MongoDB Internal Architecture | The Backend Engineering Show

The Backend Engineering Show with Hussein Nasser

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תוכן מסופק על ידי Hussein Nasser. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Hussein Nasser או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.

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How to get your confidence back 41:05

לפני 20 weeks41:05

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41:05

When negative feedback shakes your confidence, it can be difficult to get back to feeling like yourself at work. In this episode, Anne and Frances help a struggling listener who has spent years toning herself down in the workplace after being told that she was too assertive — now, she feels that her modest approach is holding her back. Together, they use Anne and Frances’s “trust triangle” framework to explore how empathy, authenticity, and logic can help you rebuild confidence and trust with your colleagues, and share helpful confidence hacks for getting comfy with discomfort. What problems are you dealing with at work? Text or call 234-FIXABLE or email fixable@ted.com to be featured on the show. For the full text transcript, visit ted.com/podcasts/fixable-transcripts Want to help shape TED’s shows going forward? Fill out our survey ! Hosted on Acast. See acast.com/privacy for more information.…

לפני 3 שנים 44:13

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I’m a big believer that database systems share similar core fundamentals at their storage layer and understanding them allows one to compare different DBMS objectively. For example, How documents are stored in MongoDB is no different from how MySQL or PostgreSQL store rows. Everything goes to disk, the trick is to fetch what you need from disk efficiently with as fewer I/Os as possible, the rest is API. In this video I discuss the evolution of MongoDB internal architecture on how documents are stored and retrieved focusing on the index storage representation. I assume the reader is well versed with fundamentals of database engineering such as indexes, B+Trees, data files, WAL etc, you may pick up my database course to learn the skills. Let us get started.

Fundamentals of Backend Engineering Design patterns udemy course (link redirects to udemy with coupon) https://backend.husseinnasser.com Fundamentals of Networking for Effective Backends udemy course (link redirects to udemy with coupon) https://network.husseinnasser.com Fundamentals of Database Engineering udemy course (link redirects to udemy with coupon) https://database.husseinnasser.com

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#Hussein Nasser #Engineering #Business #Industries #Open Source #Programming #Tech #Software Development

MongoDB Internal Architecture | The Backend Engineering Show

The Backend Engineering Show with Hussein Nasser

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published לפני 3 שנים

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531 פרקים

#Hussein Nasser #Engineering #Business #Industries #Open Source #Programming #Tech #Software Development

Усі епізоди

1
kTLS - Kernel level TLS 22:55

לפני 7 ימים22:55

22:55

Fundamentals of Operating Systems Course https://oscourse.winktls is brilliant.TLS encryption/decryption often happens in userland. While TCP lives in the kernel. With ktls, userland can hand the keys to the kernel and the kernel does crypto. When calling write, the kernel encrypts the packet and send it to the NIC.When calling read, the kernel decrypts the packet and handed it to the userspace. This mode still taxes the host’s CPU of course, so there is another mode where the kernel offloads the crypto to the NIC device! Host CPU becomes free. Incoming packets to the NIC are decrypted in device before they are DMAed to the kernel. outgoing packets are encrypted before they leave the NIC to the network.ktls still need handshake to happen in userspace. There is also enabling zerocopy in some cases (now that kernel has context) Deserves a video. So much good stuff.0:00 Intro2:00 Userspace SSL Libraries 3:00 ktls 6:00 Kernel Encrypts/Decrypts (TLS_SW)8:20 NIC offload mode (TLS_HW)10:15 NIC does it all (TLS_HW_RECORD)12:00 Write TX Example13:50 Read RX Example17:00 Zero copy (sendfile)https://docs.kernel.org/networking/tls-offload.html…

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The beauty of the CPU 9:38

לפני 6 weeks9:38

9:38

If you are bored of contemporary topics of AI and need a breather, I invite you to join me to explore a mundane, fundamental and earthy topic. The CPU. A reading of my substack article https://hnasr.substack.com/p/the-beauty-of-the-cpu

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Sequential Scans in Postgres just got faster 27:36

לפני 9 weeks27:36

27:36

This new PostgreSQL 17 feature is game changer. They know can combine IOs when performing sequential scan. Grab my database course https://courses.husseinnasser.com

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Does discipline work? 10:06

לפני 10 weeks10:06

10:06

No technical video today, just talking about the idea of discipline and consistency.

