DataFrame API: allow aggregate functions in `select()`

[Jefffrey]

Is your feature request related to a problem or challenge?

Be able to run something like this:

use datafusion::error::Result;
use datafusion::functions_aggregate::expr_fn::approx_distinct;
use datafusion::prelude::*;

#[tokio::main]
async fn main() -> Result<()> {
    let ctx = SessionContext::new();

    let testdata = datafusion::test_util::arrow_test_data();
    ctx.register_csv(
        "aggregate_test_100",
        format!("{testdata}/csv/aggregate_test_100.csv"),
        CsvReadOptions::default().has_header(true),
    )
    .await?;

    ctx.table("aggregate_test_100")
        .await?
        // Run aggregate in select() without needing to do via aggregate()
        .select(vec![
            approx_distinct(col("c9")).alias("count_c9"),
            approx_distinct(cast(col("c9"), arrow_schema::DataType::Utf8View))
                .alias("count_c9_str"),
        ])?
        .show()
        .await?;

    Ok(())
}

Currently failing with:

Error: NotImplemented("Physical plan does not support logical expression AggregateFunction(AggregateFunction { func: AggregateUDF { inner: ApproxDistinct { name: \"approx_distinct\", signature: Signature { type_signature: Any(1), volatility: Immutable } } }, params: AggregateFunctionParams { args: [Column(Column { relation: Some(Bare { table: \"aggregate_test_100\" }), name: \"c9\" })], distinct: false, filter: None, order_by: [], null_treatment: None } })")

Describe the solution you'd like

If using aggregate via select() then assume no group by.

Describe alternatives you've considered

No response

Additional context

No response

[umangPokhriyall]

take