Goals and Basics¶
Target NVMe devices. Not primarily concerned with pmem or HDD.
make use of SPDK for user-space driven IO
Use Seastar futures programming model to facilitate run-to-completion and a sharded memory/processing model
Allow zero- (or minimal) data copying on read and write paths when combined with a seastar-based messenger using DPDK
Motivation and background¶
All flash devices are internally structured in terms of segments that can be written efficiently but must be erased in their entirety. The NVMe device generally has limited knowledge about what data in a segment is still “live” (hasn’t been logically discarded), making the inevitable garbage collection within the device inefficient. We can design an on-disk layout that is friendly to GC at lower layers and drive garbage collection at higher layers.
In principle a fine-grained discard could communicate our intent to the device, but in practice discard is poorly implemented in the device and intervening software layers.
The basic idea is that all data will be stream out sequentially to large segments on the device. In the SSD hardware, segments are likely to be on the order of 100’s of MB to tens of GB.
SeaStore’s logical segments would ideally be perfectly aligned with the hardware segments. In practice, it may be challenging to determine geometry and to sufficiently hint to the device that LBAs being written should be aligned to the underlying hardware. In the worst case, we can structure our logical segments to correspond to e.g. 5x the physical segment size so that we have about ~20% of our data misaligned.
When we reach some utilization threshold, we mix cleaning work in with the ongoing write workload in order to evacuate live data from previously written segments. Once they are completely free we can discard the entire segment so that it can be erased and reclaimed by the device.
The key is to mix a small bit of cleaning work with every write transaction to avoid spikes and variance in write latency.
Data layout basics¶
One or more cores/shards will be reading and writing to the device at once. Each shard will have its own independent data it is operating on and stream to its own open segments. Devices that support streams can be hinted accordingly so that data from different shards is not mixed on the underlying media.
As the initial sequential design above matures, we’ll introduce persistent memory support for metadata and caching structures.
The design is based heavily on both f2fs and btrfs. Each reactor manages its own root. Prior to reusing a segment, we rewrite any live blocks to an open segment.
Because we are only writing sequentially to open segments, we must “clean” one byte of an existing segment for every byte written at steady state. Generally, we’ll need to reserve some portion of the usable capacity in order to ensure that write amplification remains acceptably low (20% for 2x? – TODO: find prior work). As a design choice, we want to avoid a background gc scheme as it tends to complicate estimating operation cost and tends to introduce non-deterministic latency behavior. Thus, we want a set of structures that permits us to relocate blocks from existing segments inline with ongoing client IO.
To that end, at a high level, we’ll maintain 2 basic metadata trees. First, we need a tree mapping ghobject_t->onode_t (onode_by_hobject). Second, we need a way to find live blocks within a segment and a way to decouple internal references from physical locations (lba_tree).
Each onode contains xattrs directly as well as the top of the omap and extent trees (optimization: we ought to be able to fit small enough objects into the onode).
The backing storage is abstracted into a set of segments. Each segment can be in one of 3 states: empty, open, closed. The byte contents of a segment are a sequence of records. A record is prefixed by a header (including length and checksums) and contains a sequence of deltas and/or blocks. Each delta describes a logical mutation for some block. Each included block is an aligned extent addressable by <segment_id_t, segment_offset_t>. A transaction can be implemented by constructing a record combining deltas and updated blocks and writing it to an open segment.
Note that segments will generally be large (something like >=256MB), so there will not typically be very many of them.
record: [ header | delta | delta… | block | block … ] segment: [ record … ]
See src/crimson/os/seastore/journal.h for Journal implementation See src/crimson/os/seastore/seastore_types.h for most seastore structures.
Each shard will keep open N segments for writes
HDD: N is probably 1 on one shard
NVME/SSD: N is probably 2/shard, one for “journal” and one for finished data records as their lifetimes are different.
I think the exact number to keep open and how to partition writes among them will be a tuning question – gc/layout should be flexible. Where practical, the goal is probably to partition blocks by expected lifetime so that a segment either has long lived or short lived blocks.
The backing physical layer is exposed via a segment based interface. See src/crimson/os/seastore/segment_manager.h
Journal and Atomicity¶
One open segment is designated to be the journal. A transaction is represented by an atomically written record. A record will contain blocks written as part of the transaction as well as deltas which are logical mutations to existing physical extents. Transaction deltas are always written to the journal. If the transaction is associated with blocks written to other segments, final record with the deltas should be written only once the other blocks are persisted. Crash recovery is done by finding the segment containing the beginning of the current journal, loading the root node, replaying the deltas, and loading blocks into the cache as needed.
Every block is in one of two states:
clean: may be in cache or not, reads may cause cache residence or not
dirty: the current version of the record requires overlaying deltas from the journal. Must be fully present in the cache.
