The Kivaloo Data Store(tarsnap.com)
tarsnap.com
The Kivaloo Data Store
http://www.tarsnap.com/kivaloo.html
77 comments
Is there a place I could learn more about how the background cleaning works?
I don't think I wrote much documentation about this, sorry. Basically the idea is that there's a pointer which moves through the key-space looking at pages, and if it passes any pages which are "old" it marks them as dirty so that they're rewritten as part of the next batch. The rate at which the cleaning pointer moves through key-space depends on the accumulated "cleaning debt", which is based on the amount of garbage along with the current I/O rate; the aim is to hit a steady-state where the total amount of I/O is constant and the cleaning gets the "left over" I/O after requests are serviced.
Just wanted to follow up to say I really like how clean and well commented this code is.
Thanks! I'll check out the code in a bit, but that context will help.
> It was designed to satisfy the needs of the Tarsnap online backup service for high-performance key-value storage, although it is not yet being used for that purpose
Does the fact that you're still maintaining Kivaloo this many years later imply it's now being used by Tarsnap?
Does the fact that you're still maintaining Kivaloo this many years later imply it's now being used by Tarsnap?
Tarsnap has recently started using Kivaloo. Over time I intend to use it far more -- but since Tarsnap is a backup service, I'm starting with the least critical parts first.
It wasn’t using it till now? What was the equivalent component previously?
Many things for different purposes. Files in UFS filesystems. Sorted files. Indexed sorted files. In one case, Amazon SimpleDB.
Out of curiosity, what was the use case/upstream requirement for building Kivaloo in the first place?
The Kivaloo page notes that it was designed for Tarsnap, but I'm curious as to the "why" - eg, an eventual-consistency/consensus building block, a simple local metadata service, server-side housekeeping...?
(I'm also curious what "{indexed ,}sorted files" means, and how UFS is significant.)
The Kivaloo page notes that it was designed for Tarsnap, but I'm curious as to the "why" - eg, an eventual-consistency/consensus building block, a simple local metadata service, server-side housekeeping...?
(I'm also curious what "{indexed ,}sorted files" means, and how UFS is significant.)
These are actually some really good numbers for a certain application I'm looking at (https://news.ycombinator.com/item?id=24191307), especially with bulk inserts being so high.
A few questions:
- Why 255 bytes to 255 bytes? Does this have any performance consequences?
- Your laptop is SSD right?
- Is there any more documentation on how to use Kivaloo? (not just facts about it)
A few questions:
- Why 255 bytes to 255 bytes? Does this have any performance consequences?
- Your laptop is SSD right?
- Is there any more documentation on how to use Kivaloo? (not just facts about it)
The 255 byte limit is because I store keys and values as a one-byte length followed by the relevant data. For Tarsnap what I typically want is ~40 byte keys and data (hence using those sizes for benchmarking).
Yes, my laptop has a Intel 660p 512 GB NVMe disk.
No documentation per se, although I hope the library interfaces are reasonably understandable. I'd be happy to help though -- this code deserves to be used!
Yes, my laptop has a Intel 660p 512 GB NVMe disk.
No documentation per se, although I hope the library interfaces are reasonably understandable. I'd be happy to help though -- this code deserves to be used!
Is the one-byte length central to some logic (or some performance concerns), or could one hack the `uint8_t` to a `uint16_t` in kvldskey and so on to get something that could store a bit more? We have some systems that need only 16-32 byte keys but upwards of around 16k values, we're currently using RocksDB but these performance numbers + no compaction process + mux approach are making me interested...
Interesting question. You would need to adjust kvldskey and all of the places where they are serialized (e.g. in pages and in the network protocol). You would also need a much larger page size -- the maximum key+value pair size has to fit into 1/3 of a page.
But if you're willing to make those adjustments and use 64 kB pages, I imagine it would work just fine. Please stay in touch!
But if you're willing to make those adjustments and use 64 kB pages, I imagine it would work just fine. Please stay in touch!
Forgive my complete ignorance/inexperience, but why does the page size need to be increased to 64kB, and why does the key+value length(?) have to fit into 1/3 of a page?
