2015-04-08 08:52:58 +00:00
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< h1 > Module machi_chash< / h1 >
< ul class = "index" > < li > < a href = "#description" > Description< / a > < / li > < li > < a href = "#types" > Data Types< / a > < / li > < li > < a href = "#index" > Function Index< / a > < / li > < li > < a href = "#functions" > Function Details< / a > < / li > < / ul > Consistent hashing library.
< h2 > < a name = "description" > Description< / a > < / h2 > < p > Consistent hashing library. Also known as "random slicing".< / p >
This code was originally from the Hibari DB source code at
< a href = "https://github.com/hibari" target = "_top" > < tt > https://github.com/hibari< / tt > < / a >
< h2 > < a name = "types" > Data Types< / a > < / h2 >
< h3 class = "typedecl" > < a name = "type-float_map" > float_map()< / a > < / h3 >
< p > < tt > float_map() = [{< a href = "#type-owner_name" > owner_name()< / a > , float()}]< / tt > < / p >
< p > A float map subdivides the unit interval, starting at 0.0, to
partitions that are assigned to various owners. The sum of all
floats must be exactly 1.0 (or close enough for floating point
purposes).< / p >
< h3 class = "typedecl" > < a name = "type-float_tree" > float_tree()< / a > < / h3 >
< p > < b > abstract datatype< / b > : < tt > float_tree()< / tt > < / p >
< p > We can't use gb_trees:tree() because 'nil' (the empty tree) is
never valid in our case. But teaching Dialyzer that is difficult.< / p >
< h3 class = "typedecl" > < a name = "type-nextfloat_list" > nextfloat_list()< / a > < / h3 >
< p > < tt > nextfloat_list() = [{float(), < a href = "#type-brick" > brick()< / a > }]< / tt > < / p >
< p > A nextfloat_list
differs from a float_map in two respects: 1) nextfloat_list contains
tuples with the brick name in 2nd position, 2) the float() at each
position I_n > I_m, for all n, m such that n > m.
For example, a nextfloat_list of the float_map example above,
[{0.25, {br1, nd1}}, {0.75, {br2, nd1}}, {1.0, {br3, nd1}].< / p >
< h3 class = "typedecl" > < a name = "type-owner_int_range" > owner_int_range()< / a > < / h3 >
< p > < tt > owner_int_range() = {< a href = "#type-owner_name" > owner_name()< / a > , non_neg_integer(), non_neg_integer()}< / tt > < / p >
< p > Used when "prettying" a float map.< / p >
< h3 class = "typedecl" > < a name = "type-owner_name" > owner_name()< / a > < / h3 >
< p > < tt > owner_name() = term()< / tt > < / p >
< p > Owner for a range on the unit interval. We are agnostic about its
type.< / p >
< h3 class = "typedecl" > < a name = "type-owner_weight" > owner_weight()< / a > < / h3 >
< p > < tt > owner_weight() = {< a href = "#type-owner_name" > owner_name()< / a > , < a href = "#type-weight" > weight()< / a > }< / tt > < / p >
< h3 class = "typedecl" > < a name = "type-owner_weight_list" > owner_weight_list()< / a > < / h3 >
< p > < tt > owner_weight_list() = [< a href = "#type-owner_weight" > owner_weight()< / a > ]< / tt > < / p >
< p > A owner_weight_list is a definition of brick assignments over the
unit interval [0.0, 1.0]. The sum of all floats must be 1.0. For
example, [{{br1,nd1}, 0.25}, {{br2,nd1}, 0.5}, {{br3,nd1}, 0.25}].< / p >
< h3 class = "typedecl" > < a name = "type-weight" > weight()< / a > < / h3 >
< p > < tt > weight() = non_neg_integer()< / tt > < / p >
< p > For this library, a weight is an integer which specifies the
capacity of a "owner" relative to other owners. For example, if
owner A with a weight of 10, and if owner B has a weight of 20,
then B will be assigned twice as much of the unit interval as A.< / p >
< h2 > < a name = "index" > Function Index< / a > < / h2 >
< table width = "100%" border = "1" cellspacing = "0" cellpadding = "2" summary = "function index" > < tr > < td valign = "top" > < a href = "#hash_binary_via_float_map-2" > hash_binary_via_float_map/2< / a > < / td > < td > Query a float map with a binary (inefficient).< / td > < / tr >
