def generate_metrics(self): """Generate metrics based on the column metadata""" M = DruidMetric # noqa metrics = [] metrics.append(DruidMetric( metric_name='count', verbose_name='COUNT(*)', metric_type='count', json=json.dumps({'type': 'count', 'name': 'count'}) )) # Somehow we need to reassign this for UDAFs if self.type in ('DOUBLE', 'FLOAT'): corrected_type = 'DOUBLE' else: corrected_type = self.type if self.sum and self.isnum: mt = corrected_type.lower() + 'Sum' name = 'sum__' + self.column_name metrics.append(DruidMetric( metric_name=name, metric_type='sum', verbose_name='SUM({})'.format(self.column_name), json=json.dumps({ 'type': mt, 'name': name, 'fieldName': self.column_name}) )) if self.min and self.isnum: mt = corrected_type.lower() + 'Min' name = 'min__' + self.column_name metrics.append(DruidMetric( metric_name=name, metric_type='min', verbose_name='MIN({})'.format(self.column_name), json=json.dumps({ 'type': mt, 'name': name, 'fieldName': self.column_name}) )) if self.max and self.isnum: mt = corrected_type.lower() + 'Max' name = 'max__' + self.column_name metrics.append(DruidMetric( metric_name=name, metric_type='max', verbose_name='MAX({})'.format(self.column_name), json=json.dumps({ 'type': mt, 'name': name, 'fieldName': self.column_name}) )) if self.count_distinct: name = 'count_distinct__' + self.column_name if self.type == 'hyperUnique' or self.type == 'thetaSketch': metrics.append(DruidMetric( metric_name=name, verbose_name='COUNT(DISTINCT {})'.format(self.column_name), metric_type=self.type, json=json.dumps({ 'type': self.type, 'name': name, 'fieldName': self.column_name }) )) else: mt = 'count_distinct' metrics.append(DruidMetric( metric_name=name, verbose_name='COUNT(DISTINCT {})'.format(self.column_name), metric_type='count_distinct', json=json.dumps({ 'type': 'cardinality', 'name': name, 'fieldNames': [self.column_name]}) )) session = get_session() new_metrics = [] for metric in metrics: m = ( session.query(M) .filter(M.metric_name == metric.metric_name) .filter(M.datasource_name == self.datasource_name) .filter(DruidCluster.cluster_name == self.datasource.cluster_name) .first() ) metric.datasource_name = self.datasource_name if not m: new_metrics.append(metric) session.add(metric) session.flush() utils.init_metrics_perm(caravel, new_metrics)
def post_update(self, metric): utils.init_metrics_perm(caravel, [metric])
def post_add(self, metric): utils.init_metrics_perm(caravel, [metric])
def post_add(self, new_item): utils.init_metrics_perm(caravel, [new_item])