diff options
Diffstat (limited to 'doc/book/src/design/internals.md')
| -rw-r--r-- | doc/book/src/design/internals.md | 251 |
1 files changed, 94 insertions, 157 deletions
diff --git a/doc/book/src/design/internals.md b/doc/book/src/design/internals.md index e712ae07..255335fa 100644 --- a/doc/book/src/design/internals.md +++ b/doc/book/src/design/internals.md @@ -1,158 +1,95 @@ -**WARNING: this documentation is more a "design draft", which was written before Garage's actual implementation. The general principle is similar but details have not yet been updated.** +# Internals + +## Overview + +TODO: write this section + +- The Dynamo ring + +- CRDTs + +- Consistency model of Garage tables + +See this presentation (in French) for some first information: +<https://git.deuxfleurs.fr/Deuxfleurs/garage/src/branch/main/doc/talks/2020-12-02_wide-team/talk.pdf> + + +## Garbage collection + +A faulty garbage collection procedure has been the cause of +[critical bug #39](https://git.deuxfleurs.fr/Deuxfleurs/garage/issues/39). +This precise bug was fixed in the code, however there are potentially more +general issues with the garbage collector being too eager and deleting things +too early. This has been the subject of +[PR #135](https://git.deuxfleurs.fr/Deuxfleurs/garage/pulls/135). +This section summarizes the discussions on this topic. + +Rationale: we want to ensure Garage's safety by making sure things don't get +deleted from disk if they are still needed. Two aspects are involved in this. + +### 1. Garbage collection of table entries (in `meta/` directory) + +The `Entry` trait used for table entries (defined in `tables/schema.rs`) +defines a function `is_tombstone()` that returns `true` if that entry +represents an entry that is deleted in the table. CRDT semantics by default +keep all tombstones, because they are necessary for reconciliation: if node A +has a tombstone that supersedes a value `x`, and node B has value `x`, A has to +keep the tombstone in memory so that the value `x` can be properly deleted at +node `B`. Otherwise, due to the CRDT reconciliation rule, the value `x` from B +would flow back to A and a deleted item would reappear in the system. + +Here, we have some control on the nodes involved in storing Garage data. +Therefore we have a garbage collector that is able to delete tombstones UNDER +CERTAIN CONDITIONS. This garbage collector is implemented in `table/gc.rs`. To +delete a tombstone, the following condition has to be met: + +- All nodes responsible for storing this entry are aware of the existence of + the tombstone, i.e. they cannot hold another version of the entry that is + superseeded by the tombstone. This ensures that deleting the tombstone is + safe and that no deleted value will come back in the system. + +Garage makes use of Sled's atomic operations (such as compare-and-swap and +transactions) to ensure that only tombstones that have been correctly +propagated to other nodes are ever deleted from the local entry tree. + +This GC is safe in the following sense: no non-tombstone data is ever deleted +from Garage tables. + +**However**, there is an issue with the way this interacts with data +rebalancing in the case when a partition is moving between nodes. If a node has +some data of a partition for which it is not responsible, it has to offload it. +However that offload process takes some time. In that interval, the GC does not +check with that node if it has the tombstone before deleting the tombstone, so +perhaps it doesn't have it and when the offload finally happens, old data comes +back in the system. + +**PR 135 mostly fixes this** by implementing a 24-hour delay before anything is +garbage collected in a table. This works under the assumption that rebalances +that follow data shuffling terminate in less than 24 hours. + +**However**, in distributed systems, it is generally considered a bad practice +to make assumptions that information propagates in a certain time interval: +this consists in making a synchrony assumption, meaning that we are basically +assuming a computing model that has much stronger properties than otherwise. To +maximize the applicability of Garage, we would like to remove this assumption, +and implement a system where time does not play a role. To do this, we would +need to find a way to safely disable the GC when data is being shuffled around, +and safely detect that the shuffling has terminated and thus the GC can be +resumed. This introduces some complexity to the protocol and hasn't been +tackled yet. + +### 2. Garbage collection of data blocks (in `data/` directory) + +Blocks in the data directory