mentat/query-algebrizer
Richard Newman 64acc6a7ee Support :with (#311) (#414) r=nalexander
* Pre: refactor projector code.
* Part 1: maintain 'with' variables in AlgebrizedQuery.
* Part 2: include necessary 'with' variables in SQL projection list.

The test produces projection elements for `:with`, even though there are
no aggregates in the query. This test will need to be adjusted when we
optimize this away!
2017-04-17 09:23:55 -07:00
..
src Support :with (#311) (#414) r=nalexander 2017-04-17 09:23:55 -07:00
Cargo.toml Add validation for or-join. r=nalexander 2017-03-27 16:32:45 -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.