mentat/docs/apis/rust/0.7.0/search-index.js

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searchIndex["mentat_query"] = {"doc":"","items":[],"paths":[]};
searchIndex["mentat_query_algebrizer"] = {"doc":"","items":[[3,"InvalidBinding","mentat_query_algebrizer","",null,null],[12,"function","","",0,null],[12,"inner","","",0,null],[3,"QueryInputs","","Define the inputs to a query. This is in two parts: a set of values known now, and a set of types known now. The separate map of types is to allow queries to be algebrized without full knowledge of the bindings that will be used at execution time. When built correctly, `types` is guaranteed to contain the types of `values` -- use `QueryInputs::new` or `QueryInputs::with_values` to construct an instance.",null,null],[3,"FindQuery","","A `FindQuery` represents a valid query to the query algebrizer.",null,null],[12,"find_spec","","",1,null],[12,"default_source","","",1,null],[12,"with","","",1,null],[12,"in_vars","","",1,null],[12,"in_sources","","",1,null],[12,"limit","","",1,null],[12,"where_clauses","","",1,null],[12,"order","","",1,null],[3,"Known","","A convenience wrapper around things known in memory: the schema and caches. We use a trait object here to avoid making dozens of functions generic over the type of the cache. If performance becomes a concern, we should hard-code specific kinds of cache right here, and/or eliminate the Option.",null,null],[12,"schema","","",2,null],[12,"cache","","",2,null],[3,"AlgebraicQuery","","",null,null],[12,"find_spec","","",3,null],[12,"with","","The set of variables that the caller wishes to be used for grouping when aggregating. These are specified in the query input, as `:with`, and are then chewed up during projection. If no variables are supplied, then no additional grouping is necessary beyond the non-aggregated projection list.",3,null],[12,"named_projection","","Some query features, such as ordering, are implemented by implicit reference to SQL columns. In order for these references to be 'live', those columns must be projected. This is the set of variables that must be so projected. This is not necessarily every variable that will be so required -- some variables will already be in the projection list.",3,null],[12,"order","","",3,null],[12,"limit","","",3,null],[12,"cc","","",3,null],[3,"ConjoiningClauses","","A `ConjoiningClauses` (CC) is a collection of clauses that are combined with `JOIN`.  The topmost form in a query is a `ConjoiningClauses`.",null,null],[12,"empty_because","","`Some` if this set of clauses cannot yield results in the context of the current schema.",4,null],[12,"from","","A vector of source/alias pairs used to construct a SQL `FROM` list.",4,null],[12,"computed_tables","","A vector of computed tables (typically subqueries). The index into this vector is used as an identifier in a `DatomsTable::Computed(c)` table reference.",4,null],[12,"wheres","","A list of fragments that can be joined by `AND`.",4,null],[12,"column_bindings","","A map from var to qualified columns. Used to project.",4,null],[12,"input_variables","","A list of variables mentioned in the enclosing query's :in clause. These must all be bound before the query can be executed. TODO: clarify what this means for nested CCs.",4,null],[12,"known_types","","A map from var to type. Whenever a var maps unambiguously to two different types, it cannot yield results, so we don't represent that case here. If a var isn't present in the map, it means that its type is not known in advance. Usually that state should be represented by `ValueTypeSet::Any`.",4,null],[12,"extracted_types","","A mapping, similar to `column_bindings`, but used to pull type tags out of the store at runtime. If a var isn't unit in `known_types`, it should be present here.",4,null],[3,"ColumnAlternation","","A `ColumnAlternation` constraint is satisfied if at least one of its inner constraints is satisfied. An empty `ColumnAlternation` is never satisfied.",null,null],[12,"0","","",5,null],[3,"ColumnIntersection","","A `ColumnIntersection` constraint is satisfied if all of its inner constraints are satisfied. An empty intersection is always satisfied.",null,null],[12,"0","","",6,null],[3,"OrderBy","","Represents an entry in the ORDER 
