def get_docs_to_commit(self):
        try:
            spec = {'synced': False}
            fields = {'_id': 0}
            cur = self.db.docs.find(spec, fields)
        except Exception as e:
            raise DatabaseException(e)
        return list(cur)
def run(
            self, field, query_string='', query_dsl='',
            supported_charts='table', start_time='', end_time='', limit=10):
        """Run the aggregation.

        Args:
            field (str): this denotes the event attribute that is used
                for aggregation.
            query_string (str): the query field to run on all documents prior to
                aggregating the results.
            query_dsl (str): the query DSL field to run on all documents prior
                to aggregating the results. Either a query string or a query
                DSL has to be present.
            supported_charts: Chart type to render. Defaults to table.
            start_time: Optional ISO formatted date string that limits the time
                range for the aggregation.
            end_time: Optional ISO formatted date string that limits the time
                range for the aggregation.
            limit (int): How many buckets to return, defaults to 10.

        Returns:
            Instance of interface.AggregationResult with aggregation result.

        Raises:
            ValueError: if neither query_string or query_dsl is provided.
        """
        if not (query_string or query_dsl):
            raise ValueError('Both query_string and query_dsl are missing')

        self.field = field
        formatted_field_name = self.format_field_by_type(field)

        aggregation_spec = get_spec(
            field=formatted_field_name, limit=limit, query=query_string,
            query_dsl=query_dsl)

        aggregation_spec = self._add_query_to_aggregation_spec(
            aggregation_spec, start_time=start_time, end_time=end_time)

        # Encoding information for Vega-Lite.
        encoding = {
            'x': {
                'field': field,
                'type': 'nominal',
                'sort': {
                    'op': 'sum',
                    'field': 'count',
                    'order': 'descending'
                }
            },
            'y': {'field': 'count', 'type': 'quantitative'},
            'tooltip': [
                {'field': field, 'type': 'nominal'},
                {'field': 'count', 'type': 'quantitative'}],
        }

        response = self.opensearch_aggregation(aggregation_spec)
        aggregations = response.get('aggregations', {})
        aggregation = aggregations.get('aggregation', {})

        buckets = aggregation.get('buckets', [])
        values = []
        for bucket in buckets:
            d = {
                field: bucket.get('key', 'N/A'),
                'count': bucket.get('doc_count', 0)
            }
            values.append(d)

        if query_string:
            extra_query_url = 'AND {0:s}'.format(query_string)
        else:
            extra_query_url = ''

        return interface.AggregationResult(
            encoding=encoding, values=values, chart_type=supported_charts,
            sketch_url=self._sketch_url, field=field,
            extra_query_url=extra_query_url)