#Start a machine use any method you like here, I'm doing it from the command line 40 cores, 120GB RAM, SSD with 8,500 IOPS (SAN) - Amazon linux (Centos)
ec2-run-instances ami-a10897d6 -t m4.10xlarge -g jlp -k john_page_demos -b "/dev/xvdb=:725:true:io1:8500"
#Log on
ssh -L 27017:localhost:27017 -i <your public key>.pem ec2-user@<your ip address>
#Set up disk
| ENDPOINT | |
| -------- | |
| https://data.mongodb-api.com/app/data-amzuu/endpoint/data/beta | |
| API KEY | |
| -------- | |
| 0vaT8d5Vh9cgvm3KdIQJWkl5M8alZgnoOczmApFlWVTMqisg24QWrUfMS0wkQ5Sj | |
These instructions are a quick and simple way to set up Oracle for experimenting - it is no no way fit for production use. This assumes familiarity with Amazon EC2 - you could also use RHEL 7.9 installed another way but I have not tested that.
Start an EC2 Instance in a region of your choice (Ideally the same one where you will be running MongoDB Atlas). Oracle XE has limitation on hardware and data size so it should be
| //Convert fields to a string of digits and dots | |
| var s={$reduce: {input: ["$x","$y","$s"],initialValue:"",in: {$concat:["$$value",{$toString:"$$this"},"."]}}} | |
| var mx = {$pow:[227,{$mod:[{$add:["$$this",1]},6]}]} | |
| //Iterate it doing iv=56781234 ; iv = (iv + 227^(i%6)*(s[i]+1))%1048576 | |
| //20 bit hash - can increase | |
| var c={$reduce: {input: {$range : [0,{$strLenCP:"$$s"}]},initialValue:56781234, | |
| in: {$mod: [{$add:["$$value",{$multiply:[mx,{$add:[1,{$convert:{to:"int",onError:10, | |
| input:{$substrCP:["$$s","$$this",1]}}}]}]}]},1048576]}}} | |
| var cksum = { $let : { vars: { s: s}, in:c }} | |
| var validator = { $expr : { $eq : [ "$cksum", cksum]},$jsonSchema: { required: ["x","y","s","cksum"]}} |
| doc = {_id: "test", x:1,y:1,s:5.5} | |
| try { db.readonlyfields.insertOne( doc) } catch(e) {print(e.errmsg)} | |
| Document Failed validation |
| var sign = (doc,fields) => { | |
| let toSign="" | |
| fields.forEach(f => { toSign += parseFloat(doc[f]) + "." } ) | |
| toSign = toSign.replace(/NaN/,'.') | |
| print(`Signing: ${toSign}`) | |
| iv = 56781234 | |
| for(c=0;c<toSign.length;c++) { | |
| v = parseInt(toSign[c]) | |
| if(isNaN(v)) v=10; //Dots etc | |
| v += 1; //No point multiplying 0 by anything |
| { | |
| "errInfo": { | |
| "failingDocumentId": "test", | |
| "details": { | |
| "operatorName": "$and", | |
| "clausesNotSatisfied": [ | |
| { | |
| "index": 0, | |
| "details": { | |
| "operatorName": "$expr", |
| [{ | |
| $match: { | |
| reading: { $gt: 1000, $lt: 40000 } | |
| } | |
| }, { | |
| $setWindowFields: { | |
| partitionBy: "$type", | |
| sortBy: { date: 1 }, | |
| output: { | |
| hourago: { |
| [{ | |
| $group: { | |
| _id: { | |
| date: { | |
| $dateTrunc: {date: "$date", unit: "day"} | |
| }, | |
| type: "$type" | |
| }, | |
| max: { $max: "$reading" }, | |
| min: { $min: "$reading" } |
| from bluepy.btle import Scanner, DefaultDelegate, Peripheral | |
| from pprint import pprint | |
| import time | |
| import pymongo | |
| import datetime | |
| TEMPERATURE_SERVICE_UUID = "e95d6100-251d-470a-a062-fa1922dfa9a8" | |
| TEMPERATURE_CHARACTERISTIC_UUID = "e95d9250-251d-470a-a062-fa1922dfa9a8" | |