B+Tree leaf nodes contain keys and values. In kvlds (which is the core B+Tree component of kivaloo), the code aims to keep nodes at least 2/3 full, in order to keep the tree approximately balanced. If a key-value pair can take more than 1/3 of a page, you could have a situation where a node is less than 2/3 of a page but adding another key-value pair would take it above the maximum allowed size.
This restriction could be relaxed, e.g. to require only that internal nodes are at least 2/3 full, in which case for the small key / large value case you could have pages which are barely larger than the largest value. I didn't bother doing that since it wasn't relevant to my usage.
This restriction could be relaxed, e.g. to require only that internal nodes are at least 2/3 full, in which case for the small key / large value case you could have pages which are barely larger than the largest value. I didn't bother doing that since it wasn't relevant to my usage.
Have you ever considered getting a Jepsen test done for kivaloo? The claims re: durability and linearizability are worth proving out that way
Correct me if wrong, but kivaloo isn't distributed. Jepsen seems fairly overkill without replication, partition, etc.
You are correct, as things are at the present time. I designed kivaloo to be composable with the intention that I could put a replication/sharding layer in front of it later, however.
I am genuinely intrigued about how much is costs to commission those tests. They are so complete and thorough that I can't see myself being able to afford one for some project of mine, but I would absolutely like to to have an estimate
Also, if you're willing to just write the tests yourself, Jepsen is open-source and Kyle Kingsbury offers a tutorial on how to use it on GitHub.
You might not get the same level of sophistication right away, of course, but that's just a matter of time and diligence.
You might not get the same level of sophistication right away, of course, but that's just a matter of time and diligence.
Jepsen's website says you can contact Kyle at aphyr [at] jepsen [dot] io for pricing.
> ...dropping to ~20,000 from disk
Do you mean with the OS file cache disabled?
Other questions:
1. What are, off top of your head, some design changes or code changes required that'd bring drastic performance improvements?
2. What are some key internals that you think differentiate Kivaloo from other embedded KV stores? I assume you must have gone through a lot of existing literature on the topic before building this. For example, LMDB, BDB, RocksDB, LevelDB, SQLite and the likes come to mind that can double-up as KV stores.
3. Does it store the database in flat files with a WAL in front? Is the file format of the database custom, or based on existing formats?
4. Does the database auto index the fields? Or, use any other such aids to speed up access to data?
Thanks.
Do you mean with the OS file cache disabled?
Other questions:
1. What are, off top of your head, some design changes or code changes required that'd bring drastic performance improvements?
2. What are some key internals that you think differentiate Kivaloo from other embedded KV stores? I assume you must have gone through a lot of existing literature on the topic before building this. For example, LMDB, BDB, RocksDB, LevelDB, SQLite and the likes come to mind that can double-up as KV stores.
3. Does it store the database in flat files with a WAL in front? Is the file format of the database custom, or based on existing formats?
4. Does the database auto index the fields? Or, use any other such aids to speed up access to data?
Thanks.
Do you mean with the OS file cache disabled?
No, I mean with a dataset which is too large to fit into the amount of RAM on the system.
1. What are, off top of your head, some design changes or code changes required that'd bring drastic performance improvements?
Nothing immediately comes to mind. Profiling may reveal some improvements, of course.
2. What are some key internals that you think differentiate Kivaloo from other embedded KV stores? I assume you must have gone through a lot of existing literature on the topic before building this. For example, LMDB, BDB, RocksDB, LevelDB, SQLite and the likes come to mind that can double-up as KV stores.
Well... kivaloo isn't an embedded KV store, so that would be a big differentiating factor. It's a network daemon.
3. Does it store the database in flat files with a WAL in front? Is the file format of the database custom, or based on existing formats?
The "on-disk" format is the pages of a append-only B+Tree, with the last page being the tree root.
I put "on-disk" in scare quotes because there are other backends, e.g. using Amazon DynamoDB to store pages.
4. Does the database auto index the fields? Or, use any other such aids to speed up access to data?
There are no fields. Key-value pairs, nothing more.
No, I mean with a dataset which is too large to fit into the amount of RAM on the system.
1. What are, off top of your head, some design changes or code changes required that'd bring drastic performance improvements?
Nothing immediately comes to mind. Profiling may reveal some improvements, of course.
