Clojure Day Three

The final day of Clojure introduces the language’s concurrency structures. Clojure uses software transactional memory; a mechanism not so far removed from modern database transactions. I’m not sure whether this is better or worse than the actors found in Erlang or Io. As I understand it, actors are theoritically better but programming is often about making practical compromises. I’ll have to work with concurrency more to develop a taste for different approaches.

The first problem — balancing an account — was relatively straightforward and helped me to understand the concept of transactions. The Sleeping Barber problem however was seriously challenging. I’m not embarrassed to say it took me several hours of staring at the screen to come up with a solution, and I had to go away and think about the problem a few times and even considered giving up. I’m glad I didn’t.

  1. Balancing an account
  2. The Sleeping Barber
  3. Thoughts

Balancing an account

Use references to create a vector of accounts in memory. Create debit and credit functions to change the balance of an account.

In this example I create two references to amounts you might find in your personal and business bank accounts. I add those references to the vector accounts. The credit and debit functions are essentially the same; they both take a reference to an account, and the amount that it should be altered by.

The interesting thing here is the form of the alter method. This function needs to be used like (alter reference function optional-arguments) or else Clojure throws some slightly cryptic errors at you. We’re saying “Ok, alter method, take my account reference and apply the + function to it with amount as an argument.”

Since accounts are always a reference, any function that mutates the referenced data must be wrapped in a transaction like dosync. This transaction basically negates the possibility of data being corrupted by some ugly race condition.

The Sleeping Barber

Write a multithreaded program to determine how many haircuts a barber can give in ten seconds.

This is a problem devised in 1965 by Edsger Djikstra. It has the following characteristics:

  • A barber shop takes customers.
  • Customers arrive at random intervals, from ten to thirty milliseconds.
  • The barber shop has three chairs in the waiting room.
  • The barber shop has one barber and one barber chair.
  • When the barber’s chair is empty, a customer sits in the chair, wakes up the barber, and gets a haircut.
  • If the chairs are occupied, all new customers will turn away.
  • Haircuts take twenty milliseconds.
  • After a customer receives a haircut, he gets up and leaves.

In this problem we need to use threads to spin up some concurrent processes. We do this with the monitor-waiting-room and send-customers-from-street functions by wrapping the function bodies in futures. Without the futures, the program would hit the first while loop and block, looping infinitely.

An interesting thing about collections in Clojure is that lists push and pop from the front, whereas vectors push and pop from behind. In order to model the concept of a waiting room where the first customer who comes to the store is also the first customer served, we need to use a PersistentList. If you experiment with a PersistentList in a Clojure REPL and you don’t get the syntax 100% correct, Clojure starts messing with your brain.

Most of the code is heavily commented, so I’ll let my work speak for itself.

(ns barber.core

(def chair (ref []))
(def lost-customers (ref []))
(def shop-is-open (ref false))
(def serviced-customers (ref []))
(def waiting-customers (ref clojure.lang.PersistentQueue/EMPTY))

; If there are less than three customers waiting for a haircut, we
; can welcome them in and sit them down. If there are already three
; customers waiting, the barber has lost some business.
(defn greet-customer [customer]
    (if (< (count @waiting-customers) 3)
      (alter waiting-customers conj customer)
      (alter lost-customers conj customer))))

; Take a customer and cut his hair for 20 milliseconds. Once we’re
; done, we add him to our list of satisfied customers.
(defn cut-hair [customer]
  (Thread/sleep 20)
  (dosync (alter serviced-customers conj customer)))

; While the shop is open, continuously check the waiting room for
; waiting customers. If we find one, remove him from the waiting
; room and send him to have his hair cut.
(defn monitor-waiting-room []
    (while @shop-is-open
      (if (not (empty? @waiting-customers))
          (cut-hair (first @waiting-customers))
          (dosync (alter waiting-customers pop)))))))

; Send potential customers into the barber’s shop from the street
; at random intervals between 10ms and 30ms. The rand-int function
; is non-inclusive, so we have to specify an amount one higher than
; the maximum of our desired range.
(defn send-customers-from-street []
    (while @shop-is-open
        (Thread/sleep (+ 10 (rand-int 21)))
        (greet-customer :customer)))))

; Open the barber’s shop for 10 seconds, begin sending people into
; the store from the street, and ask the barber to keep an eye on
; the waiting room.
(defn open-for-business []
  (dosync (ref-set shop-is-open true))
  (Thread/sleep (* 10 1000))
  (dosync (ref-set shop-is-open false)))

(println "serviced customers: " (count @serviced-customers))
(println "lost customers: " (count @lost-customers))

I hope my implementation is correct (it does work, and the output is within the expected range), but I suspect I haven’t followed the specification closely enough. In Dijkstra’s scenario, the barber is supposed to be asleep whenever he’s not cutting hair. In my implementation, the barber is constantly monitoring the waiting room. Let’s just pretend the door to the barber’s shop has a very loud doorbell.


Clojure feels flexible, powerful, and serious. As much as programmers love arguing about programming languages, I don’t remember ever seeing someone saying bad things about Clojure; it seems to be universally celebrated. Since immutability is a core idea, I think Clojure would be a good candidate for a language to base a career on if/when OOP is rendered inadequate, though it looks as though there’s a whole mountain of knowledge to climb. Maybe I’ll ask Rich Hickey if I can borrow his hammock.