mirror of
https://github.com/apache/superset.git
synced 2024-09-18 19:49:37 -04:00
0ca3f5ec80
* Improving SQLA query generation * Fixing debug
1361 lines
45 KiB
Python
1361 lines
45 KiB
Python
"""A collection of ORM sqlalchemy models for Caravel"""
|
|
from __future__ import absolute_import
|
|
from __future__ import division
|
|
from __future__ import print_function
|
|
from __future__ import unicode_literals
|
|
|
|
import functools
|
|
import json
|
|
import logging
|
|
import textwrap
|
|
from collections import namedtuple
|
|
from copy import deepcopy, copy
|
|
from datetime import timedelta, datetime, date
|
|
|
|
import humanize
|
|
import pandas as pd
|
|
import requests
|
|
import sqlalchemy as sqla
|
|
import sqlparse
|
|
from dateutil.parser import parse
|
|
from flask import request, g
|
|
from flask.ext.appbuilder import Model
|
|
from flask.ext.appbuilder.models.mixins import AuditMixin
|
|
from pydruid.client import PyDruid
|
|
from flask.ext.appbuilder.models.decorators import renders
|
|
from pydruid.utils.filters import Dimension, Filter
|
|
from six import string_types
|
|
from sqlalchemy import (
|
|
Column, Integer, String, ForeignKey, Text, Boolean, DateTime, Date,
|
|
Table, create_engine, MetaData, desc, select, and_, func)
|
|
from sqlalchemy.engine import reflection
|
|
from sqlalchemy.ext.declarative import declared_attr
|
|
from sqlalchemy.orm import relationship
|
|
from sqlalchemy.sql import table, literal_column, text, column
|
|
from sqlalchemy.sql.elements import ColumnClause
|
|
from sqlalchemy_utils import EncryptedType
|
|
|
|
from caravel import app, db, get_session, utils
|
|
from caravel.viz import viz_types
|
|
from caravel.utils import flasher
|
|
|
|
config = app.config
|
|
|
|
QueryResult = namedtuple('namedtuple', ['df', 'query', 'duration'])
|
|
|
|
|
|
class AuditMixinNullable(AuditMixin):
|
|
|
|
"""Altering the AuditMixin to use nullable fields
|
|
|
|
Allows creating objects programmatically outside of CRUD
|
|
"""
|
|
|
|
created_on = Column(DateTime, default=datetime.now, nullable=True)
|
|
changed_on = Column(
|
|
DateTime, default=datetime.now,
|
|
onupdate=datetime.now, nullable=True)
|
|
|
|
@declared_attr
|
|
def created_by_fk(cls): # noqa
|
|
return Column(Integer, ForeignKey('ab_user.id'),
|
|
default=cls.get_user_id, nullable=True)
|
|
|
|
@declared_attr
|
|
def changed_by_fk(cls): # noqa
|
|
return Column(
|
|
Integer, ForeignKey('ab_user.id'),
|
|
default=cls.get_user_id, onupdate=cls.get_user_id, nullable=True)
|
|
|
|
@renders('created_by')
|
|
def creator(self): # noqa
|
|
return '{}'.format(self.created_by or '')
|
|
|
|
@renders('changed_by')
|
|
def changed_by_(self):
|
|
return '{}'.format(self.changed_by or '')
|
|
|
|
@renders('changed_on')
|
|
def modified(self):
|
|
s = humanize.naturaltime(datetime.now() - self.changed_on)
|
|
return '<span class="no-wrap">{}</nobr>'.format(s)
|
|
|
|
@property
|
|
def icons(self):
|
|
return """
|
|
<a
|
|
href="{self.datasource_edit_url}"
|
|
data-toggle="tooltip"
|
|
title="{self.datasource}">
|
|
<i class="fa fa-database"></i>
|
|
</a>
|
|
""".format(**locals())
|
|
|
|
|
|
class Url(Model, AuditMixinNullable):
|
|
|
|
"""Used for the short url feature"""
|
|
|
|
__tablename__ = 'url'
|
|
id = Column(Integer, primary_key=True)
|
|
url = Column(Text)
|
|
|
|
|
|
class CssTemplate(Model, AuditMixinNullable):
|
|
|
|
"""CSS templates for dashboards"""
|
|
|
|
__tablename__ = 'css_templates'
|
|
id = Column(Integer, primary_key=True)
|
|
template_name = Column(String(250))
|
|
css = Column(Text, default='')
|
|
|
|
|
|
slice_user = Table('slice_user', Model.metadata,
|
|
Column('id', Integer, primary_key=True),
|
|
Column('user_id', Integer, ForeignKey('ab_user.id')),
|
|
Column('slice_id', Integer, ForeignKey('slices.id'))
|
|
)
|
|
|
|
|
|
class Slice(Model, AuditMixinNullable):
|
|
|
|
"""A slice is essentially a report or a view on data"""
|
|
|
|
__tablename__ = 'slices'
|
|
id = Column(Integer, primary_key=True)
|
|
slice_name = Column(String(250))
|
|
druid_datasource_id = Column(Integer, ForeignKey('datasources.id'))
|
|
table_id = Column(Integer, ForeignKey('tables.id'))
|
|
datasource_type = Column(String(200))
|
|
datasource_name = Column(String(2000))
|
|
viz_type = Column(String(250))
|
|
params = Column(Text)
|
|
description = Column(Text)
|
|
cache_timeout = Column(Integer)
|
|
perm = Column(String(2000))
|
|
|
|
table = relationship(
|
|
'SqlaTable', foreign_keys=[table_id], backref='slices')
|
|
druid_datasource = relationship(
|
|
'DruidDatasource', foreign_keys=[druid_datasource_id], backref='slices')
|
|
owners = relationship("User", secondary=slice_user)
|
|
|
|
def __repr__(self):
|
|
return self.slice_name
|
|
|
|
@property
|
|
def datasource(self):
|
|
return self.table or self.druid_datasource
|
|
|
|
@property
|
|
def datasource_link(self):
|
|
if self.table:
|
|
return self.table.link
|
|
elif self.druid_datasource:
|
|
return self.druid_datasource.link
|
|
|
|
@property
|
|
def datasource_edit_url(self):
|
|
if self.table:
|
|
return self.table.url
|
|
elif self.druid_datasource:
|
|
return self.druid_datasource.url