Periodically, we need to trim the journal (else, we’d have to replay journal deltas from the beginning of time). To do this, we need to create a checkpoint by rewriting the root blocks and all currently dirty blocks. Note, we can do journal checkpoints relatively infrequently, and they needn’t block the write stream.
Note, deltas may not be byte range modifications. Consider a btree node structured with keys to the left and values to the right (common trick for improving point query/key scan performance). Inserting a key/value into that node at the min would involve moving a bunch of bytes, which would be expensive (or verbose) to express purely as a sequence of byte operations. As such, each delta indicates the type as well as the location of the corresponding extent. Each block type can therefore implement CachedExtent::apply_delta as appopriate.
See src/os/crimson/seastore/cached_extent.h. See src/os/crimson/seastore/cache.h.
Prior to reusing a segment, we must relocate all live blocks. Because we only write sequentially to empty segments, for every byte we write to currently open segments, we need to clean a byte of an existing closed segment. As a design choice, we’d like to avoid background work as it complicates estimating operation cost and has a tendency to create non-deterministic latency spikes. Thus, under normal operation each seastore reactor will be inserting enough work to clean a segment at the same rate as incoming operations.
In order to make this cheap for sparse segments, we need a way to positively identify dead blocks. Thus, for every block written, an entry will be added to the lba tree with a pointer to the previous lba in the segment. Any transaction that moves a block or modifies the reference set of an existing one will include deltas/blocks required to update the lba tree to update or remove the previous block allocation. The gc state thus simply needs to maintain an iterator (of a sort) into the lba tree segment linked list for segment currently being cleaned and a pointer to the next record to be examined – records not present in the allocation tree may still contain roots (like allocation tree blocks) and so the record metadata must be checked for a flag indicating root blocks.
For each transaction, we evaluate a heuristic function of the currently available space and currently live space in order to determine whether we need to do cleaning work (could be simply a range of live/used space ratios).
TODO: there is not yet a GC implementation
Using the above block and delta semantics, we build two root level trees: - onode tree: maps hobject_t to onode_t - lba_tree: maps lba_t to lba_range_t
Each of the above structures is comprised of blocks with mutations encoded in deltas. Each node of the above trees maps onto a block. Each block is either physically addressed (root blocks and the lba_tree nodes) or is logically addressed (everything else). Physically addressed blocks are located by a paddr_t: <segment_id_t, segment_off_t> tuple and are marked as physically addressed in the record. Logical blocks are addressed by laddr_t and require a lookup in the lba_tree to address.
Because the cache/transaction machinery lives below the level of the lba tree, we can represent atomic mutations of the lba tree and other structures by simply including both in a transaction.
Implementations of the LBAManager interface are responsible for managing the logical->physical mapping – see crimson/os/seastore/lba_manager.h.
The BtreeLBAManager implements this interface directly on top of Journal and SegmentManager using a wandering btree approach.
Because SegmentManager does not let us predict the location of a committed record (a property of both SMR and Zone devices), references to blocks created within the same transaction will necessarily be relative addresses. The BtreeLBAManager maintains an invariant by which the in-memory copy of any block will contain only absolute addresses when !is_pending() – on_commit and complete_load fill in absolute addresses based on the actual block addr and on_delta_write does so based on the just committed record. When is_pending(), if is_initial_pending references in memory are block_relative (because they will be written to the original block location) and record_relative otherwise (value will be written to delta).
The TransactionManager is responsible for presenting a unified interface on top of the Journal, SegmentManager, Cache, and LBAManager. Users can allocate and mutate extents based on logical addresses with segment cleaning handled in the background.
Support for scanning a segment to find physically addressed blocks
Add support for trimming the journal and releasing segments.
Support for rewriting dirty blocks
Need to add support to CachedExtent for finding/updating dependent blocks
Need to add support for adding dirty block writout to try_construct_record
Add support for pinning
Add segment -> laddr for use in GC
Support for locating remaining used blocks in segments
Support in BtreeLBAManager for tracking used blocks in segments
Heuristic for identifying segments to clean
Add support for periodically generating a journal checkpoint.
Remaining ObjectStore integration
Splits, merges, and sharding¶
One of the current ObjectStore requirements is to be able to split a collection (PG) in O(1) time. Starting in mimic, we also need to be able to merge two collections into one (i.e., exactly the reverse of a split).
However, the PGs that we split into would hash to different shards of the OSD in the current sharding scheme. One can imagine replacing that sharding scheme with a temporary mapping directing the smaller child PG to the right shard since we generally then migrate that PG to another OSD anyway, but this wouldn’t help us in the merge case where the constituent pieces may start out on different shards and ultimately need to be handled in the same collection (and be operated on via single transactions).
This suggests that we likely need a way for data written via one shard to “switch ownership” and later be read and managed by a different shard.