Method write_table

datafusion/core/src/dataframe/mod.rs:1981–2018

Execute this `DataFrame` and write the results to `table_name`. Returns a single [RecordBatch] containing a single column and row representing the count of total rows written. Unlike most other `DataFrame` methods, this method executes eagerly. Data is written to the table using the [`TableProvider::insert_into`] method. This is the same underlying implementation used by SQL `INSERT INTO` statem

(
        self,
        table_name: &str,
        write_options: DataFrameWriteOptions,
    )

    /// method. This is the same underlying implementation used by SQL `INSERT
    /// INTO` statements.
    pub async fn write_table(
        self,
        table_name: &str,
        write_options: DataFrameWriteOptions,
    ) -> Result<Vec<RecordBatch>, DataFusionError> {
        let plan = if write_options.sort_by.is_empty() {
            self.plan
        } else {
            LogicalPlanBuilder::from(self.plan)
                .sort(write_options.sort_by)?
                .build()?
        };

        let table_ref: TableReference = table_name.into();
        let table_schema = self.session_state.schema_for_ref(table_ref.clone())?;
        let target = match table_schema.table(table_ref.table()).await? {
            Some(ref provider) => Ok(Arc::clone(provider)),
            _ => plan_err!("No table named '{table_name}'"),
        }?;

        let target = Arc::new(DefaultTableSource::new(target));

        let plan = LogicalPlanBuilder::insert_into(
            plan,
            table_ref,
            target,
            write_options.insert_op,
        )?
        .build()?;

        DataFrame {
            session_state: self.session_state,
            plan,
            projection_requires_validation: self.projection_requires_validation,
        }
        .collect()
        .await
    }

    /// Execute the `DataFrame` and write the results to CSV file(s).
    ///