memcached

In memory storage on nodejs server

由 [亡魂溺海] 提交于 2019-12-06 06:50:19
问题 There seem to be quite a few promising packages with no clear suggestions on which is the fastest,scalable and which is more memory efficient. npm install memoizee npm install memcached lru-cache npm install memory-cache npm install node-cache Any reliable sources of information/personal experience with these would help. So the basic usage is for simple key:value store. Just need to know if the underlying architecture of these different stores is similar/different and if different then which

CacheManager memcached configuration

由 风格不统一 提交于 2019-12-06 06:48:36
I'm going to use CacheManager for my .net project. The problem is that I can't find any examples of CacheManager.Memcached usage. This is how I use it: public class GlobalCache { private static ICacheManager<object> memcachedClient { get; set; } private static readonly object locker = new object(); static GlobalCache() { if (memcachedClient == null) { lock (locker) { memcachedClient = CacheFactory.Build("memcached", settings => settings.WithMemcachedCacheHandle("memcached")); } } } } Web.config: <configuration> <enyim.com> <memcached protocol="Binary"> <servers> <add address="127.0.0.1" port=

How can caches_action be configured to work for multiple formats?

由 主宰稳场 提交于 2019-12-06 06:25:06
问题 I have a rails action which responds to requests in various formats including AJAX requests, for example: def index # do stuff respond_to do |format| format.html do # index.html.erb end format.js do render :update do |page| page.replace_html 'userlist', :partial => "userlist", :object=>@users page.hide('spinner') page.show('pageresults') end end end end I have set this action to cache using memcached using: caches_action :index, :expires_in=>1.hour, :cache_path => Proc.new { |c| "index/#{c

Service error in memcache with Java Google App Engine Standard at random time periods

由 倖福魔咒の 提交于 2019-12-06 06:22:21
问题 In the past month, our Java Google App Engine Standard Web App started getting strange errors at seemingly random times (see stack trace below). Around this time we made the following changes: Switch from Java7 runtime to Java8/Jetty9 runtime (which allowed us more flexibility in linking to a 3rd party payments library). Switch to deploying with the Google Cloud SDK, instead of the separate Google App Engine SDK. Yesterday we experienced 3 periods with errors. One of these occurred from

How can I cache Model objects in Rails?

由 巧了我就是萌 提交于 2019-12-06 05:51:41
问题 Is there a technique that I can use in Rails so that whenever a simple "find" is performed on a Model object, memcached is first searched for the result, only if no result is found will a query by then made to the database? Ideally, I'd like the solution to be implicit, so that I can just write Model.find(id), it first checks the cache and if a database query is required that the object returned is then added to the cache i.e. I don't need to wrap the Model.find(id) with additional code to

Memcache 1 MB limit in Google App Engine

由 十年热恋 提交于 2019-12-06 05:41:21
问题 How do you store a object with size bigger than 1 MB in memcache? Is there a way to split it up, but have the data still be accessible with the same key? 回答1: There are memcache methods set_multi and get_multi that take a dictionary and a prefix as arguments. If you could split your data into a dictionary of chunks you could use this. Basically, the prefix would become your new key name. You'd have to keep track of the names of the chunks somehow. Also, ANY of the chunks could be evicted from

What is the best optimization technique for a wildcard search through 100,000 records in sql table

由 本小妞迷上赌 提交于 2019-12-06 03:19:04
I am working on an ASP.NET MVC application. This application is used by 200 users. These users constantly (every 5 mins) search for an item from the list of 100,000 items (this list is going to increase every month by 1-2 %). This list of 100,000 items are stored in a SQL Server table. The search is a wildcard search eg: Select itemCode, itemName, ItemDesc from tblItems Where itemName like '%SearchWord%' The searching needs to really fast since the main business relies on searching and selecting the item. I would like to know how to get the best performance. The search results have to come up

Pyramid with memcached: how to make it work? Error - MissingCacheParameter: url is required

由 梦想与她 提交于 2019-12-06 03:02:45
I have site on Pyramid framework and want to cache with memcached. For testing reasons I've used memory type caching and everything was OK. I'm using pyramid_beaker package. Here is my previous code (working version). In .ini file cache.regions = day, hour, minute, second cache.type = memory cache.second.expire = 1 cache.minute.expire = 60 cache.hour.expire = 3600 cache.day.expire = 86400 In views.py: from beaker.cache import cache_region @cache_region('hour') def get_popular_users(): #some code to work with db return some_dict The only .ini settings I've found in docs were about working with

Speeding up jQuery AutoComplete (Unavoidably long lists)

由 无人久伴 提交于 2019-12-06 03:01:20
问题 I began my journey to speed up jQuery's autocomplete earlier this afternoon, and decided it was probably a good idea to begin memcaching everything. As suggested in this article: Speeding up autocomplete. However, I am still dealing with slow response time even after installing and using Memcached. The problem in my case is that I am dealing with extraordinarily long lists, in my case, over 6700 individual members. (All genera or genuses of all plants) The bottleneck seems to be constructing

why does memcached not support “multi set”

由 拟墨画扇 提交于 2019-12-06 01:52:24
Can anyone explain why memcached folks decided to support multi get but not multi set. By multi I mean operation involving more than one key (see protocol at http://code.google.com/p/memcached/wiki/NewCommands ). So you can get multiple keys in one shot (basic advantage is the standard saving you get by doing less round trips) but why can not you get bulk sets? My theory is that it was meant to do less number of sets and that too individually (e.g. on a cache read and miss). But I still do not see how multi-set really conflicts with the general philosophy of memcached. I looked at the client
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