This is just to let folks know I’ve (finally) written up some documentation on how to use capjure. Hope it helps!
Capjure: a simple HBase persistence layer – updated with documentation
Posted by Amit Rathore on May 25, 2009
Posted in clojure, code, database, lisp, webscale | Leave a Comment »
Startup logbook – v0.2 – distributed Clojure system in production
Posted by Amit Rathore on May 2, 2009
This past weekend, we pushed another major release into production. We’ve been working on several things and have made a few pushes since the last time I wrote about this – but this release has a bunch of interesting Clojure related stuff.
Long-running processes
The main thing of note is that the majority of our back-end is now written in Clojure. You might recall that our online-merchant customers send us a lot of data, and we run a ton of analytics on that data. Our initial plans involved Ruby, but as we started using Clojure, it turned out that it is very well suited for this job as well (long running, message-driven processes that crunch numbers).
The raw data sits in HBase, and every night a “master” process starts up which kicks-off the processing of the previous day’s worth of data. The job of this master is only to coordinate the work (it doesn’t actually do any real work), it does this by breaking work into chunks and dispatching messages that each assign work to any worker process that picks it up. The master is single threaded for simplicity, but failure tolerant – it checkpoints everything in a local MySQL database, and if it crashes, it is automatically re-spawned and it recovers from where it left off.
An elastic cloud of worker processes run in anticipation of the master handing out this work. The worker processes use the MySQL database to keep track of their progress as well. The rest is rather domain-specific. We use intermediate representations of the raw data, which is also stored in HBase, before finally storing the summarized version again in HBase.
Swarmiji
We use an in-house distributed-programming framework called Swarmiji to make such distributed programs very easy to write and run. Swarmiji implements a flavor of staged event-driven architecture (SEDA) to allow server processes that exhibit scalable, predictable throughput. This is especially true in the face of over-load, which we can certainly expect in our environment.
The reason I wrote this framework was that I wanted to create distributed, parallel programs which exploited large numbers of machines (like in a data-center) – without being limited by clojure’s in-JVM-threads-based model. So each worker process in Swarmiji gets deployed as a shared-nothing JVM process.
I will write up a post introducing Swarmiji in the next few weeks – once its a bit more battle-tested, and I’ve added a few more features (mainly around process management).
Posted in clojure, code, distributed-systems, lisp, startup, webscale | 3 Comments »
Using messaging for scalability
Posted by Amit Rathore on April 12, 2009
I don’t understand why this whole debate about scalability is so focused on choice of the programming language.
At Runa, we provide a service to our immediate customers who are all online retailers. Their website integrates with our services in a couple of ways (via Javascript inserts and via traditional http calls) – and each time a shopper browses any of these online market-places, our services are called. Lots of times – a dozen times per retailer page-view on average.
Our load also grows in large step-functions. Each time we get a new customer, our services get called by another set of users (as all our customers’ customers get added on). We need our services to keep up with all this demand.
Finally, lets take an example of one of the things we provide via these services – dynamic pricing for products. Obviously, the response of such calls needs to be in real-time – since the price has to be shown next to the product being browsed.
So we have a load as well as a response-time concern – as most typical web-scale services do.
Our approach has been to favor simplicity – very early on we introduced a messaging backbone.
Despite the fact that this picture looks a bit more complex than it would without the RabbitMQ portion, this has allowed us to do a few things -
- For those service calls that don’t need immediate responses – (for instance, our client websites send us data that we analyze later, or we need to send an email notification) – we just drop these onto an appropriate queue. An asynchronous processor picks up the message, and does the needful.
- For those services that need responses immediate responses, the call is handled synchronously by one of the application servers.
- For those services that are heavier in terms of the computation required, we split the request into pieces and have them run on separate machines. A simple federation model is used to coordinate the responses and they’re combined to return the result to the requester.
- With the above in place, and by ensuring that each partial service handler is completely stateless, we can scale by simply adding more machines. Transparently. The same is true for all the asynchronous processors.
As an aside – I’ve written a mini-framework to help with those last couple of bits. It is called Swarmiji – and once it works (well) in production, I will open-source it. It may be useful for other folks who want a sort of message-passing based parallel programming system in Clojure.
So anyway, with this messaging system in place, we can do a lot of things with individual services. Importantly, we can try different approaches to implementing them – including trying different technologies and even languages.
IMHO, you can’t really have a conversation about scalability without context of how much load you’re talking about. When you’re just getting started with the system, this is moot – you don’t want to optimize early at all – and you can (mostly) ignore the issue altogether.
When you get to the next level – asynchronicity can get you far – and this side-steps the whole discussion of whether the language you’re using is efficient or not. Ruby is as good a choice as any in this scenario – Python or Java or most other languages will leave you in the same order of magnitude of capability. The key here is high-level design, and not doing too many obviously stupid things in the code.
