Design pattern: Combining http requests with pluggable Redis caching mechanism










0















For API work I tend to cache 3rd party API responses by wrapping the http request around Redis get / set functions e.g:



import http from 'request-promise-native';
import redis from 'redis';
import bluebird from 'bluebird';

bluebird.promisifyAll(redis.RedisClient.prototype);
bluebird.promisifyAll(redis.Multi.prototype);

const redisClient = redis.createClient();

const getData = async id =>
const cacheKey = `some-key-$id`;
const cached = await redisClient.getAsync(cacheKey);

if (cached)
return JSON.parse(cached);


const response = await http(
method: 'GET',
url: `https://example.com/$id`,
json: true,
);

redisClient.set(cacheKey, JSON.stringify(response), 'EX', 3600);
return response;



This works well for a few API calls, but when you have a complex API with tens or hundreds of calls this approach is harder to maintain and toggle.



It would be ideal if this could be plugged into the http request library (in this case request-promise-native).



Can you recommend a better solution?










share|improve this question


























    0















    For API work I tend to cache 3rd party API responses by wrapping the http request around Redis get / set functions e.g:



    import http from 'request-promise-native';
    import redis from 'redis';
    import bluebird from 'bluebird';

    bluebird.promisifyAll(redis.RedisClient.prototype);
    bluebird.promisifyAll(redis.Multi.prototype);

    const redisClient = redis.createClient();

    const getData = async id =>
    const cacheKey = `some-key-$id`;
    const cached = await redisClient.getAsync(cacheKey);

    if (cached)
    return JSON.parse(cached);


    const response = await http(
    method: 'GET',
    url: `https://example.com/$id`,
    json: true,
    );

    redisClient.set(cacheKey, JSON.stringify(response), 'EX', 3600);
    return response;



    This works well for a few API calls, but when you have a complex API with tens or hundreds of calls this approach is harder to maintain and toggle.



    It would be ideal if this could be plugged into the http request library (in this case request-promise-native).



    Can you recommend a better solution?










    share|improve this question
























      0












      0








      0








      For API work I tend to cache 3rd party API responses by wrapping the http request around Redis get / set functions e.g:



      import http from 'request-promise-native';
      import redis from 'redis';
      import bluebird from 'bluebird';

      bluebird.promisifyAll(redis.RedisClient.prototype);
      bluebird.promisifyAll(redis.Multi.prototype);

      const redisClient = redis.createClient();

      const getData = async id =>
      const cacheKey = `some-key-$id`;
      const cached = await redisClient.getAsync(cacheKey);

      if (cached)
      return JSON.parse(cached);


      const response = await http(
      method: 'GET',
      url: `https://example.com/$id`,
      json: true,
      );

      redisClient.set(cacheKey, JSON.stringify(response), 'EX', 3600);
      return response;



      This works well for a few API calls, but when you have a complex API with tens or hundreds of calls this approach is harder to maintain and toggle.



      It would be ideal if this could be plugged into the http request library (in this case request-promise-native).



      Can you recommend a better solution?










      share|improve this question














      For API work I tend to cache 3rd party API responses by wrapping the http request around Redis get / set functions e.g:



      import http from 'request-promise-native';
      import redis from 'redis';
      import bluebird from 'bluebird';

      bluebird.promisifyAll(redis.RedisClient.prototype);
      bluebird.promisifyAll(redis.Multi.prototype);

      const redisClient = redis.createClient();

      const getData = async id =>
      const cacheKey = `some-key-$id`;
      const cached = await redisClient.getAsync(cacheKey);

      if (cached)
      return JSON.parse(cached);


      const response = await http(
      method: 'GET',
      url: `https://example.com/$id`,
      json: true,
      );

      redisClient.set(cacheKey, JSON.stringify(response), 'EX', 3600);
      return response;



      This works well for a few API calls, but when you have a complex API with tens or hundreds of calls this approach is harder to maintain and toggle.



      It would be ideal if this could be plugged into the http request library (in this case request-promise-native).



      Can you recommend a better solution?







      node.js caching redis request






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked Nov 14 '18 at 4:43









      ChrisRichChrisRich

      2,46862537




      2,46862537






















          1 Answer
          1






          active

          oldest

          votes


















          0














          The design pattern you mentioned is Decorator function and you can also achieve it with wrapping your api calls with a custom function which calles redis each time before reaching out to the API.



          but it's defiantly should not be part of request-promise-native, it's too permissive and opinionated.



          when building high-load/high-concurrency applications you should consider
          not doing lot's of cpu consuming tasks / long-blocking tasks / allocations on hot path (creating lot's of new objects)



          Redis performance is bounded to the cpu(1-code) & memory & network of your machine , and a simple vm (2 cores, 4gb, 1gbit network) can handle tens of K concurrently.



          your nodejs app will blow the cpu/memory before something happens to redis .






          share|improve this answer






















            Your Answer






            StackExchange.ifUsing("editor", function ()
            StackExchange.using("externalEditor", function ()
            StackExchange.using("snippets", function ()
            StackExchange.snippets.init();
            );
            );
            , "code-snippets");