2. What are some key internals that you think differentiate Kivaloo from other embedded KV stores? I assume you must have gone through a lot of existing literature on the topic before building this. For example, LMDB, BDB, RocksDB, LevelDB, SQLite and the likes come to mind that can double-up as KV stores.
Well... kivaloo isn't an embedded KV store, so that would be a big differentiating factor. It's a network daemon.
3. Does it store the database in flat files with a WAL in front? Is the file format of the database custom, or based on existing formats?
The "on-disk" format is the pages of a append-only B+Tree, with the last page being the tree root.
I put "on-disk" in scare quotes because there are other backends, e.g. using Amazon DynamoDB to store pages.
4. Does the database auto index the fields? Or, use any other such aids to speed up access to data?
There are no fields. Key-value pairs, nothing more.
> Kivaloo (pronounced "kee-va-lieu")
FYI, that's a very American English centric way of explaining how to pronounce 'loo'!
British English pronounces the lone word 'lieu' differently (with a y/j in front of the 'ū'), as in 'lieutenant' as 'leff', and is already familiar with 'loo's and pronounces them 'loo'.
'lieu' is of course of French origin, and they pronounce it differently again.
It's obvious, given 'kivaloo', how it's supposed to be. But unless it's a deliberate joke I think repeating 'loo' is a better pronunciation key!
FYI, that's a very American English centric way of explaining how to pronounce 'loo'!
British English pronounces the lone word 'lieu' differently (with a y/j in front of the 'ū'), as in 'lieutenant' as 'leff', and is already familiar with 'loo's and pronounces them 'loo'.
'lieu' is of course of French origin, and they pronounce it differently again.
It's obvious, given 'kivaloo', how it's supposed to be. But unless it's a deliberate joke I think repeating 'loo' is a better pronunciation key!
Maybe we disagree about how to pronounce the word "value". I pronounce it roughly "val-ee-oo" but maybe you pronounce it simply as "val-oo"?
Er, neither really, 'val-you'. Two syllables, definitely not three, but there is a 'y'.
Rhymes with pew, few, you, new, yew, Kew, etc.
Rhymes with pew, few, you, new, yew, Kew, etc.
Fair enough. Yes, two syllables, but there's a sound between the "val" and the "oo" parts.
If I see "loo" absent context I would normally pronounce it without that intervening sound. Whereas "lieu" has it.
If I see "loo" absent context I would normally pronounce it without that intervening sound. Whereas "lieu" has it.
How do you pronounce “solder”?
saw-dur.
That is what I am accustomed to. However, Mr. Carlson of Mr. Carlson's lab pronounces it "soll-der". https://www.youtube.com/channel/UCU9SoQxJewrWb_3GxeteQPA
I was wondering if that is a common Canadian pronounciation.
I was wondering if that is a common Canadian pronounciation.
Wow, it's never occurred to me anyone would pronounce that much differently (Am/Can pronunciation of 'r' in 'er's aside)! UK is 'soll-duh', or I suppose 'sohl-duh', but certainly sounding the 'l'.
Wiktionary suggests Canada generally follows the pronunciation your familiar with.
Wiktionary suggests Canada generally follows the pronunciation your familiar with.
Yes, generally that is true. There are a few words, at least out west, that stand out: "About" "Schedule" "America".
The last one is in jest. The word is pronounced the same--in the US, often the US is called America, seemingly excluding Canada, Central America, South America.
And a fact that I didn't know until recently was that the Philippines prior to WW II was part of the United States. See "How to hide an empire" by Daniel Immerwahr: https://www.amazon.com/How-Hide-Empire-History-Greater/dp/03...
The last one is in jest. The word is pronounced the same--in the US, often the US is called America, seemingly excluding Canada, Central America, South America.
And a fact that I didn't know until recently was that the Philippines prior to WW II was part of the United States. See "How to hide an empire" by Daniel Immerwahr: https://www.amazon.com/How-Hide-Empire-History-Greater/dp/03...
I'm ashamed to admit I didn't get the connection of the name to "key value" until this comment. So do you yourself pronounce it kee va loo or kee va lyoo? As an American, I see no distinction between the sounds of 'loo' and 'lieu'.
Also American, I pronounce loo /lu/ and lieu /lyu/, in IPA.
