Internals

This page documents the internal data structures and storage mechanisms of Borg. It is partly based on mailing list discussion about internals and also on static code analysis.

Repository and Archives

Borg stores its data in a Repository. Each repository can hold multiple Archives, which represent individual backups that contain a full archive of the files specified when the backup was performed. Deduplication is performed across multiple backups, both on data and metadata, using Chunks created by the chunker using the Buzhash algorithm.

Each repository has the following file structure:

README
simple text file telling that this is a Borg repository
config
repository configuration
data/
directory where the actual data is stored
hints.%d
hints for repository compaction
index.%d
repository index
lock.roster and lock.exclusive/*
used by the locking system to manage shared and exclusive locks

Lock files

Borg uses locks to get (exclusive or shared) access to the cache and the repository.

The locking system is based on creating a directory lock.exclusive (for exclusive locks). Inside the lock directory, there is a file indicating hostname, process id and thread id of the lock holder.

There is also a json file lock.roster that keeps a directory of all shared and exclusive lockers.

If the process can create the lock.exclusive directory for a resource, it has the lock for it. If creation fails (because the directory has already been created by some other process), lock acquisition fails.

The cache lock is usually in ~/.cache/borg/REPOID/lock.*. The repository lock is in repository/lock.*.

In case you run into troubles with the locks, you can use the borg break-lock command after you first have made sure that no Borg process is running on any machine that accesses this resource. Be very careful, the cache or repository might get damaged if multiple processes use it at the same time.

Config file

Each repository has a config file which which is a INI-style file and looks like this:

[repository]
version = 1
segments_per_dir = 10000
max_segment_size = 5242880
id = 57d6c1d52ce76a836b532b0e42e677dec6af9fca3673db511279358828a21ed6

This is where the repository.id is stored. It is a unique identifier for repositories. It will not change if you move the repository around so you can make a local transfer then decide to move the repository to another (even remote) location at a later time.

Keys

The key to address the key/value store is usually computed like this:

key = id = id_hash(unencrypted_data)

The id_hash function is:

  • sha256 (no encryption keys available)
  • hmac-sha256 (encryption keys available)

Segments and archives

A Borg repository is a filesystem based transactional key/value store. It makes extensive use of msgpack to store data and, unless otherwise noted, data is stored in msgpack encoded files.

Objects referenced by a key are stored inline in files (segments) of approx. 5MB size in numbered subdirectories of repo/data.

They contain:

  • header size
  • crc
  • size
  • tag
  • key
  • data

Segments are built locally, and then uploaded. Those files are strictly append-only and modified only once.

Tag is either PUT, DELETE, or COMMIT. A segment file is basically a transaction log where each repository operation is appended to the file. So if an object is written to the repository a PUT tag is written to the file followed by the object id and data. If an object is deleted a DELETE tag is appended followed by the object id. A COMMIT tag is written when a repository transaction is committed. When a repository is opened any PUT or DELETE operations not followed by a COMMIT tag are discarded since they are part of a partial/uncommitted transaction.

The manifest

The manifest is an object with an all-zero key that references all the archives. It contains:

  • version
  • list of archive infos
  • timestamp
  • config

Each archive info contains:

  • name
  • id
  • time

It is the last object stored, in the last segment, and is replaced each time.

The Archive

The archive metadata does not contain the file items directly. Only references to other objects that contain that data. An archive is an object that contains:

  • version
  • name
  • list of chunks containing item metadata (size: count * ~40B)
  • cmdline
  • hostname
  • username
  • time

Note about archive limitations

The archive is currently stored as a single object in the repository and thus limited in size to MAX_OBJECT_SIZE (20MiB).

As one chunk list entry is ~40B, that means we can reference ~500.000 item metadata stream chunks per archive.

Each item metadata stream chunk is ~128kiB (see hardcoded ITEMS_CHUNKER_PARAMS).

So that means the whole item metadata stream is limited to ~64GiB chunks. If compression is used, the amount of storable metadata is bigger - by the compression factor.

If the medium size of an item entry is 100B (small size file, no ACLs/xattrs), that means a limit of ~640 million files/directories per archive.

If the medium size of an item entry is 2kB (~100MB size files or more ACLs/xattrs), the limit will be ~32 million files/directories per archive.

If one tries to create an archive object bigger than MAX_OBJECT_SIZE, a fatal IntegrityError will be raised.

A workaround is to create multiple archives with less items each, see also #1452.

