1.
Backpressure?
Resistance is not futile.
Jay Phelps | @_jayphelps

2.
Jay Phelps | @_jayphelps
Jay Phelps
@_jayphelps
Senior Software Engineer
Citadel

3.
Jay Phelps | @_jayphelps
Backpressure

4.
Jay Phelps | @_jayphelps
A term borrowed from fluid dynamics,
like in automotive exhaust and house
plumbing.

5.
Jay Phelps | @_jayphelps
“Resistance or force opposing the
desired flow of fluid through pipes.”

6.
Jay Phelps | @_jayphelps
“Resistance or force opposing the
desired flow of fluid through pipes.”

7.
Jay Phelps | @_jayphelps
“Resistance or force opposing the
desired flow of fluid through pipes.”
^ data through software.

8.
Jay Phelps | @_jayphelps
“Resistance or force opposing the
desired flow of data through software.”

9.
Jay Phelps | @_jayphelps
i.e. “input is coming in faster
than we can output”

10.
Jay Phelps | @_jayphelps
Cool

11.
Jay Phelps | @_jayphelps
…but…what is Backpressure?

12.
Jay Phelps | @_jayphelps
Let’s start with an analogy!

13.
Jay Phelps | @_jayphelps
I Love Lucy: Chocolate Factory

14.
"I Love Lucy" Job Switching - 1952 - CBS
"I Love Lucy" Job Switching - 1952 - CBS
video: https://bit.ly/1eUkJgG

15.
Jay Phelps | @_jayphelps
Lucy has Backpressure!

16.
Jay Phelps | @_jayphelps
She tries to set them to the side
(buffering)

17.
Jay Phelps | @_jayphelps
Then she tries eating and hiding them
(dropping)

18.
Jay Phelps | @_jayphelps
She needs to slow down the conveyor belt
(producer control)

19.
Jay Phelps | @_jayphelps
Let’s talk software

20.
Jay Phelps | @_jayphelps
Reading and writing files
File Systems

21.
Jay Phelps | @_jayphelps
Writing is slower than reading

22.
Jay Phelps | @_jayphelps
Read: 150 MB/s
Write: 100 MB/s
Example hard drive

23.
Jay Phelps | @_jayphelps
Example hard drive
150 MB/s - 100 MB/s = 50 MB/sdeficit

24.
Jay Phelps | @_jayphelps
Imagine needing to read/write a 6 GB file
Example hard drive

25.
Jay Phelps | @_jayphelps
Example hard drive
6 GB / 150 MB read = 40 seconds

26.
Jay Phelps | @_jayphelps
Example hard drive
50 MB deficit x 40 sec = 2 GB memory!

27.
Jay Phelps | @_jayphelps
That’s a lot of wasted memory

28.
Jay Phelps | @_jayphelps
Solution: only read as fast as you can write
(control the producer)

29.
Jay Phelps | @_jayphelps
Most I/O libraries do this for you, automatically
Node.js Streams is a great example

30.
Jay Phelps | @_jayphelps
const zlib = require('zlib');
const fs = require('fs');
const gzip = zlib.createGzip();
const input = fs.createReadStream('input.txt');
const output = fs.createWriteStream('input.txt.gz');
// handles backpressure for you
input.pipe(gzip).pipe(output);

31.
Jay Phelps | @_jayphelps
Server-to-Server Communication

32.
A
Server
B
Server
C
Server
Jay Phelps | @_jayphelps

33.
A
Server
B
Server
C
Server
100 rps 75 rps
Jay Phelps | @_jayphelps

34.
A B C
Server Server Server
60 sec * 25 rps = 1,500 rpm!
100 rps 75 rps
Jay Phelps | @_jayphelps

35.
A B C
Server Server Server
100 rps 75 rps
60 sec * 60 min * 25 rps = 90,000 rph!
Jay Phelps | @_jayphelps

36.
Jay Phelps | @_jayphelps
Solution: control the producer (or scale up)

37.
Jay Phelps | @_jayphelps
…unfortunately, that isn’t easy

38.
Jay Phelps | @_jayphelps
RSocket, gRPC, etc

39.
Jay Phelps | @_jayphelps
UI Rendering

40.
Jay Phelps | @_jayphelps
Throttling/debouncing keyboard input

41.
Jay Phelps | @_jayphelps
High volume WebSockets

42.
Jay Phelps | @_jayphelps
Events are coming in faster
than we can render them

43.
Jay Phelps | @_jayphelps
Solution: control the producer?

44.
Jay Phelps | @_jayphelps
Is this even a good User Experience?

45.
Jay Phelps | @_jayphelps
Performance problems are often UX problems!

46.
Jay Phelps | @_jayphelps
Buffer or Drop/Sample?

47.
Jay Phelps | @_jayphelps
Maybe table virtualization too?

48.
VirtualizedNOT Virtualized vs.

49.
Jay Phelps | @_jayphelps
Backpressure Strategies

50.
Jay Phelps | @_jayphelps
If you can, scale up your resources

51.
Jay Phelps | @_jayphelps
Three fundamental strategies

52.
Jay Phelps | @_jayphelps
Control the producer
Buffer
Drop

53.
Jay Phelps | @_jayphelps
Control the producer
slow down/speed up is decided by consumer

54.
Jay Phelps | @_jayphelps
const source = connectToSource();
source.pull(response1 => {
console.log(response1);
// later…
source.pull(response2 => {
console.log(response2);
});
});

55.
Jay Phelps | @_jayphelps
Controlling is usually the ideal option
but not always viable

56.
Jay Phelps | @_jayphelps
Buffer
accumulate incoming data spikes temporarily

57.
Jay Phelps | @_jayphelps
Be careful with unbounded buffers!

58.
Jay Phelps | @_jayphelps
Drop
sample a percentage of the incoming data

59.
Jay Phelps | @_jayphelps
Throttle, debounce, etc

60.
Jay Phelps | @_jayphelps
Not always acceptable to lose data

61.
Jay Phelps | @_jayphelps
Libraries for handling Backpressure

62.
Jay Phelps | @_jayphelps
Probably streams, but maybe not!

63.
Jay Phelps | @_jayphelps
Push-based streams
RxJS, Bacon.js, xstream

64.
Jay Phelps | @_jayphelps
Push: producer is in control

65.
Jay Phelps | @_jayphelps
Pull-based streams
Node.js Streams, Web Streams, Async Iterators, IxJS

66.
Jay Phelps | @_jayphelps
Pull: consumer is in control

67.
Jay Phelps | @_jayphelps
It’s not unusual to use both push
and pull streams in the same app

68.
Jay Phelps | @_jayphelps
“Resistance opposing the
desired flow of data through software.”

69.
Jay Phelps | @_jayphelps
i.e. “input is coming in faster
than we can output”

70.
Jay Phelps | @_jayphelps
Control the producer
Buffer
Drop

71.
Jay Phelps | @_jayphelps
Thanks!
@_jayphelps