Tnesia is a time-series data storage which lets you run time-based queries on a large amount of data, without scanning the whole set of data, and in a key-value manner. It can be used embedded inside an Erlang application, or stand-alone with HTTP interface to outside which talks in a simple query language called TQL.
Installation
What you need to install Tnesia is Erlang/OTP R15 or newer. Clone the repo and make it before start as follows:
$ git clone https://github.com/bisphone/Tnesia.git
$ cd Tnesia
$ make
$ make start
#=> Tnesia was started!Stand-alone Example
In stand-alone mode, what you need is an HTTP client, like curl. Then you can manipulate time-series data using TQL. For example you can create a timeline which is called 'tweets' and insert tweets on it in single mode:
$ curl localhost:1881 -H \
"Query: INSERT INTO 'tweets' {'text', 'media', 'length'}
RECORDS {'Hi Tnesia!', 'tnesia.png', '10'}"
#=> [
#=> 1436699673792910
#=> ]Or in batch mode:
$ curl localhost:1881 -H \
"Query: INSERT INTO 'tweets' {'text', 'media', 'length'}
RECORDS {'TQL is simple', 'null', '13'}
AND {'Erlang is totally fun.', 'erlang.png', '22'}
AND {'OH: Reactive!', 'null', '13'}"
#=> [
#=> 1436699709083018,
#=> 1436699709082909,
#=> 1436699709082768
#=> ]Now we can select last two tweets as follows:
$ curl localhost:1881 -H \
"Query: SELECT * FROM 'tweets'
WHERE SINCE '1436699673792910' TILL '1436699709083018'
AND LIMIT '2'
AND ORDER DES"
#=> [
#=> {
#=> "__timeline__": "tweets",
#=> "__timepoint__": "1436699709082909",
#=> "length": "22",
#=> "media": "erlang.png",
#=> "text": "Erlang is totally fun."
#=> },
#=> {
#=> "__timeline__": "tweets",
#=> "__timepoint__": "1436699709083018",
#=> "length": "13",
#=> "media": "null",
#=> "text": "OH: Reactive!"
#=> }
#=> ]Also selecting tweets which don't have media property with more than 20 text length is as simple as follows:
$ curl localhost:1881 -H \
"Query: SELECT {'text', 'media'} FROM 'tweets'
WHERE 'media' != 'null'
AND 'length' > '20'"
#=> [
#=> {
#=> "__timeline__": "tweets",
#=> "__timepoint__": "1436699709082909",
#=> "media": "erlang.png",
#=> "text": "Erlang is totally fun."
#=> }
#=> ]Embeded Example
The other way to use Tnesia is from inside an Erlang application. It is a standard OTP application, so can be included in Rebar config file. For example repeating above examples are as follows:
Inserting record in a timeline.
Timeline = "tweets",
Tweet = [{"text", "Hi Tnesia!"}, {"media", "tnesia.png"}, {"length", "10"}],
{Timeline, Timepoint} = tnesia_api:write(Timeline, Tweet),Selecting records without filtering and mapping them.
Timeline = 'tweets',
Since = tnesia_lib:get_micro_timestamp({2015, 1, 1}, {0, 0, 0}),
Till = tnesia_lib:get_micro_timestamp(({2015, 2, 1}, {0, 0, 0}),
Result = tnesia_api:query_fetch([{timeline, Timeline},
{since, Since},
{till, Till},
{order, asc},
{limit, 10}]),Selecting text property of records whose media property is null.
Since = tnesia_lib:get_micro_timestamp({2015, 1, 1}, {0, 0, 0}),
Till = tnesia_lib:get_micro_timestamp({2015, 2, 1}, {0, 0, 0}),
Timeline = "tweets",
Result = tnesia_api:query_filtermap(
[{timeline, Timeline},
{since, Since},
{till, Till},
{order, des},
{limit, 10}],
fun(Record, _RecordIndex, _RemainingLimit) ->
case proplists:get_value("media", Record) of
"null" -> false;
_ -> {true, proplists:get_value("text", Record)}
end
end).Deleting tweets whose text length is more than 20 characters.