When you do get crazy large (like Google or whatever), then you can start looking at ways to squeeze more out of each box – and here it may be possible that using the right language can be an important issue. I know Google even has a bunch of people working on compilers – purely to squeeze more out of the generated code . When you have tens of thousands of computers in your server farms, a 2% increase is probably worth a lot of money.
Still, this choice of language issue should be treated with caution. I’m personally of the opinion that programmer productivity is more important than raw language efficiency. That is one reason why we’re writing most of our system in a lisp (Clojure) this time around. The other thing is that these days runtimes are not what they used to be – Ruby code (and Python and Clojure and Scala) can all run on the JVM. So you can get the benefits of all those years of R&D basically for free.
Finally, a word on our messaging system. We’re using RabbitMQ – and it is *fast*, reliable and scalable. It truly is the backbone of our system – allowing us to pick and choose technology, language, and approach. It’s also a good way to minimize risk – a sub-system can be replaced with no impact to the rest of the pieces.
Anyway – take all of this with many grains of salt – after all, we’re not the size of Google (or even Twitter) – so what do I know?
Posted in architecture, clojure, design, languages, webscale | Leave a Comment »
Capjure: a simple HBase persistence layer
Posted by Amit Rathore on March 31, 2009
Or how to get some free help putting stuff into HBase. For Clojure programmers.
OK, so maybe this one can even be called simplistic. Still, it works for my needs right now – so I thought it might help others. I wrote about my use-case in a previous post about HBase schema design – and this is the little helper utility I mentioned towards the end of it.
How to use it
Download here. There are two vars that need appropriate bindings for capjure to work – *hbase-master* and *primary-keys-config*
*hbase-master*
This one is obvious. It must be bound to an hbase name-node or a master server. For example, I might bind it to hbase.test-site.net:60000. Watch out for the fact that Amazon’s EC2 instances need lots of configuration to open such ports to the world. This has no real relevance to this post, just thought I’d mention it.
*primary-keys-config*
This one is a bit more involved – and I’m sure I’ve done a bad job of simplifying this usage pattern. Still, lets consider the example from the previous post. When you have an array of several hashes as a value in your JSON object that is being persisted (eg. for the :cars key) -
:cars => [
{:make => 'honda', :model => 'fit', :license => 'ah12001'},
{:make => 'toyota', :model => 'yaris', :license => 'xb34544'}],
it will be converted into
{
"cars_model:ah12001" => "fit",
"cars_make:ah12001" => "honda",
"cars_model:xb34544" => "yaris",
"cars_make:xb34544" => "toyota"
}
To make this happen, capjure needs to know what to use as a primary-key. Or something like that 
Here, we have decided upon the :license attribute of each hash. Capjure then removes that property from the child-hashes being saved, and sticks the value into the key part of the flattened data-structure as shown above.
This is accomplished by -
(def encoders (config-keys (config-for :cars :license (fn [car-map] (car-map :license))))
Similarly, other primary-keys can be configured. And because the actual value used is the value returned by the function defined (as above), it can be as complex as needed. For example of the values have spaces, you can encode it using some scheme.
A similar configuration is needed for this process to be reversed during reading out of HBase. The
(def decoders (config-keys (config-for :cars :license (fn [value] value)))
In this case, we just use an identity function because the reverse mapping is straight-forward (in other words, we didn’t do anything fancy during the previous flattening operation). What happens is that a key-value pair (key being the one specified (:license)) and the value as whatever is returned by the function is added to the flattened object being re-hydrated.
Similarly, other configuration parameters can be added for other sub-objects that have primary-keys.
Together, the encoders and decoders form the *primary-keys-config*. Thus, if you do the following -
(def keys-config {:encode encoders :decode decoders})
then keys-config should be used as the value that *primary-keys-config* gets bound to.
Methods of interest
Once this is done, objects can be pushed into and out of HBase quite trivially -
(binding [*hbase-master* "hbase.test-site.net:60000" *primary-keys-config* keys-config] (capjure-insert some-json-object "hbase_table_name" "some-row-id"))
and -
(binding [*hbase-master* "hbase.test-site.net:60000" *primary-keys-config* keys-config] (read-as-hydrated "hbase_table_name" "some-row-id"))
Other convenience methods
Capjure provides other convenience methods like -
row-exists? [hbase-table-name row-id-string] cell-value-as-string [row column-name] read-all-versions-as-strings [hbase-table-name row-id-string number-of-versions column-family-as-string] read-cell [hbase-table-name row-id column-name] rowcount [hbase-table-name & columns] delete-all [hbase-table-name & row-ids-as-strings]
and others. Everything is based off (uses it underneath) the HBase client API. Thanks to Dan Larkin for clojure-json.
Limitations
I’m no expert in persistence systems – and I’m sure this one has plenty of issues. The main limitation is that the object that capjure can persist can only be so deep. Specifically, the object should be a hash that contain symbols (or strings) as keys, and the values can either be strings (or other primitives), arrays of such primitives, a hash with one level of key-values, or an array of hashes that are one level deep.
Feedback welcome
Please contact me if you have suggestions and stuff. Again, the code is on github.