The Item

Each item represents a file, directory or other fs item and is stored as an item dictionary that contains:

  • path
  • list of data chunks (size: count * ~40B)
  • user
  • group
  • uid
  • gid
  • mode (item type + permissions)
  • source (for links)
  • rdev (for devices)
  • mtime, atime, ctime in nanoseconds
  • xattrs
  • acl
  • bsdfiles

All items are serialized using msgpack and the resulting byte stream is fed into the same chunker algorithm as used for regular file data and turned into deduplicated chunks. The reference to these chunks is then added to the archive metadata. To achieve a finer granularity on this metadata stream, we use different chunker params for this chunker, which result in smaller chunks.

A chunk is stored as an object as well, of course.

Chunks

The Borg chunker uses a rolling hash computed by the Buzhash algorithm. It triggers (chunks) when the last HASH_MASK_BITS bits of the hash are zero, producing chunks of 2^HASH_MASK_BITS Bytes on average.

borg create --chunker-params CHUNK_MIN_EXP,CHUNK_MAX_EXP,HASH_MASK_BITS,HASH_WINDOW_SIZE can be used to tune the chunker parameters, the default is:

  • CHUNK_MIN_EXP = 19 (minimum chunk size = 2^19 B = 512 kiB)
  • CHUNK_MAX_EXP = 23 (maximum chunk size = 2^23 B = 8 MiB)
  • HASH_MASK_BITS = 21 (statistical medium chunk size ~= 2^21 B = 2 MiB)
  • HASH_WINDOW_SIZE = 4095 [B] (0xFFF)

The buzhash table is altered by XORing it with a seed randomly generated once for the archive, and stored encrypted in the keyfile. This is to prevent chunk size based fingerprinting attacks on your encrypted repo contents (to guess what files you have based on a specific set of chunk sizes).

For some more general usage hints see also --chunker-params.

Indexes / Caches

The files cache is stored in cache/files and is indexed on the file path hash. At backup time, it is used to quickly determine whether we need to chunk a given file (or whether it is unchanged and we already have all its pieces). It contains:

  • age
  • file inode number
  • file size
  • file mtime_ns
  • file content chunk hashes

The inode number is stored to make sure we distinguish between different files, as a single path may not be unique across different archives in different setups.

The files cache is stored as a python associative array storing python objects, which generates a lot of overhead.

The chunks cache is stored in cache/chunks and is indexed on the chunk id_hash. It is used to determine whether we already have a specific chunk, to count references to it and also for statistics. It contains:

  • reference count
  • size
  • encrypted/compressed size

The repository index is stored in repo/index.%d and is indexed on the chunk id_hash. It is used to determine a chunk’s location in the repository. It contains:

  • segment (that contains the chunk)
  • offset (where the chunk is located in the segment)

The repository index file is random access.

Hints are stored in a file (repo/hints.%d). It contains:

  • version
  • list of segments
  • compact

hints and index can be recreated if damaged or lost using check --repair.

The chunks cache and the repository index are stored as hash tables, with only one slot per bucket, but that spreads the collisions to the following buckets. As a consequence the hash is just a start position for a linear search, and if the element is not in the table the index is linearly crossed until an empty bucket is found.

When the hash table is filled to 75%, its size is grown. When it’s emptied to 25%, its size is shrinked. So operations on it have a variable complexity between constant and linear with low factor, and memory overhead varies between 33% and 300%.

Indexes / Caches memory usage

Here is the estimated memory usage of Borg:

chunk_count ~= total_file_size / 2 ^ HASH_MASK_BITS

repo_index_usage = chunk_count * 40

chunks_cache_usage = chunk_count * 44

files_cache_usage = total_file_count * 240 + chunk_count * 80

mem_usage ~= repo_index_usage + chunks_cache_usage + files_cache_usage
= chunk_count * 164 + total_file_count * 240

All units are Bytes.

It is assuming every chunk is referenced exactly once (if you have a lot of duplicate chunks, you will have less chunks than estimated above).

It is also assuming that typical chunk size is 2^HASH_MASK_BITS (if you have a lot of files smaller than this statistical medium chunk size, you will have more chunks than estimated above, because 1 file is at least 1 chunk).

If a remote repository is used the repo index will be allocated on the remote side.

E.g. backing up a total count of 1 Mi (IEC binary prefix i.e. 2^20) files with a total size of 1TiB.

