The GNU TAR (Tape Archive) format is a widely used file archive and compression format on Unix-like operating systems. It was originally designed for backing up files to magnetic tape, but is now commonly used for collecting many files into a single compressed archive file for efficient storage and transmission. The TAR format allows for preserving file attributes, directory structures, and supports various compression algorithms.
A TAR archive file consists of a series of file header records and file data blocks. Each file in the archive is represented by a header record that contains metadata about the file, followed by the file data itself. The header record is 512 bytes in size and contains fields such as the file name, file mode (permissions), owner and group IDs, file size, modification time, and checksum.
The file name field in the header record can be up to 100 characters long. If a file name exceeds 100 characters, it is stored using the 'prefix' field, which is an additional 155 bytes. The prefix is concatenated with the file name to create the full path. The file mode field contains the Unix file permissions and file type (regular file, directory, symbolic link, etc).
Following the header record is the file data, which is stored in contiguous 512-byte blocks. If the file size is not a multiple of 512 bytes, the last block is padded with null bytes. Each file's data blocks are written sequentially in the archive, with no separators or delimiters between files.
TAR archives support several types of header records in addition to regular files and directories. Symbolic links and hard links are represented using special header records that reference the target file. Device files, named pipes, and other special file types are also supported. Extended attributes and ACLs can be stored using pax interchange format headers.
One key feature of the TAR format is its support for long file names and paths. Early versions of TAR were limited to 100-character file names, but later versions, such as the widely used USTAR (Unix Standard TAR) format, extended this to support longer names. The POSIX.1-2001 standard introduced a new extensible format that allows for even longer file names and paths, as well as additional metadata fields.
Compression is commonly used in conjunction with TAR archives to reduce the file size. The most popular compression methods are gzip (.tar.gz or .tgz), bzip2 (.tar.bz2), and xz (.tar.xz). These compressed TAR archives are created by first creating a regular TAR archive and then compressing it with the chosen compression algorithm. When extracting a compressed TAR archive, the compression is first removed, and then the regular TAR extraction process is applied.
The TAR format also includes built-in error detection and recovery mechanisms. Each header record contains a checksum field that is calculated when the archive is created. When extracting files from a TAR archive, the checksum is verified to ensure data integrity. If a checksum mismatch is detected, an error is reported, and the extraction can either skip the affected file or attempt to recover as much data as possible.
In addition to the basic TAR format, there are several variations and extensions in use. The GNU version of TAR, which is widely used in Linux distributions, includes additional features such as multi-volume archives, sparse file support, and incremental backups. Other extensions, such as star and pax, offer improved performance, compatibility with non-Unix systems, and support for extended metadata.
Despite its age and limitations, the TAR format remains widely used due to its simplicity, portability, and wide support across different platforms and tools. It serves as a foundation for many higher-level backup and archiving solutions, and is often used as a container format for distributing software packages and source code. As new technologies and storage media have emerged, the TAR format has adapted and evolved to meet changing needs, ensuring its continued relevance in modern computing environments.
File compression reduces redundancy so the same information takes fewer bits. The upper bound on how far you can go is governed by information theory: for lossless compression, the limit is the entropy of the source (see Shannon’s source coding theorem and his original 1948 paper “A Mathematical Theory of Communication”). For lossy compression, the trade-off between rate and quality is captured by rate–distortion theory.
Most compressors have two stages. First, a model predicts or exposes structure in the data. Second, a coder turns those predictions into near-optimal bit patterns. A classic modeling family is Lempel–Ziv: LZ77 (1977) and LZ78 (1978) detect repeated substrings and emit references instead of raw bytes. On the coding side, Huffman coding (see the original paper 1952) assigns shorter codes to more likely symbols. Arithmetic coding and range coding are finer-grained alternatives that squeeze closer to the entropy limit, while modern Asymmetric Numeral Systems (ANS) achieves similar compression with fast table-driven implementations.
DEFLATE (used by gzip, zlib, and ZIP) combines LZ77 with Huffman coding. Its specs are public: DEFLATE RFC 1951, zlib wrapper RFC 1950, and gzip file format RFC 1952. Gzip is framed for streaming and explicitly does not attempt to provide random access. PNG images standardize DEFLATE as their only compression method (with a max 32 KiB window), per the PNG spec “Compression method 0… deflate/inflate… at most 32768 bytes” and W3C/ISO PNG 2nd Edition.
Zstandard (zstd): a newer general-purpose compressor designed for high ratios with very fast decompression. The format is documented in RFC 8878 (also HTML mirror) and the reference spec on GitHub. Like gzip, the basic frame doesn’t aim for random access. One of zstd’s superpowers is dictionaries: small samples from your corpus that dramatically improve compression on many tiny or similar files (see python-zstandard dictionary docs and Nigel Tao’s worked example). Implementations accept both “unstructured” and “structured” dictionaries (discussion).