|
|
|
|
@property
|
|
@utils.memoized
|
|
def viz(self):
|
|
d = json.loads(self.params)
|
|
viz_class = viz_types[self.viz_type]
|
|
return viz_class(self.datasource, form_data=d)
|
|
|
|
@property
|
|
def description_markeddown(self):
|
|
return utils.markdown(self.description)
|
|
|
|
@property
|
|
def datasource_id(self):
|
|
return self.table_id or self.druid_datasource_id
|
|
|
|
@property
|
|
def data(self):
|
|
d = {}
|
|
self.token = ''
|
|
try:
|
|
d = self.viz.data
|
|
self.token = d.get('token')
|
|
except Exception as e:
|
|
d['error'] = str(e)
|
|
d['slice_id'] = self.id
|
|
return d
|
|
|
|
@property
|
|
def json_data(self):
|
|
return json.dumps(self.data)
|
|
|
|
@property
|
|
def slice_url(self):
|
|
"""Defines the url to access the slice"""
|
|
try:
|
|
slice_params = json.loads(self.params)
|
|
except Exception as e:
|
|
logging.exception(e)
|
|
slice_params = {}
|
|
slice_params['slice_id'] = self.id
|
|
slice_params['json'] = "false"
|
|
slice_params['slice_name'] = self.slice_name
|
|
from werkzeug.urls import Href
|
|
href = Href(
|
|
"/caravel/explore/{obj.datasource_type}/"
|
|
"{obj.datasource_id}/".format(obj=self))
|
|
return href(slice_params)
|
|
|
|
@property
|
|
def edit_url(self):
|
|
return "/slicemodelview/edit/{}".format(self.id)
|
|
|
|
@property
|
|
def slice_link(self):
|
|
url = self.slice_url
|
|
return '<a href="{url}">{obj.slice_name}</a>'.format(
|
|
url=url, obj=self)
|
|
|
|
|
|
def set_perm(mapper, connection, target): # noqa
|
|
if target.table_id:
|
|
src_class = SqlaTable
|
|
id_ = target.table_id
|
|
elif target.druid_datasource_id:
|
|
src_class = DruidDatasource
|
|
id_ = target.druid_datasource_id
|
|
ds = db.session.query(src_class).filter_by(id=int(id_)).first()
|
|
target.perm = ds.perm
|
|
|
|
sqla.event.listen(Slice, 'before_insert', set_perm)
|
|
sqla.event.listen(Slice, 'before_update', set_perm)
|
|
|
|
|
|
dashboard_slices = Table(
|
|
'dashboard_slices', Model.metadata,
|
|
Column('id', Integer, primary_key=True),
|
|
Column('dashboard_id', Integer, ForeignKey('dashboards.id')),
|
|
Column('slice_id', Integer, ForeignKey('slices.id')),
|
|
)
|
|
|
|
dashboard_user = Table(
|
|
'dashboard_user', Model.metadata,
|
|
Column('id', Integer, primary_key=True),
|
|
Column('user_id', Integer, ForeignKey('ab_user.id')),
|
|
Column('dashboard_id', Integer, ForeignKey('dashboards.id'))
|
|
)
|
|
|
|
|
|
class Dashboard(Model, AuditMixinNullable):
|
|
|
|
"""The dashboard object!"""
|
|
|
|
__tablename__ = 'dashboards'
|
|
id = Column(Integer, primary_key=True)
|
|
dashboard_title = Column(String(500))
|
|
position_json = Column(Text)
|
|
description = Column(Text)
|
|
css = Column(Text)
|
|
json_metadata = Column(Text)
|
|
slug = Column(String(255), unique=True)
|
|
slices = relationship(
|
|
'Slice', secondary=dashboard_slices, backref='dashboards')
|
|
owners = relationship("User", secondary=dashboard_user)
|
|
|
|
def __repr__(self):
|
|
return self.dashboard_title
|
|
|
|
@property
|
|
def url(self):
|
|
return "/caravel/dashboard/{}/".format(self.slug or self.id)
|
|
|
|
@property
|
|
def metadata_dejson(self):
|
|
if self.json_metadata:
|
|
return json.loads(self.json_metadata)
|
|
else:
|
|
return {}
|
|
|
|
def dashboard_link(self):
|
|
return '<a href="{obj.url}">{obj.dashboard_title}</a>'.format(obj=self)
|
|
|
|
@property
|
|
def json_data(self):
|
|
d = {
|
|
'id': self.id,
|
|
'metadata': self.metadata_dejson,
|
|
'dashboard_title': self.dashboard_title,
|
|
'slug': self.slug,
|
|
'slices': [slc.data for slc in self.slices],
|
|
}
|
|
return json.dumps(d)
|
|
|
|
|
|
class Queryable(object):
|
|
|
|
"""A common interface to objects that are queryable (tables and datasources)"""
|
|
|
|
@property
|
|
def column_names(self):
|
|
return sorted([c.column_name for c in self.columns])
|
|
|
|
@property
|
|
def main_dttm_col(self):
|
|
return "timestamp"
|
|
|
|
@property
|
|
def groupby_column_names(self):
|
|
return sorted([c.column_name for c in self.columns if c.groupby])
|
|
|
|
@property
|
|
def filterable_column_names(self):
|
|
return sorted([c.column_name for c in self.columns if c.filterable])
|
|
|
|
@property
|
|
def dttm_cols(self):
|
|
return []
|
|
|
|
|
|
class Database(Model, AuditMixinNullable):
|
|
|
|
"""An ORM object that stores Database related information"""
|
|
|
|
__tablename__ = 'dbs'
|
|
id = Column(Integer, primary_key=True)
|
|
database_name = Column(String(250), unique=True)
|
|
sqlalchemy_uri = Column(String(1024))
|
|
password = Column(EncryptedType(String(1024), config.get('SECRET_KEY')))
|
|
cache_timeout = Column(Integer)
|
|
extra = Column(Text, default=textwrap.dedent("""\
|
|
{
|
|
"metadata_params": {},
|
|
"engine_params": {}
|
|
}
|
|
"""))
|
|
|
|
def __repr__(self):
|
|
return self.database_name
|
|
|
|
def get_sqla_engine(self):
|
|
extra = self.get_extra()
|
|
params = extra.get('engine_params', {})
|
|
return create_engine(self.sqlalchemy_uri_decrypted, **params)
|
|
|
|
def safe_sqlalchemy_uri(self):
|
|
return self.sqlalchemy_uri
|
|
|
|
def grains(self):
|
|
"""Defines time granularity database-specific expressions.