  1. with create --chunker-params 10,23,16,4095 (custom, like borg < 1.0 or attic):
mem_usage = 2.8GiB
  1. with create --chunker-params 19,23,21,4095 (default):
mem_usage = 0.31GiB

Note

There is also the --no-files-cache option to switch off the files cache. You’ll save some memory, but it will need to read / chunk all the files as it can not skip unmodified files then.

Encryption

AES-256 is used in CTR mode (so no need for padding). A 64bit initialization vector is used, a HMAC-SHA256 is computed on the encrypted chunk with a random 64bit nonce and both are stored in the chunk. The header of each chunk is: TYPE(1) + HMAC(32) + NONCE(8) + CIPHERTEXT. Encryption and HMAC use two different keys.

In AES CTR mode you can think of the IV as the start value for the counter. The counter itself is incremented by one after each 16 byte block. The IV/counter is not required to be random but it must NEVER be reused. So to accomplish this Borg initializes the encryption counter to be higher than any previously used counter value before encrypting new data.

To reduce payload size, only 8 bytes of the 16 bytes nonce is saved in the payload, the first 8 bytes are always zeros. This does not affect security but limits the maximum repository capacity to only 295 exabytes (2**64 * 16 bytes).

Encryption keys (and other secrets) are kept either in a key file on the client (‘keyfile’ mode) or in the repository config on the server (‘repokey’ mode). In both cases, the secrets are generated from random and then encrypted by a key derived from your passphrase (this happens on the client before the key is stored into the keyfile or as repokey).

The passphrase is passed through the BORG_PASSPHRASE environment variable or prompted for interactive usage.

Key files

When initialized with the init -e keyfile command, Borg needs an associated file in $HOME/.config/borg/keys to read and write the repository. The format is based on msgpack, base64 encoding and PBKDF2 SHA256 hashing, which is then encoded again in a msgpack.

The internal data structure is as follows:

version
currently always an integer, 1
repository_id
the id field in the config INI file of the repository.
enc_key
the key used to encrypt data with AES (256 bits)
enc_hmac_key
the key used to HMAC the encrypted data (256 bits)
id_key
the key used to HMAC the plaintext chunk data to compute the chunk’s id
chunk_seed
the seed for the buzhash chunking table (signed 32 bit integer)

Those fields are processed using msgpack. The utf-8 encoded passphrase is processed with PBKDF2 (SHA256, 100000 iterations, random 256 bit salt) to give us a derived key. The derived key is 256 bits long. A HMAC-SHA256 checksum of the above fields is generated with the derived key, then the derived key is also used to encrypt the above pack of fields. Then the result is stored in a another msgpack formatted as follows:

version
currently always an integer, 1
salt
random 256 bits salt used to process the passphrase
iterations
number of iterations used to process the passphrase (currently 100000)
algorithm
the hashing algorithm used to process the passphrase and do the HMAC checksum (currently the string sha256)
hash
the HMAC of the encrypted derived key
data
the derived key, encrypted with AES over a PBKDF2 SHA256 key described above

The resulting msgpack is then encoded using base64 and written to the key file, wrapped using the standard textwrap module with a header. The header is a single line with a MAGIC string, a space and a hexadecimal representation of the repository id.

Compression

Borg supports the following compression methods:

  • none (no compression, pass through data 1:1)
  • lz4 (low compression, but super fast)
  • zlib (level 0-9, level 0 is no compression [but still adding zlib overhead], level 1 is low, level 9 is high compression)
  • lzma (level 0-9, level 0 is low, level 9 is high compression).

Speed: none > lz4 > zlib > lzma Compression: lzma > zlib > lz4 > none

Be careful, higher zlib and especially lzma compression levels might take a lot of resources (CPU and memory).

The overall speed of course also depends on the speed of your target storage. If that is slow, using a higher compression level might yield better overall performance. You need to experiment a bit. Maybe just watch your CPU load, if that is relatively low, increase compression until 1 core is 70-100% loaded.

Even if your target storage is rather fast, you might see interesting effects: while doing no compression at all (none) is a operation that takes no time, it likely will need to store more data to the storage compared to using lz4. The time needed to transfer and store the additional data might be much more than if you had used lz4 (which is super fast, but still might compress your data about 2:1). This is assuming your data is compressible (if you backup already compressed data, trying to compress them at backup time is usually pointless).

Compression is applied after deduplication, thus using different compression methods in one repo does not influence deduplication.

See borg create --help about how to specify the compression level and its default.