mentat/query-algebrizer
Richard Newman 17c59bbff6 Apply newly bound values to existing columns.
This commit lifts some logic out of the scalar ground handler to apply
elsewhere.

When a new value binding is encountered for a variable to which column
bindings have already been established, we do two things:

- We apply a new constraint to the primary column. This ensures that the
  behavior for ground-first and ground-second is equivalent.
- We eliminate any existing column type extraction: it won't be
  necessary now that a constant value and constant type are known.
2017-06-15 10:28:09 -07:00
..
src Apply newly bound values to existing columns. 2017-06-15 10:28:09 -07:00
tests Add a test that late inputs aren't allowed in ground. 2017-06-15 10:28:05 -07:00
Cargo.toml Part 3: Handle ground. (#469) r=nalexander,rnewman 2017-06-09 20:18:31 -07:00
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.