select multiple columns in a single Expr

Is your feature request related to a problem or challenge?

I want to create a udf that can select multiple functions at once, such as a COLUMNS(<regex>) function.

select COLUMNS('number\d+') from my_table.

Currently this is not possible due to the fact that udfs can only ever output a single Expr.

Describe the solution you'd like

Since it would be quite a massive overhaul to refactor all of the planning and udf logic to return Vec<Expr>, I propose adding a new variant to Expr.

Expr::Columns(Vec<Column>).

This seems like the least invasive way to support selecting multiple columns in a single expr.

Describe alternatives you've considered

I'm open for alternatives, but I am not aware of any.

Additional context

Polars has this variant in their Expr

https://github.com/pola-rs/polars/blob/9fec2ecb6d4295969e1d155b386ee82db08745a1/crates/polars-plan/src/dsl/expr.rs#L72

It looks good to me, and we can gradually deprecate single column in the long-term

@universalmind303

@universalmind303 are you already working on this?

@universalmind303

@universalmind303 are you already working on this?

no, feel free to go ahead and work on it if you'd like.

This would require also modifying the protobuf definitions, are we ok with it?

How about returning DataType::Struct or DataType::List or DataType::FixedSizeList?

My current wip has a struct since it supports different data types and field names, can a List work as well?

My current wip has a struct since it supports different data types and field names, can a List work as well?

No, you are right, a List can't really support multiple different types

@universalmind303

@universalmind303 I think it would be interesting to test it, do you have an example / have you written the UDF?

I wonder if struct(col1, col2) or named_struct('a', col1, 'b', col2) would work for your usecase 🤔

> select struct(column1, column2) from abc;
+---------------------------------+
| struct(abc.column1,abc.column2) |
+---------------------------------+
| {c0: 1, c1: 2}                  |
| {c0: 4, c1: 5}                  |
+---------------------------------+
2 row(s) fetched. 
Elapsed 0.004 seconds.

that works, but isn't this unrelated to this change? I suppose it was working before too...

@alamb

@alamb by the way, how does the struct udf works? I am not sure I understand how this select only a subset of the fields, does Datafusion drop from the resulting dataset the fields that are not in the return_type ? https://github.com/apache/datafusion/blob/main/datafusion/functions/src/core/struct.rs#L97

@alamb

@alamb by the way, how does the struct udf works?

I think https://datafusion.apache.org/user-guide/sql/scalar_functions.html#struct has some pretty good examples

Apologies I wasn't precise in my question. The code of the struct udf doesn't explicitly drop fields but returns all of them.

How does the selection happens ?

How does the selection happens ?

I think you can select with something like my_struct_col['foo'] which returns the 'foo' field.

However now re-reading this ticket, I think it would be possible to create a user defined function like COLUMN by Implemening return_type_from_exprs to
🤔

How does the selection happens ?

I think you can select with something like my_struct_col['foo'] which returns the 'foo' field.

However now re-reading this ticket, I think it would be possible to create a user defined function like COLUMN by Implemening return_type_from_exprs to 🤔

What I was trying to say is that looking at that UDF isn't clear for me how the other fields are dropped. It seems that Datafusion performs an intersection between the field names returned by the return type and the ones returned by array_struct ?

FWIW, #10102 seems related as multi selection could be implemented via struct and unnest.

@edmondop

How does the selection happens ?

I think you can select with something like my_struct_col['foo'] which returns the 'foo' field.
However now re-reading this ticket, I think it would be possible to create a user defined function like COLUMN by Implemening return_type_from_exprs to 🤔

What I was trying to say is that looking at that UDF isn't clear for me how the other fields are dropped. It seems that Datafusion performs an intersection between the field names returned by the return type and the ones returned by array_struct ?

@edmondop
By default the column name is named c0, c1 ... which defined in array_struct, so in return_type we also find the associated column with name c0, c1 ...

how the other fields are dropped

I don't think we drop any field in struct.

