scalability

问题 What design patterns or techniques have you used that are specifically geared toward scalability ? Patterns such as the Flyweight pattern seem to me to be a specialized version of the Factory Pattern, to promote high scalability or when working within memory or storage constraints. What others have you used? (Denormalization of Databases, etc.) Do you find that the rules change when high availability or scalability is your primary goal? Possible situations are: Mobile devices with more

问题 I have a buddy who runs a web app for people listing cars for sale. There are a few thousand clients who use it, and each client has hundreds and sometimes thousands of rows in the database (some have been on for 5 years with hundreds of cars selling each month, and 10s of rows per sale (comments, messages, etc)). He has run this system in one SQL Server database in one physical server with like 20GB or RAM and a couple processors for the whole time, with no problems. Is this some sort of

问题 In my latest project, I have to write a web service API to return data from a database. Techs are - SQL Server 08 R2 - WCF The data is mainly key-value pairs, e.g. for get user X's favourite colour. The load isn't massive, but not small-fry either - about 1,000 requests / sec at peak. My initial thoughts are to use Redis as the cache, meaning we don't hit SQL Server as often. However I've been trying to get some benchmarks etc out of this configuration, and it's not great, making me wonder if

问题 I'm looking at a system where people RSVP to a free web conference, these web conferences can get really busy with a lot of interest and there are limited places, so there has to be some way to ensure it doesn't get over-subscribed... So, we need to have a countdown from the time they book their seat to the time that their order is completed and confirmed. This way it's the first X amount of people to actually click 'Attending' that get the seats for the conference. If the user does not

问题 I want to build a highly scalable application where I intend to use Lucene as my search engine library. While browsing through the docs and faqs, I realize that it only allows one index writer to be open on a storage location by creating some write.lock in index directory. We can open multiple IndexReaders on that index. I am interested in building an architecture where there are number of indexers running on different machines/servers and multiple searcher answering various types of queries

问题 Firebase has an interesting feature/nuisance where when you listen on a data ref, you get all the data that was ever added to that ref. So, for example, when you listen on 'child_added', you get a replay of all the children that were added to that ref from the beginning of time. We are writing a commenting system with a dataset that looks something like this: /comments /sites /sites/articles /users Sites have many articles and articles have many comments and users have many comments. We want

问题 Below is a apache bench run for 10K requests with 50 concurrent threads. I need help understanding the results, does anything stand out in the results that might be pointing to something blocking and restricting more requests per second? I'm looking at the connection time section, and see 'waiting' and 'processing'. It shows the mean time for waiting is 208, and the mean time to connect is 0 and processing is 208..yet the total is 208. Can someone explain this to me as it doesn't make much

问题 I have designed a Node.JS server that allows users to log in, join a room and exchange data with other users in this room using websockets. However I am now looking for a way to make this setup scalable. I spend all afternoon researching various loadbalancers such as nginx and haproxy, but I still can't figure out how to organise my setup. Initally users can login and view the active rooms. No biggie to makes this part scalable. However then they can join a specific room and at that point

问题 What are the options usually for re-using the same codebase across different apps (.e.g web application, winforms, etc). My immediate, high-level thought is to use web services to expose a dedicated dll of the business logic. What other options are there? Thanks 回答1: Normally, you should have a separate layer for your business logic and another for your data access. It's from the very high level view. Depending on the complexity of your application, your business layer may divided into

问题 From my reading on SignalR scaleout in Azure, the recommended way is to use Azure ServiceBus as a backplane. But in the same time there is limitation on using backplane for high frequency messaging. In terms of Limitation chapter in Scaleout in SignalR, I would characterize my app as something between chat and real-time game. Any tips how to implement SignalR scaleout (in Azure) for this? 回答1: You can set the # of topics (queues) that you use to increase throughput and scale up 来源： https:/