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we really need to talk about what do we mean by

an index very quick we added this concept of indexes

because of a problem

that we have in database systems you see we have regardless

of the way you store your data whether it's a relational table of columns and rows or documents or blob storage

this data is huge in your table you're going to have millions

and millions of rows in your documents you're going to have thousands

and thousands of documents in your blob stores you're going to

have these content these blob pictures videos whatever contiguous one of the other

but searching becomes interesting

because how do you find something in this pile of stuff you get a scan one by one

these million rows or thousands of document or tens

and thousands of these blob images which is obviously not ideal

because you have to loop one by one

and you have to visit apparently work with millions of rows to find what you're looking for

so so smart people found a way to eliminate working with millions of millions of rows

and instead work with as few

or rows as possible to find exactly what we're looking for

the the best solution to search billions of rows is to

avoid searching billions of rows right that's that's the best solution

so the trick here is to take shortcuts so indexes was well born

and there are many many types of indexes

that helps you you know find exactly what you're looking for

or at least narrow the search not exactly gives you one io or one cost bigger of one not necessarily

but it helps you you know narrow

that search that's the goal of an index

so regardless of the type of it is a b3 b

plus tree you know uh jest tree generalized search tree

or brand the goal is just let me work with as let me eliminate things

that is absolutely doesn't contain my results right just like concept of a bloom filter

so that's an index so i have an index

and you search this index so you still need to search

but it's a much much much smaller data structure compared to the millions of rows

that you have on your actual data blob store documents right

usually you keep we call this area the heap right the heap is a data structure where you just dump everything

ram it's just a dumping ground index is an optimized data structure

that helps you pick what column in your document

or on your row on your table and exactly index

that column and the goal is to give you give you a row sets right a sets of rows

that are candidate

that may give you the results after you search the index

you get a list of candidate results right could be one

or could be more you still in most situations you still

need to go to jump to the heap to the big table

which contains actual data and fetch the content

because the index will only have one column

or two right the heap will have everything in it

so you jump back but the index tells you exactly where to jump

and that is the trick here the index tells you hey jump to page 179

and pull row 73 in that page it tells you exactly

that right now it depends on the database the database is

sometimes does an additional filtering upon fetching the row itself

because there are situations where the row might have been deleted

but the index wasn't updated and and we need to see

if i'm supposed to see this row or not

so whether whether you're in a multi-version currency control or not so this is an index Cool.

Sounds like a good data structure, right?

Beautiful.

Let's always add an index.

Why not?

But careful with that.

What did we say?

We said that the index gives you a candidate rows so

that you go to the table and fetch exactly what you want.

Right?

Cool.

Keep that in mind.

Okay.

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Shadowing — это научно обоснованная техника изучения языка, изначально разработанная для подготовки профессиональных переводчиков и популяризированная полиглотом доктором Александром Аргуэльесом. Метод прост, но эффективен: вы слушаете аудио на английском от носителей языка и немедленно повторяете вслух — как тень, следующая за говорящим с задержкой в 1–2 секунды. В отличие от пассивного прослушивания или грамматических упражнений, Shadowing заставляет мозг и мышцы рта одновременно обрабатывать и воспроизводить реальные речевые паттерны. Исследования показывают, что это значительно улучшает точность произношения, интонацию, ритм, связную речь, понимание на слух и беглость речи — что делает его одним из самых эффективных методов для подготовки к IELTS Speaking и реального общения на английском.

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