In August Productions

I was just reading Jan's post about how to write a good build system

I'm in the need for a portable, fast build-system.

While I'm not about to write a build system in lua - or anything else, I thought I'd pitch in my thoughts as I've been having a similar problem recently. The problem is, autotools is the only system that doesn't require some prereq to be installed on the system ... other than a working build system. The only real downside to autotools (other than needing to learn m4) is that it is useless on Windows.

As Jan says, though, the other systems fall down on the make dist part. This is way important to me, as I also work in my tree alot and I really want to have an automated step to make sure I'm packaging up all the files I need, but not too many. This leads Jan to the inevitable choice of building his own

As a matter of fact here I stand without build-system that meets my needs. My current target is building the MySQL Proxy on Linux, MacOS X and win32.

Throwing lua into the game as a nice side-effect: the scripting language is clean and simple. You can also think about adding the lua-src itself to the build-system to do a full bootstrap in case the user doesn't have it install

First problem - if the user doesn't have the build system, and if autotools won't cut it, then how are they going to build the lua-src.

I'd like to point out that most of this is because Windows is crap. The autotools design goal of not requiring user to install a special build system other than Make is a great one. But because Windows can't even manage to ship a decent POSIX environment, this is broken. Ever tried sharing source with someone who's using VisualStudio? Ever get pissed off because there's no way to have the source figure out where a library dependency is without setting some property in the source by hand?

Anyway - I do think Jan is on to something (as usual) but I don't think the whole system needs to be rewritten - just autoconf.

Automake runs on the maintainer's machine, as does autoconf, but the automake output are the Makefile.in files that autoconf replaces stuff in. There's nothing really broken about this. make, make dist, make distcheck should all still work (ok, except on Windows where they don't have tar... my sympathy is low) But if you made a program in lua that created something like a configure script that could be run with minimal install requirements on the client (I think needing lua is ok here - as Jan says, it's easy to install)

That leaves the requirement of producing MSI targets. I think this is a requirement that should be shucked, because it's not an apples/apples thing. MSI files are the same as RPMs or DEBs. They are packaging, not part of the build, and I think if emitting them is part of the needs, then the build system also needs to be able to make debs. Divorce the work of making MSI files from the build and I think the task is really doable in the short term.

I think that the m4 stuff in autoconf is the only part of autotools that people really get annoyed with. So kill it. Replace it with lua. Or python. Or anything that's cross platform and low impact. (and by that I do not mean Java - sorry guys, the nightmare that is installing Java environments is a subject of an upcoming rant)

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Ok, in case you just showed up going "finally!", I'm sorry to let you down - I haven't yet ported NDB API to erlang.

But I should - and I want to.

Brian was just talking about concurrent program and mentioned erlang. Turns out that when I was starting off working on the NDB/Connectors, Elliot asked me if I'd considered erlang. Always up for learning a new language I did a quick check, but there were no swig bindings, so I put it off until later.

Then later came and I still hadn't written any code, so I found a book online and started reading. I have to say erlang is very cool.

There is no way on earth I can wrap the NDB API in any meaningful way using erlang. However, I might be able to reimplement the wire protocol in erlang and have the resulting thing be way more stable and scalable. Thing is - it really made me thing we should reimplement all of NDB in erlang. It handles several of the tasks done by the NDB system already by itself - and it's not C++ so it doesn't crash and die every three seconds. On the other hand, I don't think it's as fast as C++ yet - so our speed-hungry friends might not want to play.

However... hey Brian - wanna sit down an write a new clustered database engine for MySQL using erlang? Could be fun...

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Morgan is looking in to EC2 on MySQL, so I thought I'd pipe up about stuff I've been playing with.

The ephemeral nature of the data is troubling, because at best you're going to have some lag before you can back stuff up to S3 or some other place. (Unless that was happening continuously... but we'll come back to that) On the other hand, if you're doing app sharding or something similar, this essentially just makes you plan that your machines can all die at any time. If you used Google's semi-sync replication patch, you could easily spin up little replication clusters as needed.

Hm. Clusters. Well, I'm also a fan of MySQL Cluster. What if you ran MySQL Cluster on a single ec2 node (both data and sql nodes)? What if, further, you wrote (and by you, I mean me... code coming soon, I promise) an AsyncFile implementation for Cluster that read and wrote to S3 instead of local disk. Cluster itself is already decoupled from disk write latency. Sounds like a good UC talk...

Then you could do the same thing with a multi-node cluster, but Amazon doesn't let you control the network between EC2 nodes, so the latency there could kill you.

I have put together a few scripts for spinning up an EC2 node with MySQL (and Cluster) ready to go, but I'm sitting in an airport right now, so I'll have to post the code later.

I think the possibilities for scale-out here are fantastic, but like all application partitioning approaches, they do require some engineering of the application to take advantage of it.

Personally, I'm not a fan of more than one ndbd per machine...

