1.5 Cache Systems Flashcards
What is caching, and why is it important in modern computing?
Caching is a technique used to store frequently accessed data in a faster storage layer, so it can be retrieved quickly when needed. It improves system performance by reducing the time it takes to access data and decreases the load on slower storage systems (like databases or disks). Caching is used everywhere, from the front end (e.g., web browsers) to the back end (e.g., databases), to make applications faster and more efficient.
What are L1, L2, and L3 caches, and how do they work?
L1, L2, and L3 caches are types of hardware caches found in computers.
L1 Cache: The smallest and fastest cache, built directly into the CPU. It stores frequently used data and instructions so the CPU can access them quickly without waiting for slower memory.
L2 Cache: Larger but slower than L1, often located on the CPU chip or nearby. It stores more data than L1 but takes slightly longer to access.
L3 Cache: The largest and slowest of the three, often shared between multiple CPU cores. It helps reduce the time needed to fetch data from the main memory.
These caches work together to speed up data access for the CPU.
What is the Translation Lookaside Buffer (TLB), and why is it important?
The TLB is a special type of cache used by the CPU to speed up memory access. It stores recently used virtual-to-physical address translations. When a program requests data, the CPU uses the TLB to quickly find the physical memory location of the data instead of searching through slower memory. This reduces the time needed to access data and improves overall system performance.
What is the page cache, and how does it help improve performance?
The page cache is a type of cache managed by the operating system. It stores recently used disk blocks in the computer’s main memory (RAM). When a program requests data from the disk, the operating system first checks the page cache. If the data is already in the cache, it can be retrieved quickly from memory instead of reading it from the slower disk. This speeds up file access and reduces the load on the disk.
What is a CDN, and how does it use caching?
A Content Delivery Network (CDN) is a network of servers distributed across different locations. CDNs cache static content (like images, videos, and web assets) on their edge servers, which are closer to users. When a user requests content, the CDN checks its cache. If the content is already cached, it delivers it directly to the user. If not, the CDN fetches the content from the origin server, caches it, and then delivers it. This reduces latency and speeds up content delivery.
How do web browsers use caching to improve performance?
Web browsers cache HTTP responses (like images, CSS files, and JavaScript) to speed up loading times. When you visit a website for the first time, the browser stores the responses in its cache. If you visit the same website again, the browser can load the cached data instead of downloading it again. This reduces load times and improves the user experience. The cache follows rules set in the HTTP headers, like expiration policies, to decide how long to keep the data.
How can load balancers use caching to improve performance?
Load balancers can cache responses from back-end servers. When a user requests content, the load balancer checks its cache. If the content is already cached, it serves it directly to the user without forwarding the request to the back-end server. This reduces the load on the back-end servers and improves response times for users.
How do message brokers like Kafka use caching?
Message brokers like Kafka cache messages on disk instead of in memory. This allows them to store a large amount of data for a long time, based on a retention policy. Consumers (applications that read messages) can retrieve messages at their own pace. Caching messages on disk ensures that data is not lost and can be replayed if needed.
What is distributed caching, and how does Redis work?
Distributed caching involves storing data across multiple servers to provide high availability and scalability. Redis is a popular distributed cache that stores data as key-value pairs in memory. This allows for extremely fast read and write operations compared to traditional databases. Redis is often used to cache frequently accessed data, like session information or API responses, to improve application performance.
How do databases use caching to improve performance?
Databases use multiple levels of caching:
Buffer Pool: A memory area that caches query results and frequently accessed data.
Write-Ahead Log (WAL): A log that records changes before they are written to the database, ensuring data integrity.
Materialized Views: Precomputed query results stored for faster access.
Transaction Log: Records all database transactions for recovery and auditing.
Replication Log: Tracks changes for database replication.
These caching mechanisms help reduce the time needed to read and write data, improving database performance.
How do full-text search engines like Elasticsearch use caching?
Full-text search engines like Elasticsearch use indexing to cache data for quick retrieval. They create an index of documents or logs, allowing users to search for specific data efficiently. The index acts as a cache, storing metadata about the data’s location and content, which speeds up search operations.
Why is caching essential for system performance?
Caching is essential because it reduces response time and improves system efficiency. By storing frequently accessed data in faster storage layers (like memory or edge servers), caching minimizes the need to fetch data from slower sources (like disks or databases).
This speeds up applications, reduces server load, and enhances the user experience. Caching is used at every level of a system, from hardware to software, to optimize performance.
