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The more-sophisticated device-mapper targets require complex metadata
that is managed in kernel. In late 2010 we were seeing that various
different targets were rolling their own data structures, for example:
- Mikulas Patocka's multisnap implementation
- Heinz Mauelshagen's thin provisioning target
- Another btree-based caching target posted to dm-devel
- Another multi-snapshot target based on a design of Daniel Phillips
Maintaining these data structures takes a lot of work, so if possible
we'd like to reduce the number.
The persistent-data library is an attempt to provide a re-usable
framework for people who want to store metadata in device-mapper
targets. It's currently used by the thin-provisioning target and an
upcoming hierarchical storage target.
The main documentation is in the header files which can all be found
under drivers/md/persistent-data.
The block manager
This provides access to the data on disk in fixed sized-blocks. There
is a read/write locking interface to prevent concurrent accesses, and
keep data that is being used in the cache.
Clients of persistent-data are unlikely to use this directly.
The transaction manager
This restricts access to blocks and enforces copy-on-write semantics.
The only way you can get hold of a writable block through the
transaction manager is by shadowing an existing block (ie. doing
copy-on-write) or allocating a fresh one. Shadowing is elided within
the same transaction so performance is reasonable. The commit method
ensures that all data is flushed before it writes the superblock.
On power failure your metadata will be as it was when last committed.
The Space Maps
On-disk data structures that keep track of reference counts of blocks.
Also acts as the allocator of new blocks. Currently two
implementations: a simpler one for managing blocks on a different
device (eg. thinly-provisioned data blocks); and one for managing
the metadata space. The latter is complicated by the need to store
its own data within the space it's managing.
The data structures
Currently there is only one data structure, a hierarchical btree.
There are plans to add more. For example, something with an
array-like interface would see a lot of use.
The btree is 'hierarchical' in that you can define it to be composed
of nested btrees, and take multiple keys. For example, the
thin-provisioning target uses a btree with two levels of nesting.
The first maps a device id to a mapping tree, and that in turn maps a
virtual block to a physical block.
Values stored in the btrees can have arbitrary size. Keys are always
64bits, although nesting allows you to use multiple keys.