쉐도잉 연습: Top 5 Redis Use Cases - 영상으로 영어 말하기 배우기

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In this video, we discover the versatility of Redis.

We'll talk about the top use cases that have been better tested in production at various companies and at various scales.

Get insights into how Redis solves interesting scalability challenges for us

and learn why it is a great tool to know well in our system design toolset.

Let's dive right into it.

First of all, what is Redis and why do people use it?

Redis is an in -memory data structure store.

It is most commonly used as a cache.

It supports many data structures such as strings, hashes, lists, sets, and sorted sets.

Redis is known for its speed.

We made a video to explain why Redis is so fast.

Look for the link in the description if you would like to watch that video.

Now let's dive into the top use cases of Redis.

The number one use case of Redis is caching objects to speed up web applications.

In this use case, Redis stores frequently requested data in memory.

It allows the web servers to return frequently accessed data quickly.

This reduces the load on the database and improves the response time for the application.

At scale, the cache is distributed among a cluster of Redis servers.

Sharding is a common technique to distribute and caching load evenly across the cluster.

Other topics to consider when deploying Redis as a distributed cache include setting a correct TTL

and handling thundering hurt on cold start.

Another common use case is to use Redis as a session store to share session data among stateless servers.

When a user logs into a web application, the session data is stored in Redis,

along with a unique session ID that is returned to the client as a cookie.

When a user makes a request to the application, the session ID is included in the request,

and the stateless web server retrieves the session data from Redis using the ID.

It is important to note that Redis is an in -memory database.

The session data stored in Redis will be lost if the Redis server restarts.

Even though Redis provides persistent options like a snapshot and AOF or append -only file,

they allow session data to be saved to disk and reloaded into memory in the event of a restart.

These options often take too long to load to be practical.

In production, replication is usually used instead.

In this case, data is replicated to a backup instance.

In the event of a crash of the main instance, the backup instance is quickly promoted to take over the traffic.

The next use case is distributed log.

Distributed logs are used when multiple nodes in an application need to coordinate access to some shared resource.

Redis is used as a distributed log with its atomic commands like set -nx or set -if -not -exists.

It allows a caller to set a key only if it does not already exist.

Here's how it works at a high level.

Client 1 tries to acquire the log by setting a key with a unique value

and a timeout using the set -nx command.

If the key was not already set, the set -nx command returns 1, indicating that the log has been acquired by client 1.

Client 1 finishes its work and releases the log by deleting the key.

Now if the key was already set, the set -annex command returns 0, indicating that the log has already been held by another client.

In this case, client 1 waits and retries the set -annex operation until the log is released by the other client.

Note that this simple implementation might be good enough for many use cases, but it is not completely fault -tolerant.

For production use, there are many Redis client libraries that provide high -quality distributed log implementation built right off the box.

Next up is Ray Limiter.

Redis can be used as a Ray Limiter by using its increment command on some counters

and setting expiration times on those counters.

A very basic

Ray Limiting algorithm works this way.

For each incoming request, the request IP or user ID is used as a key.

The number of requests for the key is incremented using the increment command in Redis.

The current count is compared to the allowed rate limit.

If the count is within the rate limit, the request is processed.

If the count is over the limit, the request is rejected.

The keys are set to expire after a specific time window, for example, a minute, to reset the cans for the next time window.

More sophisticated rate limiters, like the leaky bucket algorithm, can also be implemented using Redis.

The last use case we would like to talk about is gaming leaderboard.

For most games that are not super high scale, Redis is a delightful way to implement various types of gaming leaderboards.

Sort of sets are the fundamental data structure that enables this.

A sort of set is a collection of unique elements, each with a score associated with it.

The elements are sorted by score.

This allows for quick retrieval of the elements by score in logarithmic time.

That's it for our top Redis use cases.

Redis is very versatile.

There are many different ways to use it.

Some features are more better tested than others.

Our creativity is the limit.

Use it with care and have fun with it.

You would like our videos.

You may like our weekly system design newsletter as well.

