I dont know your requirement and hence I cannot say for sure which is good option for you, because it depends on the concern. In terms of good option, you have to weigh your options based on above requirements. Here is an article that deals with both the issues The cache, your application rereads the file, and a new version of the item is inserted. When the file is updated, perhaps even by a separate application, the item is removed from If you write an application that processes stock quotes from an XML file, you can insert the data from the file in the Cache and maintain a dependency on that XML file. You can use this technique to remove items from the Cache when their data source changes. If a dependency changes, the cached item is invalidated and removed from the Cache. These are calledįile dependencies and key dependencies. Please consultĪSP.NET allows you to define the validity of a cached item, based on an external file, a directory, or another cached item. The dataset is available in the cache if not, you must recreate it and put a copy back in the cache. But because the dataset is not guaranteed to be in the cache, you must add logic to your page to check that Using a cache can partly offset this problem, because the cache manager will discard the dataset if the server needs memory or if cached data expires. Many users choose to create a separate blocklist just for iOS Apps they would like to block. Select an existing blocklist to edit it, or tap Add a blocklist to create a new blocklist. If you store too much data (a large dataset, or many users storing small datasets), it can affect server performance and scalability. From the Freedom iOS app, select the Blocklists tab: 2. However storing the dataset on the server uses server resources. The question then is whether to save it on client or Server. It better for your application to recreate the dataset with each round trip. If you are working with very volatile data (inventory data, for instance), you might find (An option is to store data in the page for details, see the next section.)Īnother potential drawback is that the dataset can get out of sync with the data source, since you are not refreshing the dataset each time the user clicks a button. If multiple users create large datasets, you can quickly consume available server memory. If the dataset is very large, for example, it can take considerable server memory to store it. An important one is that the dataset consumes memory between round trips. However, saving the dataset has a number of drawbacks. If you save and restore the dataset, on the other hand, you do not need to go back to the source just to get a few more records. You have two choice either to save dataset or create and dispose dataset in each run, however you have to view this in light of following info. Please read here for a brief explanation of various strategies Dataset itself is an inmemory cache of records.
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