Specify stuff about causality tokens (aka contexts)
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# Specification of the Garage K2V API (K2V = Key/Key/Value)
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- We are storing triplets of the form `(partition key, sort key, value)` -> no
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well as [here](https://github.com/ricardobcl/Dotted-Version-Vectors)
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## Data format
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### Triple format
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Triples in K2V are constituted of three fields:
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- a partition key (`pk`), an utf8 string that defines in what partition the triple is
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stored; triples in different partitions cannot be listed together, they must
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be the object of different ReadItem or ReadBatch queries
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- a sort key (`sk`), an utf8 string that defines the index of the triple inside its
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partition; triples are uniquely idendified by their partition key + sort key
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- a value (`v`), an opaque binary blob associated to the partition key + sort key;
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they are transmitted as binary when possible but in most case in the JSON API
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they will be represented as strings using base64 encoding; a value can also
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be `null` to indicate a deleted triple (a `null` value is called a tombstone)
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### Causality information
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K2V supports storing several concurrent values associated to a pk+sk, in the
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case where insertion or deletion operations are detected to be concurrent (i.e.
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there is not one that was aware of the other, they are not causally dependant
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one on the other). In practice, it even looks more like the opposite: to
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overwrite a previously existing value, the client must give a "causality token"
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that "proves" (not in a cryptographic sense) that it had seen a previous value.
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Otherwise, the value written will not overwrite an existing value, it will just
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create a new concurrent value.
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The causality token is a binary/b64-encoded representation of a context,
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specified below.
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A set of concurrent values looks like this:
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```
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(node1, tdiscard1, (v1, t1), (v2, t2)) ; tdiscard1 < t1 < t2
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(node2, tdiscard2, (v3, t3) ; tdiscard2 < t3
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```
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`tdiscard` for a node `i` means that all values inserted by node `i` with times
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`<= tdiscard` are obsoleted, i.e. have been read by a client that overwrote it
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afterwards.
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The associated context would be the following: `[(node1, t2), (node2, t3)]`,
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i.e. if a node reads this set of values and inserts a new values, we will now
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have `tdiscard1 = t2` and `tdiscard2 = t3`, to indicate that values v1, v2 and v3
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are obsoleted by the new write.
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**Basic insertion.** To insert a new value `v4` with context `[(node1, t2), (node2, t3)]`, in a
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simple case where there was no insertion in-between reading the value
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mentionned above and writing `v4`, and supposing that node2 receives the
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InsertItem query:
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- `node2` generates a timestamp `t4` such that `t4 > t3`.
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- the new state is as follows:
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```
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(node1, tdiscard1', ()) ; tdiscard1' = t2
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(node2, tdiscard2', (v4, t4)) ; tdiscard2' = t3
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```
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**A more complex insertion example.** In the general case, other intermediate values could have
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been written before `v4` with context `[(node1, t2), (node2, t3)]` is sent to the system.
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For instance, here is a possible sequence of events:
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1. First we have the set of values v1, v2 and v3 described above.
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A node reads it, it obtains values v1, v2 and v3 with context `[(node1, t2), (node2, t3)]`.
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2. A node writes a value `v5` with context `[(node1, t1)]`, i.e. `v5` is only a successor of v1 but not of v2 or v3. Suppose node1 receives the write, it will generate a new timestamp `t5` larger than all of the timestamps it knows of, i.e. `t5 > t2`. We will now have:
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```
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(node1, tdiscard1'', (v2, t2), (v5, t5)) ; tdiscard1'' = t1 < t2 < t5
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(node2, tdiscard2, (v3, t3) ; tdiscard2 < t3
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```
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3. Now `v4` is written with context `[(node1, t2), (node2, t3)]`, and node2 processes the query. It will generate `t4 > t3` and the state will become:
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```
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(node1, tdiscard1', (v5, t5)) ; tdiscard1' = t2 < t5
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(node2, tdiscard2', (v4, t4)) ; tdiscard2' = t3
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```
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**Generic algorithm for handling insertions:** A certain node i handles the InsertItem and is responsible for the correctness of this procedure.
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1. Lock the key (or the whole table?) at this node to prevent concurrent updates of the value that would mess things up
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2. Read current set of values
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3. Generate a new timestamp that is larger than the largest timestamp for node i
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4. Add the inserted value in the list of values of node i
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5. Update the discard times to be the times set in the context, and accordingly discard overwritten values
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6. Release lock
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7. Propagate updated value to other nodes
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8. Return to user when propagation achieved the write quorum (propagation to other nodes continues asynchronously)
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**Encoding of contexts:**
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Contexts consist in a list of (node id, timestamp) pairs.
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They are encoded in binary as follows:
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```
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checksum: u64, [ node: u64, timestamp: u64 ]*
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```
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The checksum is just the XOR of all of the node IDs and timestamps.
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Once encoded in binary, contexts are written and transmitted in base64.
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### Indexing
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K2V keeps an index, a secondary data structure that is updated asynchronously,
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that keeps tracks of the number of triples stored for each partition key.
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This allows easy listing of all of the partition keys for which triples exist
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in a bucket, as the partition key becomes the sort key in the index.
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TODO: writeup asynchronous counting strategy
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## API Endpoints
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