eventual-consistency

问题 In an attempt to use Dynamodb for one of projects, I have a doubt regarding the strong consistency model of dynamodb. From the FAQs Strongly Consistent Reads — in addition to eventual consistency, Amazon DynamoDB also gives you the flexibility and control to request a strongly consistent read if your application, or an element of your application, requires it. A strongly consistent read returns a result that reflects all writes that received a successful response prior to the read. From the

问题 I have the following scenario which I need to implement following the CQRS pattern: a user logs in the user enters some insurance details the user ask for a decision to be applied the user views the result of the decision This seems fairly straightforward, however my problem is between step 3 and 4, on step 3 I send a ApplyForDecision command which will get a decision from a underwriting service, an event with the result of that decision is then sent to the BUS for the read store to later

问题 Amazon documentation (http://docs.aws.amazon.com/AmazonS3/latest/dev/Introduction.html#ConsistencyModel) states: "Amazon S3 provides read-after-write consistency for PUTS of new objects in your S3 bucket in all regions with one caveat." Ignoring the caveat, this means that a client issuing a GET following a PUT for a new object is guaranteed to get the correct result. My question is, would the guarantee also apply if the GET is issued from a different client not the one which did the PUT

问题 When using distributed and scalable architecture, eventual consistency is often a requirement. Graphically, how to deal with this eventual consistency? Users are used to click save, and see the result instantaneously... with eventual consistency it's not possible. How to deal with the GUI for such scenarios? Please note the question applies both for desktop applications and web applications. PS: I'm working with the Microsoft platform, but I imagine the question applies to any technology...

问题 In a shared expenses app that shows payments dues and shared expenses details for each group. As a financial application, so many operations are transactional, which requires strong consistency to ensure data integrity. We used Entity Groups and ancestor queries which seems to have solved the issue of strong consistency, this caused the entity group to be large in size. As the shared 'group' is now the parent of members, expenses, payments, dues..etc. Until now we don't see a problem, but we

问题 first, here is what is said in Pymongo Documentation By default, PyMongo starts a request for each thread when the thread first runs an operation on MongoDB. This guarantees **read-your-writes consistency . Within a request, the thread will continue to use the same socket exclusively, and no other thread will use this socket, until the thread calls end_request() or it terminates. At that point, the socket is returned to the connection pool for use by other threads. so when using an async

问题 I have been reading and learning about NoSQL and MongoDB, CouchDB, etc, for the last two days, but I still can't tell if this is the right kind of storage for me. What worries me is the eventual consistency thing. Does that type of consistency only kick in when using clusters? (I'm hosting my sites in a single dedicated server, so I don't know if I can benefit from NoSQL) For which kind of applications is OK to have eventual consistency (instead of ACID), and for which ones it isn't? Can you

问题 In a microservice architecture, we usually have two ways to communicate 2 microservices. Let’s say service A needs to get information from service B. The first option is an remote call, usually synchronous over HTTPS, so service A query an API hosted by service B. The second option is adopting an event-driven architecture, where the state of service B can be published and consumed by service A in asynchronous way. Using this model, the service A can update its own database with the

问题 What is the meaning of eventual consistency in Cassandra when nodes in a single cluster do not contain the copies of same data but data is distributed among nodes. Now since a single peice of data is recorded at a single place (node). Why wouldn't Cassandra return the recent value from that single place of record? How do multiple copies arise in this situation? 回答1: Its up to the client to decide the appropriate consistency level (zero, any, one, quoram or all). (The consistency level

问题 I have an app where I am creating a large number of entities. I don't want to put them in the same entity group, because I could be creating a lot of them in a short period of time -- say 1 million in 24 hours. At certain points, I want to get all of these entities with a query like this: Foo.all() How long do I need to wait after the last Foo entity is created to be highly likely to get all of the Foo entities with this query? EDIT: From this question, it seems that I can't get all my