Diamond Notes » Fun with Running a Cluster on Two Servers

Others might argue with this, but I would never put the SQL nodes on the same servers as the ndbd nodes for production. Some say you can run multiple ndbd nodes on the same server and I am more comfortable with that since I can lock the ndbd daemon into memory and know its not going to change (my ndbd nodes on those two servers have been at exactly 71.3% since I started them up. If I had servers for the ndbd nodes that had 16+ gigs of RAM I might start allocating 4 gigs of RAM to a ndbd daemon with 3+ daemons per node. My understanding is that this helps keep the transactional logs for the nodes under control. When you do a ndbd node restart it takes less time for a node to get up and running because of the smaller files to read. I might be mistaken and its too late for me to look it up :) Anyone got other reasons or maybe (if I am right) someone can elaborate.

First of all, I'm very excited to see that Cluster is being used for MogileFS here. I've actually been thinking it might be fun to write a MogileFS::Store::NDB class to use NDB/Perl ... but that's another story.

One of the things that's nice about NDB is that it spread across mutliple machines. Now, granted, in development we can't always do this. I run NDB on my laptop all the time, so I certainly feel the pain there. But with a multi-node design, I say take advantage of it. People on other architecture are always asking how they can spread the load more easily across multiple machines, and here you can. If you need 8 data nodes, get 8 machines.

Practically, there is another reason. If you put 3 data nodes on a single physical machine, then if that machine crashes, you have not a single node failure, but 3 nodes failing at the same time. Although there is no specific reason that this won't work, it's also essentially an edge case and not really tested all that well. Other people may disagree with me here, especially as currently running multiple ndbd's on a single box is the only way to take advantage of more that 2 CPU cores, but I'm just not a fan. For something like this, go get a bunch of 2 CPU boxes.

To address the larger question, though, you can certainly spread the write load and the redo log burden by having more data nodes, and having the data distributed across more data nodes will certainly make the log recovery shorter on any one given node. However, there is a price to pay here in query latency. The more data nodes you have, the more nodes your data might be on. If you are not using the NDB API (or any of the NDB/Connectors) then there is no optimized node selection going on. (I've heard someone is working on an Optimized TC Selection patch for mysqld, but it's not in the mainline yet) So if you go from 2 nodes to 4 nodes, you went from a 100% chance that the TC will have your data and not have to ask someone else, to a 50% chance. At 8 nodes you are at a 25% chance that the TC selection will select a node with your data. That's for primary key operations. If you're doing a scan, then your data is going to (most likely) be on all of the nodes, which can be good or bad. But if you're doing MogileFS queries, perhaps the extra milliseconds of latency isn't a concern in this case and you'd rather have faster node recovery. I'd test that hypothesis out and see how much better the recovery is.

Another potential reason to have more data nodes even with the higher latency costs (and extra network traffic as that many more nodes have to talk to that many more nodes) is scalability. Of course, more nodes mean more scaling. But as of now ADDING a data node is not an online operation. Adding more memory can be done in a rolling fashion. So if you think you might need 8 data nodes worth of CPU processing, go ahead and get 8 data nodes with 4G of RAM a piece. Then as you need to store more data, stick in more RAM. Before long, you'll have a nice 256G system... :)

SO... as with everything cluster, there is certainly room on both side of the argument as to what's best here. And as always, testing is the best bet to see how it maps to your environment.

(Also, it's 4AM at the moment, so please forgive me if this rambles a little.)

Our friend Dathan recently suggested that The Quality of mySQL lately sucks.

I've just ran into yet another obvious bug that has made it's way into production.

While I'm not going to argue that more unit tests would be a good thing, I'd like to point out that what he's referring to is not so much a bug as it is a change that happened (and was documented) in 5.0.12:

Beginning with MySQL 5.0.12, natural joins and joins with USING, including outer join variants, are processed according to the SQL:2003 standard. The changes include elimination of redundant output columns for NATURAL joins and joins specified with a USING clause and proper ordering of output columns. The precedence of the comma operator also now is lower compared to JOIN, LEFT JOIN, and so forth.
These changes make MySQL more compliant with standard SQL. However, they can result in different output columns for some joins. Also, some queries that appeared to work correctly prior to 5.0.12 must be rewritten to comply with the standard. For details about the scope of the changes and examples that show what query rewrites are necessary, see Section 12.2.7.1, “JOIN Syntax”.

What this means is that the query in the bug report:

SELECT p.id, gt.object_id FROM Photos p, PhotosExtra px LEFT JOIN GeoTagged gt ON gt.object_id=p.id WHERE px.photo_id=p.id AND p.id = 2173;

should be rewritten to either:

SELECT p.id, gt.object_id FROM PhotosExtra px, Photos p LEFT JOIN GeoTagged gt ON gt.object_id=p.id WHERE px.photo_id=p.id AND p.id = 2173;

or even:

SELECT p.id, gt.object_id FROM , Photos p LEFT JOIN GeoTagged gt ON gt.object_id=p.id JOIN PhotosExtra px ON px.photo_id=p.id WHERE p.id = 2173;

This is a common thing people have to deal with when upgrading to 5.0.