Classes
class	TAtomicPredicate
	Atomic predicate - encapsulates comparison operations. More...

class	TPredicateNode
	Predicate node - represents a binary predicate operation on two predicate nodes. More...

class	TPredicate
	Predicate - encapsulates comparison operations. More...

class	TTableContext
	Execution context. More...

class	TPrimitive
	Primitive class: Wrapper around primitive data types. More...

class	TTableRow
	Table Row (Record) More...

class	GroupStmt
	A class representing a cached grouping statement identifier. More...

class	TRowIterator
	Iterator class for TTable rows. More...

class	TRowIteratorWithRemove
	Iterator class for TTable rows, that allows logical row removal while iterating. More...

class	TTableIterator
	Iterator over a vector of tables. More...

class	TTable
	Table class: Relational table with columnar data storage. More...

class	TTable::TLoadVecInit

Namespaces
	TSnap
	Main namespace for all the Snap global entities.

Typedefs
typedef TPt< TTable >	PTable

typedef TPair< TIntV, TFltV >	TGroupKey
	Represents grouping key with IntV for integer and string attributes and FltV for float attributes. More...

typedef TVec< TPair< TStr, TAttrType > >	Schema
	A table schema is a vector of pairs <attribute name, attribute type>. More...

typedef TPair< TStr, TAttrType >	TStrTypPr

Enumerations
enum	TPredOp { NOT, AND, OR, NOP }
	Boolean operators for selection predicates. More...

enum	TPredComp { LT = 0, LTE, EQ, NEQ, GTE, GT, SUBSTR, SUPERSTR }
	Comparison operators for selection predicates. More...

enum	TSimType { L1Norm, L2Norm, Jaccard, Haversine }
	Distance metrics for similarity joins. More...

enum	TAttrAggr { aaMin, aaMax, aaFirst, aaLast, aaMean, aaMedian, aaSum, aaCount }
	Possible policies for aggregating node attributes. More...

enum	TArithOp { aoAdd, aoSub, aoMul, aoDiv, aoMod, aoMin, aoMax }
	Possible column-wise arithmetic operations. More...

Functions
template<class PGraph >
PGraph	TSnap::ToGraph (PTable Table, const TStr &SrcCol, const TStr &DstCol, TAttrAggr AggrPolicy)
	Sequentially converts the table into a graph with links from nodes in `SrcCol` to those in `DstCol`. More...

template<class PGraph >
PGraph	TSnap::ToNetwork (PTable Table, const TStr &SrcCol, const TStr &DstCol, TStrV &SrcAttrV, TStrV &DstAttrV, TStrV &EdgeAttrV, TAttrAggr AggrPolicy)
	Converts the Table into a graph with edges from `SrcCol` to `DstCol`, and attribute vector defined by the arguments. More...

template<class PGraph >
PGraph	TSnap::ToNetwork (PTable Table, const TStr &SrcCol, const TStr &DstCol, TAttrAggr AggrPolicy)
	Calls ToNetwork with an empty attribute vector. Convenience wrapper. More...

template<class PGraph >
PGraph	TSnap::ToNetwork (PTable Table, const TStr &SrcCol, const TStr &DstCol, TStrV &EdgeAttrV, TAttrAggr AggrPolicy)
	Converts table to a network sequentially. Use if network has only edge attributes. More...

template<class PGraph >
PGraph	TSnap::ToNetwork (PTable Table, const TStr &SrcCol, const TStr &DstCol, TStrV &EdgeAttrV, PTable NodeTable, const TStr &NodeCol, TStrV &NodeAttrV, TAttrAggr AggrPolicy)
	Converts table to network sequentially. Takes edges from `Table` and nodes explicitly from `NodeCol` in `NodeTable`, with attribute vectors passed as columns in corresponding tables. More...

int	TSnap::LoadCrossNet (TCrossNet &Graph, PTable Table, const TStr &SrcCol, const TStr &DstCol, TStrV &EdgeAttrV)
	Loads the edges from the TTable and EdgeAttrV specifies columns containing edge attributes. More...

int	TSnap::LoadMode (TModeNet &Graph, PTable Table, const TStr &NCol, TStrV &NodeAttrV)
	Loads the nodes specified in column NCol from the TTable with the attributes specified in NodeAttrV. More...

template<class PGraphMP >
PGraphMP	TSnap::ToGraphMP (PTable Table, const TStr &SrcCol, const TStr &DstCol)
	Performs table to graph conversion in parallel using the sort-first algorithm. This is the recommended method to use. More...

template<class PGraphMP >
PGraphMP	TSnap::ToGraphMP3 (PTable Table, const TStr &SrcCol, const TStr &DstCol)
	Performs table to graph conversion in parallel. Uses the hash-first method, which is less optimal, use ToGraphMP instead. More...

template<class PGraphMP >
PGraphMP	TSnap::ToNetworkMP (PTable Table, const TStr &SrcCol, const TStr &DstCol, TStrV &SrcAttrV, TStrV &DstAttrV, TStrV &EdgeAttrV, TAttrAggr AggrPolicy)
	Does Table to Network conversion in parallel using the sort-first algorithm. This is the recommended method to use. More...

template<class PGraphMP >
PGraphMP	TSnap::ToNetworkMP2 (PTable Table, const TStr &SrcCol, const TStr &DstCol, TStrV &SrcAttrV, TStrV &DstAttrV, TStrV &EdgeAttrV, TAttrAggr AggrPolicy)
	Implements table to network conversion in parallel. Not the recommended algorithm, using ToNetworkMP instead. More...

template<class PGraphMP >
PGraphMP	TSnap::ToNetworkMP (PTable Table, const TStr &SrcCol, const TStr &DstCol, TStrV &EdgeAttrV, TAttrAggr AggrPolicy)
	Converts table to network in parallel. Use if network has only edge attributes. More...

template<class PGraphMP >
PGraphMP	TSnap::ToNetworkMP (PTable Table, const TStr &SrcCol, const TStr &DstCol, TAttrAggr AggrPolicy)
	Calls ToNetworkMP with empty attribute vector. Convenience wrapper. More...

template<class PGraphMP >
PGraphMP	TSnap::ToNetworkMP (PTable Table, const TStr &SrcCol, const TStr &DstCol, TStrV &EdgeAttrV, PTable NodeTable, const TStr &NodeCol, TStrV &NodeAttrV, TAttrAggr AggrPolicy)
	Converts table to network in parallel. Takes edges from `Table` and nodes explicitly from `NodeCol` in `NodeTable`, with attribute vectors passed as columns in corresponding tables. More...