Tanel Poder Blog

Here’s a little PL/SQL function create_partition_high_value_func.sql that allows you to write SQL queries against data dictionary for partition maintenance automation and examination operations, by converting the cumbersome LONG-datatype to VARCHAR2 on the

Datadog recently released a free online service explain.datadoghq.com where you can paste in your explained SQL execution plans with metrics as JSON text and it visualizes it for you.

Here are two scripts for showing GV$SYSMETRIC_HISTORY contents in a simple tabular way: vstat.sql - show up to one hour of current history at 1-minute granularity from memory awr/dstat.sql - show 1-minute granularity sysmetric history across your entire A…

Here’s part 3 of my xb.sql & xbi.sql article series that I started writing back in 2019 :-) Part 1 - Show and format execution plans by querying V$SQL_PLAN data directly Part 2 - Show plan line level “self-values” for A-Time and logical, physical I/Os Part

I have uploaded an early version of my Oracle hybrid histogram examination script that shows you the estimated row-count (cardinality) numbers when looking up a single value with a simple WHERE col = X condition from a table.

As my cat woke me up way too early for a Saturday morning, I decided to put all this extra time (and my ChatGPT Pro subscription) into good use and generated a QR-code generator for PostgreSQL, written as a single pure SQL statement.

Update: I just released xcapture v3.0.3 at P99 CONF, the first proper release of this whole concept!

I have added a static version of my CatVector demo app for visualizing embedding vectors: tanelpoder.com/catvector/ Previously you had to clone the CatBench repo and run the little Python webserver locally, but now it’s just a publicly accessible website.

I just added another tool into my 0x.tools toolset: With xstack, you can passively sample both kernel stacks and user stacks (as long as framepointers are present) with a pretty minimalistic tool, with no direct impact to your critical application process…

If you are wondering how the dimensional eBPF data collection works under the hood, check out my earlier post about xcapture: eBPF performance analysis and the 0x.tools repo Summary xtop is like the Linux top tool, but extended with x-ray vision and abili…

TL;DR: I’m doing a CatBench Vector Search on AlloyDB webinar (hacking session style!)

Today, my blog turned 18 years old!

CatBench is a Postgres + PgVector demo application that uses 25k pet photos from a Kaggle dataset for demonstrating how the similarity search features work together with the rest of your application code & schema in the backend (HammerDB Order Entry).

Here’s a useful tool for quickly testing whether a disk (or a cloud block store volume) is a good candidate for your database WAL/redo logs and any other files that require low latency writes.

Oracle’s SQL*Net break/reset to client wait event shows up whenever Oracle (SQL, PL/SQL call, etc) returns an ORA- error back to the client instead of the normal expected results (and ORA-0 under the hood): SQL> @oerr 0 ORA-0000: normal, successful compl…

When dealing with disks and I/O things on Linux, you’d regularly run commands like lsblk, lsscsi, nvme list, etc.

In this post I will introduce a much more efficient method for accounting block I/O latencies with eBPF on Linux.

To capture your attention, this is what you get: Table of contents What is xCapture?

TLDR; Starting from Linux kernel version 6.9 on x86_64, there’s a new config option CONFIG_X86_FRED enabled and it adds 16 bytes to the starting point of a task’s kernel stack area, so you’ll need to account for this extra padding in your “raw” kernel sta…

This should be something useful for Linux kernel explorers and eBPF nerds!

Last year, I published a simple demo app that visualizes embedding vectors of a bunch of cat, dog and airplane photos as heatmaps.

Last year I wrote an article about visualizing embedding vectors of a variety of different pictures as heatmaps.

Back in 2018 I wrote about how to apply Brendan Gregg’s FlameGraphs for visualizing SQL plan execution time 1, using the plan node-level context and timing data that some database engines provide.

Disclaimer: I’m not an ML expert and not even a serious ML specialist (yet?)

Here’s a 12-minute video of our chat with Silk VP of Product Tom O’Neill about my recent testing of the Silk Platform in Google Cloud.

Hands-on technical analysis of a novel data platform for high-performance block I/O in the cloud, tested by Tanel Poder, a database consultant and a long-time computer performance nerd.

Following my earlier Visualizing and Comparing Embedding Vectors as Heatmaps article, here are the launch & demo videos.

An interactive demo video is here: Part 2.

Here’s my talk from eBPF Summit 2024.

Starting from Python 3.12, you can instruct Python to enable direct perf profiling support for your Python code.

Yes!

I recently published what I have been working on for the past 5 years.

This blog post is not about tracing program system calls, but about programmatically extracting all system calls and their accepted arguments in your current system.

One evening back in January I finally had enough of thermal issues within my homelab server.

Thanks to Tomasz Sroka’s pull request for my hint.sql in the TPT repo and blog entries by Sayan 1 and Jonathan 2, we now have a HINT_SCOPE field in my hint.sql script too!

I switched my blog’s commenting system to use Giscus.

Over time, Oracle has been adding more contextual information into each allocated heap memory chunk, to make it easier to see what for your heap memory is used.

Back in 2007, my third blog entry was about a parallel index building gotcha, a warning about building & rebuilding indexes in parallel.

You probably are already familiar with my ash_wait_chains scripts that use CONNECT BY for walking through the blocking_session fields in ASH and report “wait chains”, signatures of complex waits involving other database sessions.

About 14 years ago I published the OstackProf script that ran on Windows sqlplus clients (the Oracle server could run on any platform that supported ORADEBUG SHORT_STACK).

Update: Just as I started blogging about the Optane technology, it turns out that Intel is shutting down the Optane business (after bringing the latest-gen “Crow Pass” Optane memory to market - probably just for satisfying existing commitments).

Update: Just as I started blogging about the Optane technology, it turns out that Intel is shutting down the Optane business (after bringing the latest-gen “Crow Pass” Optane memory to market - probably just for satisfying existing commitments).

Starting from v8.0.27, the MySQL daemon shows its thread names at the OS level too, for better troubleshooting.

In the previous post in this series, I showed how my scripts xb.sql and xbi.sql (eXplain Better and eXplain Better, by sqlId) help you see Oracle execution plan details in a more complete way.

Tanel at Mount Denali in Alaska (2021) In the beginning of every year I travel somewhere and take some time to think about the future and what I should be working on next.

You may remember my previous article about high-performance I/O for cloud databases, where I tested out the Silk Platform and got a single Azure VM to do over 5 GB/s (gigaBytes/s) of I/O for my large database query workload.

Update: 3 years after writing this article, I tested the latest Silk Platform in 2024, on Google Cloud Platform, with impressive results.

Over the years of troubleshooting performance problems in the Unix/Linux world, I have seen multiple cases where a regularly used command line tool in a customer server just stops working for some reason.

In this video I will present a case study of a complex performance issue where the initial symptoms pointed somewhere else than the root cause.

TL;DR: Some Linux distros and even different kernel versions within a distro have disabled IRQ time accounting.