I do commonly hear the expression "in lieu of" rendered "in loo of" but have always considered that incorrect, much like pronouncing the t in "often".
It is, of course, just dialect, and the entire idea of 'incorrect pronunciation' is suspect! But I can't help but consider /lyu/ to indicate a higher, er, register.
I do commonly hear the expression "in lieu of" rendered "in loo of" but have always considered that incorrect, much like pronouncing the t in "often".
It is, of course, just dialect, and the entire idea of 'incorrect pronunciation' is suspect! But I can't help but consider /lyu/ to indicate a higher, er, register.
The standard American pronunciation of lieu is "loo". Some people who read the word before ever hearing it (it’s a rare word in ordinary speech, more common in writing), or maybe took a high school French class and want to sound fancy, say something like "lyoo" instead, but this is non-standard and uncommon. (Neither of the two is a correct pronunciation in French.)
I think it really depends on where you're from. I've been hopelessly trying to teach my wife 'perfect' English pronunciation at her request, and the best advice I came up with is to talk with your throat and not your mouth. At least in the Southeast, this works almost perfectly. But we say 'loo' if anything at all, it's a pretty rare word.
From my experience, the more north you go the more you talk with your tongue/mouth. In my examples I was almost able to complete full sentences without moving my lips at all.
From my experience, the more north you go the more you talk with your tongue/mouth. In my examples I was almost able to complete full sentences without moving my lips at all.
"loo" being a British word for "toilet" as well :) (See noun(2) here https://www.merriam-webster.com/dictionary/loo)
Yes, that's what I referred to with:
> and is already familiar with 'loo's and pronounces them 'loo'.
It's not just (and predominantly not) the 'toilet' though, it's the room or facility; what you would call a 'washroom'.
> and is already familiar with 'loo's and pronounces them 'loo'.
It's not just (and predominantly not) the 'toilet' though, it's the room or facility; what you would call a 'washroom'.
Yeah those kind of reading explanations are garbage. There is an alphabet dedicated to that purpose, the International Phonetic Alphabet, which was created exactly for the purpose of writing pronunciation without ambiguity.
I was looking at this yesterday because of the post on "use of a life" post by cperciva. One thing on the benchmarks was I didn't know what was considered "good" numbers, even though I know it's dependent on the type of workload.
Is there a way to compare it to other key-value stores in a fair apples to apples comparison?
Is there a way to compare it to other key-value stores in a fair apples to apples comparison?
(Note the current top comment with updated benchmark numbers, FWIW)
Is there somewhere I can nominate kivaloo for some sort of easily understandable code award? Granted I'm a little biased as it looks a lot like code I would write myself, but wow, it's so refreshing to see code that's full of (useful! illuminating!) comments. Thanks cperciva!
One potentially workable approach: mention it next time someone does a "good source code to read through?" thread, like one of these old ones:
https://news.ycombinator.com/item?id=7602237
https://news.ycombinator.com/item?id=9899766
https://news.ycombinator.com/item?id=13624926
https://news.ycombinator.com/item?id=13854431
https://news.ycombinator.com/item?id=18037613
https://news.ycombinator.com/item?id=18293159
https://news.ycombinator.com/item?id=20556336
https://news.ycombinator.com/item?id=7602237
https://news.ycombinator.com/item?id=9899766
https://news.ycombinator.com/item?id=13624926
https://news.ycombinator.com/item?id=13854431
https://news.ycombinator.com/item?id=18037613
https://news.ycombinator.com/item?id=18293159
https://news.ycombinator.com/item?id=20556336
So, ~40 byte key to ~40 byte value... is kivaloo optimized for records evenly distributed throughout the key space (e.g. hash values)? If so, how?
Some other K/V stores often see ~Zipfian key distribution, e.g., a search index.
Some other K/V stores often see ~Zipfian key distribution, e.g., a search index.
I would be curious how this compares to LMDB. They both use B+Trees (which are just B-trees with siblings linked).
Limiting values to 255 bytes is quite constraining, to say the least.
Also, it seems that there are no transactions in kivaloo. That makes a big difference.
Limiting values to 255 bytes is quite constraining, to say the least.
Also, it seems that there are no transactions in kivaloo. That makes a big difference.
