After brushing the 12 sliding windows, you can tear the front end by hand

Kitchen ape gaga 2021-09-15 06:28:50
brushing sliding windows tear end


Preface

People often ask , As front-end , What algorithms have you used in your actual work , My answer was , Tree and bit operations , Recently, I am learning the network module , Found and front end , At least an algorithm related to the network , That's it The sliding window ;

We know that HTTP1.1 Send a request ,TCP The request will be transmitted to the server , And for TCP agreement , One of the most important capabilities is to control the flow rate ;

When the sender needs to send many requests , These requests will block waiting in a cache TCP send out , This is followed by a steady stream of requests , Then you can't plug it all in the cache at once , It'll blow up , At this time, the model is a sliding window

image.png

The sending process has three states :

  • Green is the of sending and connecting successfully
  • Light green is sending , But I haven't received ACK Responsive , It's possible to hang up at this time , So at this time, the sender must keep the request and be ready to resend it at any time
  • White is waiting to be sent
  • The latter are blocked requests

This is the time TCP The number of requests that can be cached is a window , Whenever light green turns dark green , Then the window can slide on the right , The state that the window still retains can still be reused , This is it. The sliding window The charm of

The biggest feature of sliding window is , During sliding window , The data state retained in the window is directly reused , No need to build again , Saving resource ;

Then let's get familiar with a slide window by doing questions , And see if there are more different situations ;

Drain  

Finish this 20 A dichotomy , Maybe you can't tear your hands off a big factory interview

Finish these questions , Maybe you can't tear your hands off a big factory interview

Finish this 30 The problem of Dao tree , Maybe you can't tear your hands off a big factory interview

Finish this 20 List questions , Maybe you can't tear your hands off a big factory interview

Finish this 15 Avenue dp topic , I can only take a chance to enter the big factory

Finish this A few Trace bit operation , Wait and consider the interview with a big factory -- Failed the audit , We'll do it later

Text

Depending on whether the sliding window size is fixed , There are two kinds of : Fixed size window and Variable window size ;

The preface talks about TCP Sliding window in , It's actually a fixed size sliding window , Of course, you can also give a part size first , Then expand according to the flow rate , That's the follow-up operation ;

More often, sliding windows of variable size , This kind of sliding window is generally created in the process , A brain runs out of resources to expand the window , Reaching a threshold , Then shrink the window , According to the specific topic , Reached a balance ;

It's like a quick trial and error process , First push the situation to the extreme , Then add the corresponding variable to shrink the window , Find a more suitable situation , Wait until the compliance situation breaks in the window , Just re expand ;

Sliding window is actually understanding the meaning of the question , It's a little split in two , That is, I can cut the state in the window from the state outside the window , But they are shift The relationship between , So keep weighing , Reach a state of dynamic balance , Is the result of some questions

Templates

Fixed size window

  • l Initialize to 0
  • initialization r, bring r-l+1 Is the window size
  • Move at the same time l and r
  • Judge whether the continuous elements in the window meet the conditions of the topic

Variable window size

  • l r All initialized to 0
  • r Move the pointer one step
  • Judge whether the continuous elements in the window meet the conditions
    • Satisfy , Then judge whether it is necessary to update the optimal solution ; Update... If necessary , And try to move l The pointer reduces the size of the window
    • dissatisfaction , Continued to

Double sliding window phenomenon

  • Ordinary sliding windows always go first r The pointer , Then the trigger condition is reached , And then contract l The pointer , Stop after the contraction fails to meet the standard , then r Pointer restart
  • But there are some problems , When r After the pointer reaches the standard , l The pointer is within a range [l1,l2), And may be related to subsequent [r1,r2) Any sliding window consisting of two pointers will constitute a compliant sliding window
  • Then use a single pointer at this time l Shrink to unsatisfactory l2, Then only [l1,l2) And r1 Conditions , And what should have been compliant lx-rx All killed (lx stay [l1,l2] in ), Because at this time l Has run to l2 It's too late
  • At this time, you need to open two pointers l1, l2 , Fixed every time r When the pointer , Let's find the first one that meets the requirements l1, And cut-off position l2, Then continue to let r go , Always keep two sliding windows during movement [l1.r],[l2,r], It can ensure that all situations are taken into account in the whole movement process
  • This kind of problem is to seek quantity , For example How many subarrays are there in a certain case , So you have to get everything out , But if only an extreme value is required , For example, in these cases that meet the requirements , What's the minimum , Then there's no need to use double sliding windows , because r The movement of the pointer will certainly enlarge the window , therefore l The pointer only needs to keep the corresponding extreme value ( First or last ), Then find the extreme value

The matching title is 930. And the same binary subarray

992. K Sub array of different integers

1248. Statistics 「 Graceful subarray 」

Last

Sliding window is a special case of double pointer , When we use double pointers to deal with problems , The status value in the previous window may not be considered , Just consider all the circumstances , In this way, many calculations are repeated , Sliding window is an optimized double pointer case .

So the algorithm is still a little useful , At least at the beginning , We can better understand the kernel of the tools we use , Not just looking at flowers in the fog , Know what it is and don't know why it is ;

So come on !!

List of topics

Fixed window

Unfixed window

版权声明
本文为[Kitchen ape gaga]所创,转载请带上原文链接,感谢
https://qdmana.com/2021/09/20210909122358672m.html

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