, , ,

DuckDB vs Polars. Wait. DuckDB and Polars.

So, the classic newbie question. DuckDB vs Polars, which one should you pick?

This is an interesting question, and actually drives a lot of search traffic to this website on which you find yourself wasting time. I thank you for that.

This is probably the most classic type of question that all developers eventually ask at some point in their sad and depressing lives. Isn’t that the same story that is as old as time? This stick is better than that rock. Rust is better than C. Databricks better than Snowflake. You know, Delta Lake better than Iceberg.

And so the world keeps turning and grinding away.

DuckDB vs Polars? That’s the wrong question.

Read more

Full vs Incremental Data Loads Explained

, , ,

Apache Iceberg Writes with DuckDB (or not)

Well, all the bottom feeders (Iceberg and DuckDB users) are howling at the moon and dancing around a bonfire at midnight trying to cast their evil spells on the rest of us. Apache Iceberg writes with DuckDB? Better late than never I suppose.

Your witchy ways won’t work on me.

Not going to lie, Iceberg writes with MotherDuck is an interesting concept. MotherDuck is lit and Iceberg only puts a little ice on the fire.

Many other tools like Polars or Daft have been offering Iceberg writes for ages now, it’s about time DuckDB preened its feathers and added write support. Up until now the DuckDB Iceberg Extension has all about the read. But, that is pretty much good for HelloWorld() crap pumped and dumped on Redditors.

We need write support in the real production world. Oh, and not on some Iceberg table stored on your laptop you ninny.

Read more

, ,

How to tune Spark Shuffle Partitions.

So, you’re just a regular old Data Engineer crawling along through the data muck, barley keeping your head above the bits and bytes threatening to drown you. At point in time you were full of spit and vinegar and enjoyed understanding and playing with every nuance known to man.

But, not you are old and wizened, exhausted with the never ending stream of JIRA tickets from which you can never get ahead. You write lots of Spark jobs, consider yourself a PySpark pipeline writing expert … but when it comes to Spark performance tuning and optimizations? That’s for the birds.

Well my friend, don’t let all the Scala experts look down on you, scare you into thinking Spark performance is simply to complex for the common developer. Liars, every last mother one of them.

Read more

, , ,

Is Data Modeling Dead?

Ok, not going to lie, I rarely find anything of value in the dregs of r/dataengineering, mostly I fear, because it’s %90 freshers with little to no experience. These green behind the ear know-it-all engineers who’ve never written a line of Perl, SSH’d into a server, and have no idea what a LAMP stack is. Weak. Sad.

We used to program our way to glory, up hill both ways in the snow. All you do is script kiddy some Python code through Cursor.

A recent post on Data Modeling, specifically that data modeling is dead, caught my eye. A rare piece of gold mixed in the usual pile of crap. It some truth being spoken on the interwebs, hold onto your panties you bright eyed data zealot. I agree %100 with this sentiment.

DATA MODELING IS DEAD.

Read more