lvheyang opened a new issue #699:
URL: https://github.com/apache/arrow-datafusion/issues/699
**Describe the bug**
Math function such as sqrt() / sin() ... does not support f32 type.
**To Reproduce**
Example Code
```
use std::sync::Arc;
use datafusion::arrow::array::{Float32Array, Float64Array};
use datafusion::arrow::datatypes::{DataType, Field, Schema};
use datafusion::arrow::record_batch::RecordBatch;
use datafusion::arrow::util::pretty;
use datafusion::datasource::MemTable;
use datafusion::error::Result;
use datafusion::prelude::*;
#[tokio::main]
async fn main() -> Result<()> {
// define a schema.
let schema = Arc::new(Schema::new(vec![
Field::new("f64", DataType::Float64, false),
Field::new("f32", DataType::Float32, false),
]));
// define data.
let batch = RecordBatch::try_new(
schema.clone(),
vec![
Arc::new(Float64Array::from(vec![1.0, 2.0, 3.0, 4.0, 5.0])),
Arc::new(Float32Array::from(vec![1.0, 2.0, 3.0, 4.0, 5.0])),
],
)?;
let mut ctx = ExecutionContext::new();
let provider = MemTable::try_new(schema, vec![vec![batch]])?;
ctx.register_table("t", Arc::new(provider))?;
// construct an expression corresponding to "SELECT sqrt(f32) FROM t" in
SQL
let df = ctx.sql("SELECT sqrt(f32) FROM t").unwrap(); // failed
// let df = ctx.sql("SELECT sqrt(f64) FROM t").unwrap(); // success
// execute
let results = df.collect().await?;
// print the results
pretty::print_batches(&results)?;
Ok(())
}
```
The code will panic, and the error output is
```
Error: ArrowError(InvalidArgumentError("column types must match schema
types, expected Float64 but found Float32 at column index 0"))
```
**Expected behavior**
The code should not panic
**Additional context**
Possible reason:
in datafusion/src/physical_plan/functions.rs
The return type of math builtin functions is Float64
```
BuiltinScalarFunction::Abs
| BuiltinScalarFunction::Acos
| ...
| BuiltinScalarFunction::Sqrt
| BuiltinScalarFunction::Tan
| BuiltinScalarFunction::Trunc => Ok(DataType::Float64),
```
But when compute the math function in
datafusion/src/physical_plan/math_expressions.rs, when compute f32 array, it
will return Float32Array
```
macro_rules! unary_primitive_array_op {
($VALUE:expr, $NAME:expr, $FUNC:ident) => {{
match ($VALUE) {
ColumnarValue::Array(array) => match array.data_type() {
DataType::Float32 => {
let result = downcast_compute_op!(array, $NAME, $FUNC,
Float32Array);
Ok(ColumnarValue::Array(result?))
}
DataType::Float64 => {
let result = downcast_compute_op!(array, $NAME, $FUNC,
Float64Array);
Ok(ColumnarValue::Array(result?))
}
other => Err(DataFusionError::Internal(format!(
"Unsupported data type {:?} for function {}",
other, $NAME,
))),
},
...
```
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