Almost every Cassandra feature has some surprising behavior

http://blog.parsely.com/post/1928/cass/

by dragonne • 11 years ago

126 73 11 years ago

blog.parsely.com

20kleagues• 11 years ago

Thank you for changing the name of the title. The default title is clickbait which I find very surprising given this is a tech post and IMO the audience for such posts hates these titles.

EdwardDiego• 11 years ago

It's a parody of clickbait.

pixelmonkey7• 11 years ago

OP here. Indeed, it is a parody of click bait, although in retrospect I think I should have avoided it.

Parse.ly's customers are media companies so we deal with news / media / headlines all the time, so we were being cute in referencing this practice in the article. I used the headlines as a mechanism to break up the prose, too, and add some levity, since this article weighs in at over 4,000 words.

But I underestimated the ability of techies to scan the headline and paragraph one of an article and say, "not worth my time" and bounce instinctively. In fact, when I tried to submit this post to r/programming, the moderators instantly deleted it, referencing the headline, despite it being a parody.

One thing I shouldn't be surprised by: The Internet adapts!

zikzikzik• 11 years ago

This Team Used Apache Cassandra Without Reading The Fine Manual… You Won’t Believe What Happened Next

  “You honestly expected that adopting a data store at your scale would not require you to learn all of its internals?”

These aren't even internals, these are basic facts about Cassandra.

dvirsky7• 11 years ago

I do believe Cassandra requires a much more intimate knowledge of its internals if you want to do anything serious with it - more so than any other database I've worked with.

threeseed4• 11 years ago

I have to agree. But with the clarification that it isn't significantly more. Spend a few days and you will be an expert.

And I think it's worth noting that the "serious" things you would do on Cassandra more often than not you couldn't do on most other databases.

robusto• 11 years ago

I agree as well. However, it seems a common mistake to assume you can just "deploy", especially coming from traditional RDBMS.

Great power, great responsibility.

cwyers• 11 years ago

Some of what the article suggests (their own serialization format, using COMPACT STORAGE) isn't in or directly contradicts what the manual suggests to do. This isn't just a case where reading the documentation would tell you everything they found worked for them.

dvirsky7• 11 years ago

The thing is that contrary to many other tools, you can't run Cassandra with almost any of its default settings (maybe besides ports). In most tools you'll need to tweak a few defaults, with Cassandra you need to thoroughly read the docs on every little configuration in the server and schema definitions (especially if you're working in multiple DCs), you'll always find a little surprise if you skim through it.

It's also almost mandatory to read the internal design docs of cassandra even if you're not the admin but just working with it. And modelling data is a lost less trivial than it looks - and almost always not what you assume.

Anyway, this is the best talk I've seen on Cassandra data modeling even if you know Cassandra but not on an expert level. I made sure everyone on my team saw it at least once. https://www.youtube.com/watch?v=qphhxujn5Es

saurik• 11 years ago

The one that is really irksome is the COMPACT STORAGE one, as it is explicitly disrecommended and deprecated by the Cassandra documentation. I have not yet gotten around to using Cassandra in any production environment, nor have I done any large-scale tests, and it has been a while since I delved deeply into the data model, but I remember looking at this part of the storage system and thinking it was "wrong", but wondered if I was just misunderstanding things, given how clearly and strongly it was discouraged. Flipping through the presentation you just linked, they are using all the new features and there are no slides that mention compact storage. "30x", as reported in this article, is clearly non-trivial: what is your take?

dvirsky7• 11 years ago

I haven't dealt with the ops side of running our clusters, and the details are not fresh in my mind, so I don't remember much about the storage engines. But we encountered surprises on almost any front when taking C* to production.

nemothekid4• 11 years ago

The GP is right, I started using Cassandra right before they got a hardon for "CQL" and the docs used to explicitly layout the data model when using the thrift interface. (The Thrift data model is basically what you get when you use COMPACT STORAGE, we still using CQL). Simply put, I bet the 30x increase in performance is not because they used COMPACT STORAGE, and is because Map/collections have terrible performance, and COMPACT STORAGE forced them describe the data the "right" way.

Instead of using a map (or COMPACT STORAGE), they should have defined their schema upfront (one of the limitations brought on by not-SQL). However if they didn't want to do that then COMPACT STORAGE is obviously a better solution than using a Map.

