System Design: Why is Kafka fast?

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totally lost me at the no-copy discussion :(

well. good video, but this is nothing new, the sendfile() syscall is around for a long time any many people used it long before kafka. neither is DMA new, it was there since the very first IBM PC machines.

Useful information.

Each kafka broker could have data from multiple topic partitions. Reading data from same kafka broker still needs to swich disk header. Will that hurt the benefit from sequential IO?

More videos like this! ❤

Thank you! Such a great delivery and explanation. Particularly, great choice of aspects to share.

Thank you so much

This was a clear and concise presentation. Thank you so much 👍

Great videos...will be even better if this was a tad slower

Thanks you! Excellent.

First time I actually WANT to subscribe to a newsletter.

useful <3

Superb content

Uhh I thought this was a final fantasy video

is there a risk of Kafka accessing other areas of the memory cache in which system calls could send wrong/private data?

Awesome video!!!!!! How those animations are made? In after effects??

Hi sir SRIO is again more faster than DMA

While sequential access can be efficient for certain tasks, it also has several downsides:

Slow Access for Individual Records: If you need to access a specific record in the middle or at the end of a sequentially accessed file or data structure, you would have to traverse through all preceding records. This can be very inefficient and time-consuming, particularly for large datasets.

Inefficient Updates and Deletions: If a record in a sequentially accessed file needs to be updated or deleted, you often have to rewrite the entire file, or at least all the data following that record, which can be very slow and inefficient.

Inefficient for Concurrent Access: In situations where multiple users or processes need to access data concurrently, sequential access can be very inefficient and may even lead to data corruption if not handled correctly.

Lack of Flexibility: Sequential access doesn't allow for as much flexibility in terms of data access patterns. You are essentially restricted to accessing data in the order it was written.

Space Inefficiency: Sequential files can become space inefficient over time. If records are deleted, the space they occupied often cannot be reused, leading to wasted space.

Data Structure Overhead: In certain data structures optimized for sequential access, such as linked lists, there can be significant overhead in terms of additional pointers or other structural information that needs to be stored along with the actual data.

Sequential access is particularly useful and efficient in certain scenarios, including:

Data Streaming: When data is being streamed from one point to another, such as in audio or video streaming services, sequential access is ideal. Data is read in the order it arrives, and there's usually no need to skip forward or backward.

Log Files: Log files are typically written and read in a sequential manner. The most recent events are appended to the end of the log, and when reviewing the logs, it's often most useful to read events in the order they occurred.

Backup and Restore Operations: When performing backup operations or restoring data from backups, the data can be processed sequentially. The backup process involves reading all data from a source and writing it to a backup medium, while restore operations read the data from the backup medium and write it back to the source or a new location.

Batch Processing: In scenarios where large volumes of data need to be processed in one go, such as overnight processing of transactions, sequential access can be used efficiently.

Data Warehousing and Data Mining: In data warehousing and mining operations where huge volumes of data are processed, sequential access is often used.

Sequential Read/Write Media: For certain types of media, such as magnetic tapes, sequential access is the only viable method. You read from or write to the tape in a linear fashion, from one end to the other.


Zero copy is a technique that reduces CPU usage and increases data processing speed by eliminating unnecessary data copying between user space and kernel space during network communication or file I/O operations. The data to be sent over the network is sent directly from the disk buffer cache to the network buffer without being copied.

Pros:

Increased Efficiency: Zero-copy can significantly speed up data transfer rates because it removes the overhead of copying data between user and kernel space.

Reduced CPU Usage: As there's no need to copy data, zero-copy methods can reduce CPU usage, freeing up resources for other tasks.

Reduced Memory Usage: Zero-copy techniques can lead to less memory usage because they avoid creating extra copies of data in memory.

Lower Latency: By avoiding the overhead of data copying, zero-copy can lead to lower latency in network communication or file I/O operations.

Cons:

Complexity: Implementing zero-copy can be complex and may require a deep understanding of the operating system and network interfaces. This can increase development time and potentially introduce more bugs.

Data Security: With zero-copy, the data stays in the kernel buffer and is directly accessible to user space. This could potentially lead to security vulnerabilities if not managed correctly.

Buffer Availability: Zero-copy can lead to buffers being locked for longer periods, as the same buffer is used for reading data from the disk and sending it over the network. This could potentially impact other tasks that need to use these buffers.

Non-Contiguous Memory Issues: If data is stored non-contiguously in memory, zero-copy can be challenging to implement effectively.

The decision to use zero-copy would largely depend on the specific needs of the system and whether the benefits of increased data transfer speed, reduced CPU usage, and lower memory footprint outweigh the increased complexity and potential risks.

Amazing Insite. Zero Copy was new to me 😊

Very well explained. Thank you.

Thank u so much!!! I had this question in my mind and got explained by your in a very easy way!!!

kafaka is not fast man.

🙄 NATS and RabbitMQ have high speed benchmark which is already available in the market.

Very insightful. The diagrams made me understand the concepts

The video title should be: How to answer a complex question in 5 mins.

Is HDD better than SSD ah ?

x1.25 speed, you’re welcome

Hey byte, Could you please tell me what your using for presentation

Exemplary Illustration on Kafka

Thanks for sharing!

Really great

Very elegantly done. I wonder what animation tool they are using ??

Once of the best channel , i came to know you from linkedin 😅

Kafka is not fast. I just dropped one poc.

Your channel is excellent.

If that improves the performances, why are all the other dB engines not using this?

Very simple with good animation to explain things clearly. Keep publishing these kinds of useful videos.

Awesome tutorial

Doesn't the kernel's memory management resolve the physical addresses to random free space on disk even if the logical address is sequential? Can anyone correct me if I'm wrong?

Hi Alex, what software do you use to create those animations? Thanks!

Thank you for the wonderful explanation of Kafkas abilities.

toooo good whoever has made it. 👍

If Kafka uses direct memory access to get data to the network buffer, what system acts as the memory master to decide who gets access to the OS buffer at what time?

Your explanation is lucid and to the point. Thanks for the video. Keep up the good work! Wish you the best of luck.

Amazing work guys! I'm subscribed to any newsletter and video you make, and it's worth it. Congratulations team 👏👏👏

Simplicity the best. Your USP is to focus on Contextual knowledge with byte size videos with great graphics. Very valuable.

wocao

Amazing explanation!