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Mike Bayer
31 lines
1.5 KiB
Python
31 lines
1.5 KiB
Python
"""A basic example of using the SQLAlchemy Sharding API.
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Sharding refers to horizontally scaling data across multiple
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databases.
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The basic components of a "sharded" mapping are:
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* multiple databases, each assigned a 'shard id'
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* a function which can return a single shard id, given an instance
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to be saved; this is called "shard_chooser"
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* a function which can return a list of shard ids which apply to a particular
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instance identifier; this is called "id_chooser". If it returns all shard ids,
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all shards will be searched.
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* a function which can return a list of shard ids to try, given a particular
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Query ("query_chooser"). If it returns all shard ids, all shards will be
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queried and the results joined together.
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In this example, four sqlite databases will store information about weather
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data on a database-per-continent basis. We provide example shard_chooser,
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id_chooser and query_chooser functions. The query_chooser illustrates
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inspection of the SQL expression element in order to attempt to determine a
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single shard being requested.
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The construction of generic sharding routines is an ambitious approach
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to the issue of organizing instances among multiple databases. For a
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more plain-spoken alternative, the "distinct entity" approach
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is a simple method of assigning objects to different tables (and potentially
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database nodes) in an explicit way - described on the wiki at
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`EntityName <http://www.sqlalchemy.org/trac/wiki/UsageRecipes/EntityName>`_.
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"""
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