To answer your question about COMPACT STORAGE, standard CQL basically does the work for you (in terms of parsing the "xsv") but you have you define the schema upfront (as in, you have know all the map keys before hand). The reason they tell you not to use COMPACT STORAGE is for those cases where you don't need a dynamic schema, using COMPACT STORAGE doesn't really get you anything.

Lastly, IMO, I wouldn't touch CQL Collections or COMPACT STORAGE unless absolutely necessary. If you do need a dynamic schema I would rather encode the data as a msgpack or protobuf blob.

threeseed4• 11 years ago

I have to disagree. But again given how scalable Cassandra is we could live in different worlds.

I've run multi-gigabyte data sets in Cassandra without any config changes. And when I responsible for a 40 node Cassandra cluster we didn't do any tweaks other than a few JVM settings here and there.

Cassandra I have to admit though is very sensitive to how you model and store your database. The whole tombstone saga is never a fun one to go through.

dvirsky7• 11 years ago

My biggest cluster was 12 nodes, actually a 3*4DCs cluster. I don't recall what the exact issues were, but it took months to stabilize this cluster, and it never performed as well as we'd wanted.

easytiger• 11 years ago

I've run multi-gigabyte data sets

WOW. You've run several GB of data through it? Wow.

fweespeech5• 11 years ago

What tools, etc. did you use to manage the 40-node cluster?

How were you querying 40-nodes or were you offloading the querying to Lucene or something [e.g. like Parsely is]?

smoyer• 11 years ago

I love that the article pokes fun at click-bait articles ... I'm not a Cassandra user but having used several other NoSQL solutions, I'm not at all surprised that this team, who dove into a new technology without caution, was surprised.

threeseed4• 11 years ago

It's not just dove in without caution but without fully checking design decisions.

For example using Maps other than for a storing a handful of values has always been discouraged.

chisleu5• 11 years ago

"We were actually hoping that Cassandra could store things more compactly than our raw data"

Why in hell would you think that?

CQL is not SQL? No shit. Actually, the docs pretty clearly spell that out. Anyone with even a cursory knowledge of Cassandra or any big data store would know you need to understand how the system works, and what it's limitations are before you model your data for the system.

COMPACT STORAGE is for backwards compatibility. Turn it on and you are turning off CQL3: http://docs.datastax.com/en/cql/3.0/cql/cql_reference/create... http://www.datastax.com/dev/blog/whats-new-in-cql-3-0

Counters are only usable for things where you don't care if the counter gets increased exactly one time. It is for stuff that doesn't really matter, like "likes" on a page or something.

I'm not even reading "Check Your Row Size: Too Wide, Too Narrow, or Just Right?" because measuring the number of columns max and the ~10MB performance limit is trivial to do and this is a datastore designed by data scientists for people who are willing to do the very little bit of knowledge gain required.

This whole article reads like someone who decided to incorporate Cassandra without actually spending any time learning how to do it correctly before trying to do it.

"He said, “You honestly expected that adopting a data store at your scale would not require you to learn all of its internals?” He has a point."

No shit.

dang• 11 years ago

Hey, it sounds like you know quite a bit about this topic, and passion for technical matters is something everyone here understands. But please follow the HN guidelines when commenting. It takes some effort, but it's effort we all need to make.

https://news.ycombinator.com/newsguidelines.html

manishsharan2• 11 years ago

Cassandra or most NoSQL databases seem to require a lot more internals knowledge than what a development or an ops team would have. Most sysops teams have a cadre of certified DBAs and administrators and they get on by without any surprises. The one thing Oracle got right was their certification program which ensures there are no gotchas -- most DBA can deliver smooth operations. I guess it is because these NOSQL products are relatively new, they require only ninja level experts to fiddle with the controls.

I would be interested in hearing more from someone who has use a third party managed cassandra service like Google' casandra product https://cloud.google.com/solutions/cassandra/. Did you still deep internal knowledge to use Cassandra ? This is important to know for me because my organization will not have the resources to manage Cassandra clusters but we need a Cassandra like store.

ddorian43• 11 years ago

That's not managed. They install it, but not manage it.

samkone3• 11 years ago

Google doesn't offer a managed cassandra, rather a manager Bigtable with the HBase Api. But we run a huge Cassandra install in multi dacenters on GCP. And we're good. And yes it requires you to understand distributed storage systems, and the some of Cassandra internals.

lobster_johnson3• 11 years ago

On the other hand, if you tried to fit the article's use case -- at that scale -- into something like PostgreSQL you would still have to start learning the internals.

