I'm writing a lazy implementation of the Recamán's Sequence, and ran into some confusion regarding where calls to lazy-seq should happen.
This first version I came up with this morning was:
(defn lazy-recamans-sequence []
(let [f (fn rec [n seen last-s]
(let [back (- last-s n)
new-s (if (and (pos? back) (not (seen back)))
back
(+ last-s n))]
(lazy-seq ; Here
(cons new-s (rec (inc n) (conj seen new-s) new-s)))))]
(f 0 #{} 0)))
Then I realized that my placement of lazy-seq was kind of arbitrary, and that it could be placed higher to wrap more of the computations:
(defn lazy-recamans-sequence2 []
(let [f (fn rec [n seen last-s]
(lazy-seq ; Here
(let [back (- last-s n)
new-s (if (and (pos? back) (not (seen back)))
back
(+ last-s n))]
(cons new-s (rec (inc n) (conj seen new-s) new-s)))))]
(f 0 #{} 0)))
Then I looked back on a review that someone gave me last night:
(defn recaman []
(letfn [(tail [previous n seen]
(let [nx (if (and (> previous n) (not (seen (- previous n))))
(- previous n)
(+ previous n))]
; Here, inside "cons"
(cons nx (lazy-seq (tail nx (inc n) (conj seen nx))))))]
(tail 0 0 #{})))
And they have theirs inside of the call to cons!
Thinking this over, it seems like it wouldn't make a difference. With a broader scope (like the second version), more code is inside the explicit function that's passed to LazySeq. With a narrower scope however, the function itself may be smaller, but since the passed function involves a recursive call, it will be executing the same code anyways.
They seem to preform nearly identically and give the same answers. Is there any reason to prefer placing lazy-seq in one place over another? Is this simply a stylistic choice, or can this have actual repercussions?
In the first two examples the lazy-seq wraps the cons call. This means that when you generate call the function you return a lazy sequence immediately without calculating the first item of the sequence.
In the first example the let expression is still outside of lazy-seq so the value of the first item is calculated immediately but the returned sequence is still lazy and not realized.
The second example is similar to the first. The lazy-seq wraps the cons cell and also the let block. This means that the function will return immediatetly and the value of the first item is calculated only when the caller starts to consume the lazy sequence.
In the third example the value of the first item in the list is calculated immediately and only the tail of the returned sequence is lazy.
Is there any reason to prefer placing lazy-seq in one place over another?
It depends on what you want to achieve. Do you want to return a sequence immediately without calculating any values? In this case make the scope of lazy-seq as broad as possible. Otherwise try to restrict the scope of lazy-seq to calculate only the tail part of the sequence.
When I was first learning Clojure, I was a bit confused by the many possible choices of lazy-seq constructs, the lack of clarity in terms of which construct to choose, and the somewhat vague explanation for how lazy-seq creates laziness in the first place (it is implemented as a Java class of ~240 lines).
To reduce repetition and keep things as simple as possible, I created the lazy-cons macro. It is used like so:
(defn lazy-countdown [n]
(when (<= 0 n)
(lazy-cons n (lazy-countdown (dec n)))))
(deftest t-all
(is= (lazy-countdown 5) [5 4 3 2 1 0] )
(is= (lazy-countdown 1) [1 0] )
(is= (lazy-countdown 0) [0] )
(is= (lazy-countdown -1) nil ))
This version does realize the initial value n immediately.
I never worry about chunking (typically batches of 32) or trying to precisely control the number of elements realized in a lazy sequence. IMHO, if you need fine-grained control such as this, it is better to use an explicit loop than to make assumptions on the timing of realizations in a lazy sequence.
Related
I have a source of items and want to separately process runs of them having the same value of a key function. In Python this would look like
for key_val, part in itertools.groupby(src, key_fn):
process(key_val, part)
This solution is completely lazy, i.e. if process doesn't try to store contents of entire part, the code would run in O(1) memory.
Clojure solution
(doseq [part (partition-by key-fn src)]
(process part))
is less lazy: it realizes each part completely. The problem is, src might have very long runs of items with the same key-fn value and realizing them might lead to OOM.
