iceberg 0.9.0

Apache Iceberg Rust implementation
Documentation 
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// Licensed to the Apache Software Foundation (ASF) under one
// or more contributor license agreements.  See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership.  The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use this file except in compliance
// with the License.  You may obtain a copy of the License at
//
//   http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing,
// software distributed under the License is distributed on an
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, either express or implied.  See the License for the
// specific language governing permissions and limitations
// under the License.

//! Test utilities.
//! This module is pub just for internal testing.
//! It is subject to change and is not intended to be used by external users.

use arrow_array::RecordBatch;
use expect_test::Expect;
use itertools::Itertools;

/// Snapshot testing to check the resulting record batch.
///
/// - `expected_schema/data`: put `expect![[""]]` as a placeholder,
///   and then run test with `UPDATE_EXPECT=1 cargo test` to automatically update the result,
///   or use rust-analyzer (see [video](https://github.com/rust-analyzer/expect-test)).
///   Check the doc of [`expect_test`] for more details.
/// - `ignore_check_columns`: Some columns are not stable, so we can skip them.
/// - `sort_column`: The order of the data might be non-deterministic, so we can sort it by a column.
pub fn check_record_batches(
    record_batches: Vec<RecordBatch>,
    expected_schema: Expect,
    expected_data: Expect,
    ignore_check_columns: &[&str],
    sort_column: Option<&str>,
) {
    assert!(!record_batches.is_empty(), "Empty record batches");

    // Combine record batches using the first batch's schema
    let first_batch = record_batches.first().unwrap();
    let record_batch =
        arrow_select::concat::concat_batches(&first_batch.schema(), &record_batches).unwrap();

    let mut columns = record_batch.columns().to_vec();
    if let Some(sort_column) = sort_column {
        let column = record_batch.column_by_name(sort_column).unwrap();
        let indices = arrow_ord::sort::sort_to_indices(column, None, None).unwrap();
        columns = columns
            .iter()
            .map(|column| arrow_select::take::take(column.as_ref(), &indices, None).unwrap())
            .collect_vec();
    }

    expected_schema.assert_eq(&format!(
        "{}",
        record_batch.schema().fields().iter().format(",\n")
    ));
    expected_data.assert_eq(&format!(
        "{}",
        record_batch
            .schema()
            .fields()
            .iter()
            .zip_eq(columns)
            .map(|(field, column)| {
                if ignore_check_columns.contains(&field.name().as_str()) {
                    format!("{}: (skipped)", field.name())
                } else {
                    format!("{}: {:?}", field.name(), column)
                }
            })
            .format(",\n")
    ));
}