I have a number of threads that need to access a collection of values, some of these values also need to be persisted to a database when any changes are made to them so that I don't lose the state in case of a server reboot etc.
Currently I'm using an atom to store these values, I have a set of functions which I call when something in the atom needs to change.
Inside these functions I'm also persisting data to a database before calling swap!, I chose this approach because I need to frequently read the values inside the atom, and it doesn't seem performant to open/close db connections every time I'm interested in one of the values.
the question:
Is this approach viable? I'm interested to know if anyone has had success implementing a similar solution or are there pitfalls I should be aware of?
Atoms are fine.
An alternative approach would be to use https://github.com/clojure/core.memoize or core.cached directly, like suggested by Stefan Kamphausen.
Approach:
Cache query results on the function level. This way you are sure that what you get back is exactly how the database would return it and not the way you would think it would serialize/deserialize.
Invalidate key/args after you have inserted/changed something in the database.
One benefit of this approach is that you can tweak the caching behavior: TTL, LRU, FIFO, etc.
Demo:
(require '[clojure.core.memoize :as memo])
;; suppose this is a real DB
(def db (atom {}))
(defn my-get [k]
;; expensive database call
(Thread/sleep 5000)
(get #db k))
(def my-get-cached
(memo/memo my-get))
(defn my-put
[k val]
(swap! db assoc k val)
(memo/memo-clear! my-get-cached [k]))
(comment
(my-put :foo "the value")
(my-get-cached :foo) ;; wait 5 seconds, "the value"
(my-get-cached :foo) ;; "the value", instantly
(my-put :bar "other-value")
(my-get-cached :foo) ;; "the value", still instantly
(my-get-cached :bar) ;; wait 5 seconds, "other value"
(my-put :foo "changed")
(my-get-cached :foo) ;; wait 5 seconds, "changed"
)
Related
I have a function which gets data periodically and then stops getting the data. This function has to return the data that it is fetching periodically to the caller of the function either
As and when it gets
At one shot
The 2nd one is an easy implementation i.e you block the caller, fetch all the data and then send it in one shot.
But I want to implement the 1st one (I want to avoid having callbacks). Is streams the things to be used here? If so, how? If not, how do I return something on which the caller can query for data and also stop when it returns a signal that there is no more data?
Note: I am on the JVM ecosystem, clojure to be specific. I have had a look at the clojure library core.async which kind of solves this kind of a problem with the use of channels. But I was thinking if there is any other way which probably looks like this (assuming streams is something that can be used).
Java snippet
//Function which will periodically fetch MyData until there is no data
public Stream<MyData> myFunction() {
...
}
myFunction().filter(myData -> myData.text.equals("foo"))
Maybe you can just use seq - which is lazy by default (like Stream) so caller can decide when to pull the data in. And when there are no more data myFunction can simply end the sequence. While doing this, you would also encapsulate some optimisation within myFunction - e.g. to get data in batch to minimise roundtrips. Or fetch data periodically per your original requirement.
Here is one naive implementation:
(defn my-function []
(let [batch 100]
(->> (range)
(map #(let [from (* batch %)
to (+ from batch)]
(db-get from to)))
;; take while we have data from db-get
(take-while identity)
;; returns as one single seq/Stream
(apply concat))))
;; use it as a normal seq/Stream
(->> (my-function)
(filter odd?))
where db-get would be something like:
(defn db-get [from to]
;; return first 1000 records only, i.e. returns nil to signal completion
(when (< from 1000)
;; returns a range of records
(range from to)))
You might want to check https://github.com/ReactiveX/RxJava and https://github.com/ReactiveX/RxClojure (seems no longer maintained?)
I am creating an agent for writing changes back to a database (as discussed in the agent-based write-behind log in Clojure Programming).
This is working fine, but I am struggling to create the agent late. I don't want to create it as a def, as I don't want it created when my tests are running (I see the pool starting up when the tests load the forms even though I use with-redefs to set a test value).
The code I started with is (using c3p0 pooling):
(def dba (agent (pool/make-datasource-spec (u/load-config "db.edn"))))
I tried making the agent nil, and investigated how I could set it in the main of my application, when it's really needed. But there doesn't seem to be an equivalent reset! function as there is with an atom. And the following code also failed saying the agent wasn't in error so didn't need restarting:
(when (not #dba)
(restart-agent dba (create-db-pool)))
So at the moment, I have an atom containing the agent, where I then do:
(def dba (atom nil))
;; ...
(defn init-db! []
(when (not #dba)
(log/info "Creating agent for pooled connection")
(reset! dba (agent (create-db-pool))))
But the very fact I'm having to do ##dba to reference the contents of the agent (i.e. the pool) makes me think this is insane.
Is there a more obvious way of creating the pool agent lazily?
delay is useful for cases like this. It causes the item to be created the first time it is read. so if your tests don't read it it will not be created.
user=> (def my-agent (delay (do (println "im making the agent now") (agent 0))))
#'user/my-agent
user=>
user=> #my-agent
im making the agent now
#object[clojure.lang.Agent 0x2cd73ca1 {:status :ready, :val 0}]
Is it ok to use binding with core.async? I'm using ClojureScript so core.async is very different.
