mentat/query-algebrizer
Richard Newman 4acc6d0658 InProgressRead, KnownEntid. r=nalexander,emily
Improve naming of read-only transactions.
    Implement entid_for_type.
    Simplify get_attribute.
    Name ignored var in algebrizer.
    Comment attribute_for_ident.
    Make KnownEntid a core concept.
    Expose lookup_value_for_attribute.
    Implement HasSchema and a new query encapsulation on Conn.
    Pre: export Queryable.
2018-01-23 08:40:18 -08:00
..
src InProgressRead, KnownEntid. r=nalexander,emily 2018-01-23 08:40:18 -08:00
tests Preliminary work for vocabulary management. r=emily,nalexander 2018-01-23 08:25:32 -08:00
Cargo.toml Partial work from simple aggregates work (#497) r=nalexander 2017-11-30 15:02:07 -08:00
README.md Partly flesh out query algebrizer. (#243) r=nalexander 2017-02-15 16:10:59 -08:00

This crate turns a parsed query, as defined by the query crate and produced by the query-parser crate, into an algebrized tree, also called a query processor tree.

This is something of a wooly definition: a query algebrizer in a traditional relational database is the component that combines the schema — including column type constraints — with the query, resolving names and that sort of thing. Much of that work is unnecessary in our model; for example, we don't need to resolve column aliases, deal with table names, or that sort of thing. But the similarity is strong enough to give us the name of this crate.

The result of this process is traditionally handed to the query optimizer to yield an execution plan. In our case the execution plan is deterministically derived from the algebrized tree, and the real optimization (such as it is) takes place within the underlying SQLite database.