These are the BTrDB Bindings for Julia allowing you painless and productive access to the Berkeley Tree Database (BTrDB). BTrDB is a time series database focusing on blazing speed with respect to univariate time series data at nanosecond scale.
To understand why BTrDB is so fast, see BTrDB Explained in the documentation and feel free to check out the underlying academic paper.
At the moment, you will need to install directly from our GitHub repo.
julia> Pkg.clone("git@github.com:PingThingsIO/BTrDB.jl.git")
INFO: Cloning Package from git://github.com/PingThingsIO/BTrDB.jl.git
Cloning into 'BTrDB.jl'...Please see our official documentation for the latest usage information. However, to give you a quick taste see the code below. More interactions such windowing queries, etc. are demonstrated in the docs.
collection = "sensors/electrical"
uuid_token = "33ecd8fe-8942-5bd3-ad9f-b3e8165399ab"
tags = Dict{String, String}(
"name" => "pmu_springfield_22",
"unit" => "volts"
)
annotations = Dict{String, Any}(
"phase" => "A",
)
stream = create(uuid_token, collection, tags, annotations)The BTrDB bindings expect an array of Pair objects for insertion into a stream. The first element of the pair is the Int64 timestamp in nanoseconds and the last element is the Float64 value.
data = [
Pair(1546300801000000000, 1.0),
Pair(1546300802000000000, 2.0),
Pair(1546300803000000000, 3.0)
]
s = stream_from_uuid(uuid_token)
insert(s, data)To retrieve the raw values in a given range of time you can use the values function which accepts a Stream object along with the start and end timestamps (Int64). This call will return an array of RawPoint objects.
s = stream_from_uuid(uuid_token)
points = values(s, 1546300802000000000, 1546300804000000000)- Support the Tables.jl interface
- Add conversion to DataFrames.jl