mentat/query-algebrizer
Emily Toop e1e7cbaa44
Closes #634 - Fix variables in predicates (#635) r=rnewman
We were forgetting to check for bound variables when resolving types other than ref types during inequality handling. This patch adds in the binding checks and `bails` if the bound variable is of the wrong type. #634
2018-05-09 16:24:12 +01:00
..
src Closes #634 - Fix variables in predicates (#635) r=rnewman 2018-05-09 16:24:12 +01:00
tests Closes #634 - Fix variables in predicates (#635) r=rnewman 2018-05-09 16:24:12 +01:00
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.