< tr > < td valign = "top" > < a href = "#hash_binary_via_float_tree-2" > hash_binary_via_float_tree/2< / a > < / td > < td > Query a float tree with a binary.< / td > < / tr >
< tr > < td valign = "top" > < a href = "#make_demo_map1-0" > make_demo_map1/0< / a > < / td > < td > Create a sample float map.< / td > < / tr >
< tr > < td valign = "top" > < a href = "#make_demo_map2-0" > make_demo_map2/0< / a > < / td > < td > Create a sample float map.< / td > < / tr >
< tr > < td valign = "top" > < a href = "#make_float_map-1" > make_float_map/1< / a > < / td > < td > Create a float map, based on a basic owner weight list.< / td > < / tr >
< tr > < td valign = "top" > < a href = "#make_float_map-2" > make_float_map/2< / a > < / td > < td > Create a float map, based on an older float map and a new weight
list.< / td > < / tr >
< tr > < td valign = "top" > < a href = "#make_tree-1" > make_tree/1< / a > < / td > < td > Create a float tree, which is the rapid lookup data structure
for consistent hash queries.< / td > < / tr >
< tr > < td valign = "top" > < a href = "#pretty_with_integers-2" > pretty_with_integers/2< / a > < / td > < td > Make a pretty/human-friendly version of a float map that describes
integer ranges between 1 and < code > Scale< / code > .< / td > < / tr >
< tr > < td valign = "top" > < a href = "#pretty_with_integers-3" > pretty_with_integers/3< / a > < / td > < td > Make a pretty/human-friendly version of a float map (based
upon a float map created from < code > OldWeights< / code > and < code > NewWeights< / code > ) that
describes integer ranges between 1 and < code > Scale< / code > .< / td > < / tr >
< tr > < td valign = "top" > < a href = "#query_tree-2" > query_tree/2< / a > < / td > < td > Low-level function for querying a float tree: the (floating
point) point within the unit interval.< / td > < / tr >
< tr > < td valign = "top" > < a href = "#sum_map_weights-1" > sum_map_weights/1< / a > < / td > < td > Create a human-friendly summary of a float map.< / td > < / tr >
< tr > < td valign = "top" > < a href = "#zzz_usage_details-0" > zzz_usage_details/0< / a > < / td > < td > Various usage examples, see source code below this function
for full details.< / td > < / tr >
< / table >
< h2 > < a name = "functions" > Function Details< / a > < / h2 >
< h3 class = "function" > < a name = "hash_binary_via_float_map-2" > hash_binary_via_float_map/2< / a > < / h3 >
< div class = "spec" >
< p > < tt > hash_binary_via_float_map(Key::binary(), Map::< a href = "#type-float_map" > float_map()< / a > ) -> {float(), < a href = "#type-owner_name" > owner_name()< / a > }< / tt > < br > < / p >
< / div > < p > Query a float map with a binary (inefficient).< / p >
< h3 class = "function" > < a name = "hash_binary_via_float_tree-2" > hash_binary_via_float_tree/2< / a > < / h3 >
< div class = "spec" >
< p > < tt > hash_binary_via_float_tree(Key::binary(), Tree::< a href = "#type-float_tree" > float_tree()< / a > ) -> {float(), < a href = "#type-owner_name" > owner_name()< / a > }< / tt > < br > < / p >
< / div > < p > Query a float tree with a binary.< / p >
< h3 class = "function" > < a name = "make_demo_map1-0" > make_demo_map1/0< / a > < / h3 >
< div class = "spec" >
< p > < tt > make_demo_map1() -> < a href = "#type-float_map" > float_map()< / a > < / tt > < br > < / p >
< / div > < p > Create a sample float map.< / p >
< h3 class = "function" > < a name = "make_demo_map2-0" > make_demo_map2/0< / a > < / h3 >
< div class = "spec" >
< p > < tt > make_demo_map2() -> < a href = "#type-float_map" > float_map()< / a > < / tt > < br > < / p >
< / div > < p > Create a sample float map.< / p >
< h3 class = "function" > < a name = "make_float_map-1" > make_float_map/1< / a > < / h3 >
< div class = "spec" >
