caching

问题 I am working on a project where I am using Meteor as an implementation. There are set of pages that are being cached and there's no concern. However, there is one page in the project that I am trying to set for no-cache. How do I achieve that? EDITED: Based on chosen accepted answer; I achieved the desired result with this wrapping code: if (Meteor.isServer) { Meteor.startup(function () { WebApp.rawConnectHandlers.use(function (req, res, next) { res.setHeader('cache-control', 'no-cache'); res

问题 I am working on a project where I am using Meteor as an implementation. There are set of pages that are being cached and there's no concern. However, there is one page in the project that I am trying to set for no-cache. How do I achieve that? EDITED: Based on chosen accepted answer; I achieved the desired result with this wrapping code: if (Meteor.isServer) { Meteor.startup(function () { WebApp.rawConnectHandlers.use(function (req, res, next) { res.setHeader('cache-control', 'no-cache'); res

问题 I'm using node and express for the back end of an iOS application. Data is stored in a SQL Server database, so iOS apps query the server, the server queries the database, server receives the db response, and then forwards the response to the iOS application. I'm trying to figure out how caching works though. I'm serving a lot of static content - blog articles for example. So I planned to use etags, but I'm not sure how it's supposed to work. I make a request, get content, and cache the

问题 I have a sequential user space program (some kind of memory intensive search data structure). The program's performance, measured as number of CPU cycles, depends on memory layout of the underlying data structures and data cache size (LLC). So far my user space program is tuned to death, now I am wondering if I can get performance gain by moving the user space code into kernel (as a kernel module). I can think of the following factors that improve the performance in kernel space ... No system

问题 I want to save some cache data for my appliaction. I used to do this by saving the data in the external storage and this worked fine. But I want my device to show my cache size in the app settings but It doesn´t. I guess this is because I save the data in external storage. What I want is that my data still exists aufter closing the app or even swichen off my device. Now I tried to save my files in the internal storage but I have troubles reading the files + the cache size is still wrong in

问题 Does Ehcache 2.1 now support the transactional cache concurrency strategy in Hibernate 3.3.2GA? That is, does Hibernate, when configured to use Ehcache 2.1 as its cache provider, allow the <cache usage="transactional"/> element in a mapping file or the Hibernate entity class annotation @Cache(usage=CacheConcurrencyStrategy.READ_WRITE) ? 回答1: According to the Ehcache Home Page page, Ehcache 2.1+ does now support all Hibernate strategies: 17 May 2010: Ehcache 2.1.0 and new ehcache-nonstopcache

问题 When I explicitly call rdd.cache, I can see from the spark console storage tab that only a fraction of the rdd is actually cached. My question is where are the remaining parts? How does Spark decide which part to leave in cache? The same question applies to the initial raw data read in by sc.textFile(). I understand these rdd's are automatically cached, even though the spark console storage table does not display any information on their cache status. Do we know how much of those are cached

问题 Can a lower level cache have higher associativity and still hold inclusion? Suppose we have 2-level of cache.(L1 being nearest to CPU and L2 being nearest to main memory) L1 cache is 2-way set associative with 4 sets and let's say L2 cache is direct mapped with 16 cache lines and assume that both caches have same block size. Then I think it will follow inclusion property even though L1(lower level) has higher associativity than L2 (upper level). As per my understanding, lower level cache can

问题 I'm experimenting with the EXPLAIN command and trying to find out what the shared hit is. Seq Scan on foo (cost=0.00..18334.00 rows=1000000 width=37) (actual time=0.030..90.500 rows=1000000 loops=1) Buffers: shared hit=512 read=7822 Total runtime: 116.080 ms I've noticed that the more shared hit number we have the faster a query is being executed. But what is that? As far as I got, shared read is just reading from a physical storage like RAID or SSD . But why is the shared hit faster? Is it

问题 The goal is to cache some responses from web service. I am using Spring for Android framework - http://www.springsource.org/spring-android#documentation to communicate with restful service. As I know I can add caching into application using some module from the common Spring Framework ( http://viralpatel.net/blogs/cache-support-spring-3-1-m1/ ). Am I right that it is not possible to do using just spring-for-android? What is the solution then? *I don't have any experience in a common Spring.