Shadowing Practice: Top 5 Redis Use Cases - Learn English Speaking with Video
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In this video, we discover the versatility of Redis.
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We'll talk about the top use cases that have been better tested in production at various companies and at various scales.
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Get insights into how Redis solves interesting scalability challenges for us
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and learn why it is a great tool to know well in our system design toolset.
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Let's dive right into it.
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First of all, what is Redis and why do people use it?
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Redis is an in -memory data structure store.
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It is most commonly used as a cache.
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It supports many data structures such as strings, hashes, lists, sets, and sorted sets.
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Redis is known for its speed.
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We made a video to explain why Redis is so fast.
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Look for the link in the description if you would like to watch that video.
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Now let's dive into the top use cases of Redis.
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The number one use case of Redis is caching objects to speed up web applications.
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In this use case, Redis stores frequently requested data in memory.
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It allows the web servers to return frequently accessed data quickly.
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This reduces the load on the database and improves the response time for the application.
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At scale, the cache is distributed among a cluster of Redis servers.
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Sharding is a common technique to distribute and caching load evenly across the cluster.
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Other topics to consider when deploying Redis as a distributed cache include setting a correct TTL
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and handling thundering hurt on cold start.
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Another common use case is to use Redis as a session store to share session data among stateless servers.
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When a user logs into a web application, the session data is stored in Redis,
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along with a unique session ID that is returned to the client as a cookie.
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When a user makes a request to the application, the session ID is included in the request,
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and the stateless web server retrieves the session data from Redis using the ID.
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It is important to note that Redis is an in -memory database.
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The session data stored in Redis will be lost if the Redis server restarts.
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Even though Redis provides persistent options like a snapshot and AOF or append -only file,
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they allow session data to be saved to disk and reloaded into memory in the event of a restart.
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These options often take too long to load to be practical.
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In production, replication is usually used instead.
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In this case, data is replicated to a backup instance.
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In the event of a crash of the main instance, the backup instance is quickly promoted to take over the traffic.
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The next use case is distributed log.
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Distributed logs are used when multiple nodes in an application need to coordinate access to some shared resource.
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Redis is used as a distributed log with its atomic commands like set -nx or set -if -not -exists.
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It allows a caller to set a key only if it does not already exist.
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Here's how it works at a high level.
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Client 1 tries to acquire the log by setting a key with a unique value
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and a timeout using the set -nx command.
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If the key was not already set, the set -nx command returns 1, indicating that the log has been acquired by client 1.
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Client 1 finishes its work and releases the log by deleting the key.
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Now if the key was already set, the set -annex command returns 0, indicating that the log has already been held by another client.
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In this case, client 1 waits and retries the set -annex operation until the log is released by the other client.
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Note that this simple implementation might be good enough for many use cases, but it is not completely fault -tolerant.
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For production use, there are many Redis client libraries that provide high -quality distributed log implementation built right off the box.
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Next up is Ray Limiter.
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Redis can be used as a Ray Limiter by using its increment command on some counters
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and setting expiration times on those counters.
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A very basic
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Ray Limiting algorithm works this way.
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For each incoming request, the request IP or user ID is used as a key.
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The number of requests for the key is incremented using the increment command in Redis.
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The current count is compared to the allowed rate limit.
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If the count is within the rate limit, the request is processed.
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If the count is over the limit, the request is rejected.
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The keys are set to expire after a specific time window, for example, a minute, to reset the cans for the next time window.
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More sophisticated rate limiters, like the leaky bucket algorithm, can also be implemented using Redis.
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The last use case we would like to talk about is gaming leaderboard.
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For most games that are not super high scale, Redis is a delightful way to implement various types of gaming leaderboards.
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Sort of sets are the fundamental data structure that enables this.
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A sort of set is a collection of unique elements, each with a score associated with it.
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The elements are sorted by score.
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This allows for quick retrieval of the elements by score in logarithmic time.
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That's it for our top Redis use cases.
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Redis is very versatile.
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There are many different ways to use it.
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Some features are more better tested than others.
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Our creativity is the limit.
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Use it with care and have fun with it.
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You would like our videos.
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You may like our weekly system design newsletter as well.
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It covers topics and trends in large -scale system design, trusted by 200 ,000 readers.