Posted in clojure, code, database, webscale | Leave a Comment »
HBase: On designing schemas for column-oriented data-stores
Posted by Amit Rathore on March 8, 2009
At Runa, we made an early decision to optimize.
We decided not go down the scaling a traditional database system (the one in question at the time was MySQL) route and instead to use a column-oriented data-store, that was built for scaling. After a cursory evaluation (which was done by me – and it involved a few hours of browsing the web (pseudo research), checking email (not research), and instant-messaging with a couple of buddies (definitely not research) – we picked HBase.
OK, so the real reason was that we knew a few companies are using it, and that there seemed to be a little bit more of a community around it. In fact, there are a couple of HBase user-groups out here in the bay area. Someone recently asked me about CouchDB, and I’ve noticed a lot more buzz about it now that I’m watching for it… I’ve no reason why we didn’t pick it instead. They’re both Apache projects… maybe we’ll have use of CouchDB someday.
HBase schemas:
So anyway, we picked HBase. Now, having done so, and also having spent all my life using relational databases, I had no idea how to begin using HBase – the very first question sort of stumped me – what should the schema look like?
Here’s what I figured out – and I’m sure people will flame me for this – you don’t really need to design one. You just take your objects, extract their data using something like protocol buffers, yaml/json, or even (ugh!) XML – and then stick those into a single column in an HBase table.
Our simplistic HBase mapper:
We use JSON – but we’re doing something slightly different. Think of our persistable object represented by a fairly shallow JSON object – like so:
:painting => {
:trees => [ "cedar", "maple", "oak"],
:houses => 4,
:cars => [
{:make => 'honda', :model => 'fit', :license => 'ah12001'},
{:make => 'toyota', :model => 'yaris', :license => 'xb34544'}],
:road => {:name => '101N', :speed => 65}
}
OK, bizarre example. Still – the way you would persist this in HBase with the common approach would be to create an HBase table that had a simple schema – a single column family with one column – and you’d store the entire JSON message as text in each row. Maybe you would compress it. The row-id could be something that makes sense in your domain – I’ve seen user-ids, other object-ids, even time-stamps used. We use time-stamps for one of our core tables.
The variation we’re using is instead of storing the whole thing as a ‘blob’, we’re splitting it into columns – so that the tree-like structure of this JSON message is represented as a flat set of key-value pairs. Then, each value can be stored under a column-family:column-name.
The example above would translate to the following flat structure -
{
"road:name" => "101N",
"road:speed" => 65,
"houses:" => 4,
"trees:cedar" => "cedar",
"trees:maple" => "maple",
"trees:oak" => "oak",
"cars_model:ah12001" => "fit",
"cars_model:xb34544" => "yaris",
"cars_make:ah12001" => "honda",
"cars_make:xb34544" => "toyota"
}
Now it is ready to be inserted into a single row in HBase. The table we’re inserting into has the following column-families -
"road" "houses" "trees" "cars_model" "cars_make"
This can then be read back and converted into the original object easily enough.
Column-names as data:
Something to note here is that there are now column-family:column-name pairs (that together constitute the ‘column-name’) contain data themselves. An example is ‘cars_model:ah12001′ which is the name of the column, whose value is ‘fit’.
Why do we do this? Because we want the entire object-graph flattened into one row, and this allows us to do that.(what is the primary key?)
The thing to remember here is that in HBase (and others like it), each row can have any number of columns (constrained only by the column-families defined) and rows can populate values for different columns, leaving others blank. Nulls are stored for free. Coupled with the fact that HBase is optimized for millions of columns, this pattern of data-modeling becomes feasible. In fact you could store tons of data in any row in this manner.
Final comments:
If you’re always going to operate on the full object graph, then you don’t really need to split things up this way – you could use one of the options described above (xml, json, or protocol buffers). If different clients of this data typically need only a subset of the object graph (say only the car models or only the speed limits of roads, or some such combination), then with this data-splitting approach, they could only load up the required columns.
This idea of using columns as data take a little getting used to. I’m sure there are better ways of using such powerful data-stores – but this is the approach we’re taking right now, and it seems to be working for us so far.
Clojure HBase helper:
I’ve written some Clojure code that helps this transformation back and forth: hash-tables into/out of HBase. It is open-source – and once I clean it up, I will write about it.
Hope this stuff helps – and if I’ve described something stupid, then please leave a correction. Thanks!
P. S. – I met a Googler today who said BigTable (and by inference HBase) is not a column-oriented database. I think that is incorrect – at least according to wikipedia. I read it on the Internet, I must be right
Posted in database, design, webscale | Leave a Comment »
Clojure: understanding dynamic vars and laziness
Posted by Amit Rathore on February 27, 2009
I spent a frustrating day figuring out why something wasn’t working as expected in a particular situation, even thought it was working just fine elsewhere. It turned out the problem was my flawed understanding of how Clojure’s dynamic vars behaved with respect to laziness. Thanks to Chouser and Chousuke on the #clojure channel in IRC, I think I have a slightly better grasp of the thing.