|
|
|
|
The idea here is to make it easy for users to change the time grain
|
|
form a datetime (maybe the source grain is arbitrary timestamps, daily
|
|
or 5 minutes increments) to another, "truncated" datetime. Since
|
|
each database has slightly different but similar datetime functions,
|
|
this allows a mapping between database engines and actual functions.
|
|
"""
|
|
Grain = namedtuple('Grain', 'name function')
|
|
db_time_grains = {
|
|
'presto': (
|
|
Grain('Time Column', '{col}'),
|
|
Grain('week', "date_trunc('week', CAST({col} AS DATE))"),
|
|
Grain('month', "date_trunc('month', CAST({col} AS DATE))"),
|
|
Grain("week_ending_saturday", "date_add('day', 5, "
|
|
"date_trunc('week', date_add('day', 1, CAST({col} AS DATE))))"),
|
|
Grain("week_start_sunday", "date_add('day', -1, "
|
|
"date_trunc('week', date_add('day', 1, CAST({col} AS DATE))))")
|
|
),
|
|
'mysql': (
|
|
Grain('Time Column', '{col}'),
|
|
Grain('day', 'DATE({col})'),
|
|
Grain("week", "DATE(DATE_SUB({col}, "
|
|
"INTERVAL DAYOFWEEK({col}) - 1 DAY))"),
|
|
Grain("month", "DATE(DATE_SUB({col}, "
|
|
"INTERVAL DAYOFMONTH({col}) - 1 DAY))"),
|
|
),
|
|
'postgresql': (
|
|
Grain("Time Column", "{col}"),
|
|
Grain("hour", "DATE_TRUNC('hour', {col})"),
|
|
Grain("day", "DATE_TRUNC('day', {col})"),
|
|
Grain("week", "DATE_TRUNC('week', {col})"),
|
|
Grain("month", "DATE_TRUNC('month', {col})"),
|
|
Grain("year", "DATE_TRUNC('year', {col})"),
|
|
),
|
|
}
|
|
db_time_grains['redshift'] = db_time_grains['postgresql']
|
|
for db_type, grains in db_time_grains.items():
|
|
if self.sqlalchemy_uri.startswith(db_type):
|
|
return grains
|
|
|
|
def grains_dict(self):
|
|
return {grain.name: grain for grain in self.grains()}
|
|
|
|
def get_extra(self):
|
|
extra = {}
|
|
if self.extra:
|
|
try:
|
|
extra = json.loads(self.extra)
|
|
except Exception as e:
|
|
logging.error(e)
|
|
return extra
|
|
|
|
def get_table(self, table_name, schema=None):
|
|
extra = self.get_extra()
|
|
meta = MetaData(**extra.get('metadata_params', {}))
|
|
return Table(
|
|
table_name, meta,
|
|
schema=schema or None,
|
|
autoload=True,
|
|
autoload_with=self.get_sqla_engine())
|
|
|
|
def get_columns(self, table_name):
|
|
engine = self.get_sqla_engine()
|
|
insp = reflection.Inspector.from_engine(engine)
|
|
return insp.get_columns(table_name)
|
|
|
|
@property
|
|
def sqlalchemy_uri_decrypted(self):
|
|
conn = sqla.engine.url.make_url(self.sqlalchemy_uri)
|
|
conn.password = self.password
|
|
return str(conn)
|
|
|
|
@property
|
|
def sql_url(self):
|
|
return '/caravel/sql/{}/'.format(self.id)
|
|
|
|
@property
|
|
def sql_link(self):
|
|
return '<a href="{}">SQL</a>'.format(self.sql_url)
|
|
|
|
|
|
class SqlaTable(Model, Queryable, AuditMixinNullable):
|
|
|
|
"""An ORM object for SqlAlchemy table references"""
|
|
|
|
type = "table"
|
|
|
|
__tablename__ = 'tables'
|
|
id = Column(Integer, primary_key=True)
|
|
table_name = Column(String(250))
|
|
main_dttm_col = Column(String(250))
|
|
description = Column(Text)
|
|
default_endpoint = Column(Text)
|
|
database_id = Column(Integer, ForeignKey('dbs.id'), nullable=False)
|
|
is_featured = Column(Boolean, default=False)
|
|
user_id = Column(Integer, ForeignKey('ab_user.id'))
|
|
owner = relationship('User', backref='tables', foreign_keys=[user_id])
|
|
database = relationship(
|
|
'Database', backref='tables', foreign_keys=[database_id])
|
|
offset = Column(Integer, default=0)
|
|
cache_timeout = Column(Integer)
|
|
schema = Column(String(256))
|
|
|
|
baselink = "tablemodelview"
|
|
|
|
__table_args__ = (
|
|
sqla.UniqueConstraint(
|
|
'database_id', 'schema', 'table_name',
|
|
name='_customer_location_uc'),)
|
|
|
|
def __repr__(self):
|
|
return self.table_name
|
|
|
|
@property
|
|
def description_markeddown(self):
|
|
return utils.markdown(self.description)
|
|
|
|
@property
|
|
def url(self):
|
|
return '/tablemodelview/edit/{}'.format(self.id)
|
|
|
|
@property
|
|
def link(self):
|
|
return '<a href="{self.url}">{self.table_name}</a>'.format(**locals())
|
|
|
|
@property
|
|
def perm(self):
|
|
return (
|
|
"[{obj.database}].[{obj.table_name}]"
|
|
"(id:{obj.id})").format(obj=self)
|
|
|
|
@property
|
|
def full_name(self):
|
|
return "[{obj.database}].[{obj.table_name}]".format(obj=self)
|
|
|
|
@property
|
|
def dttm_cols(self):
|
|
l = [c.column_name for c in self.columns if c.is_dttm]
|
|
if self.main_dttm_col not in l:
|
|
l.append(self.main_dttm_col)
|
|
return l
|
|
|
|
@property
|
|
def any_dttm_col(self):
|
|
cols = self.dttm_cols
|
|
if cols:
|
|
return cols[0]
|
|
|
|
@property
|
|
def html(self):
