This section outlines advantages and usage scenarios for the
memcached interface to
InnoDB tables introduced in
Section 14.2.17, “
InnoDB Integration with memcached”. The combination of
InnoDB tables and memcached
offers advantages over using either by themselves:
Raw performance for simple lookups. Direct access to the
InnoDB storage engine avoids the parsing
and planning overhead of SQL. Running
memcached in the same process space as the
MySQL server avoids the network overhead of passing requests
back and forth.
Data is stored in a MySQL database to protect against crashes, outages, and corruption.
The transfer between memory and disk is handled automatically, simplifying application logic.
Data can be unstructured or structured, depending on the type of application. You can make an all-new table for the data, or map the NoSQL-style processing to one or more existing tables.
You can still access the underlying table through SQL, for reporting, analysis, ad hoc queries, bulk loading, set operations such as union and intersection, and other operations well suited to the expressiveness and flexibility of SQL.
You can ensure high availability of the NoSQL data by using this feature on a master server in combination with MySQL replication.
The integration of memcached with MySQL
provides a painless way to make the in-memory data persistent,
so you can use it for more significant kinds of data. You can
similar write operations into your application, without
worrying that the data could disappear at any moment. You can
stop and start the memcached server without
losing updates made to the cached data. To guard against
unexpected outages, you can take advantage of
InnoDB crash recovery, replication, and
InnoDB does fast
primary key lookups is
a natural fit for memcached single-item
queries. The direct, low-level database access path used by
the memcached plugin is much more efficient
for key-value lookups than equivalent SQL queries.
The serialization features of memcached, which can turn complex data structures, binary files, or even code blocks into storeable strings, offer a simple way to get such objects into a database.
Because you can access the underlying data through SQL, you
can produce reports, search or update across multiple keys,
and call functions such as
MAX() on the memcached
data. All of these operations are expensive or complicated
with the standalone memcached.
You do not need to manually load data into
memcached at startup. As particular keys
are requested by an application, the values are retrieved from
the database automatically, and cached in memory using the
Because memcached consumes relatively little CPU, and its memory footprint is easy to control, it can run comfortably alongside a MySQL instance on the same system.
Because data consistency is enforced through the usual
mechanism as with regular
you do not have to worry about stale
memcached data or fallback logic to query
the database in the case of a missing key.