Different types of cache, or what can speed up our application (video, 6 minutes)
Caching is a common technique in modern computing to enhance system performance and reduce response time. ByteByteGo has discussed how significant caching is from the hardware level to the operating system, and how it plays a crucial role in optimizing various applications and systems. The channel highlighted the typical hardware caches, namely L1, L2, and L3, which differ in size and speed. The L1 cache is the fastest and smallest cache integrated into the CPU, storing frequently accessed data and instructions. L2 and L3 caches are larger but slower and serve different CPU cores. Another interesting cache discussed is the Translation Lookaside Buffer (TLB), which accelerates the translation of virtual addresses into physical addresses.
At the operating system level, ByteByteGo emphasized the presence of various caching layers that manage data, such as the page cache, which resides in main memory. The page cache allows for fast access to data that has already been accessed, while other caches like the inode cache speed up file operations. Moving away from the hardware and operating system level, the channel demonstrated caching in application architecture by talking about how web browsers cache HTTP responses and how Content Delivery Networks (CDNs) cache content for faster delivery. When content is requested for the first time, it can be stored in cache, enabling faster access for future requests from users.
Moreover, load balancers can also cache responses to backend servers, further improving performance. In messaging infrastructure, systems like Kafka allow for caching of messages on disk, enabling consumers to retrieve messages at their own pace. The use of distributed caches like Redis significantly boosts operations by storing key-value pairs in memory. Finally, ByteByteGo examined the various caching levels within databases that accelerate different operations like write-ahead logs and cached query results. Overall, ByteByteGo stressed that caching is a vital technique for optimizing system performance. From frontend to backend, various caching layers greatly improve the efficiency of applications and systems. Lastly, if you like our videos, consider subscribing to ByteByteGo’s newsletter, which covers topics related to system design and is trusted by 300,000 readers. At the time of writing this article, the video has accumulated 581,496 views and 17,454 likes.
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Introduction to caching as a technique to enhance system performance.
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Caching improves efficiency in various applications and systems.
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A typical system architecture involves multiple layers of caching.
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Overview of common hardware caches: L1, L2, and L3 caches.
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Details on L2 and L3 caches and their characteristics.
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Explanation of the Translation Lookaside Buffer (TLB) for address translations.
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Introduction to page cache managed by the operating system.
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Other operating system caches that speed up file system operations.
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Caching in application system architectures, starting with web browsers.
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Content Delivery Networks (CDNs) and their use of caching for content delivery.
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Load balancers caching resources to improve response times.
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Mention of caching in messaging infrastructure like Kafka.
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Distributed caches like Redis for high read-write performance.
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Full-text search engines using indexing for efficiency.
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Database caching mechanisms including buffer pools and materialized views.
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Importance of caching for optimizing system performance.
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Summary stating the relevance of layers of caching across applications.
Transcription
Caching is a common technique in modern computing to enhance system performance and reduce response time. From the front end to the back end, caching plays a crucial role in improving the efficiency of various applications and systems. A typical system architecture involves several layers of caching. At each layer, there are multiple strategies and mechanisms for caching data, depending on the requirements and the constraints of the specific application. Before diving into a typical system architecture, let's zoom in and look at how prevalent caching is within each computer itself. Let's first look at the computer hardware. The most common hardware caches are L1, L2, and L3 caches. L1 cache is the smallest and fastest cache. Typically integrated into the CPU itself, it stores frequently accessed data and instructions, allowing the CPU to quickly access them without having to fetch them from slower memory. L2 cache is larger but slower than L1 cache, and is typically located on the CPU die. L3 cache is even larger and slower than L2 cache, and is often shared between multiple CPU cores. Another common hardware cache is the Translation Lookaside Buffer, or TLB. It stores recently used virtual-to-physical address translations. It is used by the CPU to quickly translate virtual memory addresses to physical memory addresses, reducing the time needed to access data from memory. At the operating system level, there are page cache and other file system caches. Page cache is managed by the operating system and resides in main memory. It is used to store recently used disk blocks in memory. When a program requests data from the disk, the operating system can quickly retrieve the data from memory instead of reading it from disk. There are other caches managed by the operating system, such as the inode cache. These caches are used to speed up file system operations by reducing the number of disk accesses required to access files and directories. Now, let's zoom out and look at how caching is used in a typical application system architecture. On the application frontend, web browsers can cache HTTP responses to enable faster retrieval of data. When we request data over HTTP for the first time, and it is returned with an expiration policy in the HTTP header, we request the same data again and the browser returns the data from its cache, if available. Content Delivery Network, or CDNs, are widely used to improve the delivery of static content, such as images, videos, and other web access. One of the ways that CDNs speed up content delivery is through caching. When a user requests content from a CDN, the CDN network looks for the requested content in its cache. If the content is not already in the cache, the CDN fetches it from the origin server and caches it on its edge servers. When another user requests the same content, the CDN can deliver the content directly from its cache, eliminating the need to fetch it from the origin server again. Some load balancers can cache resources to reduce the load on backend servers. When a user requests content from a server behind a load balancer, the load balancer can cache the response and serve it directly to future users who request the same content. This can improve response times and reduce the load on backend servers. Caching does not always have to be in memory. In messaging infrastructure, message brokers, such as Kafka, can cache a massive amount of messages on disk. This allows consumers to retrieve the messages at their own pace. The messages can be cached for a long period of time based on the retention policy. Distributed caches, such as Redis, can store key value pairs in memory, providing high read-write performance compared to traditional databases. Full-text search engines, such as Elasticsearch, can index data for document search and log search, providing quick and efficient access to specific data. Even within the database, there are multiple levels of caching available. Data is typically written to a write-ahead log before being indexed in a B-tree. The buffer pool is a memory area used to cache query results, while materialized views can pre-compute query results for faster performance. The transaction log records all transactions and updates to the database, while the replication log tracks the replication state in a database cluster. Overall, caching data is an essential technique for optimizing system performance and reducing response time. From the frontend to the backend, there are many layers of caching to improve the efficiency of various applications and systems. If you like our videos, you might like our system design newsletter as well. It covers topics and trends in large-scale system design, trusted by 300,000 readers. Subscribe at blog.bytebytego.com.