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title: Introduction sidebar_position: 0 id: index 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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Row Format is a cache-friendly binary format for efficient random access and partial deserialization. Unlike object graph serialization, it lets readers access individual fields without reconstructing the complete object.

Row Format is intended only for trusted analytical data, including memory-mapped data, selective field access, and data pipelines. Use Object Serialization when the application needs general object graphs, shared or circular references, or complete object reconstruction as its primary access pattern.

Choose a Layout

Layout	Language support	Compatibility
Standard Row	Java, Python, C++, Rust	Shared Standard Row layout
Compact Row	Java	Java-only, space-oriented layout

Standard Row

Standard Row is the interoperable layout for Java, Python, C++, and Rust.

Features

• Zero-copy random access: Read selected fields directly from encoded data.
• Partial deserialization: Reconstruct only the values an application needs.
• Cross-language compatibility: Share Standard Row bytes between Java, Python, C++, and Rust.
• Apache Arrow integration: Convert rows to Arrow data in Java and Python.

Layout

Standard Row stores fixed-width values inline and variable-width values by offset and size. Rows, arrays, and maps use a schema to resolve field positions and element types. The normative byte layout, alignment rules, type table, and endianness are defined by the Row Format specification.

Language Support

Language	Standard Row compatibility	Language guide	Additional integration
Java	Compatible	Java	Arrow conversion; interface and extension-type mapping
Python	Compatible	Python	PyArrow schema and table conversion
C++	Compatible	C++	Native row readers and writers
Rust	Compatible	Rust	Borrowed struct, array, and map views

Use the language guides for installation, schema construction, encoding, random access, partial reads, and language-specific integrations.

Compact Row

Compact Row is a Java-only row encoding that reduces fixed-slot and null-bitmap overhead. It is not wire-compatible with Standard Row.

Create a Compact Encoder

RowEncoder<MyBean> encoder =
    Encoders.buildBeanCodec(MyBean.class)
        .compactEncoding()
        .build()
        .get();

BinaryRow row = encoder.toRow(value);
MyBean decoded = encoder.fromRow(row);

Reuse the encoder within one thread. Create separate encoders for concurrent threads.

Layout Tradeoffs

• Fixed-size fields use their natural widths instead of eight-byte Standard Row slots.
• Fields are sorted by alignment to reduce padding.
• The null bitmap is omitted when no field is nullable.
• Fixed-size nested structs can be stored inline.

Choose Compact Row only when every reader is Java and the space reduction justifies the Java-specific layout. Use Standard Row for Java, Python, C++, and Rust interchange.

See the Row Format specification for the exact Standard and Compact binary layouts.