* Part 1 - Parse `not` and `not-join`
* Part 2 - Validate `not` and `not-join` pre-algebrization
* Address review comments rnewman.
* Remove `WhereNotClause` and populate `NotJoin` with `WhereClause`.
* Fix validation for `not` and `not-join`, removing tests that were invalid.
* Address rustification comments.
* Rebase against `rust` branch.
* Part 3 - Add required types for NotJoin.
* Implement `PartialEq` for
`ConjoiningClauses` so `ComputedTable` can be included inside `ColumnConstraint::NotExists`
* Part 4 - Implement `apply_not_join`
* Part 5 - Call `apply_not_join` from inside `apply_clause`
* Part 6 - Translate `not-join` into `NOT EXISTS` SQL
* Address review comments.
* Rename `projected` to `unified` to better describe the fact that we are not projecting any variables.
* Check for presence of each unified var in either `column_bindings` or `input_bindings` and bail if not there.
* Copy over `input_bindings` for each var in `unified`.
* Only copy over the first `column_binding` for each variable in `unified` rather than the whole list.
* Update tests.
* Address review comments.
* Make output from Debug for NotExists more useful
* Clear up misunderstanding. Any single failing clause in the not will cause the entire not to be considered empty
* Address review comments.
* Remove Limit requirement from cc_to_exists.
* Use Entry.or_insert instead of matching on the entry to add to column_bindings.
* Move addition of value_bindings to before apply_clauses on template.
* Tidy up tests with some variable reuse.
* Addressed nits,
* Address review comments.
* Move addition of column_bindings to above apply_clause.
* Update tests.
* Add test to ensure that unbound vars fail
* Improve test for unbound variable to check for correct variable and error
* address nits
* Part 1: define ValueTypeSet.
We're going to use this instead of `HashSet<ValueType>` so that we can clearly express
the empty set and the set of all types, and also to encapsulate a switch to `EnumSet`."
* Part 2: use ValueTypeSet.
* Part 3: fix type expansion.
* Part 4: add a test for type extraction from nested `or`.
* Review comments.
* Review comments: simplify ValueTypeSet.
* Pre: put query parts in alphabetical order.
* Pre: rename 'input' to 'query' in translate tests.
* Part 1: parse :limit.
* Part 2: validate and escape variable parameters in SQL.
* Part 3: algebrize and translate limits.
This adds an `:order` keyword to `:find`.
If present, the results of the query will be an ordered set, rather than
an unordered set; rows will appear in an ordered defined by each
`:order` entry.
Each can be one of three things:
- A var, `?x`, meaning "order by ?x ascending".
- A pair, `(asc ?x)`, meaning "order by ?x ascending".
- A pair, `(desc ?x)`, meaning "order by ?x descending".
Values will be ordered in this sequence for asc, and in reverse for desc:
1. Entity IDs, in ascending numerical order.
2. Booleans, false then true.
3. Timestamps, in ascending numerical order.
4. Longs and doubles, intermixed, in ascending numerical order.
5. Strings, in ascending lexicographic order.
6. Keywords, in ascending lexicographic order, considering the entire
ns/name pair as a single string separated by '/'.
Subcommits:
Pre: make bound_value public.
Pre: generalize ErrorKind::UnboundVariable for use in order.
Part 1: parse (direction, var) pairs.
Part 2: parse :order clause into FindQuery.
Part 3: include order variables in algebrized query.
We add order variables to :with, so we can reuse its type tag projection
logic, and so that we can phrase ordering in terms of variables rather
than datoms columns.
Part 4: produce SQL for order clauses.
* 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!
This commit turns complex `or` -- `or`s in which not all variables are
unified, or in which not all arms are the same shape -- into a
computed table.
We do this by building a template CC that shares some state with the
destination CC, applying each arm of the `or` to a copy of the template
as if it were a standalone query, then building a projection list and
creating a `ComputedTable::Union`. This is pushed into the destination
CC's `computed_tables` list.
Finally, the variables projected from the UNION are bound in the
destination CC, so that unification occurs, and projection of the
outermost query can use bindings established by the `or-join`.
This commit includes projection of type codes from heterogeneous `UNION`
arms: we compute a list of variables for which a definite type is
unknown in at least one arm, and force all arms to project either a type
tag column or a fixed type. It's important that each branch of a UNION
project the same columns in the same order, hence the projection of
fixed values.
The translator is similarly extended to project the type tag column name
or the known value_type_tag to support this.
Review comment: clarify union type extraction.
Part 1, core: use Rc for String and Keyword.
Part 2, query: use Rc for Variable.
Part 3, sql: use Rc for args in SQLiteQueryBuilder.
Part 4, query-algebrizer: use Rc.
Part 5, db: use Rc.
Part 6, query-parser: use Rc.
Part 7, query-projector: use Rc.
Part 8, query-translator: use Rc.
Part 9, top level: use Rc.
Part 10: intern Ident and IdentOrKeyword.
* Add a failing test for EDN parsing '…'.
* Expose a SQLValueType trait to get value_type_tag values out of a ValueType.
* Add accessors to FindSpec.
* Implement querying.
* Implement rudimentary projection.
* Export mentat_db::new_connection.
* Export symbols from mentat.
* Add rudimentary end-to-end query tests.
