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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Bu dersin kelimeleri ve konuşma notları
Bu konuşma dersi “Top 5 Redis Use Cases” videosuna dayanıyor. En çok tekrarlanan kelimeler: Redis, log, client, session, key. Bu videoda gölgeleme çalışması için 75 cümle ve 937 kelime var. Konuşma bölümü 6:16 sürüyor. Konuşmacı dakikada yaklaşık 149 kelimelik dengeli bir hızla konuşuyor; gölgeleme için rahat bir tempo. Kelimelerin yalnızca %77’i İngilizcede en sık kullanılan 3.000 kelime arasında, bu yüzden kelime dağarcığı zorlayıcı.
Bu videodaki önemli kelimeler
Videodan öğrenmeye değer 15 kelime, telaffuzu ve anlamıyla:
| Kelime | Telaffuz | Anlam |
|---|---|---|
| distribute fiil | /dɪˈstɹɪbjuːt/ | dağıtmak, paylaştırmak |
| server isim | /ˈsɝvɚ/ | sunucu, server |
| cache isim | /kæʃ/ | önbellek |
| element isim | /ˈɛləmənt/ | öğe, eleman |
| topic isim | /ˈtɑpɪk/ | mevzu, tema |
| log isim | /lɔɡ/ | kütük |
| indicate fiil | /ˈɪndɪˌkeɪt/ | belirtmek, göstermek |
| database isim | /ˈdeɪtəˌbeɪs/ | veritabanı, veri tabanı |
| implementation isim | /ˌɪmplɪmənˈteɪʃən/ | tatbik (obsolecent), uygulama |
| implement fiil | /ˈɪmpləmənt/ | tatbik etmek, uygulamak |
| acquire fiil | /əˈkwaɪɚ/ | edinmek |
| dive fiil | /daɪv/ | dalmak |
| algorithm isim | /ˈælɡəɹɪðm̩/ | algoritma |
| cluster isim | /ˈklʌstɚ/ | salkım |
| technique isim | /tɛkˈniːk/ | teknik |
Duyacağınız deyimsel fiiller
| Kelime | Telaffuz | Anlam |
|---|---|---|
| speed up fiil | /spiːdˈʌp/ | hızlanmak, hızlandırmak |
Bu videodaki dil bilgisi
Konuşmacının en çok kullandığı yapılar, videodaki sözcüklerin aynısıyla:
| Yapı | Videoda |
|---|---|
| Edilgen yapı be + fiilin üçüncü hâli — kimin yaptığı değil, ne olduğu önemli | is known · is distributed · is stored |
| Present perfect have/has + fiilin üçüncü hâli — geçmişte olan ama şimdi de önemli olan bir eylem | have been · has been acquired · has already been held |
Dikkat edilecek telaffuzlar
- “th” sesleri: algorithm /ˈælɡəɹɪðm̩/, thunder /ˈθʌndɚ/, logarithmic /ˌlɒɡəˈɹɪðmɪk/
- “sh” ve “zh” sesleri: cache /kæʃ/, implementation /ˌɪmplɪmənˈteɪʃən/, associate /əˈsoʊʃi.ət/, hash /ˈhæʃ/, expiration /ˌɛk.spɚˈeɪ̯.ʃən/
- Uzun kelimeler — vurguyu doğru yere koyun: implementation /ˌɪmplɪmənˈteɪʃən/, associate /əˈsoʊʃi.ət/, fundamental /ˌfʌn.dəˈmɛn.təl/, creativity /kri.eɪˈtɪv.ᵻ.ti/, coordinate /koʊˈɔɹ.dəˌneɪt/
Türkçe konuşanların zorlandığı sesler:
- Kelime başındaki ünsüz kümesi — araya ünlü eklemeyin: cluster /ˈklʌstɚ/, practical /ˈpɹæk.tɪ.kəl/, string /stɹɪŋ/, creativity /kri.eɪˈtɪv.ᵻ.ti/, newsletter /ˈn(j)uzˌlɛtɚ/
- /æ/ — “e”den daha açık: cache /kæʃ/, backup /ˈbækˌʌp/, algorithm /ˈælɡəɹɪðm̩/, practical /ˈpɹæk.tɪ.kəl/, hash /ˈhæʃ/
- /ŋ/ — sondaki /g/ okunmaz: string /stɹɪŋ/, incoming /ˈɪnˌkʌmɪŋ/
Bu videoyla nasıl çalışılır
- Videonun tamamını konuşmadan bir kez dinleyin ve bilmediğiniz kelimeleri not edin.
- Normal hızda cümle cümle tekrar edin; ritminiz konuşmacıyla aynı olana kadar her cümleyi yineleyin.
- Kendinizi kaydedin ve orijinaliyle karşılaştırın; distribute, server, cache gibi kelimelere özellikle dikkat edin.
Gölgeleme Tekniği Nedir?
Gölgeleme, başlangıçta profesyonel tercüman eğitimi için geliştirilen ve çok dilli Dr. Alexander Arguelles tarafından popüler hale getirilen, bilim destekli bir dil öğrenme tekniğidir. Yöntem basit ama güçlüdür: ana dili İngilizce olan bir sesi dinler ve hemen yüksek sesle tekrar edersiniz — konuşmacıyı 1-2 saniye gecikmeyle takip eden bir gölge gibi. Pasif dinleme veya dilbilgisi alıştırmalarının aksine, gölgeleme beyninizi ve ağız kaslarınızı gerçek konuşma kalıplarını eşzamanlı olarak işlemeye ve yeniden üretmeye zorlar. Araştırmalar, telaffuz doğruluğu, tonlama, ritim, bağlı konuşma, dinleme anlama ve konuşma akıcılığını önemli ölçüde geliştirdiğini göstermektedir — bu da onu IELTS Konuşma hazırlığı ve gerçek dünya İngilizce iletişimi için en etkili yöntemlerden biri yapar.