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Vocabulary and speaking notes for this lesson
This speaking lesson is built on the video “Top 5 Redis Use Cases”. The speaker keeps coming back to these words: Redis, log, client, session, key. This video has 75 sentences and 937 words to shadow. The speech runs for 6:16. The speaker talks at a steady 149 words per minute, a comfortable pace for shadowing. Only 77% of the words are among the 3,000 most common in English, so the vocabulary is demanding.
Key vocabulary in this video
15 words from the video worth learning, with pronunciation and meaning:
| Word | Pronunciation | Meaning |
|---|---|---|
| distribute verb | /dɪˈstɹɪbjuːt/ | To divide into portions and dispense. |
| server noun | /ˈsɝvɚ/ | A program that provides services to other programs or devices, either in the same computer or over a computer network. |
| cache noun | /kæʃ/ | Such a store of physical supplies, placed by humans or other animals for practical reasons. |
| element noun | /ˈɛləmənt/ | One of the simplest or essential parts or principles of which anything consists, or upon which the constitution or fundamental powers of anything are based. |
| topic noun | /ˈtɑpɪk/ | A subject; a theme; a category or general area of interest. |
| log noun | /lɔɡ/ | The trunk of a dead tree, cleared of branches. |
| indicate verb | /ˈɪndɪˌkeɪt/ | To point out; to discover; to direct to a knowledge of; to show; to make known. |
| database noun | /ˈdeɪtəˌbeɪs/ | A collection of (usually) organized information in a regular structure, usually but not necessarily in a machine-readable format accessible by a computer. |
| 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… |
| backup noun | /ˈbækˌʌp/ | A reserve or substitute. |
| implement verb | /ˈɪmpləmənt/ | To bring about; to put into practice; to carry out. |
| acquire verb | /əˈkwaɪɚ/ | To get. |
| dive verb | /daɪv/ | To swim under water. |
| algorithm noun | /ˈælɡəɹɪðm̩/ | A collection of ordered steps that solve a mathematical problem. A precise step-by-step plan for a computational procedure that possibly begins with an input… |
| cluster noun | /ˈklʌstɚ/ | A bunch or group of several discrete items that are close to each other. |
Phrasal verbs you will hear
| Word | Pronunciation | Meaning |
|---|---|---|
| speed up verb | /spiːdˈʌp/ | To accelerate; to increase speed. |
| take over verb | To assume control of something, such as a business or enterprise, and sometimes by force. |
Grammar in this video
The structures the speaker uses most, with the exact words from the video:
| Structure | In the video |
|---|---|
| Passive voice be + past participle — the focus is on what happens, not who does it | is known · is distributed · is stored |
| Present perfect have/has + past participle — a past action that still matters now | have been · has been acquired · has already been held |
Pronunciation to watch
- The “th” sounds: algorithm /ˈælɡəɹɪðm̩/, thunder /ˈθʌndɚ/, logarithmic /ˌlɒɡəˈɹɪðmɪk/
- The “sh” and “zh” sounds: cache /kæʃ/, implementation /ˌɪmplɪmənˈteɪʃən/, associate /əˈsoʊʃi.ət/, hash /ˈhæʃ/, expiration /ˌɛk.spɚˈeɪ̯.ʃən/
- Long words — get the stress right: implementation /ˌɪmplɪmənˈteɪʃən/, associate /əˈsoʊʃi.ət/, fundamental /ˌfʌn.dəˈmɛn.təl/, creativity /kri.eɪˈtɪv.ᵻ.ti/, coordinate /koʊˈɔɹ.dəˌneɪt/
How to practise with this video
- Listen to the whole video once without speaking and note the words you do not know.
- Shadow it sentence by sentence at normal speed, repeating each one until your rhythm matches the speaker.
- Record yourself and compare with the original, paying attention to words like distribute, server, cache.
What is the Shadowing Technique?
Shadowing is a science-backed language learning technique originally developed for professional interpreter training and popularized by polyglot Dr. Alexander Arguelles. The method is simple but powerful: you listen to native English audio and immediately repeat it out loud — like a shadow following the speaker with just a 1–2 second delay. Unlike passive listening or grammar drills, shadowing forces your brain and mouth muscles to simultaneously process and reproduce real speech patterns. Research shows it significantly improves pronunciation accuracy, intonation, rhythm, connected speech, listening comprehension, and speaking fluency — making it one of the most effective methods for IELTS Speaking preparation and real-world English communication.