I think the article author's problem as that they assumed Cassandra would be similar to the technology they were already familiar with, which was not the case; it's different in so many areas, especially with regard to its performance profile, and to someone used to relational databases it's outright alien.

At the scale they're describing, they do exceed the threshold point at which one has to learn the internals of the technology. In engineering, scale is everything. Riding a bicycle doesn't require that you know how bicycles work, but sending a rocket to the moon demands a lot of knowledge about a wide range of subjects.

dmarklein• 11 years ago

SQL is "trendy"?

NDizzle• 11 years ago

It depends on the phase of the moon.

pixelmonkey7• 11 years ago

OP here. Surprised to find this article on the HN front page, a month after we originally posted it.

Glad to answer questions. Ask me anything!

samkone3• 11 years ago

So are you still running Cassandra? And why rely on counters for analytics when it's wildly known to be a bad idea.

pixelmonkey7• 11 years ago

We are still running Cassandra. It's used in a more restricted way than we originally thought we'd use it, but we're following the recommendations we wrote up in linked article.

We don't use counters -- at all. (This is discussed in one of the sections.) Counters are one of the few Cassandra features that can offer you some form of value aggregation inside the data store, but we decided they weren't worth it, due to the quirks.

What do you mean by, "when it's wildly known to be a bad idea?" What are you referencing? Lots of people use counters in Redis and MongoDB for analytics, for example.

IndianAstronaut• 11 years ago

Are you using Cassandra for analysis? What is your analysis workflow like?

pixelmonkey7• 11 years ago

We use Cassandra for data grouping and ordering. Find our other blog post on "Mage", our time series engine, for more info.

arthursilva• 11 years ago

Bashing non-COMPACT storage is nonsense.

non-COMPACT store by itself doesn't add any significant overhead (only 2 bytes per cell and even less after compressed). What really wastes space is using collections types. Even using that I doubt it will ever reach the 30x mark the author stated.

chisleu5• 11 years ago

The article is full of nonsense and the OP is here so criticism is being downvoted.

pixelmonkey7• 11 years ago

huh?

baldfat2• 11 years ago

I still think of Cassandra as the tool the Digg engineers used to kill Digg as we all loved/hated it at it's time.

samkone3• 11 years ago

If a company blames its demise on a piece of tech, then they either need better engineers to change that tech. Or the product had no future at all. And Cassandra has changed a lot since then.

baldfat2• 11 years ago

What I said still is true. Digg USED Cassandra to destroy itself. They changed business plans and removed the community with a ton of down time and a loss of data.

I agree it wasn't Tech fault for Kevin Rose allowing VCs to control Digg, but there were issues with Cassandra and especially during the SQL vs NoSQL debate at its highest levels.

takeda• 11 years ago

The demise of digg was purely due to them making a silly decision that articles were submitted automatically from third parties and users activity was pretty much reduced to voting on them. This generated huge backlash and made most users migrate to reddit.

hobofan• 11 years ago

We used C* for a similar use case and encountered some of the same issues.

The article doesn't even mention that there are a lot of places in the docs where it says: "If you configure a keyspace like this, your node will most likely crash". Not just degraded performance, any develeoper with some access might crash a node (and maybe the whole cluster) with a userspace error.

The main lesson I took away from Cassandra is that battle-tested@Netflix(/other bigcorp) doesn't mean resilient and might require a engineer on standby at all times to run correctly.

chisleu5• 11 years ago

Yeah we don't have that problem with MariaDB at all (joking.)

Bad users (read: developers) can break things. If you are worried about bad users, then put an api between users and the datastore to keep them from breaking things.

rohansingh2• 11 years ago

The main lesson I took away from Cassandra is that battle-tested@Netflix(/other bigcorp) doesn't mean resilient and might require a engineer on standby at all times to run correctly.

This is entirely true. We are big users/consumers/fans of Cassandra at Spotify. We have approximately one crap-ton of Cassandra clusters with several metric crap-tons of data. But we have an entire team that provides support and tooling around Cassandra. We contribute upstream, and have employed core Cassandra contributors in the past.