Update: Here’s a summary for those who don’t want to read the whole thing. What was happening is this – my assumption was that dynamic vars get captured in lazy objects – just like locals get captured in closures. They don’t – so if you later rebind the vars, when the lazy objects are realized, the vars will evaluate according to the latest binding. To baaad results
Here’s the chat transcript if you want to read the whole thing – it might help:
[10:24am] erohtar: chouser: u there?
[10:24am] Chouser: yep
[10:24am] erohtar: chouser: so i was thinking about our conversation yesterday about vars
[10:24am] erohtar: chouser: so vars in clojure arent the same as dynamically scoped variables in common lisp?
[10:25am] Chouser: I don’t know CL well enough to say for sure, but my understanding is that they’re pretty much equivalent.
[10:26am] Chouser: a possible difference being how threads interact with them — not sure what CL does there.
[10:26am] erohtar: chouser: the thing is… in common lisp, if i bing var-a to x, any thing down the call stack will see x…
[10:27am] erohtar: chouser: in clojure, it doesnt seem to behave like a closure… (laziness, during realization) is that correct? if var-a was bound to y elsewhere, realization of the old lazy stuff would now see y
[10:28am] erohtar: chouser: is that right?
[10:28am] Chouser: CL doesn’t do lazy seqs, right? so lets ignore that for now
[10:29am] erohtar: chouser: ok…
[10:29am] Chouser: let’s just look at how a closure works.
[10:30am] erohtar: chouser: i think i understand how a closure works, but when a closure is going to be evaluated lazily… what happens to a var that has since been rebound?
[10:31am] Chouser: (def var-a 2), (let [add (binding [var-a 5] (fn [n] (+ var-a n)))] (add 3))
[10:31am] Chouser: ok, here’s a little example that I would expect to work the same if translated to CL
[10:31am] Chouser: var-a has a root binding of 2.
[10:31am] erohtar: chouser: that should eval to 8, yes?
[10:31am] Chouser: no
[10:32am] erohtar: chouser: hmmm
[10:32am] Chouser: within the dynamic scope of the binding, a closure is created that refers to var-a
[10:32am] erohtar: chouser: ok… and that is 5?
[10:33am] Chousuke: nah, it’s var-a
[10:33am] erohtar: oh
[10:33am] Chouser: at the moment the closure is created, var-a has a thread-local binding of 5, but that doesn’t really matter because nothing is asking for var-a’s *value*, just grabbing var-a itself.
[10:33am] erohtar: i see… ok…
[10:34am] Chouser: so that closure is returned to outside the binding, and named ‘add’
[10:34am] Chousuke: I guess it’s a bit surprising though.
[10:34am] Chouser: and what does the closure have bundled inside? it knows it wants one arg n, and it has references to the vars var-a and +
[10:35am] erohtar: and it dynamically uses the value 2, for var-a when it needs it?
[10:35am] Chouser: right
[10:35am] erohtar: arent closures supposed to capture their environment?
[10:35am] Chouser: their lexical environment, yes.
[10:35am] erohtar: not the values?
[10:36am] Chouser: which is why this works: (def var-a 2), (let [m 7, add (binding [var-a 5] (fn [] (+ var-a m)))] (add))
[10:37am] Chouser: hm, not that’s not quite right, since m is still available when ‘add’ is called. But anyway, it wouldn’t have to be.
[10:38am] erohtar: thinking about this
[10:38am] Chouser: if you think about how dynamic vars are used in clojure.core, you’ll see it must be this way.
[10:38am] Chouser: let’s look at *in*
[10:38am] Chouser: er, *out*
[10:38am] Chousuke: ,(let [x 1 add (fn [] (+ 4 x))] [(binding [x 2] (add)) (binding [+ -] (add))])
[10:38am] clojurebot: java.lang.Exception: Unable to resolve var: x in this context
[10:38am] Chousuke: hmm
[10:39am] erohtar: ok – talking about *out* – is that the std-out ?
[10:39am] Chouser: somewhere there’s something like (def *out* System/out)
[10:39am] Chouser: right
[10:39am] Chousuke: ,(let [x 1] (let [add (fn [] (+ 4 x))] [(binding [x 2] (add)) (binding [+ -] (add))]))
[10:39am] erohtar: right
[10:39am] clojurebot: java.lang.Exception: Unable to resolve var: x in this context
[10:39am] Chouser: that’s the root binding of *out*
[10:39am] erohtar: ok, with u so far
[10:39am] Chousuke: hmm, I guess binding let-bound variables does not work
[10:40am] Chouser: then you’ve got functions like prn that use *out*
[10:40am] erohtar: yes… i think they need to be vars
[10:40am] erohtar: right
[10:40am] kotarak: let-bound locals are not Vars
[10:40am] Chousuke: hmm
[10:40am] Chousuke: ,(let [x 1] #’x)
[10:40am] clojurebot: java.lang.Exception: Unable to resolve var: x in this context
[10:41am] Chouser: we can pretend prn is defined something like (defn prn [& args] (.write *out* args))
[10:41am] erohtar: when u create a lazy something, that uses prn, what happens?
