j-keck

Problem

The MPOW Bluetooth 5 dongle (Model: BH456A) does not work out of the box on Ubuntu 20.04 (kernel 5.4.0-42).

Solution

Patch the bluetooth kernel module and copy the firmware binaries to /lib/firmware.

Copy the fimware

j-keck

# NVM
curl -o- https://raw.githubusercontent.com/creationix/nvm/v0.33.11/install.sh | bash
export NVM_DIR="$HOME/.nvm"
[ -s "$NVM_DIR/nvm.sh" ] && \. "$NVM_DIR/nvm.sh"  # This loads nvm
[ -s "$NVM_DIR/bash_completion" ] && \. "$NVM_DIR/bash_completion"  # This loads nvm bash_completion
nvm install 10

# Yarn
curl -o- -L https://yarnpkg.com/install.sh | bash
export PATH="$HOME/.yarn/bin:$HOME/.config/yarn/global/node_modules/.bin:$PATH"

j-keck

{
  "Version": "2012-10-17",
  "Id": "arn:aws:sqs:YOUR-AWS-REGION:YOUR-AWS-ACCOUNT-ID:YOUR-QUEUE-NAME/SQSDefaultPolicy",
  "Statement": [
    {
      "Sid": "example-statement-ID",
      "Effect": "Allow",
      "Principal": {
        "AWS": "*"
      },

j-keck

{
  "Version": "2012-10-17",
  "Id": "arn:aws:sqs:YOUR-AWS-REGION:YOUR-AWS-ACCOUNT-ID:YOUR-QUEUE-NAME/SQSDefaultPolicy",
  "Statement": [
    {
      "Sid": "example-statement-ID",
      "Effect": "Allow",
      "Principal": {
        "AWS": "*"
      },

j-keck

Quick Tips for Fast Code on the JVM

I was talking to a coworker recently about general techniques that almost always form the core of any effort to write very fast, down-to-the-metal hot path code on the JVM, and they pointed out that there really isn't a particularly good place to go for this information. It occurred to me that, really, I had more or less picked up all of it by word of mouth and experience, and there just aren't any good reference sources on the topic. So… here's my word of mouth.

This is by no means a comprehensive gist. It's also important to understand that the techniques that I outline in here are not 100% absolute either. Performance on the JVM is an incredibly complicated subject, and while there are rules that almost always hold true, the "almost" remains very salient. Also, for many or even most applications, there will be other techniques that I'm not mentioning which will have a greater impact. JMH, Java Flight Recorder, and a good profiler are your very best friend! Mea

j-keck

1. 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