Each MLD cell has source and destination nodes.
MLD is keeping a |source| x |destination| sized table
for various metrics (distances, durations, etc) from each
source to all destinations in a cell.
It stores all of the values for a metric in one large array, with
an offset for each cell to find its values. The offset is currently
limited to 32 bit values, which overflows on very large graphs
(e.g. Planet OSM).
We fix this by changing the offsets to be uint64_t types.
The generation of level masks for compactly storing partition cells
supports sizes that can be stored in 64 bits.
The current implementation fails if the total bit sum is 64 bits
exactly. A bit shift mechanism is used that is undefined when the
shift size is equal to the bit size of the underlying type. This
generates an incorrect mask value.
We fix this by adding a special case for a 64 bit offset. Given this
code is called at most |level| times, there will be no effect on
performance. We also update the assertions to reflect 64 bit masks
are now supported.
As part of graph contraction, node renumbering leads to
in-place permuting of graph state, including boolean vector elements.
std::vector<bool> returns proxy objects when referencing individual
bits. To correctly swap bool elements using MSVC, we need to explicitly
apply std::vector<bool>::swap.
Making this change fixes osrm-contract on Windows.
We also correct failing tests and other undefined behaviours
(mainly iterator access outside boundaries) highlighted by MSVC.
For very large graphs, generation of MLD level masks fail on Windows
due to bit shift overflow of unsigned long values.
Correct by using unsigned long long literals, which are 64 bit on
all major systems.
For the MLD algorithm we can partition the NodeID range into boundary
and non-boundary nodes. Since there are only we boundary nodes we can
use the ArrayStorage for those yielding much faster query times.
Rename module partition to partitioner.
This cultivates naming used in existing modules like extractor,
customizer, etc. - noun vs verb (word partition is both though).
