Hello all -
I am relatively new to using SQLAlchemy for more complex use cases. I am in
the process of creating a time series query, but I am unable to reference a
column by its alias at the top level of the query.
This is the query that I am trying to address that SQLAlchemy is currently
generating:
SELECT non_interval_query.metadata_value AS
non_interval_query_metadata_value,
coalesce(sum(non_interval_query.coalesce_2), 0) AS coalesce_1,
timestamp
FROM
(SELECT generate_series(date_trunc('day', date('2019-01-06T00:00:00+00:00'
)), date_trunc('day', date('2019-01-12T00:00:00+00:00')), '1 day') AS
timestamp) AS time_series
LEFT OUTER JOIN
(SELECT post_metadata_1.metadata_value AS post_metadata_1_metadata_value,
post_metadata_2.metadata_value AS post_metadata_2_metadata_value,
vw_post.created_at AS vw_post_created_at,
coalesce(count(DISTINCT vw_post.id), 0) AS coalesce_1
FROM vw_post
JOIN post_metadata AS post_metadata_1 ON post_metadata_1.post_id =
vw_post.id
JOIN post_metadata AS post_metadata_2 ON post_metadata_2.post_id =
vw_post.id
WHERE post_metadata_1.metadata_value IN ('<metadata_values>')
AND post_metadata_2.metadata_value IN ('<metadata_value>')
AND vw_post.created_at >= '2019-01-06T00:00:00+00:00'
AND vw_post.created_at <= '2019-01-12T00:00:00+00:00'
AND post_metadata_1.schema_uid = '<schema_uid>'
AND post_metadata_1.metadata_name = '<metadata_name>'
AND post_metadata_2.schema_uid = '<schema_uid>'
AND post_metadata_2.metadata_name = '<metadata_name>'
AND vw_post.license_id IN (<license_ids>)
GROUP BY vw_post.created_at,
post_metadata_1.metadata_value,
post_metadata_2.metadata_value,
vw_post.created_at) AS non_interval_query ON date_trunc('day',
created_at) = timestamp;
You'll notice that "non_interval_query.metadata_value AS
non_interval_query_metadata_value" specified at the beginning of the query
is ambiguous due to the 2 "metadata_value" selects in the
"non_interval_query" subquery. What I'm trying to do is have 2 selects at
the top level - one for "non_interval_query.post_metadata_1_metadata_value"
and one for "non_interval_query.post_metadata_2_metadata_value".
For reference, here is the code used to generate the above query:
def apply_date_group_by(self, session, query, range_gb_params):
field_name = self.db.get("column")
model = self._object.get("model")
if not field_name or not model:
raise ValueError("Invalid date group by")
gb_column = self._build_column()
interval = range_gb_params.get("interval")
interval_type = range_gb_params.get("interval_type")
time_series = func.generate_series(
func.date_trunc(interval_type, func.date(range_gb_params["start"])),
func.date_trunc(interval_type, func.date(range_gb_params["end"])),
interval,
).label("timestamp")
ts_column = column("timestamp")
time_series_query = session.query(time_series).subquery("time_series")
non_interval_query = query.subquery("non_interval_query")
# have to replace the original gb_column with the 'timestamp' column
# in order to properly merge the dataset into the time series dataset
non_gb_columns, gbs = self._prepare_non_gb_columns(
ts_column, gb_column, non_interval_query.columns
)
# construct query with correct position passed in from `range_gb_params`
query_position = range_gb_params.get("query_index_position", 0)
non_gb_columns.insert(query_position, ts_column)
date_gb_query = session.query(*non_gb_columns).select_from(
time_series_query.outerjoin(
non_interval_query,
func.date_trunc(interval_type, column(field_name)) == ts_column,
)
)
if gbs:
date_gb_query = date_gb_query.group_by(*gbs)
return date_gb_query.order_by(ts_column)
Any help on this would be greatly appreciated!
--
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The Python SQL Toolkit and Object Relational Mapper
http://www.sqlalchemy.org/
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