[10:41am] Chousuke: indeed.
[10:41am] Chouser: now, if prn took the value of the *out* when it was defined, there would be no way to get prn to write to any other stream — it would always use the root binding, since that’s what was in play when prn was defined.
[10:42am] Chouser: but that’s not how it works.
[10:42am] Chouser: prn has a reference to the Var *out*, not its value.
[10:42am] erohtar: so something like – (map #(prn %)
[1 2 3])
[10:42am] erohtar: chouser: i completely agree
[10:42am] Chouser: so instead, prn will use the dynamic value of *out* when you call it.
[10:42am] erohtar: chouser: hmmm
[10:42am] Chouser: ,(with-out-str (prn 5 10))
[10:42am] clojurebot: “5 10\n”
[10:43am] Chouser: got it?
[10:43am] erohtar: i do
[10:43am] erohtar: im thinking about my confusion – and trying to figure out the question to ask next
[10:44am] erohtar: so lets take my example -
[10:44am] erohtar: (map #(prn %)
[1 2 3])
[10:45am] erohtar: now, somewhere else, i rebind *out* to str… and in there, if i use the above object, will it also use the new binding?
[10:45am] erohtar: it will…
[10:45am] erohtar: i think im getting it now
[10:46am] erohtar: ok – final thought -
[10:46am] Chouser: (def q (map #(prn %)
[1 2 3])), (with-out-str (doall q))
[10:47am] Chouser: so yes, even though you created the lazy seq and closure outside the with-out-str, since its not computed or realized until the doall which is within the with-out-str, all those prn’s will use the binding provided by with-out-str
[10:47am] erohtar: got it…
[10:48am] erohtar: so my final thought – what if instead of *out* we’re talking about a connection to a database… bad use of vars, right?
[10:48am] Chouser: now lazy seqs can be a bit tricky because they cache their results and can effectively contain multiple closures.
[10:49am] Chouser: hmm….
[10:49am] erohtar: if i read from a db a list of objects using a var that holds database config…. and then i rebind the config to write into another database
[10:49am] Chouser: if you’re going to open a connection to a database, do a batch of work in a single thread on it, and then close the connection — then that would be a fine use.
[10:50am] erohtar: since the initial read may be lazy… when it realizes… it will ‘read from the wrong place’”?
[10:50am] Chouser: right
[10:50am] Chouser: basically you want to be very careful about passing closures (and therefore lazy seqs) past ‘binding’ boundaries.
[10:50am] erohtar: chouser: on that thought – what i did was, i read from a db, and to write into the other, i created agents, binding the new db config in each
[10:51am] erohtar: chouser: it didnt work…
[10:51am] erohtar: chouser: ok… im beginning to understand …
[10:51am] erohtar: i need to rethink what im doing
[10:52am] erohtar: and avoid using vars for some of this stuff, since im doing a lot of agent related stuff
[10:52am] Chouser: yes, I’d recommend trying to have the behavior of as much of your code as possible depend only on the args passed directly in.
[10:53am] erohtar: chouser: this whole mess started when i wanted to avoid passing db-config around everywhere
[10:53am] Chouser: this is better for testing, reasoning about behavior, easier to work with threads, closures, laziness, etc.
[10:53am] Chouser: heh, yeah.
[10:53am] erohtar: yup – i hear you
[10:53am] Chouser: well, another thing that may be helpful — just guessing since I haven’t seen your code…
[10:53am] erohtar: thanks a ton for your time – ur incredibly helpful
[10:54am] erohtar: ok?
[10:54am] Chouser: would be to try to keep as much of your code purely functional as possible.
[10:54am] erohtar: yes – i understand
[10:54am] Chouser: so avoid writing a function that takes some args, does some computation, and then writes to a db. Instead, have a fn that takes args, does computation, returns result.
[10:55am] Chouser: then perhaps you don’t have to pass in db config at all — whoever calls this fn can to the db write itself.
[10:55am] erohtar: i think it mostly is… except for this stuff… where i ended up inadvertently depending on “global” db-config
[10:55am] erohtar: well, this is a persistence layer
[10:56am] erohtar: i take an object in, break it up etc., and put it into hbase
[10:56am] erohtar: the code is open-sourece… would u like to see?
[10:56am] Chouser: hm, sure. I may need to ramp up on hbase soon.
[10:56am] erohtar: http://github.com/amitrathore/capjure/blob/b939a7038ebb4aed0d068d6e86291cc881ecf72b/src/org/rathore/amit/capjure.clj
[10:57am] erohtar: its kind a messy – learning clojure and hbase while doing this…
[10:57am] Chouser:
[10:57am] Chousuke: erohtar: first thought: use some newlines.