I've found this discussion where it's claimed that the following function (slightly modified for naming consistency inside post) is lazy enough
(defn lazy-partition-by [key-fn coll]
(lazy-seq
(when-let [s (seq coll)]
(let [fst (first s)
fv (key-fn fst)
part (lazy-seq (cons fst (take-while #(= fv (key-fn %)) (next s))))]
(cons part (lazy-partition-by key-fn (drop-while #(= fv (key-fn %)) s)))))))
However, I don't understand why it doesn't suffer from OOM: both parts of the cons cell hold a reference to s, so while process consumes part, s is being realized but not garbage collected. It would become eligible for GC only when drop-while traverses part.
So, my questions are:
Am I correct about lazy-partition-by not being lazy enough?
Is there an implementation of partition-by with guaranteed memory requirements, provided I don't hold any references to the previous part by the time I start realizing the next one?
EDIT:
Here's a lazy enough implementation in Haskell:
lazyPartitionBy :: Eq b => (a -> b) -> [a] -> [[a]]
lazyPartitionBy _ [] = []
lazyPartitionBy keyFn xl#(x:_) = let
fv = keyFn x
(part, rest) = span ((== fv) . keyFn) xl
in part : lazyPartitionBy keyFn rest
As can be seen from span implementation, part and rest implicitly share state. I wonder if this method could be translated into Clojure.
The rule of thumb that I use in these scenarios (ie, those in which you want a single input sequence to produce multiple output sequences) is that, of the following three desirable properties, you can generally have only two:
Efficiency (traverse the input sequence only once, thus not hold its head)
Laziness (produce elements only on demand)
No shared mutable state
The version in clojure.core chooses (1,3), but gives up on (2) by producing an entire partition all at once. Python and Haskell both choose (1,2), although it's not immediately obvious: doesn't Haskell have no mutable state at all? Well, its lazy evaluation of everything (not just sequences) means that all expressions are thunks, which start out as blank slates and only get written to when their value is needed; the implementation of span, as you say, shares the same thunk of span p xs' in both of its output sequences, so that whichever one needs it first "sends" it to the result of the other sequence, effecting the action at a distance that's necessary to preserve the other nice properties.
The alternative Clojure implementation you linked to chooses (2,3), as you noted.
The problem is that for partition-by, declining either (1) or (2) means that you're holding the head of some sequence: either the input or one of the outputs. So if you want a solution where it's possible to handle arbitrarily large partitions of an arbitrarily large input, you need to choose (1,2). There are a few ways you could do this in Clojure:
Take the Python approach: return something more like an iterator than a seq - seqs make stronger guarantees about non-mutation, and promise that you can safely traverse them multiple times, etc etc. If instead of a seq of seqs you return an iterator of iterators, then consuming items from any one iterator can freely mutate or invalidate the other(s). This guarantees consumption happens in order and that memory can be freed up.
Take the Haskell approach: manually thunk everything, with lots of calls to delay, and require the client to call force as often as necessary to get data out. This will be a lot uglier in Clojure, and will greatly increase your stack depth (using this on a non-trivial input will probably blow the stack), but it is theoretically possible.
Write something more Clojure-flavored (but still quite unusual) by having a few mutable data objects that are coordinated between the output seqs, each updated as needed when something is requested from any of them.
I'm pretty sure any of these three approaches are possible, but to be honest they're all pretty hard and not at all natural. Clojure's sequence abstraction just doesn't make it easy to produce a data structure that's what you'd like. My advice is that if you need something like this and the partitions may be too large to fit comfortably, you just accept a slightly different format and do a little more bookkeeping yourself: dodge the (1,2,3) dilemma by not producing multiple output sequences at all!
So instead of ((2 4 6 8) (1 3 5) (10 12) (7)) being your output format for something like (partition-by even? [2 4 6 8 1 3 5 10 12 7]), you could accept a slightly uglier format: ([::key true] 2 4 6 8 [::key false] 1 3 5 [::key true] 10 12 [::key false] 7). This is neither hard to produce nor hard to consume, although it is a bit lengthy and tedious to write out.
