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Re: [ANNOUNCEMENT] [SQL] [BEAM-6133] Support for user defined table functions (UDTF)

OK great. I happen to have recently read that bit of SQL 2016 so that puts it in context for me very nicely.


On Fri, Dec 14, 2018 at 3:58 AM Gleb Kanterov <gleb@xxxxxxxxxxx> wrote:
Kenn, I don't have a copy of a recent SQL standard to confirm what I'm saying. To my knowledge, initially, there was a concept of a table function. Table functions should have a static type that doesn't depend on supplied arguments. In ANSI SQL 2016, there is a concept of polymorphic table functions, that can infer types depending on provided arguments. Both TableFunction and TableMacro in Calcite are polymorphic table functions, and the difference between TableFunction and TableMacro is internal to Calcite.


On Fri, Dec 14, 2018 at 4:26 AM Kenneth Knowles <kenn@xxxxxxxxxx> wrote:
Sorry for the slow reply & review. Having UDTF support in Beam SQL is extremely useful. Are both table functions and table macros part of "standard" SQL or is this a distinction between different Calcite concepts?


On Wed, Nov 28, 2018 at 10:36 AM Gleb Kanterov <gleb@xxxxxxxxxxx> wrote:
At the moment we support only ScalarFunction UDF, it's functions that operate on row fields. In Calcite, there are 3 kinds of UDFs: aggregate functions (that we already support), table macro and table functions. The difference between table functions and macros is that macros expand to relations, and table functions can refer to anything queryable, e.g., enumerables. But in the case of Beam SQL, given everything translates to PTransforms, only table macros are relevant.

UDTF are in a way similar to external tables but don't require to specify a schema explicitly. Instead, they can derive schema based on arguments. One of the use-cases would be querying ranges of dataset partitions using a helper function like: 

SELECT COUNT(*) FROM table(readAvro(id => 'dataset', start => '2017-01-01', end => '2018-01-01'))

With BEAM-6133 (apache/beam/#7141) we would have support for UDTF in Beam SQL.