Overview
On this page, you find further information regarding how the archiving process works, triggers, and the available options for archiving data.
On this page:
Archiving Process Overview
The Historian module process to archive data is composed by 3 steps:
An event triggers the request to archive a group of values. There are two types of events (Trigger or TagChange) that you configure when creating a Historian Table.
The Historian archives the values in the Archive Location after the trigger. You can use SQL databases or a TagProvider when configuring the Archive Location.
If you enable the Store and Forward feature, the system executes the data synchronization. This option stores data in a local database if the configured database is unavailable and sends it to the target when it becomes available.
In the following sections, you find additional details regarding each step.
Triggering Events
In FrameworX, there are two possible actions that can iniciate the archiving process. You can configure a Trigger based on a Tag, or choose to save always the Tag's value changes using the Save on Change option.
Trigger
You have three options to define as triggers in the Historian module:
- A Tag value.
- A Tag property.
- Any object from the runtime namespace, such as Server.minute.
Whenever there's a change in the object's value, it sets creates an archive request event.
To ensure compatibility with the Historian process, Triggers are limited to Tags falling under the domain of Server or objects situated in server-side namespaces. This restriction exists because the Historian process operates exclusively on the Server computer.
You can choose one Trigger for each Historian Table. When the trigger happens, all current values of Tags and objects connected to that Historian Table will be archived, regardless of whether or not they have a new value.
Save On Change
As the Trigger, you set the Save on Change option when creating or edditing a Historian Table.
When you enable the Save on Change the Historian module verifies continuously all Tags connected to each Historian Table. As a Tag changes its value, the archive request event is generated. Only the Tag that changed its value will be arhived.
Archiving the DataSelecting the Target Database
After the archive request is created, the FrameworX system will check how the data will be stored depending on the Archive Location of the current Historian Table. You configure this option when creating the Historian Table.
The process of archeving the data will differs if you are using a SQL database or TagProvider as a Historian.
Archiving to SQL database (TagHistorian)
The Datasets Module has a pre-defined object named TagHistorian. By default, a SqlLite database is used, but you can choose other databases. Access the Historian Tables to learn how to do it.
When archiving to the SQL database defined by the TagHistorian object, you can choose between the Standard and Normalized table schemas.
Standard Tables
If you use Standard tables, both Trigger and TagChange events result in a single additional row in the database. Each column in the table corresponds to a Tag in the HistorianTable group, ensuring that all tags within the group receive an entry, even if only one tag has a new value.
The row's timestamp is determined by the Trigger object when the archive event is triggered or by the timestamp of the Tag that initiated the archive request in the case of OnTagChange events. All tags listed in the associated HistorianTable are stored, independent of whether they have new values or not, sharing a single timestamp as defined earlier. For OnTagChange events involving multiple tag value changes, a single row is inserted with all tags in the group, utilizing the timestamp of the tag that triggered the event.
Avoid exponential database growth
To prevent rapid database growth, you can use the Time Deadband configuration to ensure that a new row is not created every time a Tag's value change. The system will not archive a new Tag's value until the dead band time ins't reached. After the deadband, the new row is generated using the timestamp of the last event.
Standard tables schema
The following table describes all existing columns from a Standard SQL Table contain the following columns:
| Column Name | Data Type | Size | Description |
|---|---|---|---|
ID | BigInt | (8 Bytes) | Primary key used as a reference within the system. |
UTCTimeStamp_Ticks | BigInt | (8 Bytes) | Date and time in Universal Time, represented in 64-bit .NET ticks. The value is based on 100-nanosecond intervals since 12:00 A.M., January 1, 0001, following the Microsoft .NET Framework standard. |
LogType | TinyInt | (1 byte) | Auxiliary column indicating the insertion event:
|
NotSync | Int | (4 Bytes) | Auxiliary column to show if the data was synchronized or not when the Redundancy option is enabled. See Deploying Redundant Systems. |
TagName | Float | (8 Bytes) | Automatically generated column with the tag name as the title, storing data values using double precision. |
_TagName_Q | Float | (8 Bytes) | Automatically generated column for the data quality of each tag, following the OPC quality specification. |
You can usually assign up to 200 tags to each historian table. However, the exact number can vary depending on how many columns your target database can accommodate. As a best practice, define tags in the same table if they have similar storing rates and process dynamics.
Normalized Tables
Normalized tables archive data only after a OnTagChange events. If you check the Normalized feature when creating or editing the Historian Table, the Trigger option is disabled.
