From 2c79c7457845e70b6d642fb1a6b511abf4394d4b Mon Sep 17 00:00:00 2001 From: nuno-faria Date: Mon, 26 Oct 2026 20:30:05 +0000 Subject: [PATCH] Fixes to 'Best Practices for Single Row Lookups' post --- content/blog/2026-10-24-point-queries.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/content/blog/2026-10-24-point-queries.md b/content/blog/2026-10-24-point-queries.md index b2a374e1..32055998 100644 --- a/content/blog/2026-10-24-point-queries.md +++ b/content/blog/2026-10-24-point-queries.md @@ -67,9 +67,9 @@ from generate_series(1, {rows}) t(i) Unless otherwise stated, the queries tested retrieve a random row from the table by key (i.e., `select v from t where k = {}`). Most tests run on a `c4d-standard-4` (4 vCPUs, 15GB RAM) Google Cloud virtual machine, using a 100GB -[HyperDisk] (6k IOPS, 500 MB/s) to store the data. The [Runtime](#runtime) test -uses a machine with more CPU cores (`c4d-highcpu-8`). Each test builds on the -last. +[HyperDisk] (6k IOPS, 500 MB/s) to store the data. The [Target +Partitions](#target-partitions) and [Runtime](#runtime) tests use a machine with +more CPU cores (`c4d-highcpu-8`). Each test builds on the last. [HyperDisk]: https://docs.cloud.google.com/compute/docs/disks/hyperdisks @@ -273,7 +273,7 @@ page size (y). Figure 9: Throughput based on the read size and the size of the Parquet data pages (512k rows per row group). Each cell shows the ratio between its throughput value and the max throughput in its column - (darker is better).. + (darker is better).