跟读练习: MySQL took 21 years to fix this bug - 通过YouTube学习英语口语
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In my 16 years as a software developer,
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In my 16 years as a software developer,
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nothing made me happier than avoiding an annoying bug long enough for someone else to accidentally fix it,
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or for the entire feature to be removed before I ever had to touch that code.
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In fact, after years of hard work and dedication,
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I can proudly say that I have polished this skill to perfection.
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As some of the more experienced among you already know,
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avoiding a ticket without looking like you are avoiding a ticket is an art form.
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You cannot just ignore it,
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because that is amateur work.
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A seasoned senior software developer who earns their keep will occasionally comment something vague,
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like, I'll have to circle back to it when my priorities allow it,
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or this is a tough one,
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but I believe I'm finally close to a solution.
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Then, they let a little more time pass and hope for the best.
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And, hope, as you eventually learn,
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is basically at the core of software development.
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So when I tell you
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that the MySQL team avoided a single bug ticket for 21 years and somehow made it look almost professional,
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understand that I say this with deep, deep respect.
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When a bug is first reported in 2005,
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and you get to fix it in 2026,
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we should all sit down,
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take notes and learn a thing or two about surviving this industry.
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The bug in question is MySQL bug number 11472,
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filed on June 21st, 2005.
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To give you a sense of how long ago that was,
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the iPhone did not exist,
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the most popular browser on Earth was Internet Explorer 6
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and Sam Altman was busy creating a social network instead of convincing the world
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that AI tokens are as important as access to electricity or water.
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We see a future where intelligence is a utility,
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like electricity or water, and people buy it from us.
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Anyway, the reported bug was apparently pretty straightforward.
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Triggers were not firing when a foreign key cascade modified a row.
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For those unfamiliar with relational databases,
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a foreign key is basically a rule that says that this piece of data,
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like some orders, depends on some other piece of data, like a customer.
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Cascades, on the other hand,
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are what happen when the database automatically propagates a change through that relationship.
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So when you delete a customer,
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the database can be told to automatically delete that customer's orders for you.
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Now, there is a whole separate discussion about whether physically deleting records from a database is a bad practice,
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but that is not the topic of this video.
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Just keep in mind that in many cases,
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you are better off keeping the records in the database and using a soft delete instead,
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which simply means marking a row as deleted with a boolean flag.
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Back to the bug, when one of these automated cascade deletes happens,
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my SQL goes and removes the affected child rows for you,
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but it does it quietly.
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So quietly that the triggers attached to those rows have no idea anything happened.
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Triggers, if you have not run into them before,
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are little bits of code that you tell the database to run automatically whenever a specific event happens on a specific table.
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Again, there is an entire discussion on the topic of best practices
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when it comes to triggers and there is an ongoing fight about them in the industry.
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The modern application crowd will tell you triggers are invisible,
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untestable and a debugging nightmare
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and honestly they are not wrong a trigger does not show up in your git dev
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or in code review and a new developer joining your team might be surprised to find out
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that half the logic of your application is happening inside the database fired off by little scripts
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that nobody has looked at for the past 15 years also triggers do not translate
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when you migrate from one database to another because every database has its own slightly different trigger syntax.
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On the other hand, the database crowd,
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mostly old-school DBAs, will tell you
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that triggers are the only thing in your entire stack that catches every change to your data,
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no matter where it came from.
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If you have three different services,
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a cron job, and some random script all writing to the same database,
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only a trigger sees all the changes reliably.
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But enough with the boring theory,
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let's get back to the actual bug report.
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A few days after the initial report,
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the MySQL team says the plan is to fix it in their upcoming 5.1 release.
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Again, take notes, because this is the kind of confidence you guys need to succeed in this career.
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Then, a few days, sorry,
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a few years pass, and in 2007,
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a new comment from the team states that MySQL's own foreign key implementation will eventually fix this,
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but it will still take some time.
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Then, two years later, the confirmation that this bug will not be fixed in 5.1 is posted.
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In 2013, 8 years in,
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a user asks for an update.
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The official reply this time,
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and I want you to appreciate the craftsmanship here,
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says Note that there is major development work needed to fix this issue,
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it will not be a mere bug fix.
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At this point, the bug is starting to become somewhat of a meme because a user replies in the thread,
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the guys over at Oracle probably aren't getting any of these messages because their triggers aren't firing.
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This joke was funny for 13 years straight.
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It's important to note that during this time MySQL changed owners multiple times.
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It started as an open source database built by a small Swedish company.
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It was bought by Sun Microsystems in 2008 for $1 billion,
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which at the time felt like a lot of money.
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Then, in 2010, Oracle bought Sun and inherited MySQL together with the second best programming language in the world.
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And since we are talking about billions of dollars,
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Back to the video, by 2015,
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the comment section enters its second phase when users start showing up on the bug's birthday to leave congratulatory messages like,
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Happy Anniversary, it's 10 years already,
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this defect is going to be attending middle school in the fall and happy 13th birthday they grow up so fast.
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By 2020, we hit a third phase.
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A user writes, this bug is older than me.
