hengfeiyang commented on PR #3700:
URL:
https://github.com/apache/arrow-datafusion/pull/3700#issuecomment-1271752120
@alamb i tested with #3733 , it looks `with_column` still can't work.
i tested use config:
Cargo.toml
```
datafusion = { git = "https://github.com/apache/arrow-datafusion"; }
```
with the example code:
```
use std::sync::Arc;
use datafusion::arrow::array::Int32Array;
use datafusion::arrow::datatypes::{DataType, Field, Schema};
use datafusion::arrow::record_batch::RecordBatch;
use datafusion::datasource::MemTable;
use datafusion::error::Result;
use datafusion::from_slice::FromSlice;
use datafusion::prelude::{col, lit, SessionContext};
/// This example demonstrates how to use the DataFrame API against in-memory
data.
#[tokio::main]
async fn main() -> Result<()> {
// define a schema.
let schema = Arc::new(Schema::new(vec![Field::new("f.c",
DataType::Int32, false)]));
// define data.
let batch = RecordBatch::try_new(
schema.clone(),
vec![Arc::new(Int32Array::from_slice([1, 10, 10, 100]))],
)?;
// declare a new context. In spark API, this corresponds to a new spark
SQLsession
let ctx = SessionContext::new();
// declare a table in memory. In spark API, this corresponds to
createDataFrame(...).
let provider = MemTable::try_new(schema.clone(), vec![vec![batch]])?;
ctx.register_table("t", Arc::new(provider))?;
let df = ctx.table("t")?;
// construct an expression corresponding to "SELECT * FROM t WHERE f.c =
10" in SQL
let filter = col("f.c").eq(lit(10));
let df = df.filter(filter)?;
// print the results
df.show().await?;
Ok(())
}
```
Result:
```
Error: SchemaError(FieldNotFound { qualifier: Some("f"), name: "c",
valid_fields: Some(["t.f.c"]) })
```
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