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Socket management and Kernel Data structures 31:26

לפני 11 weeks31:26

31:26

Fundamentals of Operating Systems Course This video is an overview of how the operating system kernel does socket management and the different data structures it utilizes to achieve that. timestamps 0:00 Intro 1:38 Socket vs Connections 7:50 SYN and Accept Queue 18:56 Socket Sharding 23:14 Receive and Send buffers 27:00 Summary…

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The genius of long polling 28:57

לפני 28 weeks28:57

28:57

Polling is the ability to interrogate a backend to see if a piece of information is ready. It can introduce a chatty system and as a result long polling was born. In this video I explain the beauty of this design pattern and how we can push it to its limit. 0:00 Intro 0:45 Polling 2:30 Problem with Polling 3:50 Long Polling 8:18 Timeouts 10:00 Long Polling Benefits 12:00 Make requests into Long Polling 17:36 Request Resumption 21:40 Summary…

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Six stages of a good software engineer 39:27

לפני 33 weeks39:27

39:27

You get better as a software engineer when you go through these stages. 0:00 Intro 1:15 Understand a technology 7:07 Articulate how it works 15:30 Understand its’ limitations 19:48 Try to build something better 27:45 Realize what you built also has limitations 32:48 Appreciate the original tech as is Understand a technology We use technologies all the time without knowing how it works. And it is ok not knowing how things work if interests isn’t there. But when there is interest to understand how something works, pursue it. It feels good when you understand how something works because you work better with it, you swim with the tide instead of against it. When I learned how TCP/IP work.. you would appreciate every connection request, how you read requests. You will ask questions, what is my code doing here? When exactly I’m creating connections? When am I reading from the connection? Is it safe to share connections? Articulate how it works This one is not easy, you might think you understand something until you try to explain how it works. If you find yourself using jargon you probably don’t understand and you just try to impress others. Have you seen people who want to talk about something to show they understand it? It’s the opposite. Try to truly articlate how it works, you will really understand it , back to 1. I thought I understand how backend reads requests until I tried to speak to it. Understand the technology limitations Once 1,2 are done you will truly understand the tech, now you are confidant, you are excited about the tech and you will truly see when you can use the tech to its full potential and also know the weak points of the tech where it breaks, this happens a lot with TCP/IP. We know tcps limitations. Try to build something better This one is optional and can be skipped, but attempting to design or building something better then the tech because you know the limitations will truly reveal how you became better. But the challenge here is the ego, you might understand the limitations but you problem is thinking that what you will build is flawless. This step must be proceed with caution. Realize what you build also has limitation Dust settles.. this step hurts, and you may take a while to realize it, but whatever you build will have flaws… and when you realize this it is when you get better as an engineer. Appreciate the tech as is This is when you are back full circle you are back to the first stage, look at the technology and understand it but don’t judge it.. just know the limitations and its strength and flow with it. Stop fighting and instead build around a tech, does that mean you shouldn’t build anything new, of course not. Go build, but don’t stress around making something better to defeat existing tech. But actually build it for building it.…

1
This new Linux patch can speed up Reading Requests 18:12

לפני 34 weeks18:12

18:12

Fundamentals of Operating Systems Course https://oscourse.win Very clever! We often call read/rcv system call to read requests from a connection, this copies data from kernel receive buffer to user space which has a cost. This new patch changes this to allow zero copy with notification. “Reading' data out of a socket instead becomes a “notification” mechanism, where the kernel tells userspace where the data is.” This kernel patch enables zero copy from the receive queue. https://lore.kernel.org/io-uring/ZwW7_cRr_UpbEC-X@LQ3V64L9R2/T/ 0:00 Intro 1:30 patch summary 7:00 Normal Connection Read (Kernel Copy) 12:40 Zero copy Read 15:30 Performance…

