You can create an Iceberg table with required field, for example: create table test_table (id bigint not null, data string) using iceberg
However you can not change the optional field to required after creation. See this issue for more details: https://github.com/apache/iceberg/issues/3617 Manu Zhang <owenzhang1...@gmail.com> 于2024年1月11日周四 10:08写道： > It looks like there's no way to explicitly add a required column in DDL. > Any suggestions? > > Much appreciated > Manu > > On Tue, Jan 9, 2024 at 3:37 PM Manu Zhang <owenzhang1...@gmail.com> wrote: > >> Thanks Peter and Ryan for the info. >> >> As identifier fields need to be "required", how can I alter an optional >> column to be required in Spark SQL? >> >> Thanks, >> Manu >> >> On Fri, Jan 5, 2024 at 12:50 AM Ryan Blue <b...@tabular.io> wrote: >> >>> You can set the primary key fields in Spark using `ALTER TABLE`: >>> >>> `ALTER TABLE t SET IDENTIFIER FIELDS id` >>> >>> Spark doesn't support any primary key syntax, so you have to do this as >>> a separate step. >>> >>> On Thu, Jan 4, 2024 at 8:46 AM Péter Váry <peter.vary.apa...@gmail.com> >>> wrote: >>> >>>> Hi Manu, >>>> >>>> The Iceberg Schema defines `identifierFieldIds` method [1], and Flink >>>> uses that as the primary key. >>>> Are you saying there is no way to set it in Spark and Trino? >>>> >>>> Thanks, >>>> Peter >>>> >>>> [1] >>>> https://github.com/apache/iceberg/blob/9a00f7477dedac4501fb2de9e1e6d7aa83dc20b7/api/src/main/java/org/apache/iceberg/Schema.java#L280 >>>> >>>> Manu Zhang <owenzhang1...@gmail.com> ezt írta (időpont: 2024. jan. 4., >>>> Cs, 16:45): >>>> >>>>> Hi all, >>>>> >>>>> Currently, we support upserting a Flink created table with Flink SQL >>>>> where primary keys are required as equality fields. They are not required >>>>> in Java API. >>>>> >>>>> However, if the table is created by Spark, where there's no primary >>>>> key, we cannot upsert with Flink SQL. Hence, I proposed >>>>> https://github.com/apache/iceberg/pull/8195 to support specifying >>>>> equality columns with Flink SQL write options. >>>>> >>>>> @pvary <https://github.com/pvary> suggested it would be better to >>>>> support primary keys in Spark, Trino, etc. Since these engines don't have >>>>> primary keys in their table definitions, a workaround is to put primary >>>>> key >>>>> columns in table properties. Maybe there are other options I've missed. >>>>> >>>>> Flink SQL sinking to Spark tables for analysis is a typical pipeline >>>>> in our datalake. I'd like to hear your thoughts on best supporting this >>>>> case. >>>>> >>>>> Happy New Year! >>>>> Manu >>>>> >>>> >>> >>> -- >>> Ryan Blue >>> Tabular >>> >>