Brotli: optimized for web content (e.g., WOFF2 fonts, HTTP). It mixes a static dictionary with a DEFLATE-like LZ+entropy core. The spec is RFC 7932, which also notes a sliding window of 2WBITS−16 with WBITS in [10, 24] (1 KiB−16 B up to 16 MiB−16 B) and that it does not attempt random access. Brotli often beats gzip on web text while decoding quickly.
ZIP container: ZIP is a file archive that can store entries with various compression methods (deflate, store, zstd, etc.). The de facto standard is PKWARE’s APPNOTE (see APPNOTE portal, a hosted copy, and LC overviews ZIP File Format (PKWARE) / ZIP 6.3.3).
LZ4 targets raw speed with modest ratios. See its project page (“extremely fast compression”) and frame format. It’s ideal for in-memory caches, telemetry, or hot paths where decompression must be near RAM speed.
XZ / LZMA push for density (great ratios) with relatively slow compression. XZ is a container; the heavy lifting is typically LZMA/LZMA2 (LZ77-like modeling + range coding). See .xz file format, the LZMA spec (Pavlov), and Linux kernel notes on XZ Embedded. XZ usually out-compresses gzip and often competes with high-ratio modern codecs, but with slower encode times.
bzip2 applies the Burrows–Wheeler Transform (BWT), move-to-front, RLE, and Huffman coding. It’s typically smaller than gzip but slower; see the official manual and man pages (Linux).
“Window size” matters. DEFLATE references can only look back 32 KiB (RFC 1951 and PNG’s 32 KiB cap noted here). Brotli’s window ranges from about 1 KiB to 16 MiB (RFC 7932). Zstd tunes window and search depth by level (RFC 8878). Basic gzip/zstd/brotli streams are designed for sequential decoding; the base formats don’t promise random access, though containers (e.g., tar indexes, chunked framing, or format-specific indexes) can layer it on.
The formats above are lossless: you can reconstruct exact bytes. Media codecs are often lossy: they discard imperceptible detail to hit lower bitrates. In images, classic JPEG (DCT, quantization, entropy coding) is standardized in ITU-T T.81 / ISO/IEC 10918-1. In audio, MP3 (MPEG-1 Layer III) and AAC (MPEG-2/4) rely on perceptual models and MDCT transforms (see ISO/IEC 11172-3, ISO/IEC 13818-7, and an MDCT overview here). Lossy and lossless can coexist (e.g., PNG for UI assets; Web codecs for images/video/audio).
Theory: Shannon 1948 · Rate–distortion · Coding: Huffman 1952 · Arithmetic coding · Range coding · ANS. Formats: DEFLATE · zlib · gzip · Zstandard · Brotli · LZ4 frame · XZ format. BWT stack: Burrows–Wheeler (1994) · bzip2 manual. Media: JPEG T.81 · MP3 ISO/IEC 11172-3 · AAC ISO/IEC 13818-7 · MDCT.
Bottom line: choose a compressor that matches your data and constraints, measure on real inputs, and don’t forget the gains from dictionaries and smart framing. With the right pairing, you can get smaller files, faster transfers, and snappier apps — without sacrificing correctness or portability.
File compression is a process that reduces the size of a file or files, typically to save storage space or speed up transmission over a network.
File compression works by identifying and removing redundancy in the data. It uses algorithms to encode the original data in a smaller space.
The two primary types of file compression are lossless and lossy compression. Lossless compression allows the original file to be perfectly restored, while lossy compression enables more significant size reduction at the cost of some loss in data quality.
A popular example of a file compression tool is WinZip, which supports multiple compression formats including ZIP and RAR.
With lossless compression, the quality remains unchanged. However, with lossy compression, there can be a noticeable decrease in quality since it eliminates less-important data to reduce file size more significantly.
Yes, file compression is safe in terms of data integrity, especially with lossless compression. However, like any files, compressed files can be targeted by malware or viruses, so it's always important to have reputable security software in place.
Almost all types of files can be compressed, including text files, images, audio, video, and software files. However, the level of compression achievable can significantly vary between file types.
A ZIP file is a type of file format that uses lossless compression to reduce the size of one or more files. Multiple files in a ZIP file are effectively bundled together into a single file, which also makes sharing easier.
Technically, yes, although the additional size reduction might be minimal or even counterproductive. Compressing an already compressed file might sometimes increase its size due to metadata added by the compression algorithm.
To decompress a file, you typically need a decompression or unzipping tool, like WinZip or 7-Zip. These tools can extract the original files from the compressed format.