slacker
slacker is a simple RPC framework designed for Clojure and created by Clojure.
Features
- Fast network layer, fully asynchronous and multiplexed
- Plugable serialization backend, EDN, JSON and Nippy are built-in.
- Transparent and non-incursive API. Calling remote is just like local invocation.
- Extensible server and client with interceptor framework.
- Flexible cluster with Zookeeper (moved to slacker-cluster)
Slacker family
- slacker-cluster Slacker cluster, service discovery with Zookeeper, and custom grouping call.
- slacker-metrics Codahale's metrics collector as a slacker interceptor. It measures QPS and latency for every function exposed.
- slacker-htrace Distributed tracing for slacker.
- slacker-rust An experimental slacker RPC implementation in Rust.
- slacker-python A limited python library for calling slacker functions.
Examples
A pair of example server/client can be found under "examples", you
can run the examples by lein run-example-server
and
lein run-example-client
. The example client will print out various
outputs from the server as well as a RuntimeException: "Expected exception."
This exception is part of the example - not a genuine error in the slacker
source code.
Usage
Leiningen
Basic Usage
Slacker will expose all your public functions under a given namespace.
(ns slapi)
(defn timestamp
"return server time in milliseconds"
[]
(System/currentTimeMillis))
;; ...more functions
To expose slapi
from port 2104, use:
(use 'slacker.server)
(start-slacker-server [(the-ns 'slapi)] 2104)
Multiple namespaces can be exposed by appending them to the vector
You can also add option :threads 50
to configure the size of server
thread pool.
On the client side, You can use defn-remote
to create facade one by
one. Remember to add remote namespace here as facade name,
slapi/timestamp
, eg. Otherwise, the name of current namespace will
be treated as remote namespace.
(use 'slacker.client)
(def sc (slackerc "localhost:2104"))
(defn-remote sc slapi/timestamp)
(timestamp)
Also the use-remote
function is convenience for importing all functions
under a remote namespace. (Note that use-remote
uses inspection
calls to fetch remote functions, so network is required.)
(use-remote 'sc 'slapi)
(timestamp)
By checking the metadata of timestamp
, you can get some useful
information:
(slacker-meta timestamp)
=> {:slacker-remote-name "timestamp", :slacker-remote-fn true,
:slacker-client #<SlackerClient
slacker.client.common.SlackerClient@575752>, :slacker-remote-ns
"slapi" :arglists ([]), :name timestamp
:doc "return server time in milliseconds"}
Advanced Usage
Options in defn-remote
You can specify the remote function name when there are conflicts in current namespace.
(defn-remote sc remote-time
:remote-ns "slapi"
:remote-name "timestamp")
If you add an :async?
flag to defn-remote
, then the facade will be
asynchronous which returns a promise when you call it. You should
deref it by yourself to get the return value.
(defn-remote sc slapi/timestamp :async? true)
@(timestamp)
You can also assign a callback (fn [error result])
for an
asynchronous facade.
(defn-remote sc slapi/timestamp :callback #(println %2))
(timestamp)
The callback accepts two arguments
- error
- result
You need to check (nil? error) because reading the result. Also note that doing blocking tasks in callback function could ruin system performance.
Serialiation
Slacker provides plugable serialization support. From 0.13, Slacker
uses Clojure EDN as default serializer, because it doesn't introduce
in additional dependencies. Also Slacker provides built-in support for
cheshire (json) and
nippy. Personally I
recommend you to use :nippy
in real applications because it's
fast and compact.
JSON Serialization
JSON is a text based format which is more friendly to human beings. It may be useful for debugging, or communicating with external applications. In order to use JSON, be sure to include any version of cheshire in your classpath, because Slacker doesn't depend on it at compile time.
Configure slacker client to use JSON:
(def sc (slackerc "localhost:2104" :content-type :json))
One thing you should note is the representation of keyword in JSON. Keywords and strings are both encoded as JSON string in transport. But while decoding, all map keys will be decoded to keyword, and all other strings will be decoded to clojure string.
EDN Serialization
From slacker 0.4, clojure pr/read is supported. And then in 0.13, EDN
becomes default serialization. You can just set content-type as
:clj
. clojure pr/read has full support on clojure data structures
and also easy for debugging. However, it's much slower and verbose
than binary format, so you'd better not use it if you have critical
performance requirements.
Nippy Serialization
Slacker 0.13 and above has full support for
nippy serialization. Remember
to add nippy into your classpath and set the content-type as :nippy
to use it. Nippy has excellent support for custom types, you can find
detailed information on its page.
Interceptor
To add custom functions on server and client, you can define custom interceptors before or after function called.
(definterceptor logging-interceptor
:before (fn [req] (println (str "calling: " (:fname req))) req))
(start-slacker-server (the-ns 'slapi) 2104
:interceptors (interceptors logging-interceptor))
For more information about using interceptors and creating your own interceptors, query the wiki page.
Here we have two typical demo middlewares:
- The metrics middleware integrates metrics-clojure into slacker server.
- The htrace middleware enables htrace distributed tracing on both server and client side.
Slacker on HTTP
From 0.4, slacker can be configured to run on HTTP protocol. To
enable HTTP transport, just add a :http
option to your slacker
server:
(start-slacker-server ...
:http 4104)
The HTTP url pattern is http://localhost:4104/*namespace*/*function-name*.*format*. Arguments are encoded in format, and posted to server via HTTP body. If you have multiple arguments, you should put them into a clojure vector (for clj format) or javascript array (for json format).
See a curl example:
$ curl -d "[5]" http://localhost:4104/slapi/rand-ints.clj
(38945142 1413770549 1361247669 1899499977 1281637740)
Note that you can only use json
or clj
as format.
Slacker as a Ring App
You can also use slacker as a ring app with
slacker.server/slacker-ring-app
. The ring app is fully compatible
with ring spec. So it could be deployed on any ring adapter.
(use 'slacker.server)
(use 'ring.adapter.jetty)
(run-jetty (slacker-ring-app (the-ns 'slapi)) {:port 8080})
The url pattern of this ring app is same as slacker's built-in http module.
Custom client on function call
One issue with previous version of slacker is you have to define a remote function with a slacker client, then call this function with that client always. This is inflexible.
From 0.10.3, we added a macro with-slackerc
to isolate local
function facade and a specific client. You can call the function with
any slacker client.
;; conn0 and conn1 are two slacker clients
(defn-remote conn0 timestamp)
;; call the function with conn0
(timestamp)
;; call the function with conn1
(with-slackerc conn1
(timestamp))
Note that you have ensure that the function you call is also available
to the client. Otherwise, there will be a not-found
exception
raised.
API Documentation
Performance
To test performance, just start an example server with lein run -m slacker.example.server
.
Then run the performance test script:
lein exec -p scripts/performance-test.clj 200000 40
. This will run
200,000 calls with 40 threads.
Tested on my laptop(i7-5600U), 200,000 calls with 40 threads is completed in 12677.487741 msecs, which means slacker could handle more than 15700 calls per second on this machine.
License
Copyright (C) 2011-2019 Sun Ning
Distributed under the Eclipse Public License, the same as Clojure.
Donation
I'm now accepting donation on liberapay, if you find my work helpful and want to keep it going.