(def ^:dynamic token "no-token")
(defn call
[path body]
(http-post (str host path) (merge {:headers {"X-token" token}} body)))) ; returns a core.async channel
(defn user-settings
[req]
(call "/api/user/settings" req))
; elsewhere after I've logged in
(let [token (async/<! (api/login {:user "me" :pass "pass"}))]
(binding
[token token]
(user-settings {:all-settings true})))
In ClojureScript1, binding is basically with-redefs plus an extra check that the Vars involved are marked :dynamic. On the other hand, gos get scheduled for execution1 in chunks (that is, they may be "parked" and later resumed, and interleaving between go blocks is arbitrary). These models don't mesh very well at all.
In short, no, please use explicitly-passed arguments instead.
1 The details are different in Clojure, but the conclusion remains the same.
2 Using the fastest mechanism possible, setTimeout with a time of 0 if nothing better is available.
I am working on a Clojure / Jetty web service. I have a special url that I want to only be serviced one request at a time. If the url was requested, and before it returns, the url is requested again, I want to immediately return. So in more core.clj, where I defined my routes, I have something like this:
(def work-in-progress (ref false))
Then sometime later
(compojure.core/GET "/myapp/internal/do-work" []
(if #work-in-progress
"Work in Progress please try again later"
(do
(dosync
(ref-set work-in-progress true))
(do-the-work)
(dosync
(ref-set rebuild-in-progress false))
"Job completed Successfully")))
I have tried this on local Jetty server but I seem to be able to hit the url twice and double the work. What is a good pattern / way to implement this in Clojure in a threaded web server environment?
Imagine a following race condition for the solution proposed in the question.
Thread A starts to execute handler's body. #work-in-progress is false, so it enters the do expression. However, before it managed to set the value of work-in-progress to true...
Thread B starts to execute handler's body. #work-in-progress is false, so it enters the do expression.
Now two threads are executing (do-the-work) concurrently. That's not what we want.
To prevent this problem check and set the value of the ref in a dosync transaction.
(compojure.core/GET "/myapp/internal/do-work" []
(if (dosync
(when-not #work-in-progress
(ref-set work-in-progress true)))
(try
(do-the-work)
"Job completed Successfully"
(finally
(dosync
(ref-set work-in-progress false))))
"Work in Progress please try again later"))
Another abstraction which you might find useful in this scenario is an atom and compare-and-set!.
(def work-in-progress (atom false))
(compojure.core/GET "/myapp/internal/do-work" []
(if (compare-and-set! work-in-progress false true)
(try
(do-the-work)
"Job completed Successfully"
(finally
(reset! work-in-progress false)))
"Work in Progress please try again later"))
Actually this is the natural use case for a lock; in particular, a java.util.concurrent.locks.ReentrantLock.
The same pattern came up in my answer to an earlier SO question, Canonical Way to Ensure Only One Instance of a Service Is Running / Starting / Stopping in Clojure?; I'll repeat the relevant piece of code here:
(import java.util.concurrent.locks.ReentrantLock)
(def lock (ReentrantLock.))
(defn start []
(if (.tryLock lock)
(try
(do-stuff)
(finally (.unlock lock)))
(do-other-stuff)))
The tryLock method attempts to acquire the lock, returning true if it succeeds in doing so and false otherwise, not blocking in either case.
Consider queueing the access to the resource as well - in addition to getting an equivalent functionality to that of locks/flags, queues let you observe the resource contention, among other advantages.
I am learning clojure and try out its concurrency and effectiveness via a producer consumer example.
Did that and it felt pretty akward with having to use ref and deref and also watch and unwatch.
I tried to check other code snippet; but is there a better way of re factoring this other than using Java Condition await() and signal() methods along with Java Lock. I did not want to use anything in Java.
here is the code; i guess I would have made many mistakes here with my usage...
