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Distributed Transactions (XA / 2PC)

CRDTs make a single key converge without coordination. But some updates must span several keys and be all-or-nothing: move a balance from one account object to another, or write an object and its index entry together so a reader never sees one without the other. Riak’s per-key model had no answer for that – a multi-key atomic write in Riak would have needed a consensus layer it did not ship. Dyniak adds one, built on the transactional Noxu engine underneath it.

This chapter covers the two transaction paths Dyniak offers: the heavyweight two-phase commit (XA) path for full atomicity across nodes, and the lighter read-atomic (RAMP) path for the common “see all of a batch or none of it” case without blocking.

The two layers

A multi-key transaction stacks in two layers, and which one runs depends on where the keys live:

flowchart TB
  B[TxnBatch: put a, put b, delete c] --> R{keys owned by<br/>one node or many?}
  R -->|one node| L1[Layer 1:<br/>single-environment<br/>one engine transaction]
  R -->|many nodes| L2[Layer 2:<br/>cross-node XA<br/>two-phase commit]
  L1 --> C1[commit or roll back atomically]
  L2 --> C2[prepare all branches, then commit all]

A batch whose keys all land on one node commits in a single Noxu engine transaction. A batch that spans nodes is coordinated with X/Open XA two-phase commit over the DNODE peer plane.

Layer 1: single-environment
Every op in the batch routes to one node's Noxu environment and commits inside one engine transaction. Simple, fast, fully atomic.
Layer 2: cross-node XA
The batch touches keys owned by different primary nodes. Each node prepares its branch; the coordinator commits every branch only once every prepare has voted to commit. This is X/Open two-phase commit.

The client does not choose a layer. It submits a batch; the coordinator partitions the ops by owning node and picks the cheapest correct path.

Submitting a transaction

Over HTTP, a transaction is a JSON batch to POST /transactions (cluster-wide) or POST /buckets/{bucket}/transactions (bucket-scoped, where every op must target the URL’s bucket):

curl -s -X POST http://127.0.0.1:8098/transactions \
  -H 'Content-Type: application/json' \
  -d '{
    "operations": [
      {"op": "put", "bucket": "accounts", "key": "alice",
       "value": "balance=90",
       "indexes": [{"name": "owner_bin", "value": "alice"}]},
      {"op": "put", "bucket": "accounts", "key": "bob",
       "value": "balance=110"},
      {"op": "delete", "bucket": "pending", "key": "xfer-7"}
    ]
  }'

A committed batch replies 200 OK:

{"result": "committed", "operations": 3}

The ops are replayed in order inside the transaction. A put carries an optional list of 2i entries, fanned into the secondary-index layer as part of the same atomic unit, so the object and its index land together or not at all.

Note

JSON values are UTF-8; use PBC for binary

The JSON transaction endpoint carries values and index values as UTF-8 strings. Arbitrary binary payloads are not representable through JSON; the PBC transaction extension carries raw bytes. This is the same limitation the object endpoints have when you choose JSON encoding.

The abort path

A batch with "abort": true applies every op inside the transaction and then deliberately rolls back, leaving the keyspace untouched. It exists so clients and tests can exercise the rollback path deterministically:

curl -s -X POST http://127.0.0.1:8098/transactions \
  -H 'Content-Type: application/json' \
  -d '{"abort": true, "operations": [
        {"op": "put", "bucket": "b", "key": "k", "value": "v"}]}'

{"result": "aborted", "reason": "client requested abort"}

A batch that the engine rolls back because of a serialization conflict replies 409 Conflict; the client may retry. A datastore that is not transactional (any backend other than the Noxu-backed one) replies 501 Not Implemented.

The two-phase commit protocol

When a batch spans nodes, the coordinator runs X/Open XA. Each node is one resource manager backed by its own Noxu environment; the coordinator is the transaction manager.

sequenceDiagram
  participant C as coordinator
  participant E as branch east
  participant W as branch west
  Note over C: partition ops by owning node
  C->>E: xa_start, apply east ops, xa_end
  C->>W: xa_start, apply west ops, xa_end
  C->>E: xa_prepare
  E-->>C: vote OK
  C->>W: xa_prepare
  W-->>C: vote OK
  Note over C: every prepare voted OK -> commit
  C->>E: xa_commit
  C->>W: xa_commit
  E-->>C: done
  W-->>C: done

Two-phase commit across two branches. Work is applied and each branch is prepared; only after every branch votes to commit does the coordinator issue the commits. A single "no" vote (or a force-abort) rolls back every prepared branch.

