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as an only index
Use HASH index:
if it is a secondary key
if you 100% won't need to make it non-unique
if you have taken measurements on your data and you see an accountable increase in performance
if you save every byte on tuples (HASH is a little more compact)
RTREE indexes
RTREE is a multidimensional index supporting up to 20 dimensions. It is used especially for indexing spatial information, such as geographical objects. In :ref:`this example <box_index-rtree>` we demonstrate spatial searches via RTREE index.
RTREE index could not be primary, and could not be unique. The option list of this type of index may contain ``dimension`` and ``distance`` options. The ``parts`` definition must contain the one and only part with type ``array``. RTREE index can accept two types of ``distance`` functions: ``euclid`` and ``manhattan``.
Currently, the :ref:`isolation level <transaction_model_levels>` of RTREE indexes in :ref:`MVCC transaction mode <txn_mode_mvcc-tnx-manager>` is *read-committed* (not *serializable*, as stated). If a transaction uses these indexes, it can read committed or confirmed data (depending on the isolation level). However, the indexes are subject to different anomalies that can make them unserializable.
**Example 1:**
my_space = box.schema.create_space("tester")
my_space:format({ { type = 'number', name = 'id' }, { type = 'array', name = 'content' } })
hash_index = my_space:create_index('primary', { type = 'tree', parts = {'id'} })
rtree_index = my_space:create_index('spatial', { type = 'RTREE', unique = false, parts = {'content'} })
Corresponding tuple field thus must be an array of 2 or 4 numbers. 2 numbers mean a point {x, y}; 4 numbers mean a rectangle {x1, y1, x2, y2}, where (x1, y1) and (x2, y2) - diagonal point of the rectangle.
my_space:insert{1, {1, 1}}
my_space:insert{2, {2, 2, 3, 3}}
Selection results depend on a chosen iterator. The default EQ iterator searches for an exact rectangle, a point is treated as zero width and height rectangle:
tarantool> rtree_index:select{1, 1}
---
- - [1, [1, 1]]
...

tarantool> rtree_index:select{1, 1, 1, 1}
---
- - [1, [1, 1]]
...

tarantool> rtree_index:select{2, 2}
---
- []
...

tarantool> rtree_index:select{2, 2, 3, 3}
---
- - [2, [2, 2, 3, 3]]
...
Iterator ALL, which is the default when no key is specified, selects all tuples in arbitrary order:
tarantool> rtree_index:select{}
---
- - [1, [1, 1]]
- [2, [2, 2, 3, 3]]
...
Iterator LE (less or equal) searches for tuples with their rectangles within a specified rectangle:
tarantool> rtree_index:select({1, 1, 2, 2}, {iterator='le'})
---
- - [1, [1, 1]]
...
Iterator LT (less than, or strictly less) searches for tuples with their rectangles strictly within a specified rectangle:
tarantool> rtree_index:select({0, 0, 3, 3}, {iterator = 'lt'})
---
- - [1, [1, 1]]
...
Iterator GE searches for tuples with a specified rectangle within their rectangles:
tarantool> rtree_index:select({1, 1}, {iterator = 'ge'})
---
- - [1, [1, 1]]
...
Iterator GT searches for tuples with a specified rectangle strictly within their rectangles:
tarantool> rtree_index:select({2.1, 2.1, 2.9, 2.9}, {iterator = 'gt'})
---
- []
...
Iterator OVERLAPS searches for tuples with their rectangles overlapping specified rectangle:
tarantool> rtree_index:select({0, 0, 10, 2}, {iterator='overlaps'})
---
- - [1, [1, 1]]
- [2, [2, 2, 3, 3]]
...
Iterator NEIGHBOR searches for all tuples and orders them by distance to the specified point:
tarantool> for i=1,10 do
> for j=1,10 do
> my_space:insert{i*10+j, {i, j, i+1, j+1}}
> end
> end
---
...

tarantool> rtree_index:select({1, 1}, {iterator = 'neighbor', limit = 5})
---
- - [11, [1, 1, 2, 2]]
- [12, [1, 2, 2, 3]]
- [21, [2, 1, 3, 2]]
- [22, [2, 2, 3, 3]]
- [31, [3, 1, 4, 2]]
...
**Example 2:**

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testing_project / Documentation: concepts/data_model/indexes — English

tarantool> rtree_index:select{1, 1}
---
- - [1, [1, 1]]
...

tarantool> rtree_index:select{1, 1, 1, 1}
---
- - [1, [1, 1]]
...

tarantool> rtree_index:select{2, 2}
---
- []
...

tarantool> rtree_index:select{2, 2, 3, 3}
---
- - [2, [2, 2, 3, 3]]
...
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