Ah - this occurs because the non-metadata_value columns added in from "query
.c._all_columns" are still referencing the original query. I need to figure
out how to rebuild those columns as well so that they correctly reference
the clauses in the new query.
On Tuesday, February 5, 2019 at 11:51:25 AM UTC-5, Ian Miller wrote:
>
> 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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