As per my understanding, Redis uses cached memory to store the data. Currently, I am having a server with Redis and other functionality installed on it. The server memory utilization is high due to cached memory. Can I clear the cache using sync and drop caches? Would it affect Redis functionality as it stores the data in cache?
Also, correct if my understanding is wrong.
Related
I am trying to implement a way to store the cache content on local storage and automatically loads to RAM if the Varnish service restarts for any reason. Kindly suggest if we have any way to do so.
The only way to load persisted cache storage into Varnish is by using Varnish Enterprise's Massive Storage Engine.
Unfortunately, this is not possible with the open source version of Varnish.
See https://docs.varnish-software.com/varnish-cache-plus/features/mse/ for more information about the Massive Storage Engine (MSE).
The idea is that metadata is stored in a specific database that MSE provides. This concept is called "the book".
Every "book" has multiple "stores", which are large pre-allocated files containing the persisted cache storage.
When you recover both "books" and "stores", Varnish Enterprise will be able to reload the cache from these files.
If these files contain gigabytes or terabytes of data, MSE will be clever enough to only load the "hot" objects into memory.
I've recently learned that Uber uses a cache to store its map data where as twitter uses Redis to store and retrieve data related to a user's homepage. I'm trying to understand when to use a cache vs an in-memory database such as Redis. It seems like fast retrieval is required in both cases I described.
Thanks!
An in-memory database is also a cache. What we usually mean by cache is that the data is retrieved from memory, and not from disk. In the case of Uber, it looks like they are also using Redis as a cache: https://eng.uber.com/tech-stack-part-one-foundation/.
I have a questions about Redis cache and laravel. By default laravel uses file which caches views to a file and load them from that cache.
Now here's the thing, I started using ElastiCache with Redis for my Laravel 5.4 project. If I change the driver to redis and it starts to cache (which I can tell by a loading time) but what does it actually cache? Does it automatically cache and retrieve my views? css? js? anything else?
I am also using redis for sessions driver, what does that give me?
Is it worth caching database as well? I was planning to cache whole database every hour and then whenever new item is added to database, add it to the existing cache. Is that possible?
The redis could give you two advantages:
faster data retrieving. Any memory-based cache system can give you this advantage than file-based or DB-based, such as memcached.
flexible data saving in redis. redis support many data-type store such as string, list, set, sorted-set and so on.
About caching what?
Cache the frequent request thing. If your client request something or query something to you, and you do not have cache, you will have to query it from your database, which give you an disk I/O time cost. And if the thing is heavy, then the IO cost will be bigger and slow down your server. So the smart way is , just query once and then save it into redis by suitable data-type store. After that retrive thousands with Cache. But you do not need to cache the overall database. It looks rude. And when you update something in db, just delete from your cache and after next time someone query this, it will save into cache again.
About Session. this is very frequent access thing for http server , so every user'session into cache is more light weight than file or db if your app server many many many people.
Cache the static file. Actually I has not dealt with this. But it can do this definitely! E.g. In modern architecture, there is often a Http server stand before your laravel such as nginx. In this way, you will use nginx serve the static file directly. And if you want decrease the disk io about this, you can add a module like redis2-nginx-module for nginx to do a same thing : save the static file into redis once and serve thousands.
HBase has its own cache system and for reading requests it will search from cache before fetch data from HDFS. But its cache performance can be hindered by JVM memory size, and this is the reason why I want to use Redis as HBase's cache.
Please don't do it. Using one database as a cache for another database can easily turn into a nightmare situation. Dealing with cache invalidation scenarios itself can be a difficult task.
If you need an in-memory cache on application level, I would still discourage it, but that's a separate discussion.
On database level, if HBase block cache is not good enough for your use case, either HBase is not a good system for your use case or you are not using it correctly. If your only concern is that you have a lot of memory/flash(SSD) but HBase cannot properly utilize it because of JVM restrictions; you can use HBase's bucketcache, which can be used to cache blocks off-heap or on a solid state storage (hbase.bucketcache.ioengine). I would advise you read up on HBase's caching basics here.
We are moving an asp.net site to Azure Web Role and Azure Sql Database. The site is using output cache and normal Cache[xxx] (i.e. HttpRuntime.Cache). These are now stored in the classic way in the web role instance memory.
The low hanging fruit is to first start using a distributed cache for output caching. I can use in-role cache, either as co-located or with a dedicated cache role, or Redis cache. Both have outputcache providers ready made.
Are there any performance differences between the two (thee with co-located/dedicated) cache methods?
One thing to consider is that will getting the page from Redis for every pageload on every server be faster or slower than composing the page from scratch one every server every 120 seconds but inbetween just getting it from local memory?
Which will scale better when we want to start caching our own data (i.e. pocos) in a distributed cache instead of HttpRuntime.Cache?
-Mathias
Answering to your each question individually:
Are there any performance differences between the two (thee with
co-located/dedicated) cache methods?
Definately co-located caching solution is faster than dedicated cache server, as in co-located/inproc solution request will be handled locally within the process where as dedicated cache solution will involve getting data over the network. However since data will be in-memory on cache server, getting will still be faster than getting from DB.
One thing to consider is that will getting the page from Redis for
every pageload on every server be faster or slower than composing the
page from scratch one every server every 120 seconds but inbetween
just getting it from local memory?
It will depend on number of objects on page i.e. time taken to compose the page from scratch. Though getting from cache will involve network trip time but its mostly in fractions of a millisecond.
Which will scale better when we want to start caching our own data
(i.e. pocos) in a distributed cache instead of HttpRuntime.Cache?
Since HttpRuntime.Cache is in-process caching, it is limited to single process's memory therefore it is not scalable. A distributed cache on the other hand is a scalable solution where you can always add more servers to increase cache space and throughput. Also out-proc nature of distributed cache solution makes it possible to access data cached by on application process to be used by any other process.
You can also look into NCache for Azure as a distributed caching solution. NCache is a native .Net distributed caching solution.
Following blog posts by Iqbal Khan will help you better understand the need of distributed cache for ASP.Net applications:
Improve ASP.NET Performance in Microsoft Azure with Output Cache
How to use a Distributed Cache for ASP.NET Output Cache
I hope this helps :-)
-Sameer