Luyện nói tiếng Anh bằng Shadowing qua video: MySQL took 21 years to fix this bug
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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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- “to avoid a ticket without looking like you are avoiding it”: Đây là một cách nói điển hình để mô tả sự khéo léo trong việc né tránh trách nhiệm. Bạn có thể áp dụng cấu trúc này khi nói về những cách xử lý khéo léo trong môi trường làm việc.
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- “avoiding”: Từ này dễ bị phát âm sai. Hãy chú ý đến cách nhấn âm và giữ cho âm "d" rõ ràng ở cuối.
- “cascade”: Chú ý cách phát âm từ này với âm "c" và "k", không để lẫn lộn với các âm tương tự.
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