Partition Client

Data can be spread across multiple OrigoDb Server nodes, aka sharding or horizontal data partitioning. Partition logic is handled by PartitionClusterClient, the process is entirely transparent to the server instances. The client maintains a list of nodes, dispatches queries and commands to one or more nodes and merges results from multiple nodes.


By default, the client dispatches each command and query to every node. Set a custom dispatcher for command or query type T by calling SetDispatcherFor<T>(Func<T,int> dispatcher) or SetDispatcherFor<T>(Func<T,int[]> dispatcher). The dispatcher must return either a zero-based index of the target node or an array of node indices for dispatching to multiple nodes.


Results from commands and queries need to be aggregated. Register a merger function by calling SetMergerFor<T>() where T can be a command, query or result type. The function takes an array of the expected result type and must return an instance of the return type. For a query with the signature Query<M,R> a merger must have the signature Func<R[],R>. A merger with the wrong signature will throw a runtime exception.

Example code

var client = new PartitionClusterClient<TaskModel>();
var node0 = Engine.For<TaskModel>("mode=embedded;host=node1");
var node1 = Engine.For<TaskModel>("mode=embedded;host=node2");

//add nodes to the partition cluster client, usually these would be instances of `IRemoteEngine`

// Set dispatchers for each command and query type, default is to send to all nodes
client.SetDispatcherFor<AddTaskCommand>(command => command.Id % 2);
client.SetDispatcherFor<GetTaskByIdQuery>(query => query.Id % 2);

//Register merger functions by return type
client.SetMergerFor<TaskView[]>(Func<TaskView[][], TaskView[]> taskViews => {
  var list = new List<TaskView>();
  foreach(TaskView[] nodeResult in taskViews) list.AddRange(nodeResult);
  return list.ToArray();

//merger for query type takes precedence over merger for result type
  Func<TaskView[][], TaskView[]> taskViews =>
    var list = new List<TaskView>();
    foreach(TaskView[] nodeResult in taskViews) list.AddRange(nodeResult);
    list.Sort(t => t.DueBy);
    return list.Reverse().Take(10).ToArray();

Using the client

//execute commands. They will be dispatched to the correct nodes
client.Execute(new AddTaskCommand{
  Id = 1,
  Name="Play squash",

client.Execute(new AddTaskCommand{
  Id = 2,
  Name="Write some code",
  Categories = "Recreation"});

//query gets dispatched to the correct node
var taskView = client.Execute(new GetTaskByIdQuery{Id = 2});

//send query to all nodes, merge results from each node
//using merger registered for the type TaskView[]
var query = new GetTasksByCategoryQuery("Recreation");
var tasksByCatetory = client.Execute<TaskModel, TaskView[]>(query);

Partitioning schemes

The example above partitions using a modulus function and changing the number of nodes will affect the partitioning. Design a scheme that will accommodate for growth without the need to move data between nodes. For an example, see the GeekStream model, which is designed for partitioning.

Partitioning and ACID

When partitioning, atomicity, isolation and consistency are not necessarily guaranteed. Design accordingly.