I wasn’t able to write an article last week due to an unexpected complication regarding tests I was running to verify its contents. So this week, it’s going to be extra special! Also long.

What’s the fastest way to load a Postgres table? If you believe the documentation, the COPY command is the best way to unceremoniously heave data into a table. Fortunately after all of our talk about partitions, our minds are primed and ready to think in chunks. Why restrict ourselves to one COPY, when we can summon an army?

I’ve been talking about partitions a lot recently, and I’ve painted them in a very positive light. Postgres partitions are a great way to distribute data along a logical grouping and work best when data is addressed in a fairly isloated manner. But what happens if we direct a basic query at a partitioned table in such a way that we ignore the allocation scheme? Well, what happens isn’t pretty. Let’s explore in more detail.

This PG Phriday is going to be a bit different. During my trip to Postgres Open this year, I attended a talk I had originally written off as “some Red Hat stuff.” But I saw the word “containers” in the PostgreSQL in Containers at Scale talk and became intrigued. A few days later, I had something of an epiphany: I’ve been wrong about servers for years; we all have.

Well, the bell has tolled, the day is over, and at the end of it all, Postgres Open has ended its fifth year in service of the community. I will say it was certainly an honor to speak again this year, though now that it’s not conveniently in Chicago, I’ll have to work harder to justify hauling myself across the country next year. Of course at this point, I’d feel guilty if I didn’t at least try, assuming any of my submissions are accepted. :)

Most Postgres operators and informed users are aware that it uses MVCC for storage. One of the main drawbacks of this versioning mechanism is related to tuple reuse. In order to reuse the space, VACUUM must complete a cycle on the table. Unfortunately this isn’t always possible to “optimize” for larger tables. How so?