|
|
t = ((c.column_name, c.type) for c in self.columns)
|
|
df = pd.DataFrame(t)
|
|
df.columns = ['field', 'type']
|
|
return df.to_html(
|
|
index=False,
|
|
classes=(
|
|
"dataframe table table-striped table-bordered "
|
|
"table-condensed"))
|
|
|
|
@property
|
|
def name(self):
|
|
return self.table_name
|
|
|
|
@property
|
|
def explore_url(self):
|
|
if self.default_endpoint:
|
|
return self.default_endpoint
|
|
else:
|
|
return "/caravel/explore/{obj.type}/{obj.id}/".format(obj=self)
|
|
|
|
@property
|
|
def table_link(self):
|
|
return '<a href="{obj.explore_url}">{obj.table_name}</a>'.format(obj=self)
|
|
|
|
@property
|
|
def metrics_combo(self):
|
|
return sorted(
|
|
[
|
|
(m.metric_name, m.verbose_name or m.metric_name)
|
|
for m in self.metrics],
|
|
key=lambda x: x[1])
|
|
|
|
@property
|
|
def sql_url(self):
|
|
return self.database.sql_url + "?table_name=" + str(self.table_name)
|
|
|
|
@property
|
|
def sql_link(self):
|
|
return '<a href="{}">SQL</a>'.format(self.sql_url)
|
|
|
|
def query( # sqla
|
|
self, groupby, metrics,
|
|
granularity,
|
|
from_dttm, to_dttm,
|
|
filter=None, # noqa
|
|
is_timeseries=True,
|
|
timeseries_limit=15, row_limit=None,
|
|
inner_from_dttm=None, inner_to_dttm=None,
|
|
extras=None,
|
|
columns=None):
|
|
"""Querying any sqla table from this common interface"""
|
|
# For backward compatibility
|
|
if granularity not in self.dttm_cols:
|
|
granularity = self.main_dttm_col
|
|
|
|
cols = {col.column_name: col for col in self.columns}
|
|
qry_start_dttm = datetime.now()
|
|
|
|
if not granularity and is_timeseries:
|
|
raise Exception(
|
|
"Datetime column not provided as part table configuration "
|
|
"and is required by this type of chart")
|
|
|
|
metrics_exprs = [
|
|
m.sqla_col
|
|
for m in self.metrics if m.metric_name in metrics]
|
|
|
|
if metrics:
|
|
main_metric_expr = [
|
|
m.sqla_col for m in self.metrics
|
|
if m.metric_name == metrics[0]][0]
|
|
else:
|
|
main_metric_expr = literal_column("COUNT(*)").label("ccount")
|
|
|
|
select_exprs = []
|
|
groupby_exprs = []
|
|
|
|
if groupby:
|
|
select_exprs = []
|
|
inner_select_exprs = []
|
|
inner_groupby_exprs = []
|
|
for s in groupby:
|
|
col = cols[s]
|
|
outer = col.sqla_col
|
|
inner = col.sqla_col.label('__' + col.column_name)
|
|
|
|
groupby_exprs.append(outer)
|
|
select_exprs.append(outer)
|
|
inner_groupby_exprs.append(inner)
|
|
inner_select_exprs.append(inner)
|
|
elif columns:
|
|
for s in columns:
|
|
select_exprs.append(cols[s].sqla_col)
|
|
metrics_exprs = []
|
|
|
|
if granularity:
|
|
dttm_expr = cols[granularity].sqla_col.label('timestamp')
|
|
timestamp = dttm_expr
|
|
|
|
# Transforming time grain into an expression based on configuration
|
|
time_grain_sqla = extras.get('time_grain_sqla')
|
|
if time_grain_sqla:
|
|
udf = self.database.grains_dict().get(time_grain_sqla, '{col}')
|
|
timestamp_grain = literal_column(
|
|
udf.function.format(col=dttm_expr)).label('timestamp')
|
|
else:
|
|
timestamp_grain = timestamp
|
|
|
|
if is_timeseries:
|
|
select_exprs += [timestamp_grain]
|
|
groupby_exprs += [timestamp_grain]
|
|
|
|
tf = '%Y-%m-%d %H:%M:%S.%f'
|
|
time_filter = [
|
|
timestamp >= from_dttm.strftime(tf),
|
|
timestamp <= to_dttm.strftime(tf),
|
|
]
|
|
inner_time_filter = copy(time_filter)
|
|
if inner_from_dttm:
|
|
inner_time_filter[0] = timestamp >= inner_from_dttm.strftime(tf)
|
|
if inner_to_dttm:
|
|
inner_time_filter[1] = timestamp <= inner_to_dttm.strftime(tf)
|
|
else:
|
|
inner_time_filter = []
|
|
|
|
select_exprs += metrics_exprs
|
|
qry = select(select_exprs)
|
|
|
|
tbl = table(self.table_name)
|
|
if self.schema:
|
|
tbl.schema = self.schema
|
|
|
|
if not columns:
|
|
qry = qry.group_by(*groupby_exprs)
|
|
|
|
where_clause_and = []
|
|
having_clause_and = []
|
|
for col, op, eq in filter:
|
|
col_obj = cols[col]
|
|
if op in ('in', 'not in'):
|
|
values = eq.split(",")
|
|
cond = col_obj.sqla_col.in_(values)
|
|
if op == 'not in':
|
|
cond = ~cond
|
|
where_clause_and.append(cond)
|
|
if extras and 'where' in extras:
|
|
where_clause_and += [text(extras['where'])]
|
|
if extras and 'having' in extras:
|
|
having_clause_and += [text(extras['having'])]
|
|
if granularity:
|
|
qry = qry.where(and_(*(time_filter + where_clause_and)))
|
|
else:
|
|
qry = qry.where(and_(*where_clause_and))
|
|
qry = qry.having(and_(*having_clause_and))
|
|
if groupby:
|
|
qry = qry.order_by(desc(main_metric_expr))
|
|
qry = qry.limit(row_limit)
|
|
|
|
if timeseries_limit and groupby:
|
|
subq = select(inner_select_exprs)
|
|
subq = subq.select_from(tbl)
|
|
