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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.
//! Low level column reader and writer APIs.
//!
//! This API is designed for reading and writing column values, definition and repetition
//! levels directly.
//!
//! # Example of writing and reading data
//!
//! Data has the following format:
//! ```text
//! +---------------+
//! | values|
//! +---------------+
//! |[1, 2] |
//! |[3, null, null]|
//! +---------------+
//! ```
//!
//! The example uses column writer and reader APIs to write raw values, definition and
//! repetition levels and read them to verify write/read correctness.
//!
//! ```rust,no_run
//! # use std::{fs, path::Path, sync::Arc};
//! #
//! # use parquet::{
//! # column::{reader::ColumnReader, writer::ColumnWriter},
//! # data_type::Int32Type,
//! # file::{
//! # properties::WriterProperties,
//! # reader::{FileReader, SerializedFileReader},
//! # writer::SerializedFileWriter,
//! # },
//! # schema::parser::parse_message_type,
//! # };
//!
//! let path = Path::new("/path/to/column_sample.parquet");
//!
//! // Writing data using column writer API.
//!
//! let message_type = "
//! message schema {
//! optional group values (LIST) {
//! repeated group list {
//! optional INT32 element;
//! }
//! }
//! }
//! ";
//! let schema = Arc::new(parse_message_type(message_type).unwrap());
//! let file = fs::File::create(path).unwrap();
//! let mut writer = SerializedFileWriter::new(file, schema, Default::default()).unwrap();
//!
//! let mut row_group_writer = writer.next_row_group().unwrap();
//! while let Some(mut col_writer) = row_group_writer.next_column().unwrap() {
//! col_writer
//! .typed::<Int32Type>()
//! .write_batch(&[1, 2, 3], Some(&[3, 3, 3, 2, 2]), Some(&[0, 1, 0, 1, 1]))
//! .unwrap();
//! col_writer.close().unwrap();
//! }
//! row_group_writer.close().unwrap();
//!
//! writer.close().unwrap();
//!
//! // Reading data using column reader API.
//!
//! let file = fs::File::open(path).unwrap();
//! let reader = SerializedFileReader::new(file).unwrap();
//! let metadata = reader.metadata();
//!
//! let mut values = vec![0; 8];
//! let mut def_levels = vec![0; 8];
//! let mut rep_levels = vec![0; 8];
//!
//! for i in 0..metadata.num_row_groups() {
//! let row_group_reader = reader.get_row_group(i).unwrap();
//! let row_group_metadata = metadata.row_group(i);
//!
//! for j in 0..row_group_metadata.num_columns() {
//! let mut column_reader = row_group_reader.get_column_reader(j).unwrap();
//! match column_reader {
//! // You can also use `get_typed_column_reader` method to extract typed reader.
//! ColumnReader::Int32ColumnReader(ref mut typed_reader) => {
//! let (records, values, levels) = typed_reader.read_records(
//! 8, // maximum records to read
//! Some(&mut def_levels),
//! Some(&mut rep_levels),
//! &mut values,
//! ).unwrap();
//! assert_eq!(records, 2);
//! assert_eq!(levels, 5);
//! assert_eq!(values, 3);
//! }
//! _ => {}
//! }
//! }
//! }
//!
//! assert_eq!(values, vec![1, 2, 3, 0, 0, 0, 0, 0]);
//! assert_eq!(def_levels, vec![3, 3, 3, 2, 2, 0, 0, 0]);
//! assert_eq!(rep_levels, vec![0, 1, 0, 1, 1, 0, 0, 0]);
//! ```
pub mod page;
pub mod reader;
pub mod writer;