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Cloudflare's 150ms global cache purge | Deep Dive 1:02:21

לפני 35 weeks1:02:21

1:02:21

Cloudflare built a global cache purge system that runs under 150 ms. This is how they did it. Using RockDB to maintain local CDN cache, and a peer-to-peer data center distributed system and clever engineering, they went from 1.5 second purge, down to 150 ms. However, this isn’t full picture, because that 150 ms is just actually the P50. In this video I explore Clouldflare CDN work, how the old core-based centralized quicksilver, lazy purge work compared to the new coreless, decentralized active purge. In it I explore the pros and cons of both systems and give you my thoughts of this system. 0:00 Intro 4:25 From Core Base Lazy Purge to Coreless Active 12:50 CDN Basics 16:00 TTL Freshness 17:50 Purge 20:00 Core-Based Purge 24:00 Flexible Purges 26:36 Lazy Purge 30:00 Old Purge System Limitations 36:00 Coreless / Active Purge 39:00 LSM vs BTree 45:30 LSM Performance issues 48:00 How Active Purge Works 50:30 My thoughts about the new system 58:30 Summary Cloudflare blog https://blog.cloudflare.com/instant-purge/ Mentioned Videos Cloudflare blog https://blog.cloudflare.com/instant-purge/ Percentile Tail Latency Explained (95%, 99%) Monitor Backend performance with this metric https://www.youtube.com/watch?v=3JdQOExKtUY How Discord Stores Trillions of Messages | Deep Dive https://www.youtube.com/watch?v=xynXjChKkJc Fundamentals of Operating Systems Course https://os.husseinnasser.com Backend Troubleshooting Course https://performance.husseinnasser.com…

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MySQL is having a bumpy journey 28:34

לפני 38 weeks28:34

28:34

Fundamentals of Database Engineering udemy course https://databases.win MySQL has been having bumpy journey since 2018 with the release of the version 8.0. Critical crashes that made to the final product, significant performance regressions, and tons of stability and bugs issues. In this video I explore what happened to MySql, are these issues getting fixed? And what is the current state of MySQL at the end of 2024. 0:00 Intro 2:00 MySQL 8.0 vs 5.7 Performance 11:00 Critical Crash in 8.0.38, 8.4.1 and 9.0.0 15:40 Is 8.4 better than 8.0.36? 16:30 More Features = More Bugs 22:30 Summary and my thoughts resources https://x.com/MarkCallaghanDB/status/1786428909376164263 https://www.percona.com/blog/do-not-upgrade-to-any-version-of-mysql-after-8-0-37/ http://smalldatum.blogspot.com/2024/09/mysql-innodb-vs-sysbench-on-large-server.html https://www.percona.com/blog/mysql-8-0-vs-5-7-are-the-newer-versions-more-problematic/…

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How many kernel calls in NodeJS vs Bun vs Python vs native C 20:41

לפני 39 weeks20:41

20:41

Fundamentals of Operating Systems Course https://oscourse.win In this video I use strace a performance tool that measures how many system calls does a process makes. We compare a simple task of reading from a file, and we run the program in different runtimes, namely nodejs, buns , python and native C. We discuss the cost of kernel mode switches, system calls and pe 0:00 Intro 5:00 Code Explanation 6:30 Python 9:30 NodeJS 12:30 BunJS 13:12 C 16:00 Summary…