subq = subq.where(and_(*(where_clause_and + inner_time_filter)))
|
|
subq = subq.group_by(*inner_groupby_exprs)
|
|
subq = subq.order_by(desc(main_metric_expr))
|
|
subq = subq.limit(timeseries_limit)
|
|
on_clause = []
|
|
for i, gb in enumerate(groupby):
|
|
on_clause.append(
|
|
groupby_exprs[i] == column("__" + gb))
|
|
|
|
tbl = tbl.join(subq.alias(), and_(*on_clause))
|
|
|
|
qry = qry.select_from(tbl)
|
|
|
|
engine = self.database.get_sqla_engine()
|
|
sql = "{}".format(
|
|
qry.compile(
|
|
engine, compile_kwargs={"literal_binds": True},),
|
|
)
|
|
print(sql)
|
|
df = pd.read_sql_query(
|
|
sql=sql,
|
|
con=engine
|
|
)
|
|
sql = sqlparse.format(sql, reindent=True)
|
|
return QueryResult(
|
|
df=df, duration=datetime.now() - qry_start_dttm, query=sql)
|
|
|
|
def fetch_metadata(self):
|
|
"""Fetches the metadata for the table and merges it in"""
|
|
try:
|
|
table = self.database.get_table(self.table_name, schema=self.schema)
|
|
except Exception as e:
|
|
flasher(str(e))
|
|
flasher(
|
|
"Table doesn't seem to exist in the specified database, "
|
|
"couldn't fetch column information", "danger")
|
|
return
|
|
|
|
TC = TableColumn # noqa shortcut to class
|
|
M = SqlMetric # noqa
|
|
metrics = []
|
|
any_date_col = None
|
|
for col in table.columns:
|
|
try:
|
|
datatype = str(col.type)
|
|
except Exception as e:
|
|
datatype = "UNKNOWN"
|
|
dbcol = (
|
|
db.session
|
|
.query(TC)
|
|
.filter(TC.table == self)
|
|
.filter(TC.column_name == col.name)
|
|
.first()
|
|
)
|
|
db.session.flush()
|
|
if not dbcol:
|
|
dbcol = TableColumn(column_name=col.name)
|
|
num_types = ('DOUBLE', 'FLOAT', 'INT', 'BIGINT', 'LONG')
|
|
date_types = ('DATE', 'TIME')
|
|
str_types = ('VARCHAR', 'STRING')
|
|
datatype = str(datatype).upper()
|
|
if any([t in datatype for t in str_types]):
|
|
dbcol.groupby = True
|
|
dbcol.filterable = True
|
|
elif any([t in datatype for t in num_types]):
|
|
dbcol.sum = True
|
|
elif any([t in datatype for t in date_types]):
|
|
dbcol.is_dttm = True
|
|
db.session.merge(self)
|
|
self.columns.append(dbcol)
|
|
|
|
if not any_date_col and 'date' in datatype.lower():
|
|
any_date_col = col.name
|
|
|
|
quoted = "{}".format(
|
|
column(dbcol.column_name).compile(dialect=db.engine.dialect))
|
|
if dbcol.sum:
|
|
metrics.append(M(
|
|
metric_name='sum__' + dbcol.column_name,
|
|
verbose_name='sum__' + dbcol.column_name,
|
|
metric_type='sum',
|
|
expression="SUM({})".format(quoted)
|
|
))
|
|
if dbcol.max:
|
|
metrics.append(M(
|
|
metric_name='max__' + dbcol.column_name,
|
|
verbose_name='max__' + dbcol.column_name,
|
|
metric_type='max',
|
|
expression="MAX({})".format(quoted)
|
|
))
|
|
if dbcol.min:
|
|
metrics.append(M(
|
|
metric_name='min__' + dbcol.column_name,
|
|
verbose_name='min__' + dbcol.column_name,
|
|
metric_type='min',
|
|
expression="MIN({})".format(quoted)
|
|
))
|
|
if dbcol.count_distinct:
|
|
metrics.append(M(
|
|
metric_name='count_distinct__' + dbcol.column_name,
|
|
verbose_name='count_distinct__' + dbcol.column_name,
|
|
metric_type='count_distinct',
|
|
expression="COUNT(DISTINCT {})".format(quoted)
|
|
))
|
|
dbcol.type = datatype
|
|
db.session.merge(self)
|
|
db.session.commit()
|
|
|
|
metrics.append(M(
|
|
metric_name='count',
|
|
verbose_name='COUNT(*)',
|
|
metric_type='count',
|
|
expression="COUNT(*)"
|
|
))
|
|
for metric in metrics:
|
|
m = (
|
|
db.session.query(M)
|
|
.filter(M.metric_name == metric.metric_name)
|
|
.filter(M.table_id == self.id)
|
|
.first()
|
|
)
|
|
metric.table_id = self.id
|
|
if not m:
|
|
db.session.add(metric)
|
|
db.session.commit()
|
|
if not self.main_dttm_col:
|
|
self.main_dttm_col = any_date_col
|
|
|
|
|
|
class SqlMetric(Model, AuditMixinNullable):
|
|
|
|
"""ORM object for metrics, each table can have multiple metrics"""
|
|
|
|
__tablename__ = 'sql_metrics'
|
|
id = Column(Integer, primary_key=True)
|
|
metric_name = Column(String(512))
|
|
verbose_name = Column(String(1024))
|
|
metric_type = Column(String(32))
|
|
table_id = Column(Integer, ForeignKey('tables.id'))
|
|
table = relationship(
|
|
'SqlaTable', backref='metrics', foreign_keys=[table_id])
|
|
expression = Column(Text)
|
|
description = Column(Text)
|
|
|
|
@property
|
|
def sqla_col(self):
|
|
name = self.metric_name
|
|
return literal_column(self.expression).label(name)
|
|
|
|
|
|
class TableColumn(Model, AuditMixinNullable):
|
|
|
|
"""ORM object for table columns, each table can have multiple columns"""
|
|
|
|
__tablename__ = 'table_columns'
|
|
id = Column(Integer, primary_key=True)
|
|
table_id = Column(Integer, ForeignKey('tables.id'))
|
|
table = relationship(
