Function test_insert_into_checking

datafusion/core/tests/dataframe/mod.rs:6376–6427

()

// Test inserting into checking.
#[tokio::test]
async fn test_insert_into_checking() -> Result<()> {
    // Create a new schema with one field called "a" of type Int64, and setting nullable to false
    let schema = Arc::new(Schema::new(vec![Field::new("a", DataType::Int64, false)]));

    let session_ctx = SessionContext::new();

    // Create and register the initial table with the provided schema and data
    let initial_table = Arc::new(MemTable::try_new(schema.clone(), vec![vec![]])?);
    session_ctx.register_table("t", initial_table.clone())?;

    // There are two cases we need to check
    // 1. The len of the schema of the plan and the schema of the table should be the same
    // 2. The datatype of the schema of the plan and the schema of the table should be the same

    // Test case 1:
    let write_df = session_ctx.sql("values (1, 2), (3, 4)").await.unwrap();

    let e = write_df
        .write_table("t", DataFrameWriteOptions::new())
        .await
        .unwrap_err();

    assert_contains!(
        e.to_string(),
        "Inserting query must have the same schema length as the table."
    );

    // Setting nullable to true
    // Make sure the nullable check go through
    let schema = Arc::new(Schema::new(vec![Field::new("a", DataType::Int64, true)]));

    let session_ctx = SessionContext::new();

    // Create and register the initial table with the provided schema and data
    let initial_table = Arc::new(MemTable::try_new(schema.clone(), vec![vec![]])?);
    session_ctx.register_table("t", initial_table.clone())?;

    // Test case 2:
    let write_df = session_ctx.sql("values ('a123'), ('b456')").await.unwrap();

    let e = write_df
        .write_table("t", DataFrameWriteOptions::new())
        .await
        .unwrap_err();

    assert_contains!(
        e.to_string(),
        "Inserting query schema mismatch: Expected table field 'a' with type Int64, but got 'column1' with type Utf8"
    );

    Ok(())
}

async fn create_null_table() -> Result<DataFrame> {
    // create a DataFrame with null values