alexanderbianchi commented on code in PR #20821: URL: https://github.com/apache/datafusion/pull/20821#discussion_r2936982420
########## datafusion/substrait/src/logical_plan/consumer/expr/nested.rs: ########## @@ -0,0 +1,60 @@ +// Licensed to the Apache Software Foundation (ASF) under one +// or more contributor license agreements. See the NOTICE file +// distributed with this work for additional information +// regarding copyright ownership. The ASF licenses this file +// to you under the Apache License, Version 2.0 (the +// "License"); you may not use this file except in compliance +// with the License. You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, +// software distributed under the License is distributed on an +// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +// KIND, either express or implied. See the License for the +// specific language governing permissions and limitations +// under the License. + +use crate::logical_plan::consumer::SubstraitConsumer; +use crate::logical_plan::consumer::expr::from_substrait_rex; +use datafusion::common::{DFSchema, not_impl_err, substrait_err}; +use datafusion::execution::FunctionRegistry; +use datafusion::logical_expr::Expr; +use substrait::proto::expression::Nested; +use substrait::proto::expression::nested::NestedType; + +/// Convert a Substrait Nested expression (List, Struct, Map constructors) to a DataFusion Expr. +/// +/// Nested::List is converted to a `make_array(...)` scalar function call. +pub async fn from_nested( + consumer: &impl SubstraitConsumer, + nested: &Nested, + input_schema: &DFSchema, +) -> datafusion::common::Result<Expr> { + let Some(nested_type) = nested.nested_type.as_ref() else { + return substrait_err!("Nested expression must set nested_type"); + }; + + match nested_type { + NestedType::List(list) => { + let mut args = Vec::with_capacity(list.values.len()); + for expr in &list.values { + args.push(from_substrait_rex(consumer, expr, input_schema).await?); + } + + let make_array_udf = consumer.get_function_registry().udf("make_array")?; + Ok(Expr::ScalarFunction( + datafusion::logical_expr::expr::ScalarFunction::new_udf( + make_array_udf.to_owned(), Review Comment: This will fail for empty arrays, as `make_array` fails on empty arrays. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
