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To Shard, or Not to Shard

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To Shard, or Not to Shard

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When I talk with customers about sharding decisions I often start by telling the following true story…

A couple of years ago, a customer came to me looking for advice on how to shard his system. He told me he was already convinced he needed to do that since he read that some smart people at MySQL giants like Facebook and Twitter were sharding—so naturally this was something he should be doing, too.

I paused for a moment and then I asked him what the size of his database was.

“10GB,” he said.

I nodded and asked if he handles many queries or if they were very complicated.

“No,” he said. “Just a few hundred queries per second, and they have not been loading down the system by more than a few percent.”

I asked him whether he was expecting exponential growth in the near future—looking to double every week or something like that.

“No, our load and data size grew about 7 percent last year and we expect about the same growth this year and for the foreseeable future.”

My recommendation to him was not to waste time and effort on sharding because it is just not needed in his company’s case.

Before you decide how to shard, you’d best understand whether or not you really need to shard to begin with. Yes, on the extremely large-scale side of database demands, sharding is the only game in town. And not just for MySQL, but for pretty much any technology out there.

Yet thanks to emerging technologies there is an increasing amount of applications that can run databases without sharding. Today we can easily run with terabytes of data per MySQL instance and serve tens of thousands of queries in many OLTP environments. This allows organizations to build very large applications without needing to shard.

And keep this in mind: Sharding is a pain under all circumstances. Even if you have sharding provided out of the box by the database system, it is a pain because it introduces more components and complexity. Creating good distributed query execution plans is a very complicated task that needs to take network topology and load into account in addition to the data distribution and load of individual nodes.

Before you decide if you need to shard, you should look at alternatives to scale your application. In the MySQL world, the solutions are typically as follows:

Alternatives to Sharding

Functional Partitioning: In many environments a single MySQL instance becomes a dumping ground for all kinds of databases—you might end up having your main application share a database instance with Drupal, which powers your website, with WordPress, which powers your blog, and with vBulletin, which powers your forums. Splitting those pieces into different database instances is something you should consider before you look into sharding. Custom-made systems will often have many applications using different data sets that can be easily split out.

Replication: Many applications are read-heavy, so scaling reads becomes the issue earlier than it does with scaling writes. Replication is a great solution for this. MySQL’s built-in replication is very robust, though due to its asynchronous nature it adds complexity to the application. The developer must decide which of the reads can be done from the replica servers and which can’t, because you must be absolutely certain that you’re reading the most recent, actual data. This is the reason that alternative, synchronous replication technologies for MySQL like Percona XtraDB Cluster, are gaining popularity: They provide single database-like behavior from the cluster in most cases.

Caching and Queueing: Caching is a great technology for reducing the amount of reads that hit the database. There are many applications that have reduced read load on the database by 80-95% using this technology. Queueing, in contrast, optimizes writes. It does this by merging multiple write operations together so they hit the database efficiently. Most large-scale applications should rely heavily on both of these technologies. Memcached and Redis are two popular caching technologies in the MySQL space. For queueing, the most popular technologies are ActiveMQ and RabbitMQ [1].

Supplemental Technologies: MySQL is great at many things but not at everything. If you’re looking for high-performance full-text search, consider ElasticSearch, Sphinx, or Lucene. If you’re looking at large-scale data analytics, a Hadoop-based infrastructure or Vertica might work well for you. You should let MySQL handle the things it is good at, and leave the rest to supporting tools.

Optimizations to Make Before Sharding

Scaling isn’t just about architecture either. You also need to make sure your system is reasonably optimized. Many people decide sharding is inevitable for them even though there are much easier and more cost-effective ways to get the performance and scale they are looking for. All of which, I might add, are also going to be valuable if sharding is indeed eventually needed.

Hardware: Are you using the right hardware? I’ve seen many people looking into sharding when in fact simply purchasing decent hardware would solve their problems for years to come. Make sure you have plenty of memory and high-performance flash storage if you’re working with a large database. In many cases it can transform your system so much it will look like magic.

MySQL version and Configuration: Use a recent MySQL version. By that I mean the latest GA version (MySQL 5.6 at the time of this article’s publication). Percona Server, which is free, often offers additional performance improvements for demanding workloads. Use the most recent operating system too, especially if you’re using modern hardware. Finally, make sure MySQL is configured properly. The difference in MySQL performance between poorly configured MySQL and well-tuned MySQL can be 10x or more.

