The document discusses the integration of user-defined functions in ScyllaDB using WebAssembly, highlighting the benefits of low latency and efficiency. It outlines the capabilities for creating user-defined aggregates and provides examples of their usage with data manipulations. Additionally, it covers the design of a minimalistic runtime for asynchronous Rust and C++, emphasizing compatibility and performance in computational tasks.

1. Brought to you by
Keeping Latency Low
for User-Defined Functions
with WebAssembly
Piotr Sarna
Principal Software Engineer

2. Piotr Sarna
Principal Software Engineer at ScyllaDB
■ Keen on open-source projects, C++ and Rust
■ Used to develop a distributed file system
■ Wrote a few patches for the Linux kernel
■ MSc in Computer Science from University of Warsaw
■ Maintainer of the ScyllaDB Rust Driver project

3. Motivation

4. User-defined functions
ScyllaDB allows users to define their own functions for data transformations:
scylla@cqlsh:ks> SELECT id, inv(id), mult(id, inv(id)) FROM t;
id | ks.inv(id) | ks.mult(id, ks.inv(id))
----+------------+-------------------------
7 | 0.142857 | 1
1 | 1 | 1
0 | Infinity | NaN
4 | 0.25 | 1
(4 rows)

5. User-defined aggregates
True power of user-defined functions:
being a building block for user-defined aggregates!
CREATE FUNCTION accumulate_len(acc tuple<bigint,bigint>, a text)
RETURNS NULL ON NULL INPUT RETURNS tuple<bigint,bigint>
LANGUAGE lua as 'return {acc[1] + 1, acc[2] + #a}';
CREATE OR REPLACE FUNCTION present(res tuple<bigint,bigint>)
RETURNS NULL ON NULL INPUT RETURNS text
LANGUAGE lua as
'return "The average string length is " .. res[2]/res[1] .. "!"';
CREATE OR REPLACE AGGREGATE avg_length(text)
SFUNC accumulate_len
STYPE tuple<bigint,bigint>
FINALFUNC present INITCOND (0,0);

6. User-defined aggregates
True power of user-defined functions:
being a building block for user-defined aggregates!
scylla@cqlsh:ks> SELECT * FROM words;
word
------------
monkey
rhinoceros
dog
(3 rows)
scylla@cqlsh:ks> SELECT avg_length(word) FROM words;
ks.avg_length(word)
-----------------------------------------------
The average string length is 6.3333333333333!
(1 rows)

7. WebAssembly

8. WebAssembly
Binary format for expressing executable code
● easily embeddable
● portable
● secure
● efficient
WebAssembly is a binary format, but it can also be expressed in
a human-readable way: WAT (WebAssembly Text Format).

9. What compiles to WebAssembly
● AssemblyScript
● Rust
● C++
● and more!

10. Wasmtime
"A fast and secure runtime for WebAssembly"
● implemented in Rust
● good async support
● customizable
● large community
● frequent releases
alternative to consider: Wasmer (http://wasmer.io)

11. Integration with Seastar

12. Requirements
WebAssembly integration should have the following characteristics:
● long computations cannot produce stalls
○ it should be capable of yielding the CPU periodically in order to let other tasks proceed
● memory allocations should be under control
○ Seastar uses its own sharded allocators
○ ideally, allocations performed by runtime should use Seastar's memory management
● overhead induced by the integration should be minimized

13. Async Rust model
● Based on futures
● Each future represents a computation
○ it can be thought of as a state machine
● Runtime is responsible for moving the computation forward
○ in other words, transitioning the machine to the next state

14. Async Rust + async C++
Asynchronous C++ code is often written in an async framework:
● Seastar
● boost::asio
● libuv
Asynchronous Rust code needs a runtime to be executed,
but doesn't need to depend on any particular runtime.

15. Computation-only state machine
An async Rust function can be classified as computation-only
if it does not rely on any blocking operations like:
● accessing disks
● communicating over the network
● delaying its execution (think tokio::time::sleep)
● etc.
Computation-only futures have a very nice characteristic:
polling a computation-only future always moves the state machine forward

16. A minimalistic runtime
An optimal runtime for a single computation-only function is very straightforward:
while the future is not ready yet:
poll the future to proceed with the computation
yield CPU to let other tasks proceed as well

17. Integration with C++
Rust is capable of exporting C symbols, which means that Rust functions
are callable directly from C++.
It means that the minimalistic runtime from the previous slide
can be implemented in C++ too!
while (!ready) {
ready = poll_rust_future(fut);
maybe_yield();
}

18. C++ bindings
Option 1:
extern "C"
Option 2:
cxx: https://crates.io/crates/cxx

19. Integration with Seastar
while (!stop) {
std::exception_ptr eptr;
try {
stop = udf_computation->resume();
} catch (const rust::Error& e) {
eptr = std::make_exception_ptr(wasm::instance_corrupting_exception());
}
if (eptr) {
co_await coroutine::return_exception_ptr(eptr);
}
co_await coroutine::maybe_yield();
}
Ref: https://github.com/scylladb/scylladb/pull/11351 (by @wmitros)

20. Architecture
1. Rust module responsible for running user-defined functions
implemented in WebAssembly
2. A few lines of glue code responsible for polling the Rust module
That's it!

21. Brought to you by
Piotr Sarna
https://github.com/psarna
https://www.linkedin.com/in/piotr-sarna-548a76a3