It's rather hard to compare. My understanding is that LMDB is a library which accesses a shared memory-mapped file; kivaloo is a collection of daemons which are accessed via the network or a unix socket. I guess you could place a network protocol front-end on top of LMDB and compare that to kivaloo?
And sure, small values and a lack of transactions are intentional limitations which allowed me to improve performance for the use case I cared about. Of course there's nothing stopping you from constructing that functionality in other ways; in fact I'm planning on releasing a daemon which provides key-blob storage by storing large objects in Amazon S3 and using the core kivaloo functionality as an indirection table.
And sure, small values and a lack of transactions are intentional limitations which allowed me to improve performance for the use case I cared about. Of course there's nothing stopping you from constructing that functionality in other ways; in fact I'm planning on releasing a daemon which provides key-blob storage by storing large objects in Amazon S3 and using the core kivaloo functionality as an indirection table.
Last release 2011-10-11?
Interesting that the author is here commenting as well on a 9 year old project.
Interesting that the author is here commenting as well on a 9 year old project.
I didn't bother doing releases for a while, since nobody else (AFAIK) was using the code.
No worries there, I was just wondering out loud why OP posted, and how you found the thread so quickly
I assume this and a lower-voted thread were both fallout from my front-page post yesterday.
As for how I find it so quickly... I might spend too much time on HN...
As for how I find it so quickly... I might spend too much time on HN...
Paul Graham tweeted yesterday[1] an essay that the author had written which references kivaloo. At least, that's how I came to know about it yesterday.
I read the document on it, then tried to imagine what I would use it for, and couldn't really come up with a use case. I had trouble understanding where I would apply the 255 byte key to 255 byte value paradigm. I also didn't know how the benchmarks compared to similar applications.
1 - https://twitter.com/paulg/status/1307951874721697792
I read the document on it, then tried to imagine what I would use it for, and couldn't really come up with a use case. I had trouble understanding where I would apply the 255 byte key to 255 byte value paradigm. I also didn't know how the benchmarks compared to similar applications.
1 - https://twitter.com/paulg/status/1307951874721697792
255 bytes is obviously overkill for a key (a 32 or 64 byte secure hash of anything larger than 255 bytes can be assumed to unique), so it's just a question of what values are usefully in 255 bytes:
One thought that comes to mind is a distributed store with centralized master, 255 bytes is plenty for a hostname and resource ID.
One thought that comes to mind is a distributed store with centralized master, 255 bytes is plenty for a hostname and resource ID.
255 bytes is obviously overkill for a key
If they're hashes, sure. If you want to answer range requests -- e.g. "give me everything starting with ABCDEF" -- you may have a less densely utilized address space (rather like IP networking has had).
My accounting database has keys of the form "usage/"<256-bit user ID><20-byte timestamp><64-bit machine ID><usage type string>. Not 255 bytes, to be sure, but not trivially short either.
If they're hashes, sure. If you want to answer range requests -- e.g. "give me everything starting with ABCDEF" -- you may have a less densely utilized address space (rather like IP networking has had).
My accounting database has keys of the form "usage/"<256-bit user ID><20-byte timestamp><64-bit machine ID><usage type string>. Not 255 bytes, to be sure, but not trivially short either.
For DHT’s? BitTorrent Kad
Slighlty offtopic, but it's ironic how a service with the tagline "Online backups for the truly paranoid" serves insecure connections to its website and doesn't employ HSTS. Especially since the user is expected to download the client for the service from that website.
Kind of a reckless decision.
Kind of a reckless decision.
Especially since the user is expected to download the client for the service from that website.
You mean the GPG-signed client code?
You mean the GPG-signed client code?
Well yeah but the GPG key is also served insecurely:
http://www.tarsnap.com/tarsnap-signing-key-2020.asc
http://www.tarsnap.com/tarsnap-signing-key-2020.asc
... you know you can change that URL to start "https" if you like?
Of course you are right, but some commonly accepted procedure nowadays is to do that automatically with a redirect, as a service for the user. Sure, you may have a reason for not to do so, but instead of dismissing a valid argument you could maybe explain why not ...