            StackExchange.ready(function()
            var channelOptions =
            tags: "".split(" "),
            id: "1"
            ;
            initTagRenderer("".split(" "), "".split(" "), channelOptions);

            StackExchange.using("externalEditor", function()
            // Have to fire editor after snippets, if snippets enabled
            if (StackExchange.settings.snippets.snippetsEnabled)
            StackExchange.using("snippets", function()
            createEditor();
            );

            else
            createEditor();

            );

            function createEditor()
            StackExchange.prepareEditor(
            heartbeatType: 'answer',
            autoActivateHeartbeat: false,
            convertImagesToLinks: true,
            noModals: true,
            showLowRepImageUploadWarning: true,
            reputationToPostImages: 10,
            bindNavPrevention: true,
            postfix: "",
            imageUploader:
            brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
            contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
            allowUrls: true
            ,
            onDemand: true,
            discardSelector: ".discard-answer"
            ,immediatelyShowMarkdownHelp:true
            );



            );













            draft saved

            draft discarded


















            StackExchange.ready(
            function ()
            StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53293312%2fdesign-pattern-combining-http-requests-with-pluggable-redis-caching-mechanism%23new-answer', 'question_page');

            );

            Post as a guest















            Required, but never shown

























            1 Answer
            1






            active

            oldest

            votes








            1 Answer
            1






            active

            oldest

            votes









            active

            oldest

            votes






            active

            oldest

            votes









            0














            The design pattern you mentioned is Decorator function and you can also achieve it with wrapping your api calls with a custom function which calles redis each time before reaching out to the API.



            but it's defiantly should not be part of request-promise-native, it's too permissive and opinionated.



            when building high-load/high-concurrency applications you should consider
            not doing lot's of cpu consuming tasks / long-blocking tasks / allocations on hot path (creating lot's of new objects)



            Redis performance is bounded to the cpu(1-code) & memory & network of your machine , and a simple vm (2 cores, 4gb, 1gbit network) can handle tens of K concurrently.



            your nodejs app will blow the cpu/memory before something happens to redis .






            share|improve this answer



























              0














              The design pattern you mentioned is Decorator function and you can also achieve it with wrapping your api calls with a custom function which calles redis each time before reaching out to the API.



              but it's defiantly should not be part of request-promise-native, it's too permissive and opinionated.



              when building high-load/high-concurrency applications you should consider
              not doing lot's of cpu consuming tasks / long-blocking tasks / allocations on hot path (creating lot's of new objects)



              Redis performance is bounded to the cpu(1-code) & memory & network of your machine , and a simple vm (2 cores, 4gb, 1gbit network) can handle tens of K concurrently.



              your nodejs app will blow the cpu/memory before something happens to redis .






              share|improve this answer

























                0












                0








                0







                The design pattern you mentioned is Decorator function and you can also achieve it with wrapping your api calls with a custom function which calles redis each time before reaching out to the API.



                but it's defiantly should not be part of request-promise-native, it's too permissive and opinionated.



                when building high-load/high-concurrency applications you should consider
                not doing lot's of cpu consuming tasks / long-blocking tasks / allocations on hot path (creating lot's of new objects)



                Redis performance is bounded to the cpu(1-code) & memory & network of your machine , and a simple vm (2 cores, 4gb, 1gbit network) can handle tens of K concurrently.



                your nodejs app will blow the cpu/memory before something happens to redis .






                share|improve this answer













                The design pattern you mentioned is Decorator function and you can also achieve it with wrapping your api calls with a custom function which calles redis each time before reaching out to the API.



                but it's defiantly should not be part of request-promise-native, it's too permissive and opinionated.



                when building high-load/high-concurrency applications you should consider
                not doing lot's of cpu consuming tasks / long-blocking tasks / allocations on hot path (creating lot's of new objects)



                Redis performance is bounded to the cpu(1-code) & memory & network of your machine , and a simple vm (2 cores, 4gb, 1gbit network) can handle tens of K concurrently.



                your nodejs app will blow the cpu/memory before something happens to redis .







                share|improve this answer












                share|improve this answer



                share|improve this answer










                answered Nov 14 '18 at 5:51









                Mazki516Mazki516

                6431517




                6431517





























                    draft saved

                    draft discarded
















































                    Thanks for contributing an answer to Stack Overflow!


                    • Please be sure to answer the question. Provide details and share your research!

                    But avoid


                    • Asking for help, clarification, or responding to other answers.

                    • Making statements based on opinion; back them up with references or personal experience.

                    To learn more, see our tips on writing great answers.




                    draft saved


                    draft discarded














                    StackExchange.ready(
                    function ()
                    StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53293312%2fdesign-pattern-combining-http-requests-with-pluggable-redis-caching-mechanism%23new-answer', 'question_page');

                    );

                    Post as a guest















                    Required, but never shown





















































                    Required, but never shown














                    Required, but never shown












                    Required, but never shown







                    Required, but never shown

































                    Required, but never shown














                    Required, but never shown












                    Required, but never shown







                    Required, but never shown







                    Popular posts from this blog

                    Use pre created SQLite database for Android project in kotlin

                    Darth Vader #20

                    Ondo