Pratique du Shadowing: CAP Theorem Simplified - Apprendre l'anglais à l'oral avec la vidéo
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What is CAP theorem?
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How useful is it to system design?
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Let's take a look.
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The CAP theorem is a concept in computer science that explains the trade-offs between consistency,
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availability, and partition tolerance in distributed systems.
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Consistency refers to the property of a system where all nodes have a consistent view of the data.
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It means all clients see the same data at the same time,
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no matter which node they connect to.
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Availability refers to the ability of a system to respond to requests from users at all times.
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Partition tolerance refers to the ability of a system to continue operating even if there is a network partition.
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But what is a network partition?
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A network partition happens when nodes in a distributed system are unable to communicate with each other due to network failures.
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When there is a network partition,
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a system must choose between consistency and availability.
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If the system prioritizes consistency,
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it may become unavailable until the partition is resolved.
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If the system prioritizes availability,
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it may allow updates to the data.
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This could result in data inconsistencies until the partition is resolved.
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Now let's go through a concrete example.
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Let's say we have a tiny bank with two ATMs connected over the network.
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The ATM supports three operations,
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deposit, withdrawal, and check balance.
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No matter what happens, the balance should never go below zero.
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There is no central database in this bank to keep the account balance.
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It is stored on both ATMs.
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When a customer uses an ATM,
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the balance is updated on both ATMs over the network.
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This ensures that the ATMs have a consistent view of the account balance.
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If there is a network partition and the ATMs are unable to communicate with each other,
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the system must choose between consistency and unavailability.
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If the bank prioritizes consistency,
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the ATM may refuse to process deposits or withdrawals until the partition is resolved.
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This ensures that the balance remains consistent,
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but the system is unavailable to customers.
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If the bank prioritizes availability,
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the ATM may allow deposits and withdrawals to occur,
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but the balance may become inconsistent until the partition is resolved.
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When there is a network partition,
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the customer could withdraw the entire balance from both ATMs.
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When the network comes back online,
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the inconsistency is resolved and now the balance is negative.
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That is not good.
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Now let's go through another example and see how a social media platform could apply the cap theorem.
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During a network partition, if two users are commenting on the same post at the same time,
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one user's comment may not be visible to the other users until the partition is resolved.
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Alternatively, if the platform prioritizes consistency,
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the commenting feature may be unavailable to users until the partition is resolved.
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For a social network,
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it is often acceptable to prioritize availability at the cost of users seeing slightly different views some of the time.
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The CAP theorem may sound very simple,
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but the real world is messy.
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As with many things in software engineering,
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this is all about trade-offs,
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and the choices are not always so black and white.
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The CAPS theorem assumes 100% availability or 100% consistency.
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In the real world, there are degrees of consistency and availability that distributed system designers must carefully consider.
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This is where the simplistic model of the CAPS theorem could be misleading.
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Back to the bank example.
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a network partition, the ATM could allow only balanced inquiries to be processed while deposits and withdrawals are blocked.
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Alternatively, the bank could implement a hybrid approach.
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For example, the ATM could allow balanced inquiries and small withdrawals to be processed during a partition,
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but block large withdrawals and or deposits until the partition is resolved.
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It is worth noting that in the real world,
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reconciliation after a network partition could get very messy.
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The bank example above is simple to reconcile.
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In real life, the data structures involved could be complex and challenging to reconcile.
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A good example of a complex data structure is Google Docs.
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Resolving conflicting updates could be tricky.
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So is the CAT theorem useful?
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Yes, it is a useful tool to help us think through the high-level trade-offs to consider when there is a network partition.
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This is a good starting point,
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but it does not provide a complete picture of the trade-offs to consider when designing a well-rounded distributed system.
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Specifically, when the system is operating normally without a network failure,
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which is most of the time,
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there is an entire set of interesting trade-offs to consider between latency and consistency.
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This is covered by the Pakel theorem,
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which we should cover in another video.
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If you would like to learn more about system design,
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check out our books and weekly newsletter.
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Please subscribe if you learned something new.
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Thank you so much and we'll see you next time.
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Vocabulaire et conseils d’expression pour cette leçon
Cette vidéo contient 82 phrases et 820 mots à répéter en shadowing. La partie parlée dure 5:23. Le locuteur parle à un rythme naturel d’environ 152 mots par minute, proche d’une conversation courante. Seuls 75 % des mots font partie des 3 000 mots les plus courants en anglais, le vocabulaire est donc exigeant.
Vocabulaire clé de cette vidéo
15 mots de la vidéo à retenir, avec leur prononciation et leur sens :
| Mot | Prononciation | Sens |
|---|---|---|
| resolve verbe | /ɹɪˈzɑlv/ | résoudre |
| availability nom | /əˌveɪ.ləˈbɪl.ɪ.ti/ | disponibilité |
| theorem nom | /ˈθiərəm/ | théorème |
| withdrawal nom | /wɪðˈdɹɔ(ə)l/ | retrait |
| deposit nom | /dɪˈpɑ.zɪt/ | dépôt, gisement |
| distribute verbe | /dɪˈstɹɪbjuːt/ | distribuer |
| consistent adjectif | /kənˈsɪs.tənt/ | constant |
| refer verbe | /ɹɪˈfɜː/ | référer |
| unavailable adjectif | /ˌʌnəˈveɪləbəl/ | indisponible |
| connect verbe | /kəˈnɛkt/ | accoupler, connecter |
| inquiry nom | /ɪnˈkwaɪ(ə)ɹi/ | enquête |
| communicate verbe | /kəˈmjuːnɪkeɪt/ | communiquer |
| tolerance nom | /ˈtɑ.lə.ɹəns/ | tolérance |
| messy adjectif | /ˈmɛsi/ | désordonné, désorganisé |
| occur verbe | /əˈkɜː/ | se produire, avoir lieu |
Les verbes à particule que vous entendrez
| Mot | Sens |
|---|---|
| go through verbe | traverser |
| check out verbe | mater, regarder |
| come back verbe | revenir |
Prononciation à surveiller
- Les sons « th »: theorem /ˈθiərəm/, withdrawal /wɪðˈdɹɔ(ə)l/, withdraw /wɪðˈdɹɔ/
- Les sons « sh » et « zh »: partition /pɑɹˈtɪ.ʃən/, reconciliation /ˌɹɛkənˌsɪliˈeɪʃ(ə)n/
- Mots longs — placez bien l’accent: consistency /kənˈsɪs.tən.si/, availability /əˌveɪ.ləˈbɪl.ɪ.ti/, unavailable /ˌʌnəˈveɪləbəl/, inquiry /ɪnˈkwaɪ(ə)ɹi/, communicate /kəˈmjuːnɪkeɪt/
Comment s’entraîner avec cette vidéo
- Écoutez la vidéo en entier une fois sans parler et notez les mots que vous ne connaissez pas.
- Commencez à la vitesse 0,75×, répétez phrase par phrase, puis revenez à la vitesse normale quand cela devient facile.
- Enregistrez-vous et comparez avec l’original, en faisant attention à des mots comme resolve, availability, theorem.
Qu'est-ce que la technique du Shadowing ?
Le Shadowing est une technique d'apprentissage des langues fondée sur la science, développée à l'origine pour la formation des interprètes professionnels. Le principe est simple mais puissant : vous écoutez de l'anglais natif et le répétez immédiatement à voix haute — comme une ombre suivant le locuteur avec un décalage de 1 à 2 secondes. Les recherches montrent une amélioration significative de la précision de la prononciation, de l'intonation, du rythme, des liaisons, de la compréhension orale et de la fluidité.