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SeaStar is an event-driven framework allowing you to write non-blocking, asynchronous code in a relatively straightforward manner (once understood). It is based on futures.
Installing GCC 4.9 for gnu++1y:
- Beware that this installation will replace your current GCC version.
yum install fedora-release-rawhide
yum --enablerepo rawhide update gcc-c++
yum --enablerepo rawhide install libubsan libasan
Installing required packages:
yum install libaio-devel ninja-build ragel hwloc-devel numactl-devel
You then need to run the following to create the "build.ninja" file:
./configure.py
Note it is enough to run this once, and you don't need to repeat it before every build. build.ninja includes a rule which will automatically re-run ./configure.py if it changes.
Then finally:
ninja-build
To build a Docker image:
docker build -t seastar-dev .
To launch a container:
$ docker run -v $HOME/seastar/:/seastar -i -t seastar-dev /bin/bash
Finally, to build seastar inside the container:
cd /seastar
ninja-build
A future is a result of a computation that may not be available yet. Examples include:
- a data buffer that we are reading from the network
- the expiration of a timer
- the completion of a disk write
- the result computation that requires the values from one or more other futures.
a promise is an object or function that provides you with a future, with the expectation that it will fulfill the future.
Promises and futures simplify asynchronous programming since they decouple the event producer (the promise) and the event consumer (whoever uses the future). Whether the promise is fulfilled before the future is consumed, or vice versa, does not change the outcome of the code.
You consume a future by using its then() method, providing it with a callback (typically a lambda). For example, consider the following operation:
future<int> get(); // promises an int will be produced eventually
future<> put(int) // promises to store an int
void f() {
get().then([] (int value) {
put(value + 1).then([] {
std::cout << "value stored successfully\n";
});
});
}
Here, we initate a get() operation, requesting that when it completes, a put() operation will be scheduled with an incremented value. We also request that when the put() completes, some text will be printed out.
If a then() lambda returns a future (call it x), then that then() will return a future (call it y) that will receive the same value. This removes the need for nesting lambda blocks; for example the code above could be rewritten as:
future<int> get(); // promises an int will be produced eventually
future<> put(int) // promises to store an int
void f() {
get().then([] (int value) {
return put(value + 1);
}).then([] {
std::cout << "value stored successfully\n";
});
}
Loops are achieved with a tail call; for example:
future<int> get(); // promises an int will be produced eventually
future<> put(int) // promises to store an int
future<> loop_to(int end) {
if (value == end) {
return make_ready_future<>();
}
get().then([end] (int value) {
return put(value + 1);
}).then([end] {
return loop_to(end);
});
}
The make_ready_future() function returns a future that is already available --- corresponding to the loop termination condition, where no further I/O needs to take place.
When the loop above runs, both then method calls execute immediately --- but without executing the bodies. What happens is the following:
-
get()
is called, initiates the I/O operation, and allocates a temporary structure (call itf1
). - The first
then()
call chains its body tof1
and allocates another temporary structure,f2
. - The second
then()
call chains its body tof2
.
Again, all this runs immediately without waiting for anything.
After the I/O operation initiated by get()
completes, it calls the
continuation stored in f1
, calls it, and frees f1
. The continuation
calls put()
, which initiates the I/O operation required to perform
the store, and allocates a temporary object f12
, and chains some glue
code to it.
After the I/O operation initiated by put()
completes, it calls the
continuation associated with f12
, which simply tells it to call the
continuation assoicated with f2
. This continuation simply calls
loop_to()
. Both f12
and f2
are freed. loop_to()
then calls
get()
, which starts the process all over again, allocating new versions
of f1
and f2
.
If a .then()
clause throws an exception, the scheduler will catch it
and cancel any dependent .then()
clauses. If you want to trap the
exception, add a .rescue()
clause at the end:
future<buffer> receive();
request parse(buffer buf);
future<response> process(request req);
future<> send(response resp);
void f() {
receive().then([] (buffer buf) {
return process(parse(std::move(buf));
}).then([] (response resp) {
return send(std::move(resp));
}).then([] {
f();
}).rescue([] (auto get_ex) {
try {
get_ex();
} (catch std::exception& e) {
// your handler goes here
}
});
}
When the get_ex
variable is called as a function, it will rethrow
the exception that aborted processing, and you can then apply any
needed error handling. It is essentially a transformation of
buffer receive();
request parse(buffer buf);
response process(request req);
void send(response resp);
void f() {
try {
while (true) {
auto req = parse(receive());
auto resp = process(std::move(req));
send(std::move(resp));
}
} catch (std::exception& e) {
// your handler goes here
}
}