쉐도잉 연습: Cache Systems Every Developer Should Know - 영상으로 영어 말하기 배우기
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Caching is a common technique in modern computing to enhance system performance and reduce response time.
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From the front end to the back end, caching plays a crucial role in improving the efficiency of various applications and systems.
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A typical system architecture involves several layers of caching.
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At each layer, there are multiple strategies and mechanisms for caching data, depending on the requirements and the constraints of the specific application.
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Before diving into a typical system architecture, let's zoom in and look at how prevalent caching is within each computer itself.
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Let's first look at the computer hardware.
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The most common hardware caches are L1, L2, and L3 caches.
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L1 cache is the smallest and fastest cache, typically integrated into the CPU itself.
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It stores frequently accessed data and instructions, allowing the CPU to quickly access them without having to fetch them from slower memory.
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L2 cache is larger but slower than L1 cache, and is typically located on the CPU die.
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L3 cache is even larger and slower than L2 cache, and is often shared between multiple CPU cores.
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Another common hardware cache is the Translation Look -Aside Buffer, or TLB.
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It stores recently used virtual to physical address translations.
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It is used by the CPU to quickly translate virtual memory addresses to physical memory addresses, reducing the time needed to access data from memory.
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At the operating system level, there are PageCache and other file system caches.
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PageCache is managed by the operating system and resides in main memory.
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It is used to store recently used disk blocks in memory.
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When a program requests data from the disk, the operating system can quickly retrieve the data from memory instead of reading it from disk.
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There are other caches managed by the operating system such as the iNode cache.
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These caches are used to speed up file system operations by
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reducing the number of disk accesses required to access files and directories.
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Now let's zoom out and look at how caching is used in a typical application system architecture.
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On the application front end, web browsers can cache HTTP responses to enable faster retrieval of data.
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When we request data over HTTP for the first time and it is returned with an expiration policy in the HTTP header.
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We request the same data again, and the browser returns the data from its cache if available.
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Content delivery network, or CDNs, are widely used to improve the delivery of static content,
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such as images, videos, and other web access.
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One of the ways that CDNs speed up content delivery is through caching.
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When a user requests contents from a CDN, the CDN network looks for the requested content in its cache.
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If the content is not already in the cache, the CDN fetches it from the origin server and caches it on its edge servers.
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When another user requests the same content, the CDN can deliver the content directly from its cache,
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eliminating the need to fetch it from the origin server again.
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Some load balancers can cache resources to reduce the load on back -end servers.
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When a user requests content from a server behind a load balancer,
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the load balancer can cache the response and serve it directly to future users who request the same content.
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This can improve response times and reduce the load on back -end servers.
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Caching does not always have to be in memory.
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In messaging infrastructure, message brokers such as Kafka can cache a massive amount of messages on disk.
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This allows consumers to retrieve the messages at their own pace.
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The messages can be cached for a long period of time based on the retention policy.
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Distributed caches such as Redis can store key value pairs in memory, providing high read -write performance compared to traditional databases.
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Full text search engines, such as Elasticsearch, can index data for document search and log search,
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providing quick and efficient access to specific data.
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Even within the database, there are multiple levels of caching available.
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Data is typically written to a write -ahead log before being indexed in a B -tree.
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The buffer pool is a memory area used to cache query results, while materialized views can pre -compute query results for faster performance.
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The transaction log records all transactions and updates to the database, while the replication log tracks the replication state in a database cluster.
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Overall, caching data is an essential technique for optimizing system performance and reducing response time.
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From the front end to the back end, there are many layers of caching to improve the efficiency of various applications and systems.
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이 레슨의 어휘와 말하기 포인트
이 말하기 레슨은 영상 “Cache Systems Every Developer Should Know”을(를) 바탕으로 합니다. 가장 자주 반복되는 단어는 다음과 같습니다: cache, caching, memory, content, request. 이 영상에는 섀도잉할 문장 53개와 단어 802개가 있습니다. 말하는 구간의 길이는 5:37입니다. 화자는 분당 약 143단어의 일정한 속도로 말해서 섀도잉하기에 편한 속도입니다. 영어에서 가장 많이 쓰이는 3,000단어에 속하는 단어가 75%뿐이라 어휘가 어려운 편입니다.