[10:58am] danlarkin: Noooooooooooo -jure
[10:58am] erohtar: danlarkin: haha – u’ve told me that already
[10:58am] Chouser: danlarkin: hey, at least he’s got a name
[10:58am] Chousuke: erohtar: one newline after each def/defn would make it a lot nicer
[10:58am] danlarkin: erohtar, Chouser:
[10:58am] erohtar: ok – more newlines, check
[10:59am] Chousuke: well, the def group is fine I guess.
[10:59am] Chousuke: but (defn foo) (defn bar) without an empty line in the middle is a bit weird
[11:00am] erohtar: ok – those were sort of just quick utility functions… but i’ll put newlines
[11:00am] Chousuke: newlines never hurt anyone
[11:00am] Chouser: erohtar: this is what you get for posting code. unsolicited advice.
[11:01am] erohtar: haha
[11:01am] erohtar: its fine – maybe i’ll learn something too
[11:01am] Chouser: but while we’re at it — I much prefer to have the code arranged so that ‘declare’ is only needed in mutually-recusive situations.
[11:01am] Chouser: though others may disagree with me
[11:02am] erohtar: right – i struggled with that one – cause i dont like to have to order the functions in “reverse”
[11:02am] • Chouser nods
[11:02am] erohtar: see – capjure-insert is the only one that most people will call
[11:03am] Chousuke: erohtar: you could add more newlines and some kind of “headlines” for sections of code
[11:03am] erohtar: u bind the config stuff – *hbase-master* and *primary-keys-config* – and then u call capjure-insert with the params
[11:03am] Chousuke: so people can easily skip the helper function blocks
[11:03am] erohtar: most of the remaining functions are functional
[11:03am] erohtar: only the ones dealing with hbase have (obvious) side-effects
[11:04am] erohtar: and it works fine… and its in production too… ran into issues trying to use TWO hbase configs (to move data between them)
[11:04am] Chousuke: that’s a lot of functions for one namespace too, though
[11:05am] Chouser: I really don’t think more namespaces would be better.
[11:05am] Chousuke: if possible maybe it’d make sense to put the “side-effecting” functions (that deal with hbase) in a separate file or namespace?
[11:05am] erohtar: cause lazy lists of data from one hbase, seem to be getting messed up when i rebind the config to start writing into the other hbase
[11:06am] erohtar: do u know what i mean? (trying to get discussion back to lazy closures and bindings )
[11:06am] Chousuke: ah
[11:06am] Chousuke: right, I can see why that happens
[11:06am] Chousuke: the laziness gets evaluated in the context of the new hbase.
[11:06am] erohtar: well, im only starting to see it thanks to u guys…
[11:06am] erohtar: yea
[11:06am] erohtar: drove me crazy
[11:06am] erohtar: and i did all this only so i wouldnt need to pass the db config around all the functions
[11:06am] erohtar: like u said, there are a lot of them…
[11:07am] Chousuke: which means you will have to move away from using global vars for config and instead create something you explicitly pass around to the functions.
[11:07am] erohtar: so now what… ? pass the config around everywhere?
[11:08am] Chousuke: maybe only to a few core functions.
[11:08am] erohtar: yea
[11:08am] Chousuke: which then would bind the dynamic vars.
[11:09am] erohtar: well, if i pass it in, i dont need dynamic vars, rite
[11:09am] Chouser: or don’t use lazy seqs
[11:09am] Chouser: use doall or stuff them in a vector first
[11:09am] erohtar: hmmm
[11:09am] cp2 is now known as c|p.
[11:09am] erohtar: that might be one solution
[11:09am] Chousuke: right, if they are side-effecting that might be better.
[11:09am] Chousuke: though maybe not memory-efficient
[11:10am] erohtar: yea
[11:10am] erohtar: i think i will get rid of the dynamic vars
[11:10am] Chousuke: it’s a shame though
[11:10am] erohtar: what is the pattern for this kind of ’static’ config being passed around?
[11:10am] Chousuke: they make the code much easier to write
[11:10am] Chousuke: I wonder if there’s a better solution
[11:11am] Chousuke: some way to “bind” the current config to when the lazy-seq is first created
[11:11am] erohtar: in typical OO, u can create an instance variable to hold the config – i wonder if in clojure u can create something like that… and since its immutable, it should be fine, rite?
[11:11am] Chouser: yes
[11:11am] Chousuke: maybe do (let [config *global*] (return-some-lazy-seq-qith config))?
[11:11am] erohtar: but there is no way to do that, rite?
[11:11am] Chousuke: would that fix the value?
[11:12am] erohtar: yea
[11:12am] Chouser: stuff all your config into a map, and pass that single thing into functions that need to use it
[11:12am] erohtar: i thought of doing something like that… but other functions couldnt access those values…
[11:12am] erohtar: i thought of simulating an ‘immutable object oriented system’ -
[11:12am] brianh joined the chat room.
