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This page provides code examples in Java for using the low-level Memcache API.
Python code for using Memcache. Memcache is a high-performance, distributed memory object caching system that provides fast access to cached data. To learn more about memcache, read the Memcache Overview.
Low-level API example using the synchronous MemcacheService:
View MemcacheSyncCacheServlet.java on GitHub (region:
example)
Low-level API example using AsyncMemcacheService:
View MemcacheAsyncCacheServlet.java on GitHub (region:
example)
For more information on the low-level API, see the Memcache Javadoc.
Memcache is typically used with the following pattern:
- The application receives a query from the user or the application. * The
application checks whether the data needed to satisfy that query is in memcache.
- If the data is in memcache, the application uses that data.
- If the data is not in memcache, the application queries the datastore and stores the results in memcache for future requests.
The pseudocode below represents a typical memcache request:
ndb internally uses memcache to speed up queries. However, if you wish, you
can also explicitly add memcache calls to gain more control about the speed-ups.
The following example demonstrates several ways to set values in memcache using the Python API.
To learn more about the add(), set_multi(), and set() methods, see the
memcache Python API
documentation.
Note: The standard Python pickle module is used to auto pickle and depickle data moved into and out of memcache.