Hi Alireza,

Points is the most common use case, and that is why we made the
SimplePointLayer to minimise complexity for this case. This is also why you
see so many examples with points only.

However, Neo4j Spatial was built with complex geometries in mind, so they
are fully supported, and you should use a WKB or WKT layer should you use
those. The best source of examples for this are the test cases in the code
on github.

Note that you must be careful not to mix layer types. If you make a layer
with one config, you must add nodes of that same config. A safer option is
to add the geometry and allow the layer to make the node, but if you want
more control, you can add the node only if you take care yourself to ensure
the node has the same config as the layer (ie. add a WKB node to a WKB
layer).

Currently there is no choice of index, as all layer types use a RTree index
build into the graph model. This is generalized for all geometries, and is
not optimized to any particular type. We had planned to add more index
types to increase performance, but instead we are taking a different
direction, building a new 'points only' spatial support into Neo4j itself,
which will use an index optimized for points. This means that, for a while,
the best solution for points will be the built-in spatial, and the best
solution for complex geometries will be the external 'Neo4j Spatial'
library. There is, however, no scheduled release date yet.

Regards, Craig

On Sun, Aug 9, 2015 at 7:12 PM, Alireza Rezaei Mahdiraji <
[email protected]> wrote:

>
> Hi,
>
> Most of the examples I found assume one type of geometry (mostly point)
> and then build layer and index accordingly.
>
> In my case, the nodes can be points, lines or polygons. My query set range
> from
> finding nearest neighbors to finding the polygon which an arbitrary point
> is located in, etc.
>
> Any advice on a good design is appreciated: how many layers and what kind
> of indexes, etc.
>
> Thanks,
> Cheers,
> Alireza
>
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