[11:12am] erohtar: like how u do in javascript… but immutable
[11:13am] Chousuke: I did in clojurebot so that I pass a map of config stuff around with every function
[11:13am] erohtar: return a closure with the vars bound with a let… and then closures for all the other functions also
[11:13am] Chousuke: it’s a bit tedious though
[11:13am] erohtar: i dunno if im being clear
[11:13am] erohtar: very tedious
[11:14am] erohtar: macros can help
[11:14am] erohtar: essentially what id be doing is creating an immutable OO system
[11:14am] erohtar: something like that
[11:14am] erohtar: does that make sense?
[11:14am] Chousuke: erohtar: but your problem is only with lazy seqs right?
[11:14am] erohtar: lazy seqs and dynamic vars
[11:14am] Chousuke: erohtar: don’t you only need to fixate the config when returning a seq
[11:14am] erohtar: the interplay
[11:14am] erohtar: yes
[11:15am] Chouser: erohtar: clojure.zip does something like that
[11:15am] erohtar: chouser: like what?
[11:15am] Chouser: each node is a object with a several functions attached as metadata
[11:16am] erohtar: chouser: ah, i see
[11:16am] erohtar: got it
[11:16am] Chouser: most of the api fns are like (children my-node), where children calls fns from my-node’s metadata, passing in my-node
[11:16am] erohtar: i see -
[11:17am] erohtar: thats rather cool – so u can basically have my-node equivalent contain the config data
[11:17am] Chouser: sure
[11:18am] erohtar: alright folks, thanks a lot for this conversation – im going to experiment and see how to get this done with the least amount of work
[11:18am] Chouser: the only reason zip nodes have fns in metadata is so it can be polymorphic.
[11:18am] erohtar: yes- makes sense
[11:18am] erohtar: (then everyone can tell me how my code sucks )
[11:18am] Chouser: if you’re going to only have one kind of db config (seems likely) then you don’t need the metadata piece.
[11:19am] erohtar: yes – just need to take care of the fact that the config will be rebound… so just closures that capture the config, and the functions that use it
[11:19am] erohtar: something like that
P.S. erohtar is my handle on IRC… it’s the reverse of my last name. In case you were wondering.
Posted in clojure, lambda, languages, learning | Leave a Comment »
The first meetup of the Bay Area Clojure User Group
Posted by Amit Rathore on February 8, 2009
We held the first meeting of the BACUG (ugh, that’s a tedious acronym) last week, on Thursday the 5th of February. I was expecting about 6-8 people to show up, but we had about 12 people, quite a nice turn out!
After introductions and such, Chris Turner presented his unit-testing library for clojure called Clojure Spec. We talked about testing in general, and because he uses a lot of macro-writing macros in his code, we talked about macros in general and the difficulty in debugging macros. It was a good discussion – though I did throw in (tongue-in-cheek) that we’re using Test Is at Cinch. Thanks Chris, it was a good presentation.
After that talk, I gave an introduction to how we’re presently using Clojure in our startup. Since we’re using HBase as our persistent data-store, and processing that data using a bunch of clojure processes, we talked about data-modeling for HBase-like systems (I will write about my implementation of that data-model in another post).
An interesting thread came up – led by Joe Mikhail who works at Google and obviously does a lot of Map/Reduce/BigTable stuff – around how at least in the beginning, multi-threaded clojure processes can be used in place of Hadoop when processing HBase data. And he did mention that using systems like Terracotta, one can scale up such solutions. We’re going to look into that next week.
The remainder of the meeting went by in a buzz of talking about different languages, technologies, and general geek topics. The one thing of interest here was the point that software transactional memory is no panacea (surprise!) to the whole concurrency thing. Here’s an ACM article (there are several actually, just keep turning the pages) that throws some light on the issue. Here’s another.
Overall, it was a very good meeting – we’re hoping that the next one would be attended by more people, and especially some folks that have used other Lisps in the past – we’re all curious about what such folks think about Clojure. Indeed, and we want to learn from their experience in using idiomatic Lisp.
I’m thinking that we’ll do another Clojure meetup in about 6 weeks or so… join up, and stay tuned!
P.S. – A shout of thanks to my employer Runa. for hosting this meeting.
Posted in clojure, languages, learning, lisp, meetings | Leave a Comment »
Startup logbook – v0.1 – Clojure in production
Posted by Amit Rathore on January 28, 2009
Late last night, around 3 AM to be exact, we made one of our usual releases to production (unfortunately, we’re still in semi-stealth mode, so I’m not talking a lot about our product yet – I will in a few weeks). There was nothing particularly remarkable about the release from a business point of view. It had a couple of enhancements to functionality, and a couple of bug-fixes.
What was rather interesting, at least to the geek in me, was that it was something of a technology milestone for us. It was the first production release of a new architecture that I’d been working on over the past 2-3 weeks. Our service contains several pieces, and until this release we had a rather traditional architecture – we were using ruby on rails for all our back-end logic (eg. real-time analytics and pricing calculations) as well as the user-facing website. And we were using mysql for our storage requirements.
