Timeseries and ASOF Joins

Pairing up timeseries data when the timestamps don’t match exactly (in Pandas, Polars, DuckDB, Postgres & QuestDB)

Archiving Time-Series Data from PostgreSQL into Parquet

Keeping your database lean

Graph Query Interfaces: A Comparison Between SQL and Cypher

Featuring DuckDB & KuzuDB

Some Notes on Vector Indexing in DuckDB

Once you’ve indexed your vectors for similarity search, be sure to check your query plans, just in case the DB decides to opt for a sequential scan

Combining Lexical and Semantic Search with Reciprocal Rank Fusion

Best of both worlds sort of thing

Vector Indexing and Search with DuckDB & FastEmbed

Using DuckDB for vector/semantic search

Leanstore: High Performance Low-Overhead Buffer Pool

A dash of pointer swizzling, a sprinkle of optimistic locking and a touch of lean eviction, that’s the secret to a high performance buffer pool!

Larger-Than-Memory Data Management

For when the database exceeds the main memory size

Hybrid Locking & Synchronization

Fast-path optimistic locking with fallback to pessimistic RW locks under contention

Optimizing Data Placement for Distributed OLAP Systems

Using MIP solvers to model and optimize shard placement

DuckDB JIT Compiled UDFs with Numba

JIT compiling your vectorized UDFs with Numba. Plus pure SQL is plenty fast if you can figure out how to write it

Guided Local Search for the Capacitated Facility Location Problem

Overview of Guided Local Search plus how it can be applied to the capacitated facility location problem.

Minizinc: Alternative Modeling Approaches for the Facility Location Problem

Multiple views and Channeling Constraints make for faster models (in some cases)

The Facility Location Problem

Discrete Optimization: Where to construct facilities so as to minimize setup costs and customer servicing costs while ensuring each facility is able to meet customer demands.

Vectorized DuckDB UDFs with Rust and Python FFI

Implementing vectorized UDFs in Rust that you can use in DuckDB, with a little help from Arrow

Optimizing CPU & Memory Interaction: Matrix Multiplication

Same algo, different memory access patterns, what could go wrong (or right)!

x86 Cache Control Instructions

Wherein the OS and user get more control over the L1,L2 and L3 caches, mostly for performance.

Retrieving Memory and Cache Organization

Memory, Cache levels, Cache sizes, TLB, associativity and so on

Microbenchmarking: Way more than I set out to know

RDTSC, Out-of-order execution, OS interrupts, cycles, frequency and more.

Logging in Go

Best practices, Logging levels, structured logging, Logging & Telemetry (Metrics, Tracing), Audit logs

Handling Missing Values in Timeseries Datasets

Filling gaps using Last observation carried forward, next observation carried backwards, median & linear interpolation

Wrangling JSON with DuckDB

For when you need to impose some structure on semi-structured data

Parquet + Zstd: Smaller faster data formats

Often, parquet files have to be compressed. For fast compression, use LZ4 or Snappy. For the highest data compression ratio, use brotli. For both, zstd

Lateral Joins & Iterators in SQL

Sneaking for-loops into SQL without anyone noticing

SQL Grouping sets, Rollups & Cube

Computing multiple Group-bys with less steps

Generalized Range Difference, Recursion & Search Availability in PostgreSQL

We’re building a scheduling app. Users mark booked slots, represented in Postgres using time or date-range data types. Let’s see how we can find all the freely available slots efficiently

Back To Basics: The foundation of Joins in SQL

Writing SQL joins without using joins at all. A quick history of Database Models, Schemas, Constraints, Cross-products and everything in between

SQL joins as reduce/folds over relations

Of what to make of joins in sql, mental models and building better understanding