are reference-counted. In Garage versions before +PR #135, blocks could get deleted from local disk as soon as their reference +counter reached zero. We had a mechanism to not trigger this immediately at the +rc-reaches-zero event, but the cleanup could be triggered by other means (for +example by a block repair operation...). PR #135 added a safety measure so that +blocks never get deleted in a 10 minute interval following the time when the RC +reaches zero. This is a measure to make impossible race conditions such as #39. +We would have liked to use a larger delay (e.g. 24 hours), but in the case of a +rebalance of data, this would have led to the disk utilization to explode +during the rebalancing, only to shrink again after 24 hours. The 10-minute +delay is a compromise that gives good security while not having this problem of +disk space explosion on rebalance. -#### Modules - -- `membership/`: configuration, membership management (gossip of node's presence and status), ring generation --> what about Serf (used by Consul/Nomad) : https://www.serf.io/? Seems a huge library with many features so maybe overkill/hard to integrate -- `metadata/`: metadata management -- `blocks/`: block management, writing, GC and rebalancing -- `internal/`: server to server communication (HTTP server and client that reuses connections, TLS if we want, etc) -- `api/`: S3 API -- `web/`: web management interface - -#### Metadata tables - -**Objects:** - -- *Hash key:* Bucket name (string) -- *Sort key:* Object key (string) -- *Sort key:* Version timestamp (int) -- *Sort key:* Version UUID (string) -- Complete: bool -- Inline: bool, true for objects < threshold (say 1024) -- Object size (int) -- Mime type (string) -- Data for inlined objects (blob) -- Hash of first block otherwise (string) - -*Having only a hash key on the bucket name will lead to storing all file entries of this table for a specific bucket on a single node. At the same time, it is the only way I see to rapidly being able to list all bucket entries...* - -**Blocks:** - -- *Hash key:* Version UUID (string) -- *Sort key:* Offset of block in total file (int) -- Hash of data block (string) - -A version is defined by the existence of at least one entry in the blocks table for a certain version UUID. -We must keep the following invariant: if a version exists in the blocks table, it has to be referenced in the objects table. -We explicitly manage concurrent versions of an object: the version timestamp and version UUID columns are index columns, thus we may have several concurrent versions of an object. -Important: before deleting an older version from the objects table, we must make sure that we did a successfull delete of the blocks of that version from the blocks table. - -Thus, the workflow for reading an object is as follows: - -1. Check permissions (LDAP) -2. Read entry in object table. If data is inline, we have its data, stop here. - -> if several versions, take newest one and launch deletion of old ones in background -3. Read first block from cluster. If size <= 1 block, stop here. -4. Simultaneously with previous step, if size > 1 block: query the Blocks table for the IDs of the next blocks -5. Read subsequent blocks from cluster - -Workflow for PUT: - -1. Check write permission (LDAP) -2. Select a new version UUID -3. Write a preliminary entry for the new version in the objects table with complete = false -4. Send blocks to cluster and write entries in the blocks table -5. Update the version with complete = true and all of the accurate information (size, etc) -6. Return success to the user -7. Launch a background job to check and delete older versions - -Workflow for DELETE: - -1. Check write permission (LDAP) -2. Get current version (or versions) in object table -3. Do the deletion of those versions NOT IN A BACKGROUND JOB THIS TIME -4. Return succes to the user if we were able to delete blocks from the blocks table and entries from the object table - -To delete a version: - -1. List the blocks from Cassandra -2. For each block, delete it from cluster. Don't care if some deletions fail, we can do GC. -3. Delete all of the blocks from the blocks table -4. Finally, delete the version from the objects table - -Known issue: if someone is reading from a version that we want to delete and the object is big, the read might be interrupted. I think it is ok to leave it like this, we just cut the connection if data disappears during a read. - -("Soit P un problème, on s'en fout est une solution à ce problème") - -#### Block storage on disk - -**Blocks themselves:** - -- file path = /blobs/(first 3 hex digits of hash)/(rest