|
|
'SqlaTable', backref='columns', foreign_keys=[table_id])
|
|
column_name = Column(String(256))
|
|
verbose_name = Column(String(1024))
|
|
is_dttm = Column(Boolean, default=False)
|
|
is_active = Column(Boolean, default=True)
|
|
type = Column(String(32), default='')
|
|
groupby = Column(Boolean, default=False)
|
|
count_distinct = Column(Boolean, default=False)
|
|
sum = Column(Boolean, default=False)
|
|
max = Column(Boolean, default=False)
|
|
min = Column(Boolean, default=False)
|
|
filterable = Column(Boolean, default=False)
|
|
expression = Column(Text, default='')
|
|
description = Column(Text, default='')
|
|
|
|
def __repr__(self):
|
|
return self.column_name
|
|
|
|
@property
|
|
def isnum(self):
|
|
types = ('LONG', 'DOUBLE', 'FLOAT', 'BIGINT', 'INT')
|
|
return any([t in self.type.upper() for t in types])
|
|
|
|
@property
|
|
def sqla_col(self):
|
|
name = self.column_name
|
|
if not self.expression:
|
|
col = column(self.column_name).label(name)
|
|
else:
|
|
col = literal_column(self.expression).label(name)
|
|
return col
|
|
|
|
|
|
class DruidCluster(Model, AuditMixinNullable):
|
|
|
|
"""ORM object referencing the Druid clusters"""
|
|
|
|
__tablename__ = 'clusters'
|
|
id = Column(Integer, primary_key=True)
|
|
cluster_name = Column(String(250), unique=True)
|
|
coordinator_host = Column(String(256))
|
|
coordinator_port = Column(Integer)
|
|
coordinator_endpoint = Column(
|
|
String(256), default='druid/coordinator/v1/metadata')
|
|
broker_host = Column(String(256))
|
|
broker_port = Column(Integer)
|
|
broker_endpoint = Column(String(256), default='druid/v2')
|
|
metadata_last_refreshed = Column(DateTime)
|
|
|
|
def __repr__(self):
|
|
return self.cluster_name
|
|
|
|
def get_pydruid_client(self):
|
|
cli = PyDruid(
|
|
"http://{0}:{1}/".format(self.broker_host, self.broker_port),
|
|
self.broker_endpoint)
|
|
return cli
|
|
|
|
def get_datasources(self):
|
|
endpoint = (
|
|
"http://{obj.coordinator_host}:{obj.coordinator_port}/"
|
|
"{obj.coordinator_endpoint}/datasources"
|
|
).format(obj=self)
|
|
|
|
return json.loads(requests.get(endpoint).text)
|
|
|
|
def refresh_datasources(self):
|
|
for datasource in self.get_datasources():
|
|
DruidDatasource.sync_to_db(datasource, self)
|
|
|
|
|
|
class DruidDatasource(Model, AuditMixinNullable, Queryable):
|
|
|
|
"""ORM object referencing Druid datasources (tables)"""
|
|
|
|
type = "druid"
|
|
|
|
baselink = "datasourcemodelview"
|
|
|
|
__tablename__ = 'datasources'
|
|
id = Column(Integer, primary_key=True)
|
|
datasource_name = Column(String(256), unique=True)
|
|
is_featured = Column(Boolean, default=False)
|
|
is_hidden = Column(Boolean, default=False)
|
|
description = Column(Text)
|
|
default_endpoint = Column(Text)
|
|
user_id = Column(Integer, ForeignKey('ab_user.id'))
|
|
owner = relationship('User', backref='datasources', foreign_keys=[user_id])
|
|
cluster_name = Column(
|
|
String(250), ForeignKey('clusters.cluster_name'))
|
|
cluster = relationship(
|
|
'DruidCluster', backref='datasources', foreign_keys=[cluster_name])
|
|
offset = Column(Integer, default=0)
|
|
cache_timeout = Column(Integer)
|
|
|
|
@property
|
|
def metrics_combo(self):
|
|
return sorted(
|
|
[(m.metric_name, m.verbose_name) for m in self.metrics],
|
|
key=lambda x: x[1])
|
|
|
|
@property
|
|
def name(self):
|
|
return self.datasource_name
|
|
|
|
@property
|
|
def perm(self):
|
|
return (
|
|
"[{obj.cluster_name}].[{obj.datasource_name}]"
|
|
"(id:{obj.id})").format(obj=self)
|
|
|
|
@property
|
|
def url(self):
|
|
return '/datasourcemodelview/edit/{}'.format(self.id)
|
|
|
|
@property
|
|
def link(self):
|
|
return (
|
|
'<a href="{self.url}">'
|
|
'{self.datasource_name}</a>').format(**locals())
|
|
|
|
@property
|
|
def full_name(self):
|
|
return (
|
|
"[{obj.cluster_name}]."
|
|
"[{obj.datasource_name}]").format(obj=self)
|
|
|
|
def __repr__(self):
|
|
return self.datasource_name
|
|
|
|
@property
|
|
def datasource_link(self):
|
|
url = "/caravel/explore/{obj.type}/{obj.id}/".format(obj=self)
|
|
return '<a href="{url}">{obj.datasource_name}</a>'.format(
|
|
url=url, obj=self)
|
|
|
|
def get_metric_obj(self, metric_name):
|
|
return [
|
|
m.json_obj for m in self.metrics
|
|
if m.metric_name == metric_name
|
|
][0]
|
|
|
|
def latest_metadata(self):
|
|
"""Returns segment metadata from the latest segment"""
|
|
client = self.cluster.get_pydruid_client()
|
|
results = client.time_boundary(datasource=self.datasource_name)
|
|
if not results:
|
|
return
|
|
max_time = results[0]['result']['maxTime']
|
|
max_time = parse(max_time)
