ฝึกพูดภาษาอังกฤษด้วยเทคนิค Shadowing จากวิดีโอ: System Design: How to Build an API Rate Limiter
กำลังสร้างบทเรียน...
1
Let's design an API rate limiter for an application that takes thousands of requests per second.
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User journey is simple.
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User can make API calls to your server to do something.
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Each user is allowed to make 100 API calls per minute.
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If a user makes more than 100 calls per minute, then your server will not process those API calls.
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Most engineers approach this problem with a counter.
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For each user, you store user ID, count of API calls, and current minute.
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Every time a request is made by user, you increase this count, and you will reject the requests once it passes 100 requests.
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This implementation is good enough for internal API calls, but let's take two specific examples why this solution is not good.
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Let's say user Alan is a burst user, and makes 100 API calls in first two seconds.
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Then he will get rejected for the next 58 seconds.
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Alan will be able to make calls when next minute starts.
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And our second user, John, sends 100 API requests, but these requests are sent at the last second of the current minute.
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The next second clock will reset to new minute, and John can send another 100 requests.
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Basically, John sent 200 requests in 2 seconds, because according to Counter, these 100 requests belong to different minutes.
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Basically, users will experience different behavior of APIs based on when they make the API call.
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There is a fundamental issue with the approach we just discussed.
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The Counter is watching the clock instead of watching the user.
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Let's see a better approach.
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So, we will give every user a bucket that holds 100 tokens.
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Every API request from user takes one token out, and we will keep filling the bucket at a rate of 100 tokens per minute, which is approximately 1.67 tokens per second.
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For simplification, let's assume we will fill two tokens per second.
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If user doesn't make any API call, the bucket will remain at 100, and we don't need to fill.
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If the bucket is empty, we will reject the request.
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This token bucket approach is what Stripe, GitHub, and most API gateways actually use for tracking API calls.
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Now let's take a look at Alan and John's requests again, and see how this bucket system will work.
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Alan drains all 100 tokens in 2 seconds.
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Then Alan has to slow down.
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Bucket fills about 2 tokens per second.
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That's why he can now make 2 calls per second.
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John, who is making 100 API calls at the end of the minute, will also need to wait for Bucket to fill, because once he makes 100 requests in a second, Bucket will get empty.
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So he can also make about 2 per second, as Bucket fills with time.
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Next question is, how do we store these buckets?
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We just need to store the token count, and the time of the last refill, so that you can add tokens per second.
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But what if your app works at large scale, and you have 20 different servers accepting API calls.
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Two requests for the same user can land on two servers in the same millisecond.
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Therefore, you keep the bucket outside the servers, in one common shared storage.
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This storage needs to be fast, and that's why we usually use Redis.
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When any of these 20 servers processes any API call, we change the count at this common Redis.
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To make this crystal clear in your mind, you need to remember that request limit is not just one number.
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It's two numbers.
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First, how much a user can burst in one go, and second, how fast they can go after the burst.
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Vocabulary and speaking notes for this lesson
This C1 speaking lesson is built on the video “System Design: How to Build an API Rate Limiter”. The speaker keeps coming back to these words: Api, user, request, bucket, token. This video has 42 sentences and 594 words to shadow. The speech runs for 2:47. The speaker talks fast, about 213 words per minute, so expect linked and reduced sounds. 82% of the words are among the 3,000 most common in English; the rest is worth studying before you start.
Key vocabulary in this video
The 15 most advanced words in the video, with pronunciation and meaning:
| Word | Pronunciation | Meaning |
|---|---|---|
| bucket noun | /ˈbʌkɪt/ | A container made of rigid material, often with a handle, used to carry liquids or small items. |
| token noun | /ˈtoʊkən/ | Something serving as an expression of something else. |
| server noun | /ˈsɝvɚ/ | A program that provides services to other programs or devices, either in the same computer or over a computer network. |
| burst verb | /bɜːst/ | To break from internal pressure. |
| clock noun | /klɑk/ | A chronometer, an instrument that measures time, particularly the time of day. |
| crystal noun | /ˈkɹɪstəl/ | A solid composed of an array of atoms or molecules possessing long-range order and arranged in a pattern which is periodic in three dimensions. |
| belong verb | /bɪˈlɒŋ/ | To have its proper place. |
| fundamental adjective | /ˌfʌn.dəˈmɛn.təl/ | Related to a foundation, base, or basis; serving as a foundation. |
| implementation noun | /ˌɪmplɪmənˈteɪʃən/ | The process of moving an idea from concept to reality. In business, engineering and other fields, implementation refers to the building process rather than the… |
| drain noun | /dɹiːn/ | A conduit allowing liquid to flow out of an otherwise contained volume; a plughole (UK) |
| gateway noun | /ˈɡeɪtˌweɪ/ | A passage that can be closed by use of a gate. |
| reset verb | /ɹiːˈsɛt/ | To set back to the initial state. |
| limiter noun | That which limits or confines. | |
| millisecond noun | /ˈmɪlɪˌsɛkənd/ | An SI unit of time equal to 10⁻³ seconds. Symbol: ms |
| refill noun | /ˈɹiː.fɪl/ | An additional helping of food or drink at reduced cost. |
Phrasal verbs you will hear
| Word | Meaning |
|---|---|
| slow down verb | To decelerate. |
ไวยากรณ์ในวิดีโอนี้
โครงสร้างที่ผู้พูดใช้บ่อยที่สุด พร้อมคำพูดจริงจากวิดีโอ:
| โครงสร้าง | ในวิดีโอ |
|---|---|
| ประโยคเงื่อนไข if + อนุประโยค, will/would + กริยา — เงื่อนไขและผลลัพธ์ | If the bucket is empty, we will reject |
| Passive voice be + กริยาช่อง 3 — เน้นสิ่งที่เกิดขึ้น ไม่ใช่ผู้กระทำ | is allowed · is made · are sent |
Pronunciation to watch
- The “sh” and “zh” sounds: implementation /ˌɪmplɪmənˈteɪʃən/, simplification /ˌsɪm.plɪ.fɪˈkeɪ.ʃən/
- Long words — get the stress right: fundamental /ˌfʌn.dəˈmɛn.təl/, implementation /ˌɪmplɪmənˈteɪʃən/, millisecond /ˈmɪlɪˌsɛkənd/, simplification /ˌsɪm.plɪ.fɪˈkeɪ.ʃən/
How to practise with this video
- Listen to the whole video once without speaking and note the words you do not know.
- Start at 0.75× speed, shadow it sentence by sentence, then go back to normal speed once it feels easy.
- Record yourself and compare with the original, paying attention to words like bucket, token, server.
เทคนิค Shadowing คืออะไร?
Shadowing เป็นเทคนิคการเรียนรู้ภาษาที่ได้รับการรับรองทางวิทยาศาสตร์ พัฒนาขึ้นสำหรับการฝึกนักแปลมืออาชีพ วิธีการนี้เรียบง่ายแต่ทรงพลัง: คุณฟังเสียงภาษาอังกฤษจากเจ้าของภาษาและพูดตามทันที — เหมือนเงาที่ตามผู้พูดด้วยช่วงเวลาห่าง 1-2 วินาที การวิจัยแสดงว่าเทคนิคนี้ปรับปรุงความแม่นยำในการออกเสียง ทำนองเสียง จังหวะ การเชื่อมเสียง การฟังเข้าใจ และความคล่องแคล่วในการพูดได้อย่างมีนัยสำคัญ