In return we get a datastore that scales pretty much infinitely with our data sets, has performance characteristics that we are now well aware of and are able to reason about, and provides us cross-DC replication and topology-awareness. It took years to get to this point though, and to build the operational expertise required to run Cassandra. Only recently have we gotten to the point where teams are able to self-service provision their own Cassandra clusters.

This is a resilient, scalable solution, but if I were to quit tomorrow and start a five-person startup, there is no way I would consider C* as a workable solution.

skorgu• 11 years ago

What would you use?

zenogais• 11 years ago

It's been posted in the comments below, but I'll reiterate it because it needs to be said. This article is more about the issues of naive database adoption strategies than any deep fundamental flaw with Cassandra.

I've deployed C* on some similarly large datasets and encountered none of these issues - even when storing terabytes of time-series data. The difference - I read through the documentation from head to foot before getting started, did numerous dry-runs to figure out the data modeling, and when I wasn't sure about something asked the community (who are usually incredibly quick to respond on IRC, twitter, or elsewhere).

Tloewald3• 11 years ago

The thing about encoding multiple fields within a cell using \x01 somewhat bugs me -- not because it's a hack but because it's yet another example of needless reinvention of wheels. Good old ASCII has characters specifically devoted to separating fields, keys, etc. that no-one uses for anything else. Why not use them instead of inventing a new character that does the same thing? (By the same token, there was never any need for CSV or tab-delimited text since those characters can't be typed into spreadsheet cells; parsing CSV can be a pain, and TABs can be typed.)

If you care, the characters are:

FS -- file separator 1C

GS -- group separator 1D

RS -- record separator 1E

US -- unit separator 1F

As you can see, they also have the benefit of being self-describing (unlike \x01, as the article points out).

(The sad thing is I only learned about these characters because I had to parse files in a 1960s format originally designed to be stored on tape drives -- and they used these delimiters and they worked great.)

ufo• 11 years ago

as a younger programmer, the only place I have ever seen these characters is that the fish shell uses the Record Separator character when it exports an environment variable that is an array.

delluminatus• 11 years ago

I only found out about these recently because my company uses them in their custom RPC protocol, which was created about 15 years ago I think.

IMO, there are ups and downs to using unprintable characters in your protocol. On one hand, yeah, you don't need to worry about someone putting a tab in a TSV field and messing up the format. On the other hand, it can make debugging a lot harder because what you see isn't necessarily what you get, and obviously it becomes harder to hand-write requests.

Of course, OP ended up using unprintable characters anyway, so I think they might as well use the ASCII ones. But even if you know about and use those characters, I think there is still a place for [CT]SV.

I'm glad you brought them up though, because I think the nonprintable ASCII characters occupy a very interesting place in computer science -- (almost) universally supported, but (almost) never used.

Tloewald3• 11 years ago

You can make a case for CSV because it's text editor friendly, and tabs because it conceptually maps to typewriters, but we don't even have the option to use these characters. And arguing that typing escape sequences to represent common characters is better is pretty difficult to swallow.

amelius• 11 years ago

Why not use them instead of inventing a new character that does the same thing?

Perhaps because the fields could also be using these same characters internally?

Tloewald3• 11 years ago

How much would you care to wager?

serialpreneur• 11 years ago

I think you can sum up some of the grievances of the OP as "felt mislead by Cassandra/DataStax marketing". But, some of the criticism is not really the fault of Cassandra or DataStax at all IMO.

- CQL stands for Cassandra Query Language. As a user of C*, I don't remember anywhere in docs it claiming it conforming to the SQL standard. They do mention it to be "similar to SQL" which is a fair comparison.

As a counter-example of another somewhat similar database, AWS DynamoDB. The absence of a CQL like syntax really frustrates me.

- Data Modelling: Effective data modelling is difficult in all DB systems, inherently more so in NOSQL or non-ACID distributed DBs.

- Counters & Collections: I feel that criticism is legit. I felt similar pains too. I've learned the lesson there not to trust all marketing claims.

sidonie• 11 years ago

I always assumed Cassandra to be the easiest-to-operate distributed database. What are other choices could I make? I'm primarily interested in using it as a distributed, on-disk, datacenter-aware hash table.

Almost every Cassandra feature has some surprising behavior

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