Execute a distributed computation inside a TransIO computation. All the computations in the TransIO monad that enclose the cloud computation must be logged

Run a distributed computation inside the IO monad. Enables asynchronous console input (see keep).

Run a distributed computation inside the IO monad with no console input.

Create a node from a hostname (or IP address), port number and a list of services.

Add a node (first parameter) to the cluster using a node that is already part of the cluster (second parameter). The added node starts listening for incoming connections and the rest of the computation is executed on this newly added node.

Reconcile the list of nodes in the cluster using a remote node already part of the cluster. Reconciliation end up in each node in the cluster having the same list of nodes.

Setup the node to start listening for incoming connections.

Add a list of nodes to the list of existing cluster nodes.

Shuffle the list of cluster nodes and return the shuffled list.

Return the local node i.e. the node where this computation is running.

Return the list of nodes in the cluster.

Returns True if we are running in the browser.

Means that this computation will be executed in the current node. the result will be logged so the closure will be recovered if the computation is translated to other node by means of primitives like beamTo, forkTo, runAt, teleport, clustered, mclustered etc

alternative to local It means that if the computation is translated to other node this will be executed again if this has not been executed inside a local computation.

onAll foo
local foo'
local $ do
      bar
      runCloud $ do
              onAll baz
              runAt node ....
callTo node' .....

Here foo will be executed in node' but foo' bar and baz don't.

However foo bar and baz will e executed in node.

only executes if the result is demanded. It is useful when the conputation result is only used in the remote node, but it is not serializable.

executes a non-serilizable action in the remote node, whose result can be used by subsequent remote invocations

the Cloud monad has no MonadIO instance. `lliftIO= local . liftIO`

`localIO = lliftIO`

stop the current computation and does not execute any alternative computation

A wormhole opens a connection with another node anywhere in a computation. teleport uses this connection to translate the computation back and forth between the two nodes connected

copy a session data variable from the local to the remote node. If there is none set in the local node, The parameter is the default value. In this case, the default value is also set in the local node.

experimental: subsequent remote invocatioms will send logs to this closure. Therefore logs will be shorter.

Also, non serializable statements before it will not be re-executed

continue the execution in a new node

execute in the remote node a process with the same execution state

open a wormhole to another node and executes an action on it. currently by default it keep open the connection to receive additional requests and responses (streaming)

Execute a computation in the node that initiated the connection.

if the sequence of connections is n1 -> n2 -> n3 then `atCallingNode $ atCallingNode foo` in n3 would execute foo in n1, -- while `atRemote $ atRemote foo` would execute it in n3 atCallingNode :: Loggable a => Cloud a -> Cloud a atCallingNode proc= connectCaller $ atRemote proc

synonymous of callTo

Within a connection to a node opened by wormhole, it run the computation in the remote node and return the result back to the original node.

If atRemote is executed in the remote node, then the computation is executed in the original node

wormhole node2 $ do
    t <- atRemote $ do
          r <- foo              -- executed in node2
          s <- atRemote bar r   -- executed in the original node
          baz s                 -- in node2
    bat t                      -- in the original node

execute a Transient action in each of the nodes connected.

The response of each node is received by the invoking node and processed by the rest of the procedure. By default, each response is processed in a new thread. To restrict the number of threads use the thread control primitives.

this snippet receive a message from each of the simulated nodes:

main = keep $ do
   let nodes= map createLocalNode [2000..2005]
   addNodes nodes
   (foldl (<|>) empty $ map listen nodes) <|> return ()

   r <- clustered $ do
              Connection (Just(PortNumber port, _, _, _)) _ <- getSData
              return $ "hi from " ++ show port++ "\n"
   liftIO $ putStrLn r
   where
   createLocalNode n= createNode "localhost" (PortNumber n)

write to the mailbox Mailboxes are node-wide, for all processes that share the same connection data, that is, are under the same listen or connect while EVars are only visible by the process that initialized it and his children. Internally, the mailbox is in a well known EVar stored by listen in the Connection state.

write to a mailbox identified by an identifier besides the type

get messages from the mailbox that matches with the type expected. The order of reading is defined by readTChan This is reactive. it means that each new message trigger the execution of the continuation each message wake up all the getMailbox computations waiting for it.

read from a mailbox identified by an identifier besides the type

delete all subscriptions for that mailbox expecting this kind of data

clean a mailbox identified by an Int and the type

run a single thread with that action for each connection created. When the same action is re-executed within that connection, all the threads generated by the previous execution are killed

  box <-  foo
  r <- runAt node . local . single $ getMailbox box
  localIO $ print r

if foo return differnt mainbox indentifiers, the above code would print the messages of the last one. Without single, it would print the messages of all of them.

run an unique continuation for each connection. The first thread that execute unique is executed for that connection. The rest are ignored.