Generally, you should use clustering columns to model nested structures, unless they really are simply list/map structures.
But, first, as with all data modeling in Cassandra, start by looking at how you intend to query the data. Do you need to query individual addresses, email addresses, streets, etc.? If so, separate rows for each address is a better way to go. On the flip side, if the full address is just a blob that you will interpret in the app, a frozen UDT or JSON blob is a reasonable way to go. In any case, tell us about your query needs first. -- Jack Krupansky On Thu, Jan 28, 2016 at 10:29 AM, Carlos Alonso <i...@mrcalonso.com> wrote: > Hi Ahmed, > > I think modelling them as a map where you can 'label' your emails or > addresses sounds like a good option. > > More info here: > https://docs.datastax.com/en/cql/3.1/cql/cql_using/use_map_t.html > > Regards > > Carlos Alonso | Software Engineer | @calonso <https://twitter.com/calonso> > > On 28 January 2016 at 13:36, Ryan Svihla <r...@foundev.pro> wrote: > >> Ahmed, >> >> Just using text and serializing as Json is the easy way and a common >> approach. >> >> However, this list is for Cassandra commiter discussion, please be so >> kind as to use the regular user list for data modeling questions or for any >> future responses to this email thread. >> >> >> Regards, >> Ryan Svihla >> >> On Jan 28, 2016, at 7:28 AM, Ahmed Eljami <ahmed.elj...@gmail.com> wrote: >> >> Hi, >> >> I need your help for modeling a nested collection with cassanrda2.0 (UDT >> no, >> no fozen) >> >> My users table contains emails by type, each type of email contains >> multiple >> emails. >> >> Example: >> Type: pro. emails: {a...@mail.com, b...@mail.com ...} >> >> Type: private. emails: {c...@mail.com, d...@mail.com} >> ..... >> >> The user table also contains addresses, address type with fields. >> >> Example: >> >> Type: Pro. address {Street= aaa, number = 123, apartment = bbb} >> >> Type: Private. address {Street = bbb, number = 123, apartment = kkk } >> >> I am looking for a solution to store all these columns in one table. >> >> Thank you. >> >> >
