prologic

Learn Go in ~5mins

This is inspired by A half-hour to learn Rust and Zig in 30 minutes.

Basics

Your first Go program as a classical "Hello World" is pretty simple:

First we create a workspace for our project:

AmirHo3ein13

Elasticsearch Cheat-sheet

Links

• Cluster
• Nodes
• Indices
• Docs
• Search
• Tasks
• Snapshots

Cluster

angristan

Elasticsearch settings for single-node cluster

1 shard, 0 replica.

For future indices

Update default template:

curl -X PUT http://localhost:9200/_template/default -H 'Content-Type: application/json' -d '{"index_patterns": ["*"],"order": -1,"settings": {"number_of_shards": "1","number_of_replicas": "0"}}' 

noushi

An Ansible summary

Jon Warbrick, July 2014, V3.2 (for Ansible 1.7)

Configuration file

intro_configuration.html

First one found from of

ruanbekker

My Elasticsearch cheatsheet with example usage via rest api (still a work-in-progress)

Shortlinks:

• Cluster Health
  • Index Level
  • Shard Level
• Nodes Overview
• Indices Overview
• Cluster Maintenance

eferro

AWS Golang SDK examples

bastman

Docker - How to cleanup (unused) resources

Once in a while, you may need to cleanup resources (containers, volumes, images, networks) ...

delete volumes

// see: https://github.com/chadoe/docker-cleanup-volumes

$ docker volume rm $(docker volume ls -qf dangling=true)

$ docker volume ls -qf dangling=true | xargs -r docker volume rm

beaugunderson

from streams session

• end-of-stream - specify a callback to be called when a stream ends (which is surpsingly hard to get right)
• duplexify - compose a Duplex stream from a Readable and a Writable stream
• pump - pipe streams together and close all of them if one of them closes
• pumpify - combine an array of streams into a single duplex stream using pump and duplexify
• through2 - tools for making Transform streams
• from2 - tools for making Readable streams

from "participatory modules" session

nishantmodak

#user  nobody;
#Defines which Linux system user will own and run the Nginx server

worker_processes  1;
#Referes to single threaded process. Generally set to be equal to the number of CPUs or cores.

#error_log  logs/error.log; #error_log  logs/error.log  notice;
#Specifies the file where server logs. 

debasishg

General Background and Overview

1. 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.
2. Models and Issues in Data Stream Systems
3. 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
4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t