< p > < tt > make_float_map(NewOwnerWeights::< a href = "#type-owner_weight_list" > owner_weight_list()< / a > ) -> < a href = "#type-float_map" > float_map()< / a > < / tt > < br > < / p >
< / div > < p > Create a float map, based on a basic owner weight list.< / p >
< h3 class = "function" > < a name = "make_float_map-2" > make_float_map/2< / a > < / h3 >
< div class = "spec" >
< p > < tt > make_float_map(OldFloatMap::< a href = "#type-float_map" > float_map()< / a > , NewOwnerWeights::< a href = "#type-owner_weight_list" > owner_weight_list()< / a > ) -> < a href = "#type-float_map" > float_map()< / a > < / tt > < br > < / p >
< / div > < p > < p > Create a float map, based on an older float map and a new weight
list.< / p >
The weights in the new weight list may be different than (or the
same as) whatever weights were used to make the older float map.< / p >
< h3 class = "function" > < a name = "make_tree-1" > make_tree/1< / a > < / h3 >
< div class = "spec" >
< p > < tt > make_tree(Map::< a href = "#type-float_map" > float_map()< / a > ) -> < a href = "#type-float_tree" > float_tree()< / a > < / tt > < br > < / p >
< / div > < p > Create a float tree, which is the rapid lookup data structure
for consistent hash queries.< / p >
< h3 class = "function" > < a name = "pretty_with_integers-2" > pretty_with_integers/2< / a > < / h3 >
< div class = "spec" >
< p > < tt > pretty_with_integers(Map::< a href = "#type-float_map" > float_map()< / a > , Scale::integer()) -> [< a href = "#type-owner_int_range" > owner_int_range()< / a > ]< / tt > < br > < / p >
< / div > < p > Make a pretty/human-friendly version of a float map that describes
integer ranges between 1 and < code > Scale< / code > .< / p >
< h3 class = "function" > < a name = "pretty_with_integers-3" > pretty_with_integers/3< / a > < / h3 >
< div class = "spec" >
< p > < tt > pretty_with_integers(OldWeights::< a href = "#type-owner_weight_list" > owner_weight_list()< / a > , NewWeights::< a href = "#type-owner_weight_list" > owner_weight_list()< / a > , Scale::integer()) -> [< a href = "#type-owner_int_range" > owner_int_range()< / a > ]< / tt > < br > < / p >
< / div > < p > Make a pretty/human-friendly version of a float map (based
upon a float map created from < code > OldWeights< / code > and < code > NewWeights< / code > ) that
describes integer ranges between 1 and < code > Scale< / code > .< / p >
< h3 class = "function" > < a name = "query_tree-2" > query_tree/2< / a > < / h3 >
< div class = "spec" >
< p > < tt > query_tree(Val::float(), Tree::< a href = "#type-float_tree" > float_tree()< / a > ) -> {float(), < a href = "#type-owner_name" > owner_name()< / a > }< / tt > < br > < / p >
< / div > < p > Low-level function for querying a float tree: the (floating
point) point within the unit interval.< / p >
< h3 class = "function" > < a name = "sum_map_weights-1" > sum_map_weights/1< / a > < / h3 >
< div class = "spec" >
< p > < tt > sum_map_weights(Map::< a href = "#type-float_map" > float_map()< / a > ) -> {{per_owner, < a href = "#type-float_map" > float_map()< / a > }, {weight_sum, float()}}< / tt > < br > < / p >
< / div > < p > < p > Create a human-friendly summary of a float map.< / p >
The two parts of the summary are: a per-owner total of the unit
interval range(s) owned by each owner, and a total sum of all
per-owner ranges (which should be 1.0 but is not enforced).< / p >
< h3 class = "function" > < a name = "zzz_usage_details-0" > zzz_usage_details/0< / a > < / h3 >
< div class = "spec" >
< p > < tt > zzz_usage_details() -> any()< / tt > < / p >
< / div > < p > Various usage examples, see source code below this function
for full details.< / p >
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2015-05-20 03:37:28 +00:00
< p > < i > Generated by EDoc, May 20 2015, 12:36:35.< / i > < / p >
2015-04-08 08:52:58 +00:00
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