orcxx-rs

Rust wrapper for the official C++ library for Apache ORC.

It uses a submodule pointing to an Apache ORC release, builds its C++ part (including vendored protobuf, lz4, zstd, ...), and links against that.

The orcxx_derive crate provides a custom derive macro.

orcxx_derive examples

RowIterator API

extern crate orcxx;
extern crate orcxx_derive;

use std::num::NonZeroU64;

use orcxx::deserialize::{OrcDeserialize, OrcStruct};
use orcxx::row_iterator::RowIterator;
use orcxx::reader;
use orcxx_derive::OrcDeserialize;

// Define structure
#[derive(OrcDeserialize, Clone, Default, Debug, PartialEq, Eq)]
struct Test1 {
    long1: Option<i64>,
}

// Open file
let orc_path = "../orcxx/orc/examples/TestOrcFile.test1.orc";
let input_stream = reader::InputStream::from_local_file(orc_path).expect("Could not open .orc");
let reader = reader::Reader::new(input_stream).expect("Could not read .orc");

let batch_size = NonZeroU64::new(1024).unwrap();
let mut rows: Vec<Option<Test1>> = RowIterator::new(&reader, batch_size)
    .expect("Could not open ORC file")
    .collect();

assert_eq!(
    rows,
    vec![
        Some(Test1 {
            long1: Some(9223372036854775807)
        }),
        Some(Test1 {
            long1: Some(9223372036854775807)
        })
    ]
);

Loop API

RowIterator clones structures before yielding them. This can be avoided by looping and writing directly to a buffer:

extern crate orcxx;
extern crate orcxx_derive;

use orcxx::deserialize::{CheckableKind, OrcDeserialize, OrcStruct};
use orcxx::reader;
use orcxx_derive::OrcDeserialize;

// Define structure
#[derive(OrcDeserialize, Default, Debug, PartialEq, Eq)]
struct Test1 {
    long1: Option<i64>,
}

// Open file
let orc_path = "../orcxx/orc/examples/TestOrcFile.test1.orc";
let input_stream = reader::InputStream::from_local_file(orc_path).expect("Could not open .orc");
let reader = reader::Reader::new(input_stream).expect("Could not read .orc");

// Only read columns we need
let options = reader::RowReaderOptions::default().include_names(Test1::columns());

let mut row_reader = reader.row_reader(&options).expect("Could not open ORC file");
Test1::check_kind(&row_reader.selected_kind()).expect("Unexpected schema");

let mut rows: Vec<Option<Test1>> = Vec::new();

// Allocate work buffer
let mut batch = row_reader.row_batch(1024);

// Read structs until the end
while row_reader.read_into(&mut batch) {
    let new_rows = Option::<Test1>::from_vector_batch(&batch.borrow()).unwrap();
    rows.extend(new_rows);
}

assert_eq!(
    rows,
    vec![
        Some(Test1 {
            long1: Some(9223372036854775807)
        }),
        Some(Test1 {
            long1: Some(9223372036854775807)
        })
    ]
);

Nested structures

The above two examples also work with nested structures:

extern crate orcxx;
extern crate orcxx_derive;

use orcxx_derive::OrcDeserialize;

#[derive(OrcDeserialize, Default, Debug, PartialEq)]
struct Test1Option {
    boolean1: Option<bool>,
    byte1: Option<i8>,
    short1: Option<i16>,
    int1: Option<i32>,
    long1: Option<i64>,
    float1: Option<f32>,
    double1: Option<f64>,
    bytes1: Option<Vec<u8>>,
    string1: Option<String>,
    list: Option<Vec<Option<Test1ItemOption>>>,
}

#[derive(OrcDeserialize, Default, Debug, PartialEq)]
struct Test1ItemOption {
    int1: Option<i32>,
    string1: Option<String>,
}

orcxx examples

ColumnTree API

Columns can also be read directly without writing their values to structures. This is particularly useful to read files whose schema is not known at compile time.

Low-level API

This reads batches directly from the C++ library, and leaves the Rust code to dynamically cast base vectors to more specific types; here string vectors.

extern crate orcxx;
extern crate orcxx_derive;

use orcxx::reader;
use orcxx::vector::ColumnVectorBatch;

let input_stream = reader::InputStream::from_local_file("../orcxx/orc/examples/TestOrcFile.test1.orc")
    .expect("Could not open");

let reader = reader::Reader::new(input_stream).expect("Could not read");

println!("{:#?}", reader.kind()); // Prints the type of columns in the file

let mut row_reader = reader.row_reader(&reader::RowReaderOptions::default()).unwrap();
let mut batch = row_reader.row_batch(1024);

let mut total_elements = 0;
let mut all_strings: Vec<String> = Vec::new();
while row_reader.read_into(&mut batch) {
    total_elements += (&batch).num_elements();

    let struct_vector = batch.borrow().try_into_structs().unwrap();
    let vectors = struct_vector.fields();

    for vector in vectors {
        match vector.try_into_strings() {
            Ok(string_vector) => {
                for s in string_vector.iter() {
                    all_strings.push(
                        std::str::from_utf8(s.unwrap_or(b"<null>"))
                        .unwrap().to_owned())
                }
            }
            Err(e) => {}
        }
    }
}

assert_eq!(total_elements, 2);
assert_eq!(
    all_strings,
    vec!["\0\u{1}\u{2}\u{3}\u{4}", "", "hi", "bye"]
        .iter()
        .map(|s| s.to_owned())
        .collect::<Vec<_>>()
);