|
|
# Query segmentMetadata for 7 days back. However, due to a bug,
|
|
# we need to set this interval to more than 1 day ago to exclude
|
|
# realtime segments, which trigged a bug (fixed in druid 0.8.2).
|
|
# https://groups.google.com/forum/#!topic/druid-user/gVCqqspHqOQ
|
|
intervals = (max_time - timedelta(days=7)).isoformat() + '/'
|
|
intervals += (max_time - timedelta(days=1)).isoformat()
|
|
segment_metadata = client.segment_metadata(
|
|
datasource=self.datasource_name,
|
|
intervals=intervals)
|
|
if segment_metadata:
|
|
return segment_metadata[-1]['columns']
|
|
|
|
def generate_metrics(self):
|
|
for col in self.columns:
|
|
col.generate_metrics()
|
|
|
|
@classmethod
|
|
def sync_to_db(cls, name, cluster):
|
|
"""Fetches metadata for that datasource and merges the Caravel db"""
|
|
print("Syncing Druid datasource [{}]".format(name))
|
|
session = get_session()
|
|
datasource = session.query(cls).filter_by(datasource_name=name).first()
|
|
if not datasource:
|
|
datasource = cls(datasource_name=name)
|
|
session.add(datasource)
|
|
flasher("Adding new datasource [{}]".format(name), "success")
|
|
else:
|
|
flasher("Refreshing datasource [{}]".format(name), "info")
|
|
datasource.cluster = cluster
|
|
|
|
cols = datasource.latest_metadata()
|
|
if not cols:
|
|
return
|
|
for col in cols:
|
|
col_obj = (
|
|
session
|
|
.query(DruidColumn)
|
|
.filter_by(datasource_name=name, column_name=col)
|
|
.first()
|
|
)
|
|
datatype = cols[col]['type']
|
|
if not col_obj:
|
|
col_obj = DruidColumn(datasource_name=name, column_name=col)
|
|
session.add(col_obj)
|
|
if datatype == "STRING":
|
|
col_obj.groupby = True
|
|
col_obj.filterable = True
|
|
if col_obj:
|
|
col_obj.type = cols[col]['type']
|
|
col_obj.datasource = datasource
|
|
col_obj.generate_metrics()
|
|
|
|
def query( # druid
|
|
self, groupby, metrics,
|
|
granularity,
|
|
from_dttm, to_dttm,
|
|
filter=None, # noqa
|
|
is_timeseries=True,
|
|
timeseries_limit=None,
|
|
row_limit=None,
|
|
inner_from_dttm=None, inner_to_dttm=None,
|
|
extras=None, # noqa
|
|
select=None,): # noqa
|
|
"""Runs a query against Druid and returns a dataframe.
|
|
|
|
This query interface is common to SqlAlchemy and Druid
|
|
"""
|
|
# TODO refactor into using a TBD Query object
|
|
qry_start_dttm = datetime.now()
|
|
|
|
inner_from_dttm = inner_from_dttm or from_dttm
|
|
inner_to_dttm = inner_to_dttm or to_dttm
|
|
|
|
# add tzinfo to native datetime with config
|
|
from_dttm = from_dttm.replace(tzinfo=config.get("DRUID_TZ"))
|
|
to_dttm = to_dttm.replace(tzinfo=config.get("DRUID_TZ"))
|
|
|
|
query_str = ""
|
|
aggregations = {
|
|
m.metric_name: m.json_obj
|
|
for m in self.metrics if m.metric_name in metrics
|
|
}
|
|
granularity = granularity or "all"
|
|
if granularity != "all":
|
|
granularity = utils.parse_human_timedelta(
|
|
granularity).total_seconds() * 1000
|
|
if not isinstance(granularity, string_types):
|
|
granularity = {"type": "duration", "duration": granularity}
|
|
origin = extras.get('druid_time_origin')
|
|
if origin:
|
|
dttm = utils.parse_human_datetime(origin)
|
|
granularity['origin'] = dttm.isoformat()
|
|
|
|
qry = dict(
|
|
datasource=self.datasource_name,
|
|
dimensions=groupby,
|
|
aggregations=aggregations,
|
|
granularity=granularity,
|
|
intervals=from_dttm.isoformat() + '/' + to_dttm.isoformat(),
|
|
)
|
|
filters = None
|
|
for col, op, eq in filter:
|
|
cond = None
|
|
if op == '==':
|
|
cond = Dimension(col) == eq
|
|
elif op == '!=':
|
|
cond = ~(Dimension(col) == eq)
|
|
elif op in ('in', 'not in'):
|
|
fields = []
|
|
splitted = eq.split(',')
|
|
if len(splitted) > 1:
|
|
for s in eq.split(','):
|
|
s = s.strip()
|
|
fields.append(Filter.build_filter(Dimension(col) == s))
|
|
cond = Filter(type="or", fields=fields)
|
|
else:
|
|
cond = Dimension(col) == eq
|
|
if op == 'not in':
|
|
cond = ~cond
|
|
if filters:
|
|
filters = Filter(type="and", fields=[
|
|
Filter.build_filter(cond),
|
|
Filter.build_filter(filters)
|
|
])
|
|
else:
|
|
filters = cond
|
|
|
|
if filters:
|
|
qry['filter'] = filters
|
|
|
|
client = self.cluster.get_pydruid_client()
|
|
orig_filters = filters
|
|
if timeseries_limit and is_timeseries:
|
|
# Limit on the number of timeseries, doing a two-phases query
|
|
pre_qry = deepcopy(qry)
|
|
pre_qry['granularity'] = "all"
|
|
pre_qry['limit_spec'] = {
|
|
"type": "default",
|
|
"limit": timeseries_limit,
|
|
'intervals': (
|
|
inner_from_dttm.isoformat() + '/' +
|
|
inner_to_dttm.isoformat()),
|
|
"columns": [{
|
|
"dimension": metrics[0] if metrics else self.metrics[0],
|
|
"direction": "descending",
|
|
}],
|
|
}
|
|
client.groupby(**pre_qry)
|
|
query_str += "// Two phase query\n// Phase 1\n"
|
|
query_str += json.dumps(client.query_dict, indent=2) + "\n"
|
|
query_str += "//\nPhase 2 (built based on phase one's results)\n"
|
|
df = client.export_pandas()
|
|
if df is not None and not df.empty:
|
|
dims = qry['dimensions']
|
|
filters = []
|
|
for _, row in df.iterrows():
|
|
fields = []
|
|
for dim in dims:
|
|
f = Filter.build_filter(Dimension(dim) == row[dim])
|
|
fields.append(f)
|
|
if len(fields) > 1:
|
|
filt = Filter(type="and", fields=fields)
|
|
filters.append(Filter.build_filter(filt))
|
|
elif fields:
|
|
filters.append(fields[0])
|
|
|
|
if filters:
|
|
ff = Filter(type="or", fields=filters)
|
|
if not orig_filters:
|
|
qry['filter'] = ff
|
|
else:
|
|
qry['filter'] = Filter(type="and", fields=[
|
|
Filter.build_filter(ff),
|
|
Filter.build_filter(orig_filters)])
|
|
qry['limit_spec'] = None
|
|
if row_limit:
|
|
qry['limit_spec'] = {
|
|
"type": "default",
|
|
"limit": row_limit,
|
|
"columns": [{
|
|
"dimension": metrics[0] if metrics else self.metrics[0],
|
|
"direction": "descending",
|
|
}],
|
|
}
|
|
client.groupby(**qry)
|
|
query_str += json.dumps(client.query_dict, indent=2)
|
|
df = client.export_pandas()
|
|
if df is None or df.size == 0:
|
|
raise Exception("No data was returned.")