It covers topics and trends in large -scale system design, trusted by 200 ,000 readers.

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이 레슨의 어휘와 말하기 포인트

이 말하기 레슨은 영상 “Top 5 Redis Use Cases”을(를) 바탕으로 합니다. 가장 자주 반복되는 단어는 다음과 같습니다: Redis, log, client, session, key. 이 영상에는 섀도잉할 문장 75개와 단어 937개가 있습니다. 말하는 구간의 길이는 6:16입니다. 화자는 분당 약 149단어의 일정한 속도로 말해서 섀도잉하기에 편한 속도입니다. 영어에서 가장 많이 쓰이는 3,000단어에 속하는 단어가 77%뿐이라 어휘가 어려운 편입니다.

이 영상의 핵심 어휘

영상에 나오는 익혀 둘 만한 단어 15개를 발음, 뜻과 함께 정리했습니다.

단어	발음	뜻
server 명사	/ˈsɝvɚ/	서버, 봉사기
cache 명사	/kæʃ/	캐시
element 명사	/ˈɛləmənt/	요소
topic 명사	/ˈtɑpɪk/	화제, 주제
log 명사	/lɔɡ/	통나무
indicate 동사	/ˈɪndɪˌkeɪt/	가리키다
database 명사	/ˈdeɪtəˌbeɪs/	데이터베이스
implementation 명사	/ˌɪmplɪmənˈteɪʃən/	이행
backup 명사	/ˈbækˌʌp/	백업
acquire 동사	/əˈkwaɪɚ/	획득하다
dive 동사	/daɪv/	잠수하다
algorithm 명사	/ˈælɡəɹɪðm̩/	알고리즘, 알고리듬
practical 형용사	/ˈpɹæk.tɪ.kəl/	실질적인
technique 명사	/tɛkˈniːk/	기술
compare 동사	/kəmˈpɛɚ/	비교하다, 비유하다

이 영상의 문법

화자가 가장 많이 쓰는 문형을 영상 속 실제 표현과 함께 정리했습니다.

문형	영상 속 표현
수동태 be + 과거분사 — 누가 하는지보다 무슨 일이 일어나는지에 초점	is known · is distributed · is stored
현재완료 have/has + 과거분사 — 과거의 일이 지금도 관련이 있을 때	have been · has been acquired · has already been held

주의할 발음

“th” 소리: algorithm /ˈælɡəɹɪðm̩/, thunder /ˈθʌndɚ/, logarithmic /ˌlɒɡəˈɹɪðmɪk/
“sh”와 “zh” 소리: cache /kæʃ/, implementation /ˌɪmplɪmənˈteɪʃən/, associate /əˈsoʊʃi.ət/, hash /ˈhæʃ/, expiration /ˌɛk.spɚˈeɪ̯.ʃən/
긴 단어 — 강세 위치에 주의: implementation /ˌɪmplɪmənˈteɪʃən/, associate /əˈsoʊʃi.ət/, fundamental /ˌfʌn.dəˈmɛn.təl/, creativity /kri.eɪˈtɪv.ᵻ.ti/, coordinate /koʊˈɔɹ.dəˌneɪt/

한국어 화자가 어려워하는 소리:

/f/ — ㅍ(/p/)으로 바꾸지 말고 윗니를 아랫입술에 대기: fundamental /ˌfʌn.dəˈmɛn.təl/, delightful /dəˈlaɪt.fl̩/
/v/ — ㅂ(/b/)과 구별하기: server /ˈsɝvɚ/, dive /daɪv/, solve /sɒlv/, discover /dɪˈskʌvə/, creativity /kri.eɪˈtɪv.ᵻ.ti/
/z/ — ㅈ이 아니라 성대를 울리는 /s/: resource /ɹɪˈzɔːs/, newsletter /ˈn(j)uzˌlɛtɚ/

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, server, cache, element 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.

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쉐도잉 연습: Top 5 Redis Use Cases - 영상으로 영어 말하기 배우기

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