append', default_statistic=True, statistic_size=10))
+        a_search=Search(
+            many_and='append', default_statistic=True, statistic_size=10,
+            statistic_order='_count'))
 
     labels_springer_classification = Quantity(
         type=str, shape=['0..*'],
         description='Springer classification by property.',
-        a_search=Search(many_and='append', default_statistic=True, statistic_size=10))
+        a_search=Search(
+            many_and='append', default_statistic=True, statistic_size=10,
+            statistic_order='_count'))
 
     optimade = SubSection(
         sub_section=OptimadeEntry,

nomad/metainfo/search_extension.py

@@ -64,6 +64,9 @@ class Search(Elastic):
         default_statistic: Indicates this quantity to be part of the default statistics.
         statistics_size:
             The maximum number of values in a statistic. Default is 10.
+        statistics_order:
+            The order key that is passed to elastic search to determine the order of
+            the statistic values.
         group: Indicates that his quantity can be used to group results. The value will
             be the name of the group.
         search_field: The qualified field in the elastic mapping that is used to search.
@@ -81,6 +84,7 @@ class Search(Elastic):
             group: str = None, metric: str = None, metric_name: str = None,
             default_statistic: bool = False,
             statistic_size: int = 10,
+            statistic_order: str = '_key',
             derived: Callable[[Any], Any] = None,
             search_field: str = None,
             **kwargs):
@@ -97,6 +101,7 @@ class Search(Elastic):
         self.metric = metric
         self.metric_name = metric_name
         self.statistic_size = statistic_size
+        self.statistic_order = statistic_order
         self.search_field = search_field
 
         self.derived = derived

nomad/search.py

@@ -281,25 +281,23 @@ class SearchRequest:
         self._add_metrics(self._search.aggs, metrics_to_use)
         return self
 
-    def default_statistics(self, metrics_to_use: List[str] = [], statistics_order: str = '_key'):
+    def default_statistics(self, metrics_to_use: List[str] = []):
         '''
         Configures the domain's default statistics.
         '''
-        mode = 'desc'
-        if statistics_order == '_key':
-            mode = 'asc'
-        order = {statistics_order: mode}
-
         for search_quantity in default_statistics[self._domain]:
+            statistic_order = search_quantity.statistic_order
             self.statistic(
                 search_quantity.qualified_name,
                 search_quantity.statistic_size,
                 metrics_to_use=metrics_to_use,
-                order=order)
+                order={statistic_order: 'asc' if statistic_order == '_key' else 'desc'})
 
         return self
 
-    def statistic(self, quantity_name: str, size: int, metrics_to_use: List[str] = [], order: Dict[str, str] = dict(_key='asc')):
+    def statistic(
+            self, quantity_name: str, size: int, metrics_to_use: List[str] = [],
+            order: Dict[str, str] = dict(_key='asc')):
         '''
         This can be used to display statistics over the searched entries and allows to
         implement faceted search on the top values for each quantity.
@@ -323,6 +321,7 @@ class SearchRequest:
             metrics_to_use: The metrics calculated over the aggregations. Can be
                 ``unique_code_runs``, ``datasets``, other domain specific metrics.
                 The basic doc_count metric ``code_runs`` is always given.
+            order: The order dictionary is passed to the elastic search aggregation.
         '''
         quantity = search_quantities[quantity_name]
         terms = A('terms', field=quantity.search_field, size=size, order=order)