sequenceDiagram
participant E as entrypoint
participant AS as ActionSpace
participant MS as MotorSystem
participant BP as BasePolicy
participant RAF as read_action_file
I hereby claim:
- I am tristanls on github.
- I am tristanls (https://keybase.io/tristanls) on keybase.
- I have a public key ASBa6_-Unbrn-U6KcZ0BDRic8CiEH6rfCm6LyTDKDa9xOAo
To claim this, I am signing this object:
$ curl -LO -b "oraclelicense=a" http://download.oracle.com/otn-pub/java/jdk/9.0.4+11/c2514751926b4512b076cc82f959763f/jdk-9.0.4_linux-x64_bin.tar.gz
- When setting up a service control plane (for example commands such as
CreateTenant
, orDeleteTenant
) Serverless is useful as the commands aren't executed often, and the latency is not really a constraint. - Processing events from an event stream up to a certain throughput when cost starts to dominate and running dedicated servers (which possibly is "roll your own serverless") becomes a more economical choice.
- When setting up a service data plane (for example, proxying a request with minimal latency), Serverless doesn't work well
The "cpblty" scheme is used to identify capabilities.
There are two types of "cpblty" URIs. They are distinguished by the mechanism used to identify the authority responsible for resolving the capability.
The first type of capability URI uses IP address or DNS resolution to identify authority.
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"use strict"; | |
const crypto = require("crypto"); | |
const http = require("http"); | |
const url = require("url"); | |
const indexHtml = | |
`<!doctype html> | |
<!--[if lt IE 7]><html class="no-js lt-ie9 lt-ie8 lt-ie7"><![endif]--> | |
<!--[if IE 7]><html class="no-js lt-ie9 lt-ie8"><![endif]--> |
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{ | |
"message": "hello there", | |
"status": "200 OK" | |
} |
- General Background and Overview
- Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
- Models and Issues in Data Stream Systems
- Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
- Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
- [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep
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var iso8601durationregex = /^P([0-9]+(?:[,\.][0-9]+)?Y)?([0-9]+(?:[,\.][0-9]+)?M)?([0-9]+(?:[,\.][0-9]+)?D)?(?:T([0-9]+(?:[,\.][0-9]+)?H)?([0-9]+(?:[,\.][0-9]+)?M)?([0-9]+(?:[,\.][0-9]+)?S)?)?$/ |
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dostuffEmitter.on('task1', function (callback) { | |
dostuffEmitter.emit('task3', x, callback); | |
}); | |
dostuffEmitter.on('task2', function (x, callback) { | |
dostuffEmitter.emit('finish', y, callback); | |
}); | |
dostuffEmitter.on('task3', function (y, callback) { | |
dostuffEmitter.emit('task2', z, callback); |
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