Edit: On second thought, I recognize this whole subthread started with the wrong tone ("ironic", "reckless"), kind of dismissive or patronizing and not calling for a constructive discussion, so please disregard this comment of mine, sorry.
Edit: On second thought, I recognize this whole subthread started with the wrong tone ("ironic", "reckless"), kind of dismissive or patronizing and not calling for a constructive discussion, so please disregard this comment of mine, sorry.
I do think that a certain level of scrutiny is invited by using a term like "for the truly paranoid".
With HSTS, you don't have to.
Well, if the user actually checks the signatures and remembers from their last visit that their should be one coming along with the software, maybe. That's a big if though.
Considering there's no disadvantage in deploying HSTS and there's no good reason to serve an insecure website, especially since they already have HTTPS set up, I'm baffled by that decision. Maybe it's just an oversight but that's not too reassuring either.
Considering there's no disadvantage in deploying HSTS and there's no good reason to serve an insecure website, especially since they already have HTTPS set up, I'm baffled by that decision. Maybe it's just an oversight but that's not too reassuring either.
> Well, if the user actually checks the signatures and remembers from their last visit that their should be one coming along with the software, maybe. That's a big if though.
HTTPS+HSTS adds no security here.
The only (reasonable) way to validate a payload end-to-end is an offline signature validation. This is true regardless of transport-level security measures like HTTPS.
Doing this properly with gpg makes even more sense due to the service targeting the paranoid, who is exactly the group of individuals who are certain to validate a signature.
> Considering there's no disadvantage in deploying HSTS and there's no good reason to serve an insecure website, especially since they already have HTTPS set up, I'm baffled by that decision. Maybe it's just an oversight but that's not too reassuring either.
It's easy, but adds nothing in ways of security here. Just privacy.
(Not that privacy does not have value, of course, but that's an entirely different argument.)
HTTPS+HSTS adds no security here.
The only (reasonable) way to validate a payload end-to-end is an offline signature validation. This is true regardless of transport-level security measures like HTTPS.
Doing this properly with gpg makes even more sense due to the service targeting the paranoid, who is exactly the group of individuals who are certain to validate a signature.
> Considering there's no disadvantage in deploying HSTS and there's no good reason to serve an insecure website, especially since they already have HTTPS set up, I'm baffled by that decision. Maybe it's just an oversight but that's not too reassuring either.
It's easy, but adds nothing in ways of security here. Just privacy.
(Not that privacy does not have value, of course, but that's an entirely different argument.)
Assuming your attacker can count bytes, there's no privacy added by using TLS to download static content from the Tarsnap website. There simply aren't enough similarly-sized files.
But such an attacker would need to know that the content was downloaded from the Tarsnap website, right? If TLS is configured with Encrypted SNI, the handshake no longer reveals server information and thereby TLS does add privacy.
(However, Encrypted SNI is not widely adopted yet.)
(However, Encrypted SNI is not widely adopted yet.)
Surely "truly paranoid" people don't rely on a website using HSTS and hit it with HTTPS directly?
I'm pretty sure the preferred download method is via FreeBSD ports ;)
That page is not very informative. It doesn't explain why anyone should be interested in this project, and compare with alternatives. What's the novelty, what's the edge, etc.
Hardly surprising that it didn't gain much traction.
Hardly surprising that it didn't gain much traction.
For reference, on my laptop (Dell Latitude 7390 with an i7-8650U CPU):
* Bulk inserts run at ~600,000/second (up from 125,000).
* Bulk extracts run at ~660,000/second while in RAM (up from 30,000) and ~220,000/second from disk (up from 20,000).
* Bulk updates run at ~700,000/second in RAM dropping to ~300,000 from disk (up from 110,000 dropping to 60,000).
* Random reads run at ~800,000/second in RAM dropping to ~20,000 from disk (up from 220,000 dropping to 11,000).
* Random mixed run at ~400,000/second in RAM dropping to ~10,000 from disk (up from 30,000 dropping to 4,000).
* Hot-spot reads run at ~800,000/second in RAM dropping to ~500,000 from disk (up from 220,000 dropping to 60,000).
Note that "in RAM" means "the dataset fits into RAM" -- in all cases data is durably stored to disk.
There is almost certainly room for improvement; I haven't done extensive profiling yet.