Page History

Key Concepts and Terms

DatasetDB

Connections settings created by the Dataset Module to communicate with an external database.

DatasetQuery

Logical name associated with the configuration for SQL query statements with a Database, and its properties and methods for running que queries.  

DatasetTable

Logical name created to hold configuration settings to access specific tables in a connected database, mapping tags to table columns for operations.

DatasetFile

Logical name defining

Key Concepts and Terminology

Dataset DBs

In order for the Dataset Module to communicate with an external database, a connection must be created with certain parameters. These connections, which are created within the Datasets → DBs section of the module, are referred to as Dataset DBs.

Dataset Queries

In the context of the Dataset Module, a Dataset Query refers not only to an SQL query string, but also to a Project object that has a logical name, an SQL query related to that logical name, and other parameters defined within the Datasets → Queries section. There are many ways to automatically map the results of a query execution with Tags.

Dataset Tables

A Dataset Table is a logical name that is created within a project to set up access to a specific table in a connected database. These tables are listed within the Datasets → Tables section of the module. The Tags in the real-time database can easily be mapped to columns in the tables to perform insert, update, or read operations.

Dataset Files

A Dataset File is a logical name that defines parameters for reading and writing files in ASCII, Unicode, or XML formats.

Understanding the

Datasets Module

Features Highlights

1. SQL Query Support: The Dataset Module provides support for SQL queries, allowing users to easily extract, manipulate, and transform data from a variety of sources.

2. Integration with External Data Sources: The Dataset Module can integrate with a wide range of external data sources, including databases, CSV files, and other external sources, providing a flexible and powerful tool for data collection and analysis.

3. Access Types: Access Types allow users to group and organize data points based on their usage and permissions, providing a powerful tool for managing and controlling access to data within the Dataset Module.

4. Visual Query Editor: The Visual Query Editor provides a user-friendly interface for creating and editing SQL queries, making it easy for users to define complex queries without needing extensive SQL knowledge.

5. Customizable Dashboards: The Dataset Module provides the ability to create custom dashboards and visualizations based on the data collected by the module, allowing users to easily view and analyze data in real-time.

6. Store Procedures Execution: The Dataset Module can execute Store Procedures and return the results to the platform, allowing users to perform advanced data manipulation and analysis within the context of the platform.

7. Real-Time Execution: The Dataset Module supports real-time execution of SQL queries, allowing users to monitor and analyze data as it is generated in real-time.

Configuring the Dataset Module

Configuration Workflow

The typical configuration workflow for the Dataset Module has the following sequence:

Creating DB Connections

When using SQLite databases, the Module Dataset can automatically create the Database if necessary; for other ones, the Database itself must already exist before you set your connection. Users with any Permission groups can create new connections in the Project, but only the Administrator can configure databases password logins.

To create a new Database connection:

• Go to Datasets → DBs.

• Click Create New. The Create New Database Connection window displays.

• Enter or select information, as needed.

• Click OK. The database is added as a new row in the table.

• Edit the row fields to modify the required settings.

Dataset DB Configuration Properties 

Column

Description

Name

Enter a name for the database configuration. The system allows you to know if the name is not valid.

Provider

Identifies the Provider technology used in this connection 

Database

Identifies to which type of dataset is this connection

ConnectionString

Enter the information needed to connect with the database. You use macros on the connection string.  

Example: for the filename in a SQLite connection string, use <ProjectName> that is replaced by the name of the project.

LogonName

Enter a valid login name for the database.

LogonPassword

Enter the password that corresponds to the database login. (Only accessible by Administrators)

ServerIP

Optionally, an IP or DNS name for a computer to be used as a Secure Gateway.

Description

Enter a description for the database connection.

Customizing Pre-defined Databases

There are four database connection already created in any new Project:

Datasets DB - Pre-defined database connections

DB

Database

Path Location

Usage

Retentive

SQLite

<ProjectNameAndPath>.dbRetentive

Stores values for Retentive Tags.

RuntimeUsers

SQLite

 <ProjectNameAndPath>.dbRuntimeUsers

Stores dynamically created Users.

AlarmHistorian

SQLite

 <ProjectNameAndPath>.dbAlarmHistorian

Stores Alarm and AuditTrail records.

TagHistorian

SQLite

<ProjectNameAndPath>.dbTagHistorian

Stores Tag Historian and Annotations.

Any of them can be customized to any type of database. 

The selection of best storage location depends on all kind of factors, from internal company procedures to the volume of data and how the data shall be used. Therefore, that is decision to each Project according to its requirements.

If needed to use another database for the pre-defined connections, execute the following steps:

• Rename or Delete the previous DB. This step is necessary, as the system would not allow to create two objects with the same name. 

• Crate a new DB with the same name of the previous DB, with the required Database and connection strings.

• That is all!
  

ConnectionString example for SQL Express 

Image Removed

• Data Source: The server path and instance that will have the databases.

• Initial Catalog: The name of the database that will be used.

Additional Settings for Tag Historian and AlarmHistorian 

• Store and Forward: Enabling this option will cause the system to store the data locally if communication with the database is lost, and forward the data to synchronize once the connection is back again.

Datasets Queries Configuration

You can configure queries to perform more advanced functions with SQL statements to work with data from external databases.

To configure Dataset queries:

• Go to Datasets → Queries.

• Enter the field values as needed.

Dataset Query Configuration Properties  

Column

Description

Name

Enter a name for the query. The system allows you to know if the name is not valid.

DB

Select the database configuration.

SqlStatement

Enter the query using SQL syntax.

Mapping

Click "..." to select the tags that you want to populate with data from specific columns returned by the query.

