Skip to main content

Consistent hashing vs order-preserving partitioning in distributed databases

The Cassandra distributed database supports two partitioning schemes now: the traditional consistent hashing scheme, and an order-preserving partitioner.

The reason that almost all similar systems use consistent hashing (the dynamo paper has the best description; see sections 4.1-4.3) is that it provides a kind of brain-dead load balancing from the hash algorithm spreading keys across the ring. But the dynamo authors go into some detail about how this by itself doesn't actually give good results in practice; their solution was to assign multiple tokens to each node in the cluster and they describe several approaches to that. But Cassandra's original designer considers this a hack and prefers real load balancing.

An order-preserving partitioner, where keys are distributed to nodes in their natural order, has huge advantages over consistent hashing, particularly the ability to do range queries across the keys in the system (which has also been committed to Cassandra now). This is important, because the corollary of "the partitioner uses the key to determine what node the data is on" is, "each key should only have an amount of data associated with it (see the data model explanation) that is relatively small compared to a node's capacity." Cassandra column families will often have more columns in them than you'd see in a traditional database, but "millions" is pushing it (depending on column size) and "billions" is a bad idea. So you'll want to model things such that you spread data across multiple keys and if you then pick an appropriate key naming convention, range queries will let you slice and dice that data as needed.

Cassandra is in the process of implementing load balancing still, but in the meantime order-preserving partitioning is still be useful without that if you know what your key distribution will look like in advance and can pick your node tokens accordingly. Otherwise, there's always the old-school hash-based partitioner until we get that done (for the release after the one we'll have in the next week or so).

See the introduction and getting started pages of the Cassandra wiki for more on Cassandra, and drop us a line on the mailing list or in IRC if you have questions; we're actively trying to improve our docs.

Comments

Jay Farrimond said…
Very interesting. BTW, reading the post I get the feeling you're now a part of the Cassandra development team. Is this true?
Jonathan Ellis said…
Yes, I was added as a committer at the end of March.
Jay Farrimond said…
Cool! I started to say "good for you", then I realized that it's really "good for Cassandra!"

Popular posts from this blog

A week of Windows Subsystem for Linux

I first experimented with WSL2 as a daily development environment two years ago. Things were still pretty rough around the edges, especially with JetBrains' IDEs, and I ended up buying a dedicated Linux workstation so I wouldn't have to deal with the pain.  Unfortunately, the Linux box developed a heat management problem, and simultaneously I found myself needing a beefier GPU than it had for working on multi-vector encoding , so I decided to give WSL2 another try. Here's some of the highlights and lowlights. TLDR, it's working well enough that I'm probably going to continue using it as my primary development machine going forward. The Good NVIDIA CUDA drivers just work. I was blown away that I ran conda install cuda -c nvidia and it worked the first try. No farting around with Linux kernel header versions or arcane errors from nvidia-smi. It just worked, including with PyTorch. JetBrains products work a lot better now in remote development mod...

Python at Mozy.com

At my day job, I write code for a company called Berkeley Data Systems. (They found me through this blog, actually. It's been a good place to work.) Our first product is free online backup at mozy.com . Our second beta release was yesterday; the obvious problems have been fixed, so I feel reasonably good about blogging about it. Our back end, which is the most algorithmically complex part -- as opposed to fighting-Microsoft-APIs complex, as we have to in our desktop client -- is 90% in python with one C extension for speed. We (well, they, since I wasn't at the company at that point) initially chose Python for speed of development, and it's definitely fulfilled that expectation. (It's also lived up to its reputation for readability, in that the Python code has had 3 different developers -- in serial -- with very quick ramp-ups in each case. Python's succinctness and and one-obvious-way-to-do-it philosophy played a big part in this.) If you try it out, pleas...

Why PHP sucks

(July 8 2005) Apparently I got linked by some PHP sites, and while there were a few well-reasoned comments here I mostly just got people who only knew PHP reacting like I told them their firstborn was ugly. These people tended to give variants on one or more themes: All environments have warts, so PHP is no worse than anything else in this respect I can work around PHP's problems, ergo they are not really problems You aren't experienced enough in PHP to judge it yet As to the first, it is true that PHP is not alone in having warts. However, the lack of qualitative difference does not mean that the quantitative difference is insignificant. Similarly, problems can be worked around, but languages/environments designed by people with more foresight and, to put it bluntly, clue, simply don't make the kind of really boneheaded architecture mistakes that you can't help but run into on a daily baisis in PHP. Finally, as I noted in my original introduction, with PHP, ...