The latest from the MySQL community

Our first post showed MySQL 9.7 with one change: mark a table ENGINE=DuckDB and its analytical queries run in DuckDB instead of InnoDB. The question we kept getting after that was about replication. Can you keep a normal InnoDB primary for the writes, and run a replica where the big tables are ENGINE=DuckDB? Then the heavy reports run on a column store, and ordinary MySQL replication keeps it current. No export job. No second database to sync by hand.

So we tried it. The first run failed, and it failed in a way that is easy to miss: the replica took every transaction, reported success, and stored nothing. We tracked down why, fixed it, and the whole test suite passes now. This post is what we tested, how we checked it, the bug we found, and where it stands.

It’s still an experiment, not production software. The code and the test harness are on GitHub under GPLv2: …

We ran DuckDB MySQL storage engine at scale factor 500. It is around 500 GB of raw TPC-H, three billion lineitem rows  on an 80-core server with 187 GB of RAM. Three engines on the same box: InnoDB, our MySQL+DuckDB engine, and plain DuckDB as the reference.

Here is what came out. InnoDB finished 18 of the 22 queries and spent more than 28 hours of query time on them. Four never finished. Our engine ran all 22 in about three minutes. It loaded the data 25 times faster than InnoDB, and it used 5 times less disk. On the queries it stays close to plain DuckDB, and on a few it is ahead.

It’s still an experiment, not production software. Code and the benchmark harness are on GitHub under GPLv2: https://github.com/Percona-Lab/ducksdb-mysql-engine.

The machine, and how we ran it

• One server, 80 cores, 187.5 GB RAM.
…

I have known for some times that there is an interesting improvement in MySQL 8.0.17 regarding GTID Crash Safety, but I have not had the time nor the need to look into it before.  When writing my last post (Understanding MySQL Replication "fatal error 1236": [...]), I saw something interesting related to this, and it is now time to cover this on my blog. From my point of view, this change is

This article is also available in Chinese: 中文版. Browse all English articles.

Have you ever run into a mysqld process that has been starting for a long time and still won’t come up? When that happens, you can use perf top to check what the MySQL process is mainly doing. If what you see looks like the figure below — the MySQL main thread (the one starting from mysqld_main) spending the vast majority of its time rolling back transactions — then you are very likely hitting a large-transaction rollback.

The most common way to get here is a large transaction that fills up the disk while writing its binlog, crashing the instance. The largest binlog file I have run into was over 114GB. Since the Binlog Cache’s …

As a junior once I asked a seasoned MySQL DBA (Abuelo) “How do you stay so calm in critical situations?”Abuelo DBA then uttered golden words: “Son, I keep my dirty…

The post InnoDB Flushing is simple – explained first appeared on Change Is Inevitable.

Introduction

Many MySQL configurations inherit redo log sizing from defaults, aging blog posts, or configuration folklore.

innodb_redo_log_capacity gets set once… and then quietly fades into the background.

But redo log capacity directly shapes how efficiently MySQL absorbs writes, manages checkpoint pressure, and handles burst-heavy workloads.

Set it too low, and aggressive flushing can throttle throughput.
Set it too high, and crash recovery can become painfully long.

Redo logs are more than crash insurance.

They are part of your write-performance architecture.

Redo logs are the shock absorbers of write-heavy MySQL. Too small, and performance jolts. Too large, and recovery drags.

Why Redo Logs Matter

InnoDB redo logs are often described as crash recovery journals, but that description undersells their real operational value.

Redo …

The following report is covering performance evaluation of the currently available OpenSSL releases when they are used by MySQL in CPU-intensive OLTP workloads. However, the main focus is on OpenSSL-3.5.5, which will be used by default in the next MySQL releases.

Read more... (19 min remaining to read)

Having a separate DR cluster for production databases is a modern day requirement or necessity for tech and other related businesses that rely heavily on their database systems. Setting up such a [DC -> DR] topology for Percona XtraDB Cluster (PXC), which is a virtually- synchronous cluster, can be a bit challenging in a complex Kubernetes environment.

Here, Percona Operator for MySQL comes in handy, with a minimal number of steps to configure such a topology, which ensures a remote side backup or a disaster recovery solution.

So without taking much time, let’s see how the overall setup and configurations look from a practical standpoint.

PXC Cross-Site/Disaster Recovery

DC Configuration

1) Here we have a three-node PXC cluster running on the DC side.

shell> kubectl get pods -n pxc
NAME                                               READY   STATUS …

You read this right, symbolic links (symlinks) are unsafe in MySQL since at least 8.0.39.  As always, it is a little more complicated than that, but if you are using symbolic links and in certain conditions, you risk a crash.  I think it is important to raise awareness on this, hence this post.

My attention was brought to this via the now private Bug #120156: MySQL 8.0.39/8.0.42

I am continuing my blog post series on using indexes — or tables — as queues.  In this post, I cover Row Deletion Jobs (I do not call these purge jobs, to avoid confusion with the InnoDB Purge).  Such jobs are tempting to implement using an index, but this might be a wrong / suboptimal way.  I write about the right / better / cheaper way