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479 lines
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ReStructuredText
479 lines
16 KiB
ReStructuredText
.. include:: global.rst.inc
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.. highlight:: none
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.. _internals:
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Internals
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=========
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This page documents the internal data structures and storage
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mechanisms of |project_name|. It is partly based on `mailing list
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discussion about internals`_ and also on static code analysis.
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Repository and Archives
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-----------------------
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|project_name| stores its data in a `Repository`. Each repository can
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hold multiple `Archives`, which represent individual backups that
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contain a full archive of the files specified when the backup was
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performed. Deduplication is performed across multiple backups, both on
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data and metadata, using `Chunks` created by the chunker using the Buzhash_
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algorithm.
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Each repository has the following file structure:
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README
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simple text file telling that this is a |project_name| repository
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config
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repository configuration
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data/
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directory where the actual data is stored
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hints.%d
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hints for repository compaction
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index.%d
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repository index
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lock.roster and lock.exclusive/*
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used by the locking system to manage shared and exclusive locks
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Lock files
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----------
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|project_name| uses locks to get (exclusive or shared) access to the cache and
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the repository.
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The locking system is based on creating a directory `lock.exclusive` (for
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exclusive locks). Inside the lock directory, there is a file indication
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hostname, process id and thread id of the lock holder.
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There is also a json file `lock.roster` that keeps a directory of all shared
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and exclusive lockers.
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If the process can create the `lock.exclusive` directory for a resource, it has
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the lock for it. If creation fails (because the directory has already been
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created by some other process), lock acquisition fails.
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The cache lock is usually in `~/.cache/borg/REPOID/lock.*`.
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The repository lock is in `repository/lock.*`.
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In case you run into troubles with the locks, you can use the ``borg break-lock``
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command after you first have made sure that no |project_name| process is
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running on any machine that accesses this resource. Be very careful, the cache
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or repository might get damaged if multiple processes use it at the same time.
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Config file
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-----------
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Each repository has a ``config`` file which which is a ``INI``-style file
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and looks like this::
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[repository]
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version = 1
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segments_per_dir = 10000
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max_segment_size = 5242880
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id = 57d6c1d52ce76a836b532b0e42e677dec6af9fca3673db511279358828a21ed6
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This is where the ``repository.id`` is stored. It is a unique
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identifier for repositories. It will not change if you move the
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repository around so you can make a local transfer then decide to move
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the repository to another (even remote) location at a later time.
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Keys
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----
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The key to address the key/value store is usually computed like this:
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key = id = id_hash(unencrypted_data)
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The id_hash function is:
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* sha256 (no encryption keys available)
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* hmac-sha256 (encryption keys available)
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Segments and archives
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---------------------
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A |project_name| repository is a filesystem based transactional key/value
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store. It makes extensive use of msgpack_ to store data and, unless
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otherwise noted, data is stored in msgpack_ encoded files.
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Objects referenced by a key are stored inline in files (`segments`) of approx.
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5MB size in numbered subdirectories of ``repo/data``.
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They contain:
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* header size
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* crc
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* size
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* tag
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* key
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* data
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Segments are built locally, and then uploaded. Those files are
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strictly append-only and modified only once.
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Tag is either ``PUT``, ``DELETE``, or ``COMMIT``. A segment file is
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basically a transaction log where each repository operation is
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appended to the file. So if an object is written to the repository a
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``PUT`` tag is written to the file followed by the object id and
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data. If an object is deleted a ``DELETE`` tag is appended
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followed by the object id. A ``COMMIT`` tag is written when a
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repository transaction is committed. When a repository is opened any
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``PUT`` or ``DELETE`` operations not followed by a ``COMMIT`` tag are
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discarded since they are part of a partial/uncommitted transaction.
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The manifest
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------------
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The manifest is an object with an all-zero key that references all the
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archives.
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It contains:
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* version
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* list of archive infos
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* timestamp
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* config
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Each archive info contains:
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* name
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* id
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* time
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It is the last object stored, in the last segment, and is replaced
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each time.
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The Archive
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-----------
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The archive metadata does not contain the file items directly. Only
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references to other objects that contain that data. An archive is an
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object that contains:
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* version
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* name
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* list of chunks containing item metadata (size: count * ~40B)
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* cmdline
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* hostname
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* username
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* time
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.. _archive_limitation:
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Note about archive limitations
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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The archive is currently stored as a single object in the repository
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and thus limited in size to MAX_OBJECT_SIZE (20MiB).
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As one chunk list entry is ~40B, that means we can reference ~500.000 item
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metadata stream chunks per archive.
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Each item metadata stream chunk is ~128kiB (see hardcoded ITEMS_CHUNKER_PARAMS).
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So that means the whole item metadata stream is limited to ~64GiB chunks.
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If compression is used, the amount of storable metadata is bigger - by the
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compression factor.
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If the medium size of an item entry is 100B (small size file, no ACLs/xattrs),
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that means a limit of ~640 million files/directories per archive.
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If the medium size of an item entry is 2kB (~100MB size files or more
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ACLs/xattrs), the limit will be ~32 million files/directories per archive.