;a simple producer class
(ns my.clojure.producer
(:use my.clojure.consumer)
(:gen-class)
)
(def tasklist( ref (list) )) ;this is declared as a global variable; to make this
;mutable we need to use the fn ref
(defn gettasklist[]
(deref tasklist) ;we need to use deref fn to return the task list
)
(def testagent (agent 0)); create an agent
(defn emptytasklist[akey aref old-val new-val]
(doseq [item (gettasklist)]
(println(str "item is") item)
(send testagent consume item)
(send testagent increment item)
)
(. java.lang.Thread sleep 1000)
(dosync ; adding a transaction for this is needed to reset
(remove-watch tasklist "key123"); removing the watch on the tasklist so that it does not
; go to a recursive call
(ref-set tasklist (list ) ) ; we need to make it as a ref to reassign
(println (str "The number of tasks now remaining is=") (count (gettasklist)))
)
(add-watch tasklist "key123" emptytasklist)
)
(add-watch tasklist "key123" emptytasklist)
(defn addtask [task]
(dosync ; adding a transaction for this is needed to refset
;(println (str "The number of tasks before") (count (gettasklist)))
(println (str "Adding a task") task)
(ref-set tasklist (conj (gettasklist) task )) ; we need to make it as a ref to reassign
;(println (str "The number of tasks after") (count (gettasklist)))
)
)
Here is the consumer code
(ns my.clojure.consumer
)
(defn consume[c item]
(println "In the consume method:Item is " c item )
item
)
(defn increment [c n]
(println "parmeters are" c n)
(+ c n)
)
And here is the test code ( I have used maven to run clojure code and used NetBeans to edit as this is more familiar to me coming from Java - folder structure and pom at - https://github.com/alexcpn/clojure-evolve
(ns my.clojure.Testproducer
(:use my.clojure.producer)
(:use clojure.test)
(:gen-class)
)
(deftest test-addandcheck
(addtask 1)
(addtask 2)
(is(= 0 (count (gettasklist))))
(println (str "The number of tasks are") (count (gettasklist)))
)
If anybody can refactor this lightly so that I can read and understand the code then it will be great; Else I guess I will have to learn more
Edit -1
I guess using a global task list and making it available to other functions by de-referencing it (deref) and again making it mutable by ref is not the way in clojure;
So changing the addTask method to directly send the incoming tasks to an agent
(defn addtask [task]
(dosync ; adding a transaction for this is needed to refset
(println (str "Adding a task") task)
;(ref-set tasklist (conj (gettasklist) task )) ; we need to make it as a ref to reassign
(def testagent (agent 0)); create an agent
(send testagent consume task)
(send testagent increment task)
)
However when I tested it
(deftest test-addandcheck
(loop [task 0]
(when ( < task 100)
(addtask task)
(recur (inc task))))
(is(= 0 (count (gettasklist))))
(println (str "The number of tasks are") (count (gettasklist)))
)
after sometime the I am getting Java rejected execution exception -- This is fine if you do Java threads, because you take full control. But from clojure this looks odd, especially since you are not selecting the ThreadPool stratergy yourself
Adding a task 85
Exception in thread "pool-1-thread-4" java.util.concurrent.RejectedExecutionExce
ption
at java.util.concurrent.ThreadPoolExecutor$AbortPolicy.rejectedExecution
(ThreadPoolExecutor.java:1759)
at java.util.concurrent.ThreadPoolExecutor.reject(ThreadPoolExecutor.jav
a:767)
at java.util.concurrent.ThreadPoolExecutor.execute(ThreadPoolExecutor.ja
va:658)
at clojure.lang.Agent$Action.execute(Agent.java:56)
at clojure.lang.Agent$Action.doRun(Agent.java:95)
at clojure.lang.Agent$Action.run(Agent.java:106)
at java.util.concurrent.ThreadPoolExecutor$Worker.runTask(ThreadPoolExec
utor.java:885)Adding a task 86
Adding a task 87
I think modeling producer & consumer in clojure would be done the easiest (and most efficiently) using lamina channels.
I have made similar clojure program with producer/consumer pattern in Computing Folder Sizes Asynchronously.
I don't think that you really need to use Refs.
You have single tasklist that is mutable state that you want to alter synchronously. Changes are relatively quick and do not depend on any other external state, only the variable that comes in to consumer.
As far with atoms there is swap! function which can help you do the changes the way I understood you need.
You can look at my snippet Computing folder size i think it can at least show you proper use of atoms & agents. I played with it a lot, so it should be correct.
Hope it helps!
Regards,
Jan
I was looking at the Clojure examples for Twitter storm. He just used LinkedBlockingQueue. It's easy to use, concurrent and performs well. Sure, it lacks the sex-appeal of an immutable Clojure solution, but it will work well.
I've come across several use cases where I need the ability to:
strictly control the number of worker threads on both the producer and consumer side
control the maximum size of the "work queue" in order to limit memory consumption
detect when all work has been completed so that I can shut down the workers
I've found that the clojure built-in concurrency features (while amazingly simple and useful in their own right) make the first two bullet points difficult. lamina looks great, but I didn't see a way that it would address my particular use cases w/o the same sort of extra plumbing that I'd need to do around an implementation based on BlockingQueue.
So, I ended up hacking together a simple clojure library to try to solve my problems. It is basically just a wrapper around BlockingQueue that attempts to conceal some of the Java constructs and provide a higher-level producer-consumer API. I'm not entirely satisfied with the API yet; it'll likely evolve a bit further... but it's operational:
https://github.com/cprice-puppet/freemarket
Example usage:
(def myproducer (producer producer-work-fn num-workers max-work))
(def myconsumer (consumer myproducer consumer-work-fn num-workers max-results))
(doseq [result (work-queue->seq (:result-queue myconsumer))]
(println result))
Feedback / suggestions / contributions would be welcomed!