byteink commented on issue #6492:
URL:
https://github.com/apache/arrow-datafusion/issues/6492#issuecomment-1573076672
Another similar case of failure:
```shell
DataFusion CLI v25.0.0
❯ create table t (a int not null);
0 rows in set. Query took 0.004 seconds.
❯ insert into t values(1);
Error during planning: Inserting query must have the same schema with the
table.
```
Two non-matching schemas are：
**input schema**: Schema { fields: [Field { name: "a", data_type: Int32,
nullable: **true**, dict_id: 0, dict_is_ordered: false, metadata: {} }],
metadata: {} }
**table schema**: Schema { fields: [Field { name: "a", data_type: Int32,
nullable: **false**, dict_id: 0, dict_is_ordered: false, metadata: {} }],
metadata: {} }
Can we ignore the schema part of batches and only focus on the actual data
part?
And use the function `RecordBatch::try_new` to check if the data in the
RecordBatch matches the schema of the target table.
```rust
impl MemTable {
/// Create a new in-memory table from the provided schema and record
batches
pub fn try_new(schema: SchemaRef, partitions: Vec<Vec<RecordBatch>>) ->
Result<Self> {
let mut batches = Vec::with_capacity(partitions.len());
for partition in partitions {
let new_partition = partition
.iter()
.map(|batch| {
RecordBatch::try_new(schema.clone(),
batch.columns().to_vec())
.map_err(DataFusionError::ArrowError)
})
.collect::<Result<Vec<_>>>()?;
batches.push(Arc::new(RwLock::new(new_partition)));
}
Ok(Self { schema, batches })
}
}
```
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