The reason why I iterated over .c._all_columns was because it shows the
references to the 2 "metadata_value" columns, whereas selectable.c only
references 1.
For example, selectable.c shows the following:
(Pdb++) list(query.c)
[Column('metadata_value', VARCHAR(length=255), table=<non_interval_query>),
Column('created_at', TIMESTAMP(), table=<non_interval_query>), <sqlalchemy.
sql.elements.ColumnClause at 0x7f15e1f6fef0; %(139731962070520 coalesce)s>]
Enter code here...
selectable.c._all_columns shows the following:
(Pdb++) query.c._all_columns
[Column('metadata_value', VARCHAR(length=255), table=<non_interval_query>),
Column('metadata_value', VARCHAR(length=255), table=<non_interval_query>),
Column('created_at', TIMESTAMP(), table=<non_interval_query>), <sqlalchemy.
sql.elements.ColumnClause at 0x7f15e1f6fef0; %(139731962070520 coalesce)s>]
Enter code here...
On Thursday, February 7, 2019 at 12:53:51 PM UTC-5, Mike Bayer wrote:
>
> just as a note, don't access .c._all_columns, just iterate over
> selectable.c
>
> On Thu, Feb 7, 2019 at 10:45 AM Ian Miller <[email protected]
> <javascript:>> wrote:
> >
> > Hello Mike,
> >
> > Thank you for your response! I have currently constructed the ORM
> implementation that you suggested in your response. Here's the code:
> >
> > def _rebuild_non_interval_query_for_group_by(self, session, query):
> > from sqlalchemy import table, column, select
> > from sqlalchemy.orm import aliased
> > from collections import defaultdict, OrderedDict
> >
> > post_metadata = table(
> > "post_metadata", column("post_id"), column("metadata_value")
> > )
> > campaign_metadata = table(
> > "campaign_metadata", column("campaign_id"),
> column("metadata_value")
> > )
> > asset_metadata = table(
> > "asset_metadata", column("asset_id"), column("metadata_value")
> > )
> >
> > vw_asset = table("vw_asset", column("id"))
> > vw_campaign = table("vw_campaign", column("id"))
> > vw_post = table("vw_post", column("id"))
> >
> > METADATA_PRIMARY_TABLE_MAP = {
> > asset_metadata.name: vw_asset,
> > campaign_metadata.name: vw_campaign,
> > post_metadata.name: vw_post,
> > }
> >
> > METADATA_NAME_TABLE_MAP = {
> > asset_metadata.name: asset_metadata,
> > campaign_metadata.name: campaign_metadata,
> > post_metadata.name: post_metadata,
> > }
> >
> > primary_tables = set()
> > metadata_columns_count = defaultdict(int)
> > metadata_alias = OrderedDict()
> > columns = []
> > for c in query.c._all_columns:
> > if c.name == "metadata_value":
> > parent_column = list(c.base_columns)[0]
> > table = parent_column.table
> > primary_tables.add(METADATA_PRIMARY_TABLE_MAP[table.name])
> > metadata_columns_count[METADATA_NAME_TABLE_MAP[table.name]]
> += 1
> > alias_number =
> metadata_columns_count[METADATA_NAME_TABLE_MAP[table.name]]
> > alias_name = "{}_{}".format(table.name, alias_number)
> > alias = aliased(parent_column.table, alias_name)
> > metadata_alias[alias_name] = alias
> > column = alias.c.metadata_value.label(
> > "{}_{}_{}".format(table.name, alias_number,
> "metadata_value")
> > )
> > columns.append(column)
> > else:
> > columns.append(c)
> >
> > # start constructing query
> > non_interval_query =
> session.query(*columns).select_from(*primary_tables)
> >
> > for alias_name, alias in metadata_alias.items():
> > object_type = self._get_object_type_from_metadata_name(
> alias.original.name)
> > non_interval_query = (
> > non_interval_query
> > .join(
> > alias,
> > getattr(alias.c, "{}_id".format(object_type)) ==
> METADATA_PRIMARY_TABLE_MAP[alias.original.name].c.id
> > )
> > )
> >
> > non_interval_query =
> non_interval_query.subquery("non_interval_query")
> >
> > return non_interval_query
> >
> >
> >
> > The "metadata_alias" values are [('post_metadata_1", alias),
> ('post_metadata_2', alias)] - the alias correspond to the post_metadata_1
> and post_metadata_2 alias in your example. However, when I reference these
> in the join, the aliased table names are not "post_metadata_1" or
> "post_metadata_2" - they're "post_metadata_3" and "post_metadata_4". I'm
> unable to figure out why there's a new join seemingly created instead of
> referencing the aliased tables that were passed in.
> >
> > Here's the query that the above generates:
> >
> > SELECT post_metadata_1.metadata_value AS post_metadata_1_metadata_value,
> > post_metadata_2.metadata_value AS post_metadata_2_metadata_value,
> > non_interval_query.created_at,
> > non_interval_query.coalesce_1 \nFROM
> > (SELECT post_metadata_3.metadata_value AS metadata_value,
> post_metadata_4.metadata_value AS metadata_value, vw_post.created_at AS
> created_at, coalesce(count(DISTINCT vw_post.id), :coalesce_2) AS
> coalesce_1 \nFROM vw_post
> > JOIN post_metadata AS post_metadata_3 ON post_metadata_3.post_id =
> vw_post.id
> > JOIN post_metadata AS post_metadata_4 ON post_metadata_4.post_id =
> vw_post.id \nWHERE post_metadata_3.metadata_value IN (:metadata_value_1,
> :metadata_value_2)
> > AND post_metadata_4.metadata_value IN (:metadata_value_3,
> :metadata_value_4)
> > AND vw_post.created_at >= :created_at_1
> > AND vw_post.created_at <= :created_at_2
> > AND post_metadata_3.schema_uid = :schema_uid_1
> > AND post_metadata_3.metadata_name = :metadata_name_1
> > AND post_metadata_4.schema_uid = :schema_uid_2
> > AND post_metadata_4.metadata_name = :metadata_name_2
> > AND vw_post.license_id IN (:license_id_1, :license_id_2)
> > GROUP BY vw_post.created_at, post_metadata_3.metadata_value,
> post_metadata_4.metadata_value, vw_post.created_at) AS non_interval_query,
> > 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;
> >
> >
> >
> >
> > 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!
> >
> >
> > --
> > SQLAlchemy -
> > The Python SQL Toolkit and Object Relational Mapper
> >
> > http://www.sqlalchemy.org/
> >
> > To post example code, please provide an MCVE: Minimal, Complete, and
> Verifiable Example. See http://stackoverflow.com/help/mcve for a full
> description.
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--
SQLAlchemy -
The Python SQL Toolkit and Object Relational Mapper
http://www.sqlalchemy.org/
To post example code, please provide an MCVE: Minimal, Complete, and Verifiable
Example. See http://stackoverflow.com/help/mcve for a full description.
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