Since = tnesia_lib:get_micro_timestamp({2015, 1, 1}, {0, 0, 0}),
Till = tnesia_lib:get_micro_timestamp({2015, 2, 1}, {0, 0, 0}),
Timeline = "tweets",
ok = tnesia_api:query_foreach(
[{timeline, Timeline},
{since, Since},
{till, Till},
{order, des},
{limit, 10}],
fun(Record, RecordIndex, _RemainingLimit) ->
{_, _, {Timeline, Timepoint}} = RecordIndex,
Text = proplists:get_value("text", Record),
case length(Text) > 20 of
true ->
tnesia_api:remove(Timeline, Timepoint),
true;
_ -> false
end
end).The goal is to reduce disk seeks in order to find a time range of data values in a timeline, ascending or descending, and from or to any arbitrary points of time. There are few terms that can help you to understand how Tnesia stores and retrieves data, among them Timeline, Timepoint and Timestep are the main ones.
- Timeline: An identifier to a series of chronological timepoints.
- Timepoint: A pointer to a given data value.
- Timestep: A partition on a timeline that spilited timepoints
TL: Timeline TS: Timestep *: Timepoint
+------------------------------------------------------+
TL * * ** |* ** * |* * * | *** * | * ** *
+------------------------------------------------------+
TS TS TS TS TS
- Each timestep can contain arbitrary number of timepoints.
- All the orders are based on microsecond UNIX timestamp.
- Timepoints are just a pointer to its data value which stores somewhere else.
- Timepoints, as index, are stored on RAM to faster lookup.
- Data values are stored on Disk to have more room for storage.
- All seeks are key-value.
- Timestep precision is configurable depends on the timepoints frequency.
The Makefile which is in root directory performs the following tasks:
# building
$ make
# functionality testing
$ make test
# benchmark testing
$ make light_bench
$ make normal_bench
$ make heavy_bench
# starting and etc
$ make start
$ make attach
$ make stop
$ make liveSelect
SELECT * | record_keys()
FROM timeline()
[ WHERE
[ [ AND ] conditions() ]
[ [ AND ] SINCE datetime() TILL datetime() ]
[ [ AND ] ORDER order() ]
[ [ AND ] LIMIT limit() ] ]Insert
INSERT INTO timeline() record_keys()
RECORDS record_values()Delete
DELETE FROM timeline()
WHEN record_time()timeline() :: 'string()'
record_keys() :: {'string()', ...}
record_values() :: {'string()', ...}
record_time() :: 'string()'
datetime() :: 'integer()'
order() :: 'asc' | 'des'
limit() :: 'integer()'
conditions() :: condition() AND condition()
condition() :: 'string()' comparator() 'string()'
comparator() :: == | != | > | >= | < | <=Write
Writes a record on a timeline.
tnesia_api:write(Timeline, Record) -> {Timeline, Timepoint}Read
Reads a record from a timeline by its timepoint.
tnesia_api:read(Timeline, Timepoint) -> RecordRemove
Removes a record from a timeline by its timepoint.
tnesia_api:remove(Timeline, Timepoint) -> okQuery fetch
Queries a timeline to return records without any filttering or mapping.
tnesia_api:query_fetch(Query) -> [Record]Query filtermap
Queries a timeline to return records with filltering and mapping.
tnesia_api:query_filtermap(Query, FiltermapFun) -> [Record]Query foreach
Queries a timeline and traverse on the records.
tnesia_api:query_foreach(Query, ForeachFun) -> okQuery raw
Queries a timeline deciding on the return and traversal method.
tnesia_api:query_raw(Query, Return, Fun) -> [Record] | okTimeline :: any()
Record :: [{any(), any()}]
Timepoint :: integer()
Query :: [{timeline, Timeline},
{since, Since},
{till, Till},
{order, Order},
{limit, Limit}]
Since = Till :: integer()
Order :: asc | des
Limit :: integer() | unlimited
FiltermapFun :: fun((Record, RecordIndex, Limit) -> {true, Record} | false)
ForeachFun :: fun((RecordIndex, Record, Limit) -> true | any())
Fun :: FiltermapFun | ForeachFun
Return :: true | falseComments, contributions and patches are greatly appreciated.
The MIT License (MIT).