Structs Data Lifecycle

The XINA structs mnemonic data lifecycle involves four primary phases:

Source Files

Each origin maintains a set of source files, containing all data imported into XINA for that origin.

The primary type of source files are archive source files. Archive files are considered the definitive record of source data for a range of time for a single origin. These are stored in the XINA xbin binary file format. These are imported directly with the STRUCT ARCHIVE IMPORT action. Archive files are mined through the XINA Structs Mine task into XINA databases in order to be viewed in the XINA client, and are used to generate export packages.

Alternatively, an origin may use buffer source files. Buffer files may be imported in a variety of data formats and are not subject to the same strict requirements as archive files. These may are imported directly with the STRUCT BUFFER IMPORT action. Mnemonic data from buffer files is loaded into a temporary buffer database for immediate viewing in the XINA client. Buffer files are archived (merged and converted into archive files) through the XINA Structs Archive task, which can be run manually or configured to run in regular intervals. This is the recommended approach for importing mnemonic data when getting started with XINA Structs.

Data Flow

In general, there are three supported approaches for origin data flow: buffer import, variable time archive import, and fixed time archive import. While a single origin can only support one workflow, a model may combine multiple workflows using multiple origins.

Buffer Import

The buffer import workflow is the most flexible mnemonic import method. Buffer files do not need to adhere to strict requirements (aside from conforming to standard accepted file formats). Buffer files for a given origin may have duplicated data, overlapping data, and can introduce new mnemonic definitions on demand.

Buffer files are imported with the STRUCT BUFFER IMPORT action. This invokes three effects:

• the raw buffer file is parsed, validated, and stored in the model origin mnemonic buffer file database
• new mnemonic definitions are created for any unrecognized mnemonic labels
• data is added to the mnemonic buffer database for the associated origin

No additional data processing occurs as part of this step. XINA models utilizing buffer source files must implement routine execution of the STRUCT_BUFFER_ARCHIVE asynchronous task (typically every hour) to merge the files into archive files in a fixed-time archive format, which can then be processed by STRUCT_ARCHIVE_MINE tasks to fully process data into model standard databases.

Pros

• minimal client side configuration required to get started
• allows smaller, faster file uploads to view data close to real-time
• flexible and responsive to changing environments, mnemonics, requirements

Cons

• performance is worse than client side aggregation
• not recommended above 1k total data points per second

Struct Archive Task

The XINA Struct Archive task merges and compresses buffer files into archive files. This step is required to resolve any data discrepancies and ensure data is preserved in accordance with the requirements of archive files. The task performs the following steps:

• load all unprocessed files from the buffer file database
• for each time ranges affected by unprocessed files
  • process each file into processed format
  • load any existing processed files in those time ranges
  • merge data from all processed files for time range into single archive file
  • upload newly processed buffer files
  • delete unprocessed buffer files
  • upload merged archive file
  • run mining task on merged archive file
  • delete any mnemonic data already present for time range
  • import mnemonic data generated by mining task

Direct Archive Import

Archive files are imported directly with the STRUCT ARCHIVE IMPORT action.

Pros

• much higher performance ceiling than server side aggregation
• stringent validation ensures data conforms to standard

Cons

• more complex initial setup
• mnemonic definitions must be pre-defined and cannot be added on-the-fly
• mnemonic definitions need coordination between client and server
• changes are more complex and likely involve human interaction

Fixed-Time Archive Import

With fixed-time archive import each archive has a fixed time range. This is a recommended solution for projects which generate a persistent data stream (for example, data sources piped through a FEDS server).

Variable-Time Archive Import

With variable-time archive import each archive specifies a custom time range. This is a recommended solution for projects which generate their own archival equivalent (for example, outputting a discrete data set after running a script). Because the time ranges are determined by the source data, theit archiveis database for this approach includes all interval fields as well,recommended to support handling the database as angenerate interval database.events Itmatching iseach configuredfile as a multiple-file-per-record structure.

Required Fields

Field	Type	Description
uuid	uuid	universally unique ID
p_id	int(8)	primary ID
s_id	int(8)	secondary ID
t_start	instant(us)	start time ofrange data in file
t_end	instant(us)	end time of data in file
duration	duration	t_end - t_start
t_min	instant(us)	earliest time of data in file
t_max	instant(us)	latest time of data in file
label	utf8vstring(128)	plain text label
content	utf8text	extended text / CSV / HTML
type	int(2)	interval type code
level	int(1)	level code
meta	jsonobject (may be null)	arbitrary metadata as needed
format	asciivstring(16)	file format (see below)
conf	jsonobject (may be null)	configuration parameters, depending on format

Fixed-Time Archive Import

With fixed-time archive import each archive has a fixed time range. This is a recommended solution for projects which generate a persistent data stream (for example, data sources piped through a FEDS server). Unlike the variable-time archive database, this database is not treated as an interval database, because the time windows are arbitrary. It is configured as a multiple-file-per-record structure.reference.

Required Fields

Field	Type	Description
uuid	uuid	universally unique ID
t_start	instant(us)	start time of data in file
t_end	instant(us)	end time of data in file
duration	duration	t_end - t_start
t_min	instant(us)	earliest time of data in file
t_max	instant(us)	latest time of data in file
meta	jsonobject (may be null)	arbitrary metadata as needed
format	asciivstring(16)	file format (see below)
conf	jsonobject (may be null)	configuration parameters, depending on format

Source File Formats

Currently there are two natively supported general purpose formats, one using the codes csv/tsv (full documentation here), and a binary format using the code xbin (full documentation here) Additional formats will be added in the future, and custom project-specific formats may be added as needed.

Assumptions and Limitations

Each archive source file is considered the single source of truth for all mnemonics, instants, and intervals for it's associated origin for its time range. This has the following implications:

Archive files with the same origin cannot contain overlapping time ranges. If an import operation is performed with a file violating this constraint the operation will fail and return an error.

Within a single model, each mnemonic may only come from a single origin. Because mnemonics are not necessarily strictly associated with models, and the source may vary between models, this cannot be verified on import and must be verified on the client prior to importing data.