of hash) - -**Reverse index for GC & other block-level metadata:** - -- file path = /meta/(first 3 hex digits of hash)/(rest of hash) -- map block hash -> set of version UUIDs where it is referenced - -Usefull metadata: - -- list of versions that reference this block in the Casandra table, so that we can do GC by checking in Cassandra that the lines still exist -- list of other nodes that we know have acknowledged a write of this block, usefull in the rebalancing algorithm - -Write strategy: have a single thread that does all write IO so that it is serialized (or have several threads that manage independent parts of the hash space). When writing a blob, write it to a temporary file, close, then rename so that a concurrent read gets a consistent result (either not found or found with whole content). - -Read strategy: the only read operation is get(hash) that returns either the data or not found (can do a corruption check as well and return corrupted state if it is the case). Can be done concurrently with writes. - -**Internal API:** - -- get(block hash) -> ok+data/not found/corrupted -- put(block hash & data, version uuid + offset) -> ok/error -- put with no data(block hash, version uuid + offset) -> ok/not found plz send data/error -- delete(block hash, version uuid + offset) -> ok/error - -GC: when last ref is deleted, delete block. -Long GC procedure: check in Cassandra that version UUIDs still exist and references this block. - -Rebalancing: takes as argument the list of newly added nodes. - -- List all blocks that we have. For each block: -- If it hits a newly introduced node, send it to them. - Use put with no data first to check if it has to be sent to them already or not. - Use a random listing order to avoid race conditions (they do no harm but we might have two nodes sending the same thing at the same time thus wasting time). -- If it doesn't hit us anymore, delete it and its reference list. - -Only one balancing can be running at a same time. It can be restarted at the beginning with new parameters. - -#### Membership management - -Two sets of nodes: - -- set of nodes from which a ping was recently received, with status: number of stored blocks, request counters, error counters, GC%, rebalancing% - (eviction from this set after say 30 seconds without ping) -- set of nodes that are part of the system, explicitly modified by the operator using the web UI (persisted to disk), - is a CRDT using a version number for the value of the whole set - -Thus, three states for nodes: - -- healthy: in both sets -- missing: not pingable but part of desired cluster -- unused/draining: currently present but not part of the desired cluster, empty = if contains nothing, draining = if still contains some blocks - -Membership messages between nodes: - -- ping with current state + hash of current membership info -> reply with same info -- send&get back membership info (the ids of nodes that are in the two sets): used when no local membership change in a long time and membership info hash discrepancy detected with first message (passive membership fixing with full CRDT gossip) -- inform of newly pingable node(s) -> no result, when receive new info repeat to all (reliable broadcast) -- inform of operator membership change -> no result, when receive new info repeat to all (reliable broadcast) - -Ring: generated from the desired set of nodes, however when doing read/writes on the ring, skip nodes that are known to be not pingable. -The tokens are generated in a deterministic fashion from node IDs (hash of node id + token number from 1 to K). -Number K of tokens per node: decided by the operator & stored in the operator's list of nodes CRDT. Default value proposal: with node status information also broadcast disk total size and free space, and propose a default number of tokens equal to 80%Free space / 10Gb. (this is all user interface) - - -#### Constants - -- Block size: around 1MB ? --> Exoscale use 16MB chunks -- Number of tokens in the hash ring: one every 10Gb of allocated storage -- Threshold for storing data directly in Cassandra objects table: 1kb bytes (maybe up to 4kb?) -- Ping timeout (time after which a node is registered as unresponsive/missing): 30 seconds -- Ping interval: 10 seconds -- ?? - -#### Links - -- CDC: <https://www.usenix.org/system/files/conference/atc16/atc16-paper-xia.pdf> -- Erasure coding: <http://web.eecs.utk.edu/~jplank/plank/papers/CS-08-627.html> -- [Openstack Storage Concepts](https://docs.openstack.org/arch-design/design-storage/design-storage-concepts.html) -- [RADOS](https://ceph.com/wp-content/uploads/2016/08/weil-rados-pdsw07.pdf) |