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If one tries to create an archive object bigger than MAX_OBJECT_SIZE, a fatal
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IntegrityError will be raised.
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A workaround is to create multiple archives with less items each, see
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also :issue:`1452`.
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The Item
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--------
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Each item represents a file, directory or other fs item and is stored as an
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``item`` dictionary that contains:
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* path
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* list of data chunks (size: count * ~40B)
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* user
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* group
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* uid
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* gid
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* mode (item type + permissions)
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* source (for links)
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* rdev (for devices)
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* mtime, atime, ctime in nanoseconds
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* xattrs
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* acl
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* bsdfiles
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All items are serialized using msgpack and the resulting byte stream
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is fed into the same chunker algorithm as used for regular file data
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and turned into deduplicated chunks. The reference to these chunks is then added
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to the archive metadata. To achieve a finer granularity on this metadata
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stream, we use different chunker params for this chunker, which result in
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smaller chunks.
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A chunk is stored as an object as well, of course.
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.. _chunker_details:
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Chunks
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------
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The |project_name| chunker uses a rolling hash computed by the Buzhash_ algorithm.
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It triggers (chunks) when the last HASH_MASK_BITS bits of the hash are zero,
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producing chunks of 2^HASH_MASK_BITS Bytes on average.
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``borg create --chunker-params CHUNK_MIN_EXP,CHUNK_MAX_EXP,HASH_MASK_BITS,HASH_WINDOW_SIZE``
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can be used to tune the chunker parameters, the default is:
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- CHUNK_MIN_EXP = 19 (minimum chunk size = 2^19 B = 512 kiB)
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- CHUNK_MAX_EXP = 23 (maximum chunk size = 2^23 B = 8 MiB)
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- HASH_MASK_BITS = 21 (statistical medium chunk size ~= 2^21 B = 2 MiB)
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- HASH_WINDOW_SIZE = 4095 [B] (`0xFFF`)
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The buzhash table is altered by XORing it with a seed randomly generated once
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for the archive, and stored encrypted in the keyfile. This is to prevent chunk
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size based fingerprinting attacks on your encrypted repo contents (to guess
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what files you have based on a specific set of chunk sizes).
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For some more general usage hints see also ``--chunker-params``.
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Indexes / Caches
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----------------
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The **files cache** is stored in ``cache/files`` and is indexed on the
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``file path hash``. At backup time, it is used to quickly determine whether we
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need to chunk a given file (or whether it is unchanged and we already have all
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its pieces).
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It contains:
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* age
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* file inode number
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* file size
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* file mtime_ns
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* file content chunk hashes
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The inode number is stored to make sure we distinguish between
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different files, as a single path may not be unique across different
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archives in different setups.
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The files cache is stored as a python associative array storing
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python objects, which generates a lot of overhead.
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The **chunks cache** is stored in ``cache/chunks`` and is indexed on the
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``chunk id_hash``. It is used to determine whether we already have a specific
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chunk, to count references to it and also for statistics.
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It contains:
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* reference count
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* size
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* encrypted/compressed size
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The **repository index** is stored in ``repo/index.%d`` and is indexed on the
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``chunk id_hash``. It is used to determine a chunk's location in the repository.
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It contains:
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* segment (that contains the chunk)
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* offset (where the chunk is located in the segment)
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The repository index file is random access.
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Hints are stored in a file (``repo/hints.%d``).
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It contains:
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* version
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* list of segments
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* compact
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hints and index can be recreated if damaged or lost using ``check --repair``.
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The chunks cache and the repository index are stored as hash tables, with
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only one slot per bucket, but that spreads the collisions to the following
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buckets. As a consequence the hash is just a start position for a linear
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search, and if the element is not in the table the index is linearly crossed
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until an empty bucket is found.
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When the hash table is filled to 75%, its size is grown. When it's
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emptied to 25%, its size is shrinked. So operations on it have a variable
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complexity between constant and linear with low factor, and memory overhead
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varies between 33% and 300%.
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.. _cache-memory-usage:
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Indexes / Caches memory usage
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-----------------------------
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Here is the estimated memory usage of |project_name|:
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chunk_count ~= total_file_size / 2 ^ HASH_MASK_BITS
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repo_index_usage = chunk_count * 40
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chunks_cache_usage = chunk_count * 44
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files_cache_usage = total_file_count * 240 + chunk_count * 80
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mem_usage ~= repo_index_usage + chunks_cache_usage + files_cache_usage
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= chunk_count * 164 + total_file_count * 240
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All units are Bytes.
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It is assuming every chunk is referenced exactly once (if you have a lot of
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duplicate chunks, you will have less chunks than estimated above).
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It is also assuming that typical chunk size is 2^HASH_MASK_BITS (if you have
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a lot of files smaller than this statistical medium chunk size, you will have
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more chunks than estimated above, because 1 file is at least 1 chunk).
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If a remote repository is used the repo index will be allocated on the remote side.
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E.g. backing up a total count of 1 Mi (IEC binary prefix e.g. 2^20) files with a total size of 1TiB.
