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MySQL Debian/Ubuntu packaging sprint
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Debian/Ubuntu packaging sprint participants. From left: James Page, Norvald H. Ryeng, George Lorch, Akhil Mohan, Otto Kekäläinen, Robie Basak.

Last week, Canonical invited the MySQL packaging team in Debian to a packaging sprint in their London office, and most of us were able to participate. We’ve met online on IRC and UOSs before, but this was the first time we were all in the same room.

The results of our sprint will soon be available in a .deb near you. …

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Open Source Collaboration: This is how we did it ‘together’ !
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It was not long before when we all were discussing to meet in person during UDS. We did not have good enough reasons to get the logistics mobilized back then but over time we realized the vibrant MySQL Ecosystem on Debian and Ubuntu needs a brainstorming session. While we did try Google Hangout as the […]

A Year In The Life Of MaxScale
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Fri, 2014-12-19 09:14mriddoch

 

This time of the year it is traditional, at least in the UK, to look back and reflect on the year that is coming to a close. Since we have just produced the release candidate for MaxScale and are looking forward to the GA release early in the New Year, it seems like a good time to reflect on the events that have bought us to this stage in the story of MaxScale.

Going Public

The start of 2014 also marked the start for MaxScale, with the first public announcements regarding MaxScale and the first downloadable binaries. MaxScale itself had been started internally before that, but we wanted to hold off on letting …

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Shinguz: Avoid temporary disk tables with MySQL
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Taxonomy upgrade extras: temporary tablediskselectquery tuning

For processing SELECT queries MySQL needs some times the help of temporary tables. These temporary tables can be created either in memory or on disk.

The number of creations of such temporary tables can be found with the following command:

mysql> SHOW GLOBAL STATUS LIKE 'created_tmp%tables'; …
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Drop Table slow
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A few days back we were given a MySQL database hosted in EC2 with around 5TB data to move some of the tables to a new server.  The intention was to share the tables between 2 EC2 instances. Since AWS had the option to take online snapshots, the plan was to take a snapshot, create a new machine with that snapshot and drop the unwanted tables.So everything went as planned until creating a new machine with the snapshot.  The real challenge was dropping the unwanted tables.  It took around 4 minutes to Drop a table whose size is 20GB.  It took 20 minutes to drop a 100GB table. The time kept on increasing for larger tables. MySQL even went to …

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Orchestrator 1.2.9 GA released
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Orchestrator 1.2.9 GA has been released. Noteworthy:

  • Added "ReadOnly" (true/false) configuration param. You can have orchestrator completely read-only
  • Added "AuthenticationMethod": "multi": works like BasicAuth (your normal HTTP user+password) only it also accepts the special user called "readonly", which, surprise, can only view and not modify
  • Centralized/serialized most backend database writes (with …
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Making HAProxy 1.5 replication lag aware in MySQL
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HAProxy is frequently used as a software load balancer in the MySQL world. Peter Boros, in a past post, explained how to set it up with Percona XtraDB Cluster (PXC) so that it only sends queries to available nodes. The same approach can be used in a regular master-slaves setup to spread the read load across multiple slaves. However with MySQL replication, another factor comes into play: replication lag. In this case the approach mentioned for  …

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Monitor MySQL Performance Interactively With VividCortex
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If you’re monitoring MySQL performance on dozens or hundreds of servers, chances are you have a “rainbow chart” – a time-series chart with hundreds of tiny area graphs stacked on top of each other, crawling imperceptibly one pixel at a time across the big-screen monitor in your office. The trouble with these charts is they’re hard to see. It takes many minutes for enough new pixels to display after a change. In the meantime you can’t see the change clearly.

At VividCortex, we think we’ve found a better way to keep tabs on what’s going on in your infrastructure: a bubble visualization. It is compact, and …

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Scaling TokuDB Performance with Binlog Group Commit
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TokuDB offers high throughput for write intensive applications, and the throughput scales with the number of concurrent clients.  However, when the binary log is turned on, TokuDB 7.5.2 throughput suffers.  The throughput scaling problem is caused by a poor interaction between the binary log group commit algorithm in MySQL 5.6 and the way TokuDB commits transactions.   TokuDB 7.5.4 for Percona Server 5.6 fixes this problem, and the result is roughly an order of magnitude increase in SysBench throughput for in memory workloads.

MySQL uses two phase commit protocol to synchronize the MySQL binary log with the …

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InnoDB’s multi-versioning handling can be Achilles’ heel
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I believe InnoDB storage engine architecture is great for a lot of online workloads, however, there are no silver bullets in technology and all design choices have their trade offs. In this blog post I’m going to talk about one important InnoDB limitation that you should consider.

InnoDB is a multiversion concurrency control (MVCC) storage engine which means many versions of the single row can exist at the same time. In fact there can be a huge amount of such row versions. Depending on the isolation mode you have chosen, InnoDB might have to keep all row versions going back to the earliest active read view, but at the very …

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Showing entries 1 to 10 of 33579 10 Older Entries

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