1
2
Pev: Postgres ‘Explain’ Visualizer (2016)
Postgres Explain Visualizer (Pev) is a tool I wrote to make EXPLAIN output easier to grok. It creates a graphical representation of the query plan.
3
Be Careful with UUID or GUID as Primary Keys
You can use of UUIDs as the primary key to avoid database scale problems. But should you? I propose an alternative.
4
5
Why Use Postgres?
Five years ago I wrote a post that got some good attention on why you should use Postgres. Almost a year later I added a bunch of things I missed. Many of those items bear repeating, and I’ll recap a few of those in the latter half of this post. But in the last 4-5 years there’s been a lot of improvements and more…
6
7
New Features Coming in PostgreSQL 10
The list of new features coming in PostgreSQL 10 is extremely impressive. I've been involved in the PostgreSQL project since the 8.4 releas...
8
The internals of PostgreSQL
After a temporary stay in Japan to focus on my health and personal responsibilities, I am fully recovered, ready, and excited to work abroad again.
9
A Minimalist Guide to SQLite
Benchmarks & Tips for Big Data, Hadoop, AWS, Google Cloud, PostgreSQL, Spark, Python & More...
10
Is PostgreSQL good enough?
tldr; you can do jobs, queues, real time change feeds, time series, object store, document store, full text search with PostgreSQL. How to,...
11
12
Apache Arrow and the “Things I Hate About Pandas”
This post is the first of many to come on Apache Arrow, pandas, pandas2, and the general trajectory of my work in recent times and into the foreseeable future. This is a bit of a read and overall fairly technical, but if interested I encourage you to take the time to work through it.
13
Python For Finance: Algorithmic Trading
Originally published at https://www.datacamp.com/community/tutorials/finance-python-trading
14
Effectively Using Matplotlib
Matplotlib is a valuable but misunderstood foundation of the python data science stack.
15
How Postgres Makes Transactions Atomic
A dive into the mechanics that allow Postgres to provide strong atomic guarantees despite the chaotic entropy of production.
16
Analyzing Cryptocurrency Markets Using Python
A data-driven approach to cryptocurrency (Bitcoin, Ethereum, Litecoin, Ripple etc.) market analysis and visualization using Python.
17
18
Interesting data structures: the BK-tree
A BK-tree is a tree data structure specialized to index data in a metric space . A metric space is essentially a set of objects which we equip with a distance function $d(a, b)$ for every pair of elements $(a, b)$. This distance function must satisfy a set of axioms in order to ensure it’s well-behaved. The exact…
19
Working with time in Postgres
A massive amount of reporting queries, whether really intensive data analysis, or just basic insights into your business involving looking at data over a certain time period. Postgres has really rich support for dealing with time out of the box, something that’s often very underweighted when dealing with a database…
20
Unlearning descriptive statistics
If you've ever used an arithmetic mean, a Pearson correlation or a standard deviation to describe a dataset, I'm writing this for you. Better numbers exist to summarize location, association and spread: numbers that are easier to interpret and that don't act up with wonky data and outliers.
21
Modes, Medians and Means: A Unifying Perspective
Introduction / Warning Link to heading Any traditional introductory statistics course will teach students the definitions of modes, medians and means. But, because introductory courses can’t assume that students have much mathematical maturity, the close relationship between these three summary statistics can’t be…
22
The Marketing Behind MongoDB
Countless NoSQL databases competed to be the database of choice. MongoDB's marketing strategy helped it become the winner.
23
A/B test of banner ads vs. traffic
9 months of daily A/B-testing of Google AdSense banner ads on Gwern.net indicates banner ads decrease total traffic substantially, possibly due to spillover effects in reader engagement and resharing.
24
25
1.1B Taxi Rides on Kdb+/q and 4 Xeon Phi CPUs
Benchmarks & Tips for Big Data, Hadoop, AWS, Google Cloud, PostgreSQL, Spark, Python & More...
26
Better Database Migrations in Postgres
As your database grows and scales there are some operations that you need to take more care of than you did when you were just starting. When working with your application in your dev environment you may not be fully aware of the cost of some operations until you run them against production. And at some point most of…
27
A Data-Driven Guide to Becoming a Consistent Billionaire
Did You Really Think All Billionaires Were the Same? Recently, I became a bit obsessed with the one percent of the one percent – Billionaires. I was intrigued when I stumbled on articles telling us…
28
Introduction to R Programming
This is a detailed step-by-step introduction to R programming. Starting with the two major reasons to learn R for Data Science, it will guide you through the installation process, and prepare you for the basics of R: arithmetics, variables assignment, data types, functions, and documentations.
29
Dear Postgres
Dear Postgres, I’ve always felt an affinity for you in my 9 years of working with you. I know others have known you longer, but that doesn’t mean they love you more. Years ago when others complained about your rigidness or that you weren’t as accommodating as others I found solace in your steadfast values: Don’t lose…
30