이 영상의 핵심 어휘
영상에 나오는 익혀 둘 만한 단어 15개를 발음, 뜻과 함께 정리했습니다.
| 단어 | 발음 | 뜻 |
|---|---|---|
| cache 명사 | /kæʃ/ | 캐시 |
| server 명사 | /ˈsɝvɚ/ | 서버, 봉사기 |
| disk 명사 | /dɪsk/ | 디스크, 원반 |
| database 명사 | /ˈdeɪtəˌbeɪs/ | 데이터베이스 |
| architecture 명사 | /ˈɑː.kɪˌtɛk.t͡ʃə/ | 건축, 건축학 |
| layer 명사 | /ˈleɪ̯ɚ/ | 층 |
| hardware 명사 | /ˈhɑɹdˌwɛɹ/ | 하드웨어, 굳은모 |
| fetch 동사 | /fɛt͡ʃ/ | 가지고 오다 |
| technique 명사 | /tɛkˈniːk/ | 기술 |
| virtual 형용사 | /ˈvɜɹt͡ʃuəl/ | 사실상의 |
| transaction 명사 | /tɹænˈzækʃən/ | 처리 |
| query 명사 | /ˈkwɪɹ.i/ | 질문 |
| topic 명사 | /ˈtɑpɪk/ | 화제, 주제 |
| infrastructure 명사 | /ˈɪnfɹəˌstɹʌkt͡ʃə/ | 기반시설, 기간시설 |
| compare 동사 | /kəmˈpɛɚ/ | 비교하다, 비유하다 |
영상에 나오는 구동사
| 단어 | 발음 | 뜻 |
|---|---|---|
| zoom out 동사 | /ˌzuːm ˈaʊt/ | 줌 아웃하다, 축소(縮小)하다 |
주의할 발음
- “sh”와 “zh” 소리: cache /kæʃ/, efficiency /ɪˈfɪʃ.ən.si/, transaction /tɹænˈzækʃən/, efficient /ɪˈfɪʃənt/, translation /tɹænzˈleɪʃən/
- 긴 단어 — 강세 위치에 주의: architecture /ˈɑː.kɪˌtɛk.t͡ʃə/, efficiency /ɪˈfɪʃ.ən.si/, infrastructure /ˈɪnfɹəˌstɹʌkt͡ʃə/, mechanism /ˈmɛk.ə.nɪ.zəm/, eliminate /ɪˈlɪm.ɪ.neɪt/
한국어 화자가 어려워하는 소리:
- /f/ — ㅍ(/p/)으로 바꾸지 말고 윗니를 아랫입술에 대기: fetch /fɛt͡ʃ/, efficiency /ɪˈfɪʃ.ən.si/, buffer /ˈbʌfəɹ/, infrastructure /ˈɪnfɹəˌstɹʌkt͡ʃə/, efficient /ɪˈfɪʃənt/
- /v/ — ㅂ(/b/)과 구별하기: server /ˈsɝvɚ/, virtual /ˈvɜɹt͡ʃuəl/, retrieve /ɹɪˈtɹiːv/, involve /ɪnˈvɑlv/, dive /daɪv/
- /z/ — ㅈ이 아니라 성대를 울리는 /s/: transaction /tɹænˈzækʃən/, browser /ˈbɹaʊ.zəɹ/, zoom /zuːm/, resource /ɹɪˈzɔːs/, translation /tɹænzˈleɪʃən/
이 영상으로 연습하는 방법
- 먼저 말하지 않고 영상을 끝까지 듣고 모르는 단어를 적어 둡니다.
- 보통 속도로 한 문장씩 섀도잉하고, 화자의 리듬과 맞을 때까지 반복합니다.
- 자신의 목소리를 녹음해 원본과 비교하고, cache, server, disk 같은 단어에 특히 주의합니다.
쉐도잉이란? 영어 실력을 빠르게 키우는 과학적 방법
쉐도잉(Shadowing)은 원래 전문 통역사 훈련을 위해 개발된 언어 학습 기법으로, 다언어 학자인 Dr. Alexander Arguelles에 의해 대중화된 방법입니다. 핵심 원리는 간단하지만 매우 강력합니다: 원어민의 영어를 들으면서 1~2초의 짧은 지연으로 즉시 소리 내어 따라 말하는 것——마치 '그림자(shadow)'처럼 화자를 따라가는 것입니다. 문법 공부나 수동적인 청취와 달리, 쉐도잉은 뇌와 입 근육이 동시에 실시간으로 영어를 처리하고 재현하도록 훈련합니다. 연구에 따르면 이 방법은 발음 정확도, 억양, 리듬, 연음, 청취력, 말하기 유창성을 크게 향상시킵니다. IELTS 스피킹 준비와 자연스러운 영어 소통을 원하는 분들에게 특히 효과적입니다.