docs/guide/rust/row-format.md

title: Row Format sidebar_position: 9 id: row_format license: | 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

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Apache Fory™ provides a high-performance row format for zero-copy deserialization.

Overview

Unlike traditional object serialization that reconstructs entire objects in memory, row format enables random access to fields directly from binary data without full deserialization.

Key benefits:

Zero-copy access: Read fields without allocating or copying data
Partial deserialization: Access only the fields you need
Memory-mapped files: Work with data larger than RAM
Cache-friendly: Sequential memory layout for better CPU cache utilization
Lazy evaluation: Defer expensive operations until field access

When to Use Row Format

Analytics workloads with selective field access
Large datasets where only a subset of fields is needed
Memory-constrained environments
High-throughput data pipelines
Reading from memory-mapped files or shared memory

Basic Usage

use fory::{to_row, from_row};
use fory::ForyRow;
use std::collections::BTreeMap;

#[derive(ForyRow)]
struct UserProfile {
    id: i64,
    username: String,
    email: String,
    scores: Vec<i32>,
    preferences: BTreeMap<String, String>,
    is_active: bool,
}

let profile = UserProfile {
    id: 12345,
    username: "alice".to_string(),
    email: "alice@example.com".to_string(),
    scores: vec![95, 87, 92, 88],
    preferences: BTreeMap::from([
        ("theme".to_string(), "dark".to_string()),
        ("language".to_string(), "en".to_string()),
    ]),
    is_active: true,
};

// Serialize to row format
let row_data = to_row(&profile);

// Zero-copy deserialization - no object allocation!
let row = from_row::<UserProfile>(&row_data);

// Access fields directly from binary data
assert_eq!(row.id(), 12345);
assert_eq!(row.username(), "alice");
assert_eq!(row.email(), "alice@example.com");
assert_eq!(row.is_active(), true);

// Access collections efficiently
let scores = row.scores();
assert_eq!(scores.size(), 4);
assert_eq!(scores.get(0), 95);
assert_eq!(scores.get(1), 87);

let prefs = row.preferences();
assert_eq!(prefs.keys().size(), 2);
assert_eq!(prefs.keys().get(0), "language");
assert_eq!(prefs.values().get(0), "en");

How It Works

Fields are encoded in a binary row with fixed offsets for primitives
Variable-length data (strings, collections) stored with offset pointers
Null bitmap tracks which fields are present
Nested structures supported through recursive row encoding

Performance Comparison

Operation	Object Format	Row Format
Full deserialization	Allocates all objects	Zero allocation
Single field access	Full deserialization required	Direct offset read
Memory usage	Full object graph in memory	Only accessed fields in memory
Suitable for	Small objects, full access	Large objects, selective access

ForyRow vs ForyObject