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a) with ``create --chunker-params 10,23,16,4095`` (custom, like borg < 1.0 or attic):
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mem_usage = 2.8GiB
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b) with ``create --chunker-params 19,23,21,4095`` (default):
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mem_usage = 0.31GiB
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.. note:: There is also the ``--no-files-cache`` option to switch off the files cache.
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You'll save some memory, but it will need to read / chunk all the files as
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it can not skip unmodified files then.
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Encryption
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----------
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AES_-256 is used in CTR mode (so no need for padding). A 64bit initialization
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vector is used, a `HMAC-SHA256`_ is computed on the encrypted chunk with a
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random 64bit nonce and both are stored in the chunk.
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The header of each chunk is: ``TYPE(1)`` + ``HMAC(32)`` + ``NONCE(8)`` + ``CIPHERTEXT``.
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Encryption and HMAC use two different keys.
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In AES CTR mode you can think of the IV as the start value for the counter.
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The counter itself is incremented by one after each 16 byte block.
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The IV/counter is not required to be random but it must NEVER be reused.
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So to accomplish this |project_name| initializes the encryption counter to be
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higher than any previously used counter value before encrypting new data.
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To reduce payload size, only 8 bytes of the 16 bytes nonce is saved in the
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payload, the first 8 bytes are always zeros. This does not affect security but
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limits the maximum repository capacity to only 295 exabytes (2**64 * 16 bytes).
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Encryption keys (and other secrets) are kept either in a key file on the client
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('keyfile' mode) or in the repository config on the server ('repokey' mode).
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In both cases, the secrets are generated from random and then encrypted by a
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key derived from your passphrase (this happens on the client before the key
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is stored into the keyfile or as repokey).
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The passphrase is passed through the ``BORG_PASSPHRASE`` environment variable
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or prompted for interactive usage.
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Key files
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---------
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When initialized with the ``init -e keyfile`` command, |project_name|
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needs an associated file in ``$HOME/.config/borg/keys`` to read and write
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the repository. The format is based on msgpack_, base64 encoding and
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PBKDF2_ SHA256 hashing, which is then encoded again in a msgpack_.
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The internal data structure is as follows:
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version
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currently always an integer, 1
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repository_id
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the ``id`` field in the ``config`` ``INI`` file of the repository.
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enc_key
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the key used to encrypt data with AES (256 bits)
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enc_hmac_key
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the key used to HMAC the encrypted data (256 bits)
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id_key
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the key used to HMAC the plaintext chunk data to compute the chunk's id
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chunk_seed
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the seed for the buzhash chunking table (signed 32 bit integer)
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Those fields are processed using msgpack_. The utf-8 encoded passphrase
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is processed with PBKDF2_ (SHA256_, 100000 iterations, random 256 bit salt)
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to give us a derived key. The derived key is 256 bits long.
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A `HMAC-SHA256`_ checksum of the above fields is generated with the derived
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key, then the derived key is also used to encrypt the above pack of fields.
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Then the result is stored in a another msgpack_ formatted as follows:
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version
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currently always an integer, 1
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salt
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random 256 bits salt used to process the passphrase
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iterations
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number of iterations used to process the passphrase (currently 100000)
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algorithm
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the hashing algorithm used to process the passphrase and do the HMAC
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checksum (currently the string ``sha256``)
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hash
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the HMAC of the encrypted derived key
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data
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the derived key, encrypted with AES over a PBKDF2_ SHA256 key
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described above
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The resulting msgpack_ is then encoded using base64 and written to the
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key file, wrapped using the standard ``textwrap`` module with a header.
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The header is a single line with a MAGIC string, a space and a hexadecimal
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representation of the repository id.
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Compression
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-----------
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|project_name| supports the following compression methods:
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- none (no compression, pass through data 1:1)
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- lz4 (low compression, but super fast)
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- zlib (level 0-9, level 0 is no compression [but still adding zlib overhead],
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level 1 is low, level 9 is high compression)
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- lzma (level 0-9, level 0 is low, level 9 is high compression).
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Speed: none > lz4 > zlib > lzma
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Compression: lzma > zlib > lz4 > none
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Be careful, higher zlib and especially lzma compression levels might take a
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lot of resources (CPU and memory).
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The overall speed of course also depends on the speed of your target storage.
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If that is slow, using a higher compression level might yield better overall
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performance. You need to experiment a bit. Maybe just watch your CPU load, if
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that is relatively low, increase compression until 1 core is 70-100% loaded.
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Even if your target storage is rather fast, you might see interesting effects:
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while doing no compression at all (none) is a operation that takes no time, it
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likely will need to store more data to the storage compared to using lz4.
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The time needed to transfer and store the additional data might be much more
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than if you had used lz4 (which is super fast, but still might compress your
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data about 2:1). This is assuming your data is compressible (if you backup
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already compressed data, trying to compress them at backup time is usually
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pointless).
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Compression is applied after deduplication, thus using different compression
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methods in one repo does not influence deduplication.
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See ``borg create --help`` about how to specify the compression level and its default.
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