Three details make this robust against the network failure modes a single-process commit never sees:

  • Read-only optimization. A branch that performed no writes votes read-only on prepare and skips the second phase entirely – no commit round for a branch that changed nothing.
  • Presumed abort. If a prepare fails or times out, the coordinator presumes abort and rolls back every branch already prepared. No branch is left holding a prepared-but-undecided transaction.
  • Commit-in-doubt recovery. A branch that voted to commit is recorded in a durable in-doubt log. If the coordinator crashes after the commit decision but before every branch confirmed, a cold restart re-reads the log and forward-recovers each in-doubt branch, so a branch that voted to commit is never left dangling.

The local-branch machinery (XaParticipant, one per node) is shared verbatim between the in-process coordinator and the cross-node coordinator; only the transport differs. The cross-node coordinator drives the identical prepare-then-commit phases over the DNODE peer plane described in Dyniak wire protocols.

Note

Road not taken: 2PC, not Paxos or Raft, for cross-node transactions

Two-phase commit is famously blocking: if the coordinator fails at the wrong instant, a prepared branch can be stuck until recovery runs. Consensus protocols like Paxos or Raft are non-blocking under the same failure. So why 2PC?

First, the failure window is narrow and Dyniak closes it with the durable in-doubt log and automatic cold-restart recovery above – a branch that voted to commit always reaches a decision. Second, Dyniak’s whole design bet is distribution as a thin layer over a transactional storage engine: Noxu already implements XA branches with a durable prepared-transaction log, so 2PC is a thin coordinator over machinery that exists, whereas a per-transaction consensus group would be a large new subsystem duplicating what Noxu already guarantees locally. Third, a Raft-per-key or Raft-per-transaction design is exactly the strong-consistency subsystem Dyniak deliberately leaves out of scope (Riak’s riak_ensemble); adopting it for transactions would drag the whole store toward a consistency model it does not promise. The full argument is in Roads Not Taken.

The read-atomic path (RAMP)

Full 2PC is the right tool when you need serializable atomicity, but it is heavy: it blocks, it coordinates, it commits in two rounds. For the very common case of “read several keys and see a consistent snapshot, or write several keys so no reader ever sees a partial batch,” Dyniak offers a lighter path: RAMP-Fast (Bailis et al., SIGMOD 2014).

RAMP guarantees read-atomic isolation: a transaction sees all of another transaction’s writes or none of them – never a fractured read where you observe transaction T’s write to key a but miss its write to key b. Crucially, a reader never blocks on a writer.

sequenceDiagram
  participant Wr as writer
  participant Rd as reader
  Note over Wr: pick one timestamp ts for the whole batch
  Wr->>Wr: PREPARE: write each key at ts (invisible),<br/>metadata = sibling keys
  Wr->>Wr: COMMIT: advance each key's visible pointer to ts
  Rd->>Rd: round 1: read latest-visible + metadata for all keys
  alt no fracture detected
    Note over Rd: snapshot is already atomic
  else metadata names a newer sibling
    Rd->>Rd: round 2: fetch exactly the missing versions by ts
  end
  Note over Rd: fracture-free snapshot

RAMP-Fast. Writes are two-phase but non-blocking: prepare writes invisible versions, commit advances the visible pointers. Reads take one round plus a conditional second round only when the first round detects a fracture. In the contention-free case the second round is skipped.

A RAMP write picks one monotonic timestamp for the whole batch, writes every key as an invisible versioned record carrying the set of sibling keys, then advances each key’s visible pointer. A RAMP read fetches the latest visible version plus metadata for every key; if any version’s metadata names a sibling the reader saw at an older version, round 2 fetches exactly those missing versions – which prepare guarantees are present – and the repaired snapshot is fracture-free.

Over HTTP:

# atomic multi-key write
curl -s -X POST http://127.0.0.1:8098/ramp/transactions \
  -H 'Content-Type: application/json' \
  -d '{"writes": [{"bucket": "b", "key": "a", "value": "1"},
                  {"bucket": "b", "key": "b", "value": "2"}]}'
# {"result":"committed","ts":<timestamp>,"keys":2}

# atomic multi-key read (fracture-free snapshot)
curl -s -X POST http://127.0.0.1:8098/ramp/read \
  -H 'Content-Type: application/json' \
  -d '{"keys": [{"bucket": "b", "key": "a"}, {"bucket": "b", "key": "b"}]}'
# {"snapshot": {"a": "1", "b": "2"}, "rounds": 1}

The response reports rounds (1 or 2) so you can see when the read hit contention.

XA versus RAMP: which to use

Use XA / 2PC when
You need full atomicity with the possibility of rollback on conflict -- move money, enforce an invariant across keys, write an object and its index as one unit that can fail cleanly.
Use RAMP when
You need a consistent multi-key snapshot or an all-or-nothing multi-key write, but you do not need to abort on conflict and you want readers never to block. Lower latency, availability-native.
Use a single CRDT when
The update is confined to one key. No transaction needed -- the merge is automatic. See Convergent Data Types.

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