searchIndex["mentat_query_projector"] = {"doc":"","items":[[3,"ConstantProjector","mentat_query_projector","A projector that produces a `QueryResult` containing fixed data. Takes a boxed function that should return an empty result set of the desired type.",null,null],[3,"RelResult","","The result you get from a 'rel' query, like:",null,null],[12,"width","","",0,null],[12,"values","","",0,null],[3,"QueryOutput","","",null,null],[12,"spec","","",1,null],[12,"results","","",1,null],[3,"CombinedProjection","","Combines the things you need to turn a query into SQL and turn its results into `QueryResults`: SQL-related projection information (`DISTINCT`, columns, etc.) and a Datalog projector that turns SQL into structures.",null,null],[12,"sql_projection","","A SQL projection, mapping columns mentioned in the body of the query to columns in the output.",2,null],[12,"pre_aggregate_projection","","If a query contains aggregates, we need to generate a nested subquery: an inner query that returns our distinct variable bindings (and any `:with` vars), and an outer query that applies aggregation. That's so we can put `DISTINCT` in the inner query and apply aggregation afterwards -- `SELECT DISTINCT count(foo)` counts then uniques, and we need the opposite to implement Datalog distinct semantics. If this is the case, `sql_projection` will be the outer query's projection list, and `pre_aggregate_projection` will be the inner. If the query doesn't use aggregation, this field will be `None`.",2,null],[12,"datalog_projector","","A Datalog projection. This consumes rows of the appropriate shape (as defined by the SQL projection) to yield one of the four kinds of Datalog query result.",2,null],[12,"distinct","","True if this query requires the SQL query to include DISTINCT.",2,null],[12,"group_by_cols","","",2,null],[4,"SimpleAggregationOp","","",null,null],[13,"Avg","","",3,null],[13,"Count","","",3,null],[13,"Max","","",3,null],[13,"Min","","",3,null],[13,"Sum","","",3,null],[4,"QueryResults","","",null,null],[13,"Scalar","","",4,null],[13,"Tuple","","",4,null],[13,"Coll","","",4,null],[13,"Rel","","",4,null],[5,"projected_column_for_var","","Return the projected column -- that is, a value or SQL column and an associated name -- for a given variable. Also return the type. Callers are expected to determine whether to project a type tag as an additional SQL column.",null,{"inputs":[{"name":"variable"},{"name":"conjoiningclauses"}],"output":{"name":"result"}}],[5,"query_projection","","Compute a suitable SQL projection for an algebrized query. This takes into account a number of things: - The variable list in the find spec. - The presence of any aggregate operations in the find spec. TODO: for now we only handle   simple variables - The bindings established by the topmost CC. - The types known at algebrizing time. - The types extracted from the store for unknown attributes.",null,{"inputs":[{"name":"schema"},{"name":"algebraicquery"}],"output":{"generics":["either"],"name":"result"}}],[0,"errors","","",null,null],[4,"ProjectorError","mentat_query_projector::errors","",null,null],[13,"NotYetImplemented","","We're just not done yet.  Message that the feature is recognized but not yet implemented.",5,null],[13,"CannotProjectImpossibleBinding","","",5,null],[13,"CannotApplyAggregateOperationToTypes","","",5,null],[13,"InvalidProjection","","",5,null],[13,"UnboundVariable","","",5,null],[13,"NoTypeAvailableForVariable","","",5,null],[13,"UnexpectedResultsType","","",5,null],[13,"AmbiguousAggregates","","",5,null],[6,"Result","","",null,null],[11,"fmt","","",5,{"inputs":[{"name":"self"},{"name":"formatter"}],"output":{"name":"result"}}],[11,"cause","","",5,{"inputs":[{"name":"self"}],"output":{"generics":["fail"],"name":"option"}}],[11,"backtrace","","",5,{"inputs":[{"name":"self"}],"output":{"generics":["backtrace"],"name":"option"}}],[11,"fmt","","",5,{"inputs":[{"name":"self"},{"name":"formatter"}],"output":{"name":"result"}}],[11,"clone","mentat_query_projector","",3,{"inputs":[{"name":"self"}],"output":{"name":"simpleaggregationop"}}],[11,"
searchIndex["mentat_query_pull"] = {"doc":"","items":[[3,"Puller","mentat_query_pull","A `Puller` constructs on demand a map from a provided set of entity IDs to a set of structured maps.",null,null],[5,"pull_attributes_for_entity","","",null,{"inputs":[{"name":"schema"},{"name":"connection"},{"name":"entid"},{"name":"a"}],"output":{"generics":["structuredmap"],"name":"result"}}],[5,"pull_attributes_for_entities","","",null,{"inputs":[{"name":"schema"},{"name":"connection"},{"name":"e"},{"name":"a"}],"output":{"generics":["btreemap"],"name":"result"}}],[0,"errors","","",null,null],[4,"PullError","mentat_query_pull::errors","",null,null],[13,"UnnamedAttribute","","",0,null],[13,"RepeatedDbId","","",0,null],[6,"Result","","",null,null],[11,"fmt","","",0,{"inputs":[{"name":"self"},{"name":"formatter"}],"output":{"name":"result"}}],[11,"cause","","",0,{"inputs":[{"name":"self"}],"output":{"generics":["fail"],"name":"option"}}],[11,"backtrace","","",0,{"inputs":[{"name":"self"}],"output":{"generics":["backtrace"],"name":"option"}}],[11,"fmt","","",0,{"inputs":[{"name":"self"},{"name":"formatter"}],"output":{"name":"result"}}],[11,"prepare","mentat_query_pull","",1,{"inputs":[{"name":"schema"},{"generics":["pullattributespec"],"name":"vec"}],"output":{"generics":["puller"],"name":"result"}}],[11,"pull","","",1,{"inputs":[{"name":"self"},{"name":"schema"},{"name":"connection"},{"name":"e"}],"output":{"generics":["btreemap"],"name":"result"}}]],"paths":[[4,"PullError"],[3,"Puller"]]};
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