LuQQiu opened a new issue, #15038:
URL: https://github.com/apache/datafusion/issues/15038
### Describe the bug
Executing `array_has_any(column_name, [])` results in an error:
```
ArrowError(InvalidArgumentError("RowConverter column schema mismatch,
expected Utf8 got Int64"), None)
```
The error message is misleading and does not clearly indicate that an empty
array might be an invalid or unsupported input. The issue could be improved by
either:
- Providing a more meaningful error message that explicitly states that an
empty array is not a valid input.
- Handling the query more gracefully, ensuring that an empty array input
does not cause a type mismatch in schema conversion.
Can reproduce the issue with the following script:
datafusion version "44.0"
```
use std::sync::Arc;
use datafusion::arrow::array::{Int32Array, StringArray, ArrayRef, ListArray};
use datafusion::arrow::datatypes::{DataType, Field, Schema};
use datafusion::arrow::record_batch::RecordBatch;
use datafusion::arrow::buffer::OffsetBuffer;
use datafusion::datasource::MemTable;
use datafusion::error::Result;
use datafusion::prelude::*;
#[tokio::main]
async fn main() -> Result<()> {
// Create a simple datafusion table
let ctx = SessionContext::new();
let schema = Arc::new(Schema::new(vec![
Field::new("id", DataType::Int32, false),
Field::new("taxonomy", DataType::List(Arc::new(Field::new(
"item",
DataType::Utf8,
true,
))), false),
]));
let id_array = Arc::new(Int32Array::from(vec![1, 2, 3]));
let values = Arc::new(StringArray::from(vec![
"category_1", "category_2", // For id=1
"category_3", // For id=2
"category_4" // For id=3
]));
let offsets = OffsetBuffer::new(vec![0, 2, 3, 4].into());
let field = Arc::new(Field::new("item", DataType::Utf8, true));
let taxonomy_array = Arc::new(ListArray::new(field, offsets, values,
None));
let batch = RecordBatch::try_new(
schema.clone(),
vec![id_array, taxonomy_array],
)?;
let partitions = vec![vec![batch]];
let table = MemTable::try_new(schema, partitions)?;
ctx.register_table("test_table", Arc::new(table))?;
println!("Original data:");
let df = ctx.table("test_table").await?;
df.show().await?;
// Execute the problematic query with empty array
println!("\nExecuting filter with empty array:");
let query = "SELECT * FROM test_table WHERE array_has_any(taxonomy, [])";
// print
// Error: ArrowError(InvalidArgumentError("RowConverter column schema
mismatch, expected Utf8 got Int64"), None)
ctx.sql(query).await?.show().await?;
Ok(())
}
```
### To Reproduce
_No response_
### Expected behavior
_No response_
### Additional context
_No response_
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