Ok, with the DAL I solved it in the following way and did the join
"manually":
# get last val_date for each prop
maxdate = db.prop_val.val_date.max().with_alias('max_val_date')
rows1 = db().select(db.prop_val.prop_id.with_alias('prop_id'), maxdate,
groupby=db.prop_val.prop_id)
# get name, price, last val_date and amount for each prop
result = []
for row in rows1:
query = (db.prop_val.val_date == row.max_val_date) & \
(db.prop_val.prop_id == row.prop_id) & \
(db.prop_val.prop_id == db.prop.id)
rows = db(query).select(db.prop.name.with_alias('name'),
db.prop.price.with_alias('price'),
db.prop_val.val_date.with_alias('val_date'),
db.prop_val.amount.with_alias('amount'))
result.extend(rows)
But I think this method will become cumbersome if the analysis is a little
bit more complicated and more aggregates have to be joined together.
stex
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