Schema and Queries: The same application logic can be expressed using a variety of schema and queries. I’ve seen a lot of similar applications approaching things differently, and the difference in the performance between an optimal approach and a poor one (but still used in production) can be 100x or more. Many of the changes can be retrofitted to existing schema—such as minor query changes and changes to the index structure—however, if your schema doesn’t fit your application needs well, then you might be looking at a complete redesign. So it is a good idea to think things through early.

When to Shard

So when should you start thinking about sharding? Basically, if none of the measures listed above have given you the performance you need, it might be time to consider sharding. Sharding does have the advantage of allowing you to potentially use lower-cost hardware or cheaper cloud instances.

Most developers are using agile development methods these days and there is a common term, “Architectural Runway,” which defines how far the application can go with its current architecture. If you’ve already found success using replication in particular, it might be a bad decision to add sharding because it will force your developers to deal with the complexity of sharding and asynchronous replication. However, replication is still typically used to achieve high availability even if you’re already sharding, but in this case it’s not for scaling reads.

If you’ve come to the point where you’re sure you need to shard, here are some of the questions you need to ask about how you’ll implement your sharding strategy:

Shard Level: At which level should we shard? It does not have to be at the database level. Many applications, SaaS in particular, often “shard” on higher levels, deploying multiple copies of their full stack to offer complete isolation for availability, performance, security etc. In many large scale applications you will see multiple copies of a full stack deployed, each having its own sharded MySQL environment.

Shard Key: How do we shard? In many cases the choice depends on whether you’re authenticating for user accounts or your organization, but in other cases it is not so obvious. When making a sharding choice, you need to think about two things: 1) as many data access points as possible should go into a single shard, because cross-shard access is expensive if supported at all, and 2) making sure such sharding does not produce a shard that is too large to handle either in terms of data size or traffic. For example, sharding by country is a poor idea because the requirements to handle Belgium traffic won’t be the same for the United States or China, which require a lot more resources.

Shard by Schema or Instance: What is the unit of your shard? The typical choices are MySQL instance or database (schema). I like the shard = database approach, which doesn’t limit you to a single MySQL instance per physical box. That way you do not have to run too many MySQL instances, but you can run more than one if the application works better that way.

Shard Unit: If you shard by a single MySQL server, you will run into a problem with high availability very soon. When you have 100 MySQL servers there are roughly 100 more chances for one of them to crash compared with having only one, so ensuring there is a high availability solution becomes critical. Instead of sharing across MySQL servers you will usually be sharding across “Replication Clusters,” such as one MySQL primary node and one or several replica or PXC (Percona XtraDB Cluster) nodes.

Shard Technology: What technology can you use to assist you with sharding? Within the MySQL world there is no standard sharding technology as of yet that everyone uses. Most of the large web properties have implemented something in-house for their sharding needs, and some have released their solutions as open source projects. One example is Vitess, contributed by Google, and another is JetPants, contributed by Tumblr. Rolling out your own simple sharding framework might look easy for some developers until you have to deal with operational issues like balancing the shards, resharding, etc., on a large scale. There are a number of purpose-built technologies that can help you with sharding if this doesn’t sound like something your team can manage.

Sharding Technologies

Here are technologies that you should consider:

MySQL Fabric: This is the sharding technology being developed by the MySQL team at Oracle. MySQL Fabric is GA, but its functionality right now is rather limited, especially in terms of their support for multi-sharded queries. Given more time however, it has the potential to become the standard sharding technology for MySQL.

Tesora: Tesora has a proxy-based solution for MySQL sharding that became open source some time ago. I would be especially looking at Tesora if you’re also looking at deploying OpenStack, as they’ve invested a lot into the integration.

ScaleArc: ScaleArc is a commercial database proxy solution that can do caching, filtering, routing, and sharding. It is a pretty mature solution that handles multiple database technologies and not just MySQL.

ScaleBase: ScaleBase is a sharding solution designed specifically for MySQL and the cloud, which similarly to MySQL, operates at the proxy level.

There are many technologies in the MySQL space that can help you scale your application without sharding. If you’re going to build the next “Facebook,” however, you will surely need to shard, and there are a number of technologies that can help you do it as painlessly as possible. Large-scale applications on large-scale databases will always introduce complexity, which makes them more complicated to develop against and manage. Success comes with cost.

[1] http://dzone.com/research/guide-to-enterprise-integration

Peter Zaitsev co-founded Percona in 2006, assuming the role of CEO. Percona helps companies of all sizes maximize their success with MySQL. Peter enjoys mixing business leadership with hands on technical expertise. Peter is also the co-author of O’Reilly’s High Performance MySQL, one of the most popular books on MySQL performance.

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