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])
def post_update(self, metric):
utils.init_metrics_perm(caravel, [metric])
def post_add(self, metric):
utils.init_metrics_perm(caravel, [metric])