Here is one reasonable implementation of the producing function:
(defn lazy-partition-by [f coll]
(lazy-seq
(when (seq coll)
(let [x (first coll)
k (f x)]
(list* [::key k] x
((fn part [k xs]
(lazy-seq
(when (seq xs)
(let [x (first xs)
k' (f x)]
(if (= k k')
(cons x (part k (rest xs)))
(list* [::key k'] x (part k' (rest xs))))))))
k (rest coll)))))))
And here's how to consume it, first defining a generic reduce-grouped that hides the details of the grouping format, and then an example function count-partition-sizes to output the key and size of each partition without keeping any sequences in memory:
(defn reduce-grouped [f init groups]
(loop [k nil, acc init, coll groups]
(if (empty? coll)
acc
(if (and (coll? (first coll)) (= ::key (ffirst coll)))
(recur (second (first coll)) acc (rest coll))
(recur k (f k acc (first coll)) (rest coll))))))
(defn count-partition-sizes [f coll]
(reduce-grouped (fn [k acc _]
(if (and (seq acc) (= k (first (peek acc))))
(conj (pop acc) (update-in (peek acc) [1] inc))
(conj acc [k 1])))
[] (lazy-partition-by f coll)))
user> (lazy-partition-by even? [2 4 6 8 1 3 5 10 12 7])
([:user/key true] 2 4 6 8 [:user/key false] 1 3 5 [:user/key true] 10 12 [:user/key false] 7)
user> (count-partition-sizes even? [2 4 6 8 1 3 5 10 12 7])
[[true 4] [false 3] [true 2] [false 1]]
Edit: Looking at it again, I'm not really convinced my reduce-grouped is much more useful than (reduce f init (map g xs)), since it doesn't really give you any clear indication of when the key changes. So if you do need to know when a group changes, you'll want a smarter abstraction, or to use my original lazy-partition-by with nothing "clever" wrapping it.
Although this question evokes very interesting contemplation about language design, the practical problem is you want to process on partitions in constant memory. And the practical problem is resolvable with a little inversion.
Rather than processing over the result of a function that returns a sequence of partitions, pass the processing function into the function that produces the partitions. Then, you can control state in a contained manner.
First we'll provide a way to fuse together the consumption of the sequence with the state of the tail.
(defn fuse [coll wick]
(lazy-seq
(when-let [s (seq coll)]
(swap! wick rest)
(cons (first s) (fuse (rest s) wick)))))
Then a modified version of partition-by
(defn process-partition-by [processfn keyfn coll]
(lazy-seq
(when (seq coll)
(let [tail (atom (cons nil coll))
s (fuse coll tail)
fst (first s)
fv (keyfn fst)
pred #(= fv (keyfn %))
part (take-while pred s)
more (lazy-seq (drop-while pred #tail))]
(cons (processfn part)
(process-partition-by processfn keyfn more))))))
Note: For O(1) memory consumption processfn must be an eager consumer! So while (process-partition-by identity key-fn coll) is the same as (partition-by key-fn coll), because identity does not consume the partition, the memory consumption is not constant.
Tests
(defn heavy-seq []
;adjust payload for your JVM so only a few fit in memory
(let [payload (fn [] (long-array 20000000))]
(map #(vector % (payload)) (iterate inc 0))))
(defn my-process [s] (reduce + (map first s)))
(defn test1 []
(doseq [part (partition-by #(quot (first %) 10) (take 50 (heavy-seq)))]
(my-process part)))
(defn test2 []
(process-partition-by
my-process #(quot (first %) 20) (take 200 (heavy-seq))))
so.core=> (test1)
OutOfMemoryError Java heap space [trace missing]
so.core=> (test2)
(190 590 990 1390 1790 2190 2590 2990 3390 3790)
Am I correct about lazy-partition-by not being lazy enough?
Well, there's a difference between laziness and memory usage. A sequence can be lazy and still require lots of memory - see for instance the implementation of clojure.core/distinct, which uses a set to remember all the previously observed values in the sequence. But yes, your analysis of the memory requirements of lazy-partition-by is correct - the function call to compute the head of the second partition will retain the head of the first partition, which means that realizing the first partition causes it to be retained in-memory. This can be verified with the following code:
user> (doseq [part (lazy-partition-by :a
(repeatedly
(fn [] {:a 1 :b (long-array 10000000)})))]
(dorun part))
; => OutOfMemoryError Java heap space
Since neither doseq nor dorun retains the head, this would simply run forever if lazy-partition-by were O(1) in memory.
Is there an implementation of partition-by with guaranteed memory requirements, provided I don't hold any references to the previous part by the time I start realizing the next one?
It would be very difficult, if not impossible, to write such an implementation in a purely functional manner that would work for the general case. Consider that a general lazy-partition-by implementation cannot make any assumptions about when (or if) a partition is realized. The only guaranteed correct way of finding the start of the second partition, short of introducing some nasty bit of statefulness to keep track of how much of the first partition has been realized, is to remember where the first partition began and scan forward when requested.
For the special case where you're processing records one at a time for side effects and want them grouped by key (as is implied by your use of doseq above), you might consider something along the lines of a loop/recur which maintains a state and re-sets it when the key changes.
