adtac

#!/usr/bin/env -S bash -c "docker run -p 8080:8080 -it --rm \$(docker build --progress plain -f \$0 . 2>&1 | tee /dev/stderr | grep -oP 'sha256:[0-9a-f]*')"

# syntax = docker/dockerfile:1.4.0

FROM node:20

WORKDIR /root

RUN npm install sqlite3

mnadel

#!/usr/bin/env bash

PROGNAME=$(basename $0)

function usage {
    echo "usage: $PROGNAME [-n NAMESPACE] [-m MAX-PODS] -s SERVICE -- COMMAND"
    echo "  -s SERVICE   K8s service, i.e. a pod selector (required)"
    echo "     COMMAND   Command to execute on the pods"
    echo "  -n NAMESPACE K8s namespace (optional)"
    echo "  -m MAX-PODS  Max number of pods to run on (optional; default=all)"

simonswine

kubectl get rs,secrets -o json --namespace old | jq '.items[].metadata.namespace = "new"' | kubectl create-f  -

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