This release has seen our production system undergo some changes. Going forward, the rails portion will continue to do what it was originally designed for – supporting a user-facing web-UI. The run-time service is now a combination of rails and a cluster of clojure processes.
When data needs to be collected (for further analytics down the line), the rails application simply drops JSON messages on a queue (we’re using the excellent erlang-based RabbitMQ), and one of a cluster of clojure processes picks it up, processes it, and stores it in an HBase store. Since each message can result in several actions that need to be performed (and these are mostly independent), clojure’s safe concurrency helps a lot. And since its a lisp, the code is just so much shorter than equivalent ruby could ever be.
Currently, all business rules, analytics, and pricing calculations are still being handled by the ruby/rails code. Over the next few releases we’re looking to move away from this – to instead let the clojure processes do most of the heavy lifting.
We’re hoping we can continue to do this in a highly incremental fashion, as the risk of trying to get this perfect the first time is too high. We absolutely need to get the feedback that only production can give us – so we’re more sure that we’re building the thing right.
The last few days have been the most fun I’ve had in any job so far. Besides learning clojure, and hadoop/ hbase pretty much at the same time (and getting paid for doing that!), it has also been a great opportunity to do this as incrementally as possible. I strongly believe in set-based engineering methods, and this is the approach I took with this as well – currently, we haven’t turned off the ruby/rails/mysql system – it is doing essentially the same thing that the new clojure/hbase system is doing. We’re looking to build the rest of the system out (incrementally), ensure it works (and repeat until it does) – before turning off the (nearly legacy) ruby system.
I’ll keep posting as I progress on this front. Overall, we’re very excited at the possibilities that using clojure represents – and hey, if it turns out to be a mistake – we’ll throw it out instead.
Posted in architecture, clojure, design, lisp, multi-paradigm, ruby, startup | 1 Comment »
Announcing the Bay Area Clojure User Group
Posted by Amit Rathore on January 19, 2009
Rob Berger and I’ve just started the Bay Area Clojure User Group. If you’re interested in Lisp/Scheme, concurrent programming, or functional languages, then please stop by! We’re having the first meetup on 5th of Feb in the Runa office down in Mountain View.
More details here – meetup.com/The-Bay-Area-Clojure-User-Group
Posted in clojure, code, languages, learning | Leave a Comment »
Design for throwability
Posted by Amit Rathore on January 16, 2009
Build one to throw away, you will anyhow. — Fred Brooks
Fred Brooks said what he did many, many years ago but it is probably just as true today. How many times have you and your team gotten a few months into a project only to realize all the design mistakes you made? Ask any engineer, and they’ll tell you they would build it right the second time.
This is just reality, the nature of discovering the complexity of the domain or the technology or the usage pattern or whatever else you didn’t know about when you started.
On the other hand, there’s this [what Joel Spolsky says about rewriting software] -
It is the single worst strategic mistake that any software company can make — Joel Spolsky
So… what gives? The answer, IMHO, is basically two things -
1. Understand and internalize the idea of the strangler application
2. Architect your system in such a way to support strangling it later
In essence, this means that because it would be a bad idea to rewrite the entire system from scratch, it must be built in a way so as to enable swapping out components of it as they are rewritten (or perhaps heavily refactored).
The architecture must draw from an approach called concurrent set-based engineering (CSBE) – and indeed, sometimes each logical component would have more than one implementation. At Runa, two components of our system actually have two implementations each. And in each case, they’re both running in production – in parallel.
The way we accomplish this is through very loose-coupling. Additionally, because we take a very release-driven approach to our software process, our architecture evolves according to our current needs… and we refactor and extend things as new requirements are prioritized. At all times, despite our super-short release-cycles, our goal is to always have a version of the system in production. Whenever our pipeline tells us that a peice of the existing design may not work in the long term, we start to work on the replacements – more than one, and in parallel.
We run them in what I’ve been calling shadow-mode. This implies that its not quite part of the official system, but is running in order to prove some design hypothesis. Once everyone involved is satisfied with the results, we pick the most suitable sub-system and decommission the other contenders (including the old one). At Runa, we achieve much of our inter-component loose-coupling via messaging (our current choice is RabbitMQ).
To summarize – we design everything with one over-arching goal in mind – the thing will be thrown away someday, and be replaced with another. As I said before, this enforces a few things -
1. Loose coupling
2. Clear interfaces between components
3. Good automated system testing!
About that last point – because we have many moving parts, functional testing becomes even more important. We currently use Selenium for true functional testing (Runa is a web-based service) – and a variety of other home-grown tools for custom systems testing. Not only do automated system tests tell us that the collaborating set of components are working right, but they also allow us to change things with impunity – knowing that we’ll know if things break.
This thinking is what I’ve been jokingly calling Design For Throwability – and it’s been working rather nicely. It’s essentially a design philosophy that embraces CSBE – and is especially useful for small startups where everything is changing quickly – almost by definition.
Posted in architecture, design, process, startup | Leave a Comment »
