Functions

collections()

Returns an array of all collection strings

collections(starts_with::String)

Returns an array of all collection strings that start with a given String

streams(collection::String)

Returns an Array of Stream objects found with the supplied collection.

refresh(uuid::String)

Returns a new Stream object with the latest metadata from the server.

refresh(stream::Stream)

Returns a new Stream object with the latest metadata from the server.

stream_from_uuid(uuid::String)

Returns a new Stream object with the latest metadata from the server. Alias for refresh(uuid::String)

create(uuid::String, collection::String, tags::Dict{String, String}, annotations::Dict{String, Any})

Creates a new stream on the server.

obliterate(uuid::String)

Deletes a Stream with a given UUID from the server permanently.

obliterate(stream::Stream)

Deletes a Stream from the server permanently.

settags(stream::Stream, tags::Dict{String, String})

Overwrites existing tags.

Notes

Tags are used internally by the system and are not generally meant to be manipulated by end users.

If you would like to add your own custom metadata, please use annotations.

setannotations(stream::Stream, annotations::Dict{String, Any})

Overwrites existing annotations.

Notes

Stream annotations are provided so that you may store Stream related custom metadata.

You cannot delete annotations at this time though this will change in a future update.

insert(uuid::String, data::Array{Pair{Int64, Float64},1})

Insert new data in the form (time, value) into the series.

Inserts a list of new (time, value) tuples into the series. The tuples in the list need not be sorted by time. If the arrays are larger than appropriate, this function will automatically chunk the inserts. As a consequence, the insert is not necessarily atomic, but can be used with a very large array.

Arguments

• uuid : a String for the stream's unique identifier
• data : an Array of Pair objects representings points where the first pair item is the time (Int64) and the second item is the value (Float64)

insert(stream::Stream, data::Array{Pair{Int64, Float64},1})

Insert new data in the form (time, value) into the series.

Inserts a list of new (time, value) tuples into the series. The tuples in the list need not be sorted by time. If the arrays are larger than appropriate, this function will automatically chunk the inserts. As a consequence, the insert is not necessarily atomic, but can be used with a very large array.

Arguments

• stream : the Stream to use for data insertion
• data : an Array of Pair objects representings points where the first pair item is the time (Int64) and the second item is the value (Float64)

delete(uuid::String, start::Int64, stop::Int64)

"Delete" all points between start (inclusive) and end (exclusive), both in nanoseconds. As BTrDB has persistent multiversioning, the deleted points will still exist as part of an older version of the stream.

Arguments

• uuid : the String UUID of the stream to use for data deletion
• start : the start time (Int64) in nanoseconds for the range to be deleted (inclusive)
• stop : the end time (Int64) in nanoseconds for the range to be deleted (exclusive)

delete(stream::Stream, start::Int64, stop::Int64)

"Delete" all points between start (inclusive) and end (exclusive), both in nanoseconds. As BTrDB has persistent multiversioning, the deleted points will still exist as part of an older version of the stream.

Arguments

• stream : the Stream to use for data deletion
• start : the start time (Int64) in nanoseconds for the range to be deleted (inclusive)
• stop : the end time (Int64) in nanoseconds for the range to be deleted (exclusive)

flush(uuid::String)

Forces the database to commit buffered data. This function is generally not needed by end users.

flush(stream::Stream)

Forces the database to commit buffered data. This function is generally not needed by end users.

nearest(stream::Stream, time::Int64, version::Int=0, backward::Bool=false)

Finds the closest point in the stream to a specified time.

Return the point nearest to the specified time in nanoseconds since Epoch in the stream with version while specifying whether to search forward or backward in time. If backward is false, the returned point will be >= time. If backward is true, the returned point will be < time. The version of the stream used to satisfy the query is returned.

Arguments

• stream : The Stream object to search
• time : The Int64 time (in nanoseconds since Epoch) to search near
• version : Int64 version of the stream to use in search
• backward : boolean (true) to search backwards from time, else false for forward

earliest(stream::Stream, version::Int=0)

Returns the first point of data in the stream.

Arguments

• stream : The Stream object to search
• version : Int64 version of the stream to use in search

latest(stream::Stream, version::Int=0)

Returns last point of data in the stream.

Arguments

• stream : The Stream object to search
• version : Int64 version of the stream to use in search

values(stream::Stream, start::Int64, stop::Int64, version::Int=0)

Read raw values from BTrDB between time [start, stop) in nanoseconds.

RawValues queries BTrDB for the raw time series data points between start and end time, both in nanoseconds since the Epoch for the specified stream version.

Arguments

• start : The start time (Int64) in nanoseconds for the range to be queried (inclusive)
• stop : The end time (Int64) in nanoseconds for the range to be queried (exclusive)
• version : Int64 version of the stream to use when querying data

Notes

Note that the raw data points are the original values at the sensor's native sampling rate (assuming the time series represents measurements from a sensor). This is the lowest level of data with the finest time granularity. In the tree data structure of BTrDB, this data is stored in the vector nodes.

windows(stream::Stream, start::Int64, stop::Int64, width::Int, depth::Int, version::Int=0)

Read arbitrarily-sized windows of data from BTrDB. StatPoint objects will be returned representing the data for each window.

Arguments

• start : The start time (Int64) in nanoseconds for the range to be queried (inclusive)
• stop : The end time (Int64) in nanoseconds for the range to be queried (exclusive)
• version : Int64 version of the stream to use when querying data
• width : the number (Int) of nanoseconds in each window, subject to the depth parameter.
• depth : The precision of the window duration as a power of 2 in nanoseconds. E.g 30 would make the window duration accurate to roughly 1 second

Notes

Windows returns arbitrary precision windows from BTrDB. It is slower than AlignedWindows, but still significantly faster than RawValues. Each returned window will be width nanoseconds long. start is inclusive, but end is exclusive (e.g if end < start+width you will get no results). That is, results will be returned for all windows that start at a time less than the end timestamp. If (end - start) is not a multiple of width, then end will be decreased to the greatest value less than end such that (end - start) is a multiple of width (i.e., we set end = start + width * floordiv(end - start, width). The depth parameter is an optimization that can be used to speed up queries on fast queries. Each window will be accurate to 2^depth nanoseconds. If depth is zero, the results are accurate to the nanosecond. On a dense stream for large windows, this accuracy may not be required. For example for a window of a day, +- one second may be appropriate, so a depth of 30 can be specified. This is much faster to execute on the database side.

aligned_windows(stream::Stream, start::Int64, stop::Int64, pointwidth::Int, version::Int=0)

Read statistical aggregates of windows of data from BTrDB.

Query BTrDB for aggregates (or roll ups or windows) of the time series with version between time start (inclusive) and end (exclusive) in nanoseconds. Each point returned is a statistical aggregate of all the raw data within a window of width 2**pointwidth nanoseconds. These statistical aggregates currently include the mean, minimum, and maximum of the data and the count of data points composing the window.

Note that start is inclusive, but end is exclusive. That is, results will be returned for all windows that start in the interval [start, end). If end < start+2^pointwidth you will not get any results. If start and end are not powers of two, the bottom pointwidth bits will be cleared. Each window will contain statistical summaries of the window. Statistical points with count == 0 will be omitted.

Arguments

• start : The start time (Int64) in nanoseconds for the range to be queried (inclusive)
• stop : The end time (Int64) in nanoseconds for the range to be queried (exclusive)
• pointwidth : the number of ns between data points (2**pointwidth)
• version : Int64 version of the stream to use when querying data

Notes

As the window-width is a power-of-two, it aligns with BTrDB internal tree data structure and is faster to execute than windows().