random_slicing

Source: crates/dynomite/examples/random_slicing.rs -- run with cargo run -p dynomite --example random_slicing

What it demonstrates

How the dispatcher turns a key into an owning peer, and how the random-slicing distribution mode spreads keys across peers. It builds the ring by hand -- four peers, one rack, one datacenter -- and then asks the dispatcher to plan 10,000 requests, counting where each lands.

#![allow(unused)]
fn main() {
let cfg = PoolConfig {
    dc: "dc1".into(),
    rack: "r1".into(),
    hash: HashType::Murmur3X64_64,
    distribution: Distribution::RandomSlicing,
    ..PoolConfig::default()
};
// ... build four Peers, mark them Normal, rebuild the ring ...
let disp = ClusterDispatcher::new(pool);

for i in 0..10_000 {
    let req = Msg::new(i as u64, MsgType::ReqRedisGet, true);
    let key = format!("key-{i:08x}");
    match disp.plan(&req, key.as_bytes()) {
        DispatchPlan::Replicas { targets, .. } => counts[targets[0].peer_idx as usize] += 1,
        DispatchPlan::LocalDatastore => counts[0] += 1,
        DispatchPlan::NoTargets | DispatchPlan::Drop => {}
    }
}
}

The output is a histogram of ownership -- the same information the operator command dyn-admin distribution-dump reports for a live cluster.

Design decisions and trade-offs

Hand-built pool, no server

This example constructs ServerPool and ClusterDispatcher directly rather than through ServerBuilder. It is studying the routing layer in isolation, so it skips listeners, gossip, and backends entirely.

DispatchPlan exposed

Matching on DispatchPlan::{Replicas, LocalDatastore, NoTargets, Drop} shows the four outcomes the planner can produce for a key. Only the first replica is counted here, which measures primary ownership.

10,000 synthetic keys

Enough to see the distribution shape without being slow. A perfectly even split would be 2,500 per peer; the spread from that is the point of comparing distribution modes.

When to use this pattern

When you want to reason about or test routing and ownership without standing up a cluster: comparing distribution modes, checking that a token assignment balances, or unit-testing changes to the dispatcher.

Where to go next

• The Ring and the Token Space explains the token math this example exercises.
• Distribution Modes compares random slicing against the alternatives.