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The original reporter, who filed a bug in 2005,
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gets pinged by someone asking if he's still alive
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and he shows up the next day to confirm he is still using MySQL.
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Now, jokes aside, the reason this bug took 21 years to fix is actually pretty interesting
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and it traces its roots in an architectural decision made in the late 90s
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that turned out to be very hard to walk back.
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To explain what happened, I need to tell you a little about how MySQL is built,
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because once you understand the structure,
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the whole bug starts to make sense.
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MySQL is built into layers.
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On top, you have what is called the SQL layer,
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sometimes also called the server layer.
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This is the part of MySQL that takes your queries,
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parses them, plans how to execute them,
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and then asks for the data.
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It is also the part that handles things like triggers,
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views, stored procedures and user permissions.
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Anything that thinks in terms of SQL statements lives here.
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Underneath, you have the storage engine.
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The storage engine is the part that actually reads and writes the bytes on disk.
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This component deals with pages, indexes, logs and transactions.
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My SQL is unusual because its storage engine is pluggable,
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which means you can swap it out,
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but for the past 15 years,
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everyone has been using InnoDB.
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Now, in most databases, foreign keys live in the SQL layer.
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This layer knows about the foreign key,
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this layer enforces it, and when a cascade fires,
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this is the layer that generates the cascade operation as if it were a normal SQL statement.
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As a result, triggers fire normally,
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because triggers are also a SQL layer concept.
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MySQL on the other hand implemented foreign keys inside the InnoDB storage engine.
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The reason is historical and this is also your awesome trivia for the day.
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Early versions of MySQL did not support foreign keys at all.
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The MySQL team famously did not really believe in them
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and you can actually find a page in their version 3 manual titled Reasons not to use foreign keys.
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Their arguments age like milk.
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The first reason they mentioned in the manual is
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that foreign keys make life very complicated because the foreign key definitions must be stored in a database.
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The second reason was that foreign keys are slow and unnecessary and you,
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the developer, will simply remember to insert records in the right order.
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So when they finally added foreign key support,
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they bolted it onto InnoDB,
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because InnoDB was the only engine at the time that supported transactions.
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The SQL layer was never involved,
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so foreign keys became strictly an InnoDB feature.
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So when you run a query such as this one,
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here is what actually happens step by step.
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The SQL layer parses your query,
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it fires the before delete trigger if it exists,
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then it hands the actual delete operation to InnoDB.
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InnoDB then notices, on its own,
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that there is a foreign key with onDelete cascade pointing at the orders table.
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So it walks the orders table,
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finds all the orders that belong to that customer and deletes them itself right there in the storage engine.
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But then, the engine never bubbles back up to the SQL layer to notify it about the additional deletions.
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So the SQL layer, sitting up there with all the triggers,
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is perfectly willing to fire them,
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waiting for someone to tell it that rows on the orders table have changed.
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This was the issue, and as you can see,
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this is what the MySQL team meant in 2013,
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when they wrote that this was not a mere bug fix,
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but major development work.
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The two systems that need to talk to each other are architecturally separated.
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And to finally fix the problem,
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the team did the thing they had been putting off for 21 years.
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They moved foreign keys out of InnoDB and up into the SQL layer.
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If you liked this video,
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you should consider joining our community where I'm posting more dedicated weekly content.
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Please don't forget to smash all the buttons and until next time,
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thank you for watching.
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背景及上下文
在這段視頻中，一位經驗豐富的軟體開發者分享了自己在職業生涯中的一個有趣經歷，他提到了一個存在了21年的MySQL錯誤。這位講者在軟體開發領域有16年的經歷，並且認為避開麻煩的錯誤是一種卓越的技能。他幽默地表示，藉由讓別人不小心修正錯誤，或是在該功能被移除之前從未接觸到相關代碼，令自己感到非常愉快。這段對話不僅展現了技術圈的幽默，也引發了對問題管理和開發流程的思考。
日常交流的前五個短語
- 我需要再思考一下。 (I need to circle back to it.)
- 這個問題很棘手。 (This is a tough one.)
- 我相信我已經接近解決方案。 (I believe I'm finally close to a solution.)
- 希望一切能有好的結果。 (Hope for the best.)
- 我會再檢查這個問題。 (I'll check back on this issue.)
這些短語不僅在工作中常用，還可以在雅思口語練習中作為非常實用的口語表達，有助於英語口語練習者在不同情境下流利地交流。
逐步影子跟讀指南
要有效利用這段視頻進行英语影子跟读，您可以按照以下步驟操作：
- 觀看視頻：首先，完整觀看視頻以理解講者的語氣和表達方式。
- 分段跟讀：將視頻分成小段，每次集中於1-2句話，觀看並聽取之後重複。
- 聽寫練習：在聽到講者時，嘗試記下關鍵詞和短語，幫助您記憶並提升反應能力。
- 模仿口音：專注於模仿講者的口音、語調和停頓，這將增強您的語言表達能力。
- 反思和改進：在練習後，回顧自己所錄下的音頻，尋找改進的空間，這有助於提高您的口語流利度。
運用這些技巧，您將能夠增強自己的shadow speech能力，提升雅思口語練習成效，讓英語口語練習變得更加高效有趣！
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。