Normalized tables store In this table schema, each one has only the TimeStamp of Tag, ID of the Tag, and the Value of Tag that generated the arquive event.
Normalized Tables Schema
| Column Name | Data Type | Size | Description |
|---|---|---|---|
ID | BigInt | (8 Bytes) | Primary key used as a reference within the system. |
TagName | NVarchar | The name of all the Tags configured as normalized databases on the Historian. | |
NotSync | Integer | (4 Bytes) | Not used for this release. It was created for future changes and new features. |
The system automatically creates more four tables:
- TableName_BIT
- TableName_FLOAT
- TableName_NTEXT
- TableName_REAL
The following table describes the schemas used by the created tables.
| Column Name | Data Type | Size | Description |
|---|---|---|---|
ID | BigInt | (8 Bytes) | The primary key of the table used as reference by the system. |
UTCTimeStamp_Ticks | BigInt | (8 Bytes) | Date and time in Universal Time expressed in 64-bit .NET ticks. The value represents 100-nanosecond intervals since 12:00 A.M., January 1, 0001, following to the Microsoft .NET Framework's time standard. |
ObjIndex | Integer | (4 Bytes) | Foreign key referencing the ID column in the TagsDictionary table, establishing a relationship. |
ObjValue | Can be: Bit, Float, NText, or Real, depending on which table it is | Represents the value of the tag at the specified timestamp, with the data type varying based on the context of the associated table. | |
ObjQuality | TinyInt | (1 Byte) | Indicates the quality of the tag at the specified time, based on the OPC quality specification. |
NotSync | Int | (4 Bytes) | Currently not utilized in this release. Reserved for potential future changes and new features. |
It is not possible to synchronize a normalized database using the Redundancy option.
Archiving Externally using a TagProvider
When archiving data externally using a TagProvider, the external system defines the schemas and determines the structural organization, naming conventions, and other specific settings.
Protocol
You need to specify the Protocol to add a new Archive Location using a TagProvider. The Protocol is an intermediary between the solution you build with FramewroX and the external data historian systems. They interpret and translate data formats, protocols, and other communication specifics to ensure seamless data archiving and retrieval. Currently, FrameworX provides three protocol options to connect using TagProviders:
CanaryLabs: A robust data historian system that's optimized for real-time data collection and analytics. When archiving to CanaryLabs, the data is stored in a highly compressed format that facilitates faster retrieval and analytics.
InfluxDB: An open-source time-series database designed for high availability and real-time analytics. InfluxDB is particularly useful when working with large sets of time-series data where timely data retrieval is of the essence.
GE Proficy: A comprehensive platform that provides real-time data collection and advanced analytics capabilities. GE Proficy is a scalable system designed to integrate and analyze vast amounts of industrial data.
You can use the Store and Forward feature when configuring a new Archive Location using TagProvider.
Using Store and Forward
The Store and Forward feature ensures you will not lose data if the system can't connect with the external database.
When you define an Archive Locasion using a TagProvider and disable Store and Forward, the archive requests events are sent directly to the external database as the events occur, independent of an existing working connection. A built-in protection exists for SQL-Dataset-TagHistorian targets with Normalized tables, buffering new rows and including them in the database every 5 seconds.
Store and Forward process
When the Historian module receives an archive request, it'll try to store the data in the Archive Location. If unsuccessful, it stores the data in a locally created SQLite database. After an unsuccessful attempt, the Historian module will attempt to copy data from the local SQLite database (rows inserted when the Target database was inaccessible) to the Target Database every 5 seconds, in maximum blocks of 250 rows.
Historian tables are verified within a 4-second window. If not all tables are processed in time, the verification continues in the next 5-second cycle. If the copy process to the Archive Location succeeds, meaning the connection was reestablished, the copied rows are removed from the temporary SQLite cache. If the temporary SQLite database is empty after the process, it is deleted.
In applications with a high volume of data and several tables to be synchronized, the data availability in the Archive Location (external database) may take some time. The synchronization velocity depends on the insertion performance of the main database and the local databases' insertion performance (SQLite). In most applications, the Store and Forward synchronization process takes up to 1 second per table.
Due to the possible synchronization restrictions, it's essential to take the following points when deciding the database system to be used in your solution:
- For large projects with significant data volumes, it's recommended to use robust databases like SQL Server or Oracle for better performance.
- SQLite has a 10GB limit and limited performance and is suitable for smaller data models. The Keep a Local Copy feature works well for projects not requiring immediate synchronization, especially if the main database experiences occasional unavailability due to other projects or third-party software usage.
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