Should cons be inside (lazy-seq ...)
(def lseq-in (lazy-seq (cons 1 (more-one))))
or out?
(def lseq-out (cons 1 (lazy-seq (more-one))))
I noticed
(realized? lseq-in)
;;; ⇒ false
(realized? lseq-out)
;;; ⇒ <err>
;;; ClassCastException clojure.lang.Cons cannot be cast to clojure.lang.IPending clojure.core/realized? (core.clj:6773)
All the examples on the clojuredocs.org use "out".
What are the tradeoffs involved?
You definitely want (lazy-seq (cons ...)) as your default, deviating only if you have a clear reason for it. clojuredocs.org is fine, but the examples are all community-provided and I would not call them "the docs". Of course, a consequence of how it's built is that the examples tend to get written by people who just learned how to use the construct in question and want to help out, so many of them are poor. I would refer instead to the code in clojure.core, or other known-good code.
Why should this be the default? Consider these two implementations of map:
(defn map1 [f coll]
(when-let [s (seq coll)]
(cons (f (first s))
(lazy-seq (map1 f (rest coll))))))
(defn map2 [f coll]
(lazy-seq
(when-let [s (seq coll)]
(cons (f (first s))
(map2 f (rest coll))))))
If you call (map1 prn xs), then an element of xs will be realized and printed immediately, even if you never intentionally realize an element of the resulting mapped sequence. map2, on the other hand, immediately returns a lazy sequence, delaying all its work until an element is requested.
With cons inside lazy-seq, the evaluation of the expression for the first element of your seq gets deferred; with cons on the outside, it's done right away and only the construction of the "rest" part of the seq is deferred. (So (rest lseq-out) will be a lazy seq.)
Thus, if computing the first element is expensive and it might not be needed at all, putting cons inside lazy-seq makes more sense. If the initial element is supplied to the lazy seq producer as an argument, it may make more sense to use cons on the outside (this is the case with clojure.core/iterate). Otherwise it doesn't make that much of a difference. (The overhead of creating a lazy seq object at the start is negligible.)
Clojure itself uses both approaches (although in the majority of cases lazy-seq wraps the whole seq-producing expression, which may not necessarily start with cons).
I'm trying to work through Stuart Halloway's book Programming Clojure. This whole functional stuff is very new to me.
I understand how
(defn fibo[]
(map first (iterate (fn [[a b]] [b (+ a b)]) [0 1])))
generates the Fibonacci sequence lazily. I do not understand why
(last (take 1000000 (fibo)))
works, while
(nth (fibo) 1000000)
throws an OutOfMemoryError. Could someone please explain how these two expressions differ? Is (nth) somehow holding on to the head of the sequence?
Thanks!
I think you are talking about issue that was discussed in google group and Rich Hickey provided patch that solved the problem. And the book, whick was published later, didn't cover this topic.
In clojure 1.3 your nth example works with minor improvements in fibo function. Now, due to changes in 1.3, we should explicitly flag M to use arbitrary precision, or it falls with throwIntOverflow.
(defn fibo[]
(map first (iterate (fn [[a b]] [b (+ a b)]) [0M 1M])))
And with these changes
(nth (fibo) 1000000)
succeed (if you have enough memory)
What Clojure version are you using? Try (clojure-version) on a repl. I get identical results for both expressions in 1.3.0, namely an integer overflow.
For
(defn fibo[]
(map first (iterate (fn [[a b]] [b (+ a b)]) [(bigint 0) 1])))
I get correct results for both expressions (a really big integer...).
I think that you may be hitting a specific memory limit for your machine, and not a real difference in function.
Looking at the source code for nth in https://github.com/clojure/clojure/blob/master/src/jvm/clojure/lang/RT.java it does not look like either nth or take are retaining the head.
However, nth uses zero-based indexing, rather than a count by item number. Your code with nth selects the 1000001st element of the sequence (the one at index 1000000). You code with take is returning the final element in a 1000000 element sequence. That's the item with the index 999999. Given how fast fib grows, that last item could be the one that broke the camel's back.
Also, I was checking the 1.3.0 source. Perhaps earlier versions had different implementations. To get your fibo to work properly in 1.3.0 you need to use the arithmetic functions that will promote numbers to bignums:
(defn fibo[]
(map first (iterate (fn [[a b]] [b (+' a b)]) [0 1])))
I'm trying to solve the count a sequence excercise at 4clojure.com. The excercise is to count the number of elements in a collection without using the count function.