|
|
|
|
if (
|
|
not is_timeseries and
|
|
granularity == "all" and
|
|
'timestamp' in df.columns):
|
|
del df['timestamp']
|
|
|
|
# Reordering columns
|
|
cols = []
|
|
if 'timestamp' in df.columns:
|
|
cols += ['timestamp']
|
|
cols += [col for col in groupby if col in df.columns]
|
|
cols += [col for col in metrics if col in df.columns]
|
|
cols += [col for col in df.columns if col not in cols]
|
|
df = df[cols]
|
|
return QueryResult(
|
|
df=df,
|
|
query=query_str,
|
|
duration=datetime.now() - qry_start_dttm)
|
|
|
|
|
|
class Log(Model):
|
|
|
|
"""ORM object used to log Caravel actions to the database"""
|
|
|
|
__tablename__ = 'logs'
|
|
|
|
id = Column(Integer, primary_key=True)
|
|
action = Column(String(512))
|
|
user_id = Column(Integer, ForeignKey('ab_user.id'))
|
|
dashboard_id = Column(Integer)
|
|
slice_id = Column(Integer)
|
|
user_id = Column(Integer, ForeignKey('ab_user.id'))
|
|
json = Column(Text)
|
|
user = relationship('User', backref='logs', foreign_keys=[user_id])
|
|
dttm = Column(DateTime, default=func.now())
|
|
dt = Column(Date, default=date.today())
|
|
|
|
@classmethod
|
|
def log_this(cls, f):
|
|
"""Decorator to log user actions"""
|
|
@functools.wraps(f)
|
|
def wrapper(*args, **kwargs):
|
|
user_id = None
|
|
if g.user:
|
|
user_id = g.user.id
|
|
d = request.args.to_dict()
|
|
d.update(kwargs)
|
|
slice_id = d.get('slice_id', 0)
|
|
slice_id = int(slice_id) if slice_id else 0
|
|
log = cls(
|
|
action=f.__name__,
|
|
json=json.dumps(d),
|
|
dashboard_id=d.get('dashboard_id') or None,
|
|
slice_id=slice_id,
|
|
user_id=user_id)
|
|
db.session.add(log)
|
|
db.session.commit()
|
|
return f(*args, **kwargs)
|
|
return wrapper
|
|
|
|
|
|
class DruidMetric(Model, AuditMixinNullable):
|
|
|
|
"""ORM object referencing Druid metrics for a datasource"""
|
|
|
|
__tablename__ = 'metrics'
|
|
id = Column(Integer, primary_key=True)
|
|
metric_name = Column(String(512))
|
|
verbose_name = Column(String(1024))
|
|
metric_type = Column(String(32))
|
|
datasource_name = Column(
|
|
String(250),
|
|
ForeignKey('datasources.datasource_name'))
|
|
# Setting enable_typechecks=False disables polymorphic inheritance.
|
|
datasource = relationship('DruidDatasource', backref='metrics',
|
|
enable_typechecks=False)
|
|
json = Column(Text)
|
|
description = Column(Text)
|
|
|
|
@property
|
|
def json_obj(self):
|
|
try:
|
|
obj = json.loads(self.json)
|
|
except Exception:
|
|
obj = {}
|
|
return obj
|
|
|
|
|
|
class DruidColumn(Model, AuditMixinNullable):
|
|
|
|
"""ORM model for storing Druid datasource column metadata"""
|
|
|
|
__tablename__ = 'columns'
|
|
id = Column(Integer, primary_key=True)
|
|
datasource_name = Column(
|
|
String(250),
|
|
ForeignKey('datasources.datasource_name'))
|
|
# Setting enable_typechecks=False disables polymorphic inheritance.
|
|
datasource = relationship('DruidDatasource', backref='columns',
|
|
enable_typechecks=False)
|
|
column_name = Column(String(256))
|
|
is_active = Column(Boolean, default=True)
|
|
type = Column(String(32))
|
|
groupby = Column(Boolean, default=False)
|
|
count_distinct = Column(Boolean, default=False)
|
|
sum = Column(Boolean, default=False)
|
|
max = Column(Boolean, default=False)
|
|
min = Column(Boolean, default=False)
|
|
filterable = Column(Boolean, default=False)
|
|
description = Column(Text)
|
|
|
|
def __repr__(self):
|
|
return self.column_name
|
|
|
|
@property
|
|
def isnum(self):
|
|
return self.type in ('LONG', 'DOUBLE', 'FLOAT')
|
|
|
|
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:
|
|
mt = 'count_distinct'
|
|
name = 'count_distinct__' + self.column_name
|
|
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()
|
|
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:
|
|
session.add(metric)
|
|
session.commit()
|
|
|
|
|
|
class FavStar(Model):
|
|
__tablename__ = 'favstar'
|
|
|
|
id = Column(Integer, primary_key=True)
|
|
user_id = Column(Integer, ForeignKey('ab_user.id'))
|
|
class_name = Column(String(50))
|
|
obj_id = Column(Integer)
|
|
dttm = Column(DateTime, default=func.now())
|