1
When do you use threads? 31:08

לפני 40 weeks31:08

31:08

Fundamentals of Operating Systems Course https://os.husseinnasser.com When do you use threads? I would say in scenarios where the task is either 1) IO blocking task 2) CPU heavy 3) Large volume of small tasks In any of the cases above, it is favorable to offload the task to a thread. 1) IO blocking task When you read from or write to disk, depending on how you do it and the kernel interface you used, the write might be blocking. This means the process that executes the IO will not be allowed to execute any more code until the write/read completes. That is why you see most logging operations are done on a secondary thread (like libuv that Node uses) this way the thread is blocked but the main process/thread can resume its work. If you can do file reads/writes asynchronously with say io_uring then you technically don't need threading. Now notice how I said file IO because it is different than socket IO which is always done asynchronously with epoll/select etc. 2) CPU heavy The second use case is when the task requires lots of CPU time, which then starves/blocks the rest of the process from doing its normal job. So offloading that task to a thread so that it runs on a different core can allow the main process to continue running on its the original core. 3) Large volume of small tasks The third use case is when you have large amount of small tasks and single process can't deliver as much throughput. An example would be accepting connections, a single process can only accept connections so fast, to increase the throughput in case where you have massive amount of clients connecting, you would spin multiple threads to accept those connections and of course read and process requests. Perhaps you would also enable port reuse so that you avoid accept mutex locking. Keep in mind threads come with challenges and problems so when it is not required. 0:00 Intro 1:40 What are threads? 7:10 IO blocking Tasks 17:30 CPU Intensive Tasks 22:00 Large volume of small tasks…

1
Frontend and Backends Timeouts 25:23

לפני 41 weeks25:23

25:23

I am fascinated by how timeouts affect backend and frontend programming. When a party is waiting on something you can place a timeout to break the wait. This is useful for freeing resources to more critical processes, detecting slow operations and even avoiding DOS attacks. Contrary to common beliefs, timeouts are not exclusive to request processing, they can be applied to other parts of the frontend-backend communications. Let us explore this briefly. 0:00 Intro 2:30 Connection Timeout 5:00 Request Read timeout 10:00 Wait Timeout 12:00 Usage Timeout 14:00 Response Timeout 16:00 Canceling a request 19:50 Proxies and timeouts…

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Postgres is combining IO in version 17 27:39

לפני 42 weeks27:39

27:39

Learn more about database and OS internals, check out my courses Fundamentals of database engineering https://databases.win Fundamentals of operating systems https://oscourse.win This new PostgreSQL 17 feature is game changer. You see, postgres like most databases work with fixed size pages. Pretty much everything is in this format, indexes, table data, etc. Those pages are 8K in size, each page will have the rows, or index tuples and a fixed header. The pages are just bytes in files and they are read and cached in the buffer pool. To read page 0, for example, you would call read on offset 0 for 8192 bytes, To read page 1 that is another read system call from offset 8193 for 8192, page 7 is offset 57,345 for 8192 and so on. If table is 100 pages stored a file, to do a full table scan, we would be making 100 system calls, each system call had an overhead (I talk about all of that in my OS course). The enhancement in Postgres 17 is to combine I/Os you can specify how much IO to combine, so technically while possible you can scan that entire table in one system call doesn’t mean its always a good idea of course and Ill talk about that. This also seems to included a vectorized I/O, with preadv system call which takes an array of offsets and lengths for random reads. The challenge will become how to not read too much, say I’m doing a seq scan to find something, I read page 0 and found it and quit I don’t need to read any more pages. With this feature I might read 10 pages in one I/O and pull all its content, put in shared buffers only to find my result in the first page (essentially wasting disk bandwidth, memory etc) It is going to be interesting to balance this out.…

1
Windows vs Linux Kernel 37:23

לפני 42 weeks37:23

37:23

Fundamentals of Operating Systems Course https://os.husseinnasser.com Why Windows Kernel connects slower than Linux I explore the behavior of TCP/IP stack in Windows kernel when it receives a RST from the backend server especially when the host is available but the port we are trying to connect to is not. This behavior is exacerbated by having both IPv6 and IPv4 and if the happy eye ball protocol is in place where IPv6 is favorable. 0:00 Intro 0:30 Fundamentals TCP/IP 3:00 Unreachable Port Behavior 6:00 Client Kernel Behavior (Linux vs Windows) 11:40 Slow TCP Connect on Windows 15:00 localhost, IPv6 and IPv4 20:00 Happy Eyeballs 28:00 Registry keys to change the behavior 31:00 Port Unreachable vs Host Unreachable https://daniel.haxx.se/blog/2024/08/14/slow-tcp-connect-on-windows/…

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