One of the example can be

statement ok
create table t(a1 int, a2 float) as values(1, 1.2), (2, 2.4);

query IR
select a1, a2 from t;
----
1 1.2
2 2.4

// make this works
query IR
select columns(a1, a2) from t;
----
1 1.2
2 2.4

I want to create a udf that can select multiple functions at once, such as a COLUMNS() function.

select COLUMNS('number\d+') from my_table.

looking at the struct UDF, it seems that it only receives the columns that are passed to function invocation and doesn't have access to other columns, i.e. in the struct udf, all columns are returned as a struct, which suggests that the engine only pass a subset of the available columns

However, in the case of COLUMNS('number\d+'), you need to have all the columns, and only return few of them from the function. In my understanding neither udf nor udaf or udwf from what I have seen. We would need maybe a fourth type of udf something like udgf which is invoked on all the columns of a logical plan?

However, in the case of COLUMNS('number\d+'), you need to have all the columns, and only return few of them from the function

I agree, we can't get all the columns by the current design of function, it is quite challenging than I thought 🤔. We expect to build up a projection plan given the syntax columns(..). The function mentioned here is similar to unnest, it is more like a table function. Therefore, I think we need a user-defined table function that we can define the returned Expr given the function we parsed in the parser.

The difference behaviour in parser (datafusion/sql) between these.

UDF/UDAF/UDWF: returns Expr::ScalarFunction / Expr::AggregateFunction / Expr::WindowFunction respectively
Unnest: returns Expr::Unnest
Columns(regex): returns Expr::Columns(Vec<Column>)
UDTF (user-defined table function): returns Expr

To make the mentioned function possible, we don;t even need to introduce Expr::Columns, but returns Vec<Expr> for sql_to_expr.

datafusion/datafusion/sql/src/select.rs

Lines 449 to 457 in 7535d93

    
           SelectItem::UnnamedExpr(expr) => { 
        
               let expr = self.sql_to_expr(expr, plan.schema(), planner_context)?; 
        
               let col = normalize_col_with_schemas_and_ambiguity_check( 
        
                   expr, 
        
                   &[&[plan.schema()]], 
        
                   &plan.using_columns()?, 
        
               )?; 
        
               Ok(vec![col]) 
        
           }

@jayzhan211

@jayzhan211 that function already returns a Vec<Expr>, or am I missing something? Do we still need to have udtf?

@jayzhan211

@jayzhan211 that function already returns a Vec, or am I missing something? Do we still need to have udtf?

sql_to_expr returns Result<Expr>, we can extend it to Result<Vec<Expr>>. Which function are you mentioning?

I didn't find equivalent behavior in postgres. I'm not sure should we support this kind of returns subset of columns based on column name matching

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select multiple columns in a single `Expr` #10102

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	SelectItem::UnnamedExpr(expr) => {
	let expr = self.sql_to_expr(expr, plan.schema(), planner_context)?;
	let col = normalize_col_with_schemas_and_ambiguity_check(
	expr,
	&[&[plan.schema()]],
	&plan.using_columns()?,
	)?;
	Ok(vec![col])
	}

select multiple columns in a single Expr #10102

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Is your feature request related to a problem or challenge?

Describe the solution you'd like

Describe alternatives you've considered

Additional context

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jayzhan211 commented on Apr 19, 2024

edmondop commented on Apr 20, 2024

universalmind303 commented on Apr 21, 2024

edmondop commented on Apr 22, 2024

alamb commented on Apr 23, 2024

edmondop commented on Apr 23, 2024

alamb commented on Apr 24, 2024

edmondop commented on Apr 24, 2024

alamb commented on Apr 24, 2024

edmondop commented on Apr 25, 2024

edmondop commented on Apr 25, 2024

alamb commented on Apr 25, 2024

edmondop commented on Apr 25, 2024

alamb commented on Apr 25, 2024

edmondop commented on Apr 27, 2024

universalmind303 commented on Apr 29, 2024

jayzhan211 commented on May 8, 2024

edmondop commented on May 16, 2024

jayzhan211 commented on May 16, 2024

edmondop commented on May 16, 2024

jayzhan211 commented on May 17, 2024

jayzhan211 commented on May 19, 2024

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select multiple columns in a single `Expr` #10102