I thought I can do this via recursion, by the usage of rest. If what I get isn't empty, I return 1 + recur on the sequence rest returned. The problem is, that I end up getting
java.security.PrivilegedActionException: java.lang.UnsupportedOperationException:
Can only recur from tail position
even though I'm calling recur as the very last statement.
(fn [coll] (let [tail (rest coll)]
(if (empty tail)
1
(+ 1 (recur tail)))))
Am I missing something?
The last statement is the addition, not the call to recur, which is why it doesn't work. The fact that it's inside an if has nothing to do with it. (fn [coll] (let [tail (rest coll)] (+ 1 (recur tail)))) wouldn't work either.
The usual way to turn a function like this into a tail-recursive one is to make the function take a second argument, which holds the accumulator for the value you're adding up and then recurse like this: (recur tail (+ acc 1)) instead of trying to add 1 to the result of recur.
As a general rule: If you're doing anything to the result of recur (like for example adding 1 to it), it can't be in a tail position, so it won't work.
The error that you are getting is pointing out that your final expression of (+ 1 (recur tail)) is not tail-call-optimization optimizable (is that a word?). The problem is that it needs to keep a bunch of (+ 1 ...) expressions on the stack in order to evaluate result of the function. Tail call optimization can only occur if the value of the called function is the only thing needed to know the return of the function making the call.
What you are trying to write is pretty much a fold. In this case the function should pass along the rest of the collection as well as the count so far.
(fn [count coll] (let [tail (rest coll)]
(if (empty tail)
count
(recur (+ 1 count) tail)))))
everyone, I've started working yesterday on the Euler Project in Clojure and I have a problem with one of my solutions I cannot figure out.
I have this function:
(defn find-max-palindrom-in-range [beg end]
(reduce max
(loop [n beg result []]
(if (>= n end)
result
(recur (inc n)
(concat result
(filter #(is-palindrom? %)
(map #(* n %) (range beg end)))))))))
I try to run it like this:
(find-max-palindrom-in-range 100 1000)
and I get this exception:
java.lang.Integer cannot be cast to clojure.lang.IFn
[Thrown class java.lang.ClassCastException]
which I presume means that at some place I'm trying to evaluate an Integer as a function. I however cannot find this place and what puzzles me more is that everything works if I simply evaluate it like this:
(reduce max
(loop [n 100 result []]
(if (>= n 1000)
result
(recur (inc n)
(concat result
(filter #(is-palindrom? %)
(map #(* n %) (range 100 1000))))))))
(I've just stripped down the function definition and replaced the parameters with constants)
Thanks in advance for your help and sorry that I probably bother you with idiotic mistake on my part. Btw I'm using Clojure 1.1 and the newest SLIME from ELPA.
Edit: Here is the code to is-palindrom?. I've implemented it as a text property of the number, not a numeric one.
(defn is-palindrom? [n]
(loop [num (String/valueOf n)]
(cond (not (= (first num) (last num))) false
(<= (.length num) 1) true
:else (recur (.substring num 1 (dec (.length num)))))))
The code works at my REPL (1.1). I'd suggest that you paste it back at yours and try again -- perhaps you simply mistyped something?
Having said that, you could use this as an opportunity to make the code simpler and more obviously correct. Some low-hanging fruit (don't read if you think it could take away from your Project Euler fun, though with your logic already written down I think it shouldn't):
You don't need to wrap is-palindrome? in an anonymous function to pass it to filter. Just write (filter is-palindrome? ...) instead.
That loop in is-palindrome? is pretty complex. Moreover, it's not particularly efficient (first and last both make a seq out of the string first, then last needs to traverse all of it). It would be simpler and faster to (require '[clojure.contrib.str-utils2 :as str]) and use (= num (str/reverse num)).
Since I mentioned efficiency, using concat in this manner is a tad dangerous -- it creates a lazy seq, which might blow up if you pile up two many levels of laziness (this will not matter in the context of Euler 4, but it's good to keep it in mind). If you really need to extend vectors to the right, prefer into.
To further simplify things, you could consider breaking them apart into a function to filter a given sequence so that only palindromes remain and a separate function to return all products of two three-digit numbers. The latter can be accomplished with e.g.
(for [f (range 100 1000)
s (range 100 1000)
:when (<= f s)] ; avoid duplication of effort
(* f s))