跟读练习: Cache Systems Every Developer Should Know - 通过视频学习英语口语
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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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本课的词汇与口语要点
这节口语课以视频“Cache Systems Every Developer Should Know”为素材。 视频中反复出现的词有：cache, caching, memory, content, request。 这段视频共有 53 个句子、802 个单词可供跟读。 讲话部分时长为 5:37。 说话人语速平稳，每分钟约 143 个词，很适合跟读。 只有 75% 的单词属于英语最常用的 3,000 词，词汇难度较高。
视频中的重点词汇
视频中 15 个值得学习的单词，附发音和释义：
| 单词 | 发音 | 释义 |
|---|---|---|
| cache 名词 | /kæʃ/ | 緩存 /缓存, 快取 |
| server 名词 | /ˈsɝvɚ/ | 服務器 /服务器, 伺服器 |
| disk 名词 | /dɪsk/ | 圓盤 /圆盘 |
| database 名词 | /ˈdeɪtəˌbeɪs/ | 數據庫 /数据库 |
| architecture 名词 | /ˈɑː.kɪˌtɛk.t͡ʃə/ | 建築 /建筑, 建築學 /建筑学 |
| layer 名词 | /ˈleɪ̯ɚ/ | 層 /层 |
| hardware 名词 | /ˈhɑɹdˌwɛɹ/ | 硬件, 硬體 /硬体 |
| fetch 动词 | /fɛt͡ʃ/ | 取 |
| technique 名词 | /tɛkˈniːk/ | 技術 /技术, 技巧 |
| efficiency 名词 | /ɪˈfɪʃ.ən.si/ | 效率, 效能 |
| transaction 名词 | /tɹænˈzækʃən/ | 處理 /处理 |
| retrieve 动词 | /ɹɪˈtɹiːv/ | 重拾 |
| query 名词 | /ˈkwɪɹ.i/ | 問題 /问题, 質問 /质问 |
| topic 名词 | /ˈtɑpɪk/ | 主題 /主题, 話題 /话题 |
| infrastructure 名词 | /ˈɪnfɹəˌstɹʌkt͡ʃə/ | 基礎設施 /基础设施 |
视频中出现的短语动词
| 单词 | 发音 | 释义 |
|---|---|---|
| speed up 动词 | /spiːdˈʌp/ | 加速, 加快 |
| zoom out 动词 | /ˌzuːm ˈaʊt/ | 縮小 /缩小 |
需要注意的发音
- “sh” 和 “zh” 音: cache /kæʃ/, efficiency /ɪˈfɪʃ.ən.si/, transaction /tɹænˈzækʃən/, efficient /ɪˈfɪʃənt/, translation /tɹænzˈleɪʃən/
- 长单词——注意重音位置: architecture /ˈɑː.kɪˌtɛk.t͡ʃə/, efficiency /ɪˈfɪʃ.ən.si/, infrastructure /ˈɪnfɹəˌstɹʌkt͡ʃə/, mechanism /ˈmɛk.ə.nɪ.zəm/, eliminate /ɪˈlɪm.ɪ.neɪt/
中文母语者容易读错的音：
- /v/ — 不要读成 /w/，上齿轻触下唇: server /ˈsɝvɚ/, virtual /ˈvɜɹt͡ʃuəl/, retrieve /ɹɪˈtɹiːv/, involve /ɪnˈvɑlv/, dive /daɪv/
- 词尾辅音 — 要读清楚，后面不要加元音: cache /kæʃ/, disk /dɪsk/, database /ˈdeɪtəˌbeɪs/, fetch /fɛt͡ʃ/, technique /tɛkˈniːk/
- /r/ 和 /l/ 的区别: virtual /ˈvɜɹt͡ʃuəl/, translation /tɹænzˈleɪʃən/, crucial /ˈkɹuː.ʃəl/, translate /tɹænzˈleɪt/, prevalent /ˈpɹɛvələnt/
如何用这段视频练习
- 先完整听一遍视频，不要开口，记下不认识的单词。
- 用正常速度逐句跟读，每句重复到你的节奏与说话人一致为止。
- 录下自己的声音并与原声对比，特别注意 cache, server, disk 这类单词。
什么是跟读法？
跟读法 (Shadowing) 是一种有科学依据的语言学习技巧，最初开发用于专业口译员的培训，并由多语言者Alexander Arguelles博士普及。这个方法简单而强大：您在听英语母语原声的同时立即大声重复——就像是一个延迟1-2秒紧跟说话者的影子。与被动听力或语法练习不同，跟读法强迫您的大脑和口腔肌肉同时处理并模仿真实的讲话模式。研究表明它能显着提高发音准确性，语调，节奏，连读，听力理解和口语流利度——使其成为雅思口语备考和真实英语交流最有效的方法之一。