MappingDateTime

Select the time reference (UTC or Local).

Description

Enter a description for the table configuration.

Datasets Tables Configuration

To configure database tables:

• Go to Datasets → Tables.

• Enter the field values as needed.

Dataset Table Configuration Properties  

Field / Column

Description

Name

Enter a name for the table configuration. The system lets you know if the name is not valid.

DB

Select the database connecton.

TableName

Select or type the table name in the Database you want to access

WhereCondition

Specify the parameters that will filter the data using SQL syntax. E.g. "ColumnName = {tag.tagInt}"

Access

Select the access permissions for the table.

Mapping

Click "..." to select the tags that you want to populate with data in the first row of the table with data from specific columns.

MappingDateTime

Select the time reference (UTC or Local).

Description

Enter a description for the table configuration.

Datasets Files Configuration

To configure dataset files:

• Go to Datasets → Files.

• Enter the field values as needed.

Dataset File Configuration Properties

Column

Description

Name

Enter a name for the file configuration. The system allows you to know if the name is not valid.

FileName

Enter the full path to the file. The file path can have Tag values embedded using curly brackets syntax. E.g.: ExampleFile{{tag.Test}}.txt. 

When executing, the area in curly brackets is replaced by the value of the Tag.

FileType

Select the type of file.

Objects

Click "..." to select the tags that you want to populate with data from the file with data from specific columns.

Description

Enter a description for the file configuration.

XMLSchemaType

Represents the schema type of an XML file, which can be: a TagList, XML that contains a tag list with the tag name and tag value; or a TagObject, XML that contains the entire tag tree and its children.

Using the Visual Query Editor

With the Visual Query Editor, users can drag and drop tables, define relationships, and add filters and conditions using a simple graphical interface. Once the query is created, it can be saved and executed like any other query within the Dataset Module. Check the Visual SQL Query Builder page for complete information.

The Datasets Module enables users to interact with SQL databases seamlessly. The module supports real-time Tags within SQL statements, and manages files and recipes in ASCII, Unicode, or XML formats.

The data retrieved from databases can be utilized in various ways throughout your solution. For example:

• In the Displays Module: Visualization tools like DataGrids can present query results on screens and dashboards, creating custom views of the data that are accessible and easy to understand for your users.
• In the Scripting Module: Custom scripts can reference query results and trigger specific actions, such as sending notifications, updating tags, or performing calculations, thereby implementing complex logic based on database data.
• Devices:  Sending data from field equipments to a SQL database, or applying settings from the database to the field equipments.

Pre-defined Database Connections

The Dataset Module also serves as a data storage configuration hub for other modules. The following Database connections are pre-defined by the Dataset Module.

• AlarmHistorian: Events and records for long-term retention.
• TagHistorian: Time-series storage for process variables,
• RuntimeUsers: Dynamics users and credentials created when running the solution.
• Retentive: Persistent records for tags and properties that need to be kept across multiple starts of the solution (typically configuration settings and setpoints).

Processing Data Requests

The Datasets Module has its implementation running as a service, which ensures high performance and real-time responses to multiple client requests.

This architecture also enhances protection and security for the database, as client displays and scripts won't access the databases directly, but through the Datasets Service.

Another benefit is the ability for Data Source Virtualization, meaning that when the solution is using Dataset.Query.Query1 in its displays or scripts, the database running that query, along with the query itself, can be maintained or replaced without affecting the overall solution configuration. This feature allows the solution to work with the data, regardless of the underlying data storage technology.

For an advanced deeper understanding of the Datasets Services, see Dataset Advanced Topics.

Configuring the Datasets Module

Configuration Workflow

The typical configuration workflow for the Dataset module has the following sequence:

Managing DB Connections

There are four database connections pre-defined in any new solution.

When using SQLite databases, the Dataset Module can automatically create the database locally if it doesn't already exist. For other database types, the database itself must already exist before you set your connection.

→ Read more about Datasets DBs.

DatasetQueries Configuration

Use the DatasetQueries to define SQL Statements, for queries and stored procedures to execute in connection of the created DatasetDB databases. 

→ Read more about Datasets Queries

DatasetTables Configuration

Use the DatasetTables to access or exchange data with databases tables, with simplified query syntax. It allows allow insert new rows directly on database tables.

→ Read more about Datasets Tables.

DatasetFiles Configuration

The DatasetFiles are used to customize file interactions in the Dataset Module. With this feature you can read or write realtime tags to ASCII, Unicode and XAML files.

→ Read more about Datasets Files.

Working with the Datasets Module

Runtime Execution

When executing the solution, there is an infrastructure of services that manages access to the database and transports that information to where it is requested. For instance, to display a Dataset Query result on an HTML5 page, that request first goes to the server, which then requests the database (which can be on another computer), and the information flows back to the requester.

As database operations can take some time to execute, it is very important to understand some aspects of the Datasets Module execution, including the concept of synchronous vs. asynchronous requests.

The page Datasets Module Execution details concepts that describe the module's internal operations.

Showing DataGrids Tables on Displays

One typical use of the Dataset Module is to display query results on displays and dashboards.

In order to so, create or DatasetQuery, or DatasetTable, then use the DataGrid Control on your displays.

Using Query Results on Scripts and Tags

It's possible to define the SQL statements with code (either using the Scripts Module or Display CodeBehind) and connect the results with tags early on.

The property Dataset.Query.Query1.SqlStatament holds the query that will be executed; just modify that property within your scripts. 

The Tag Type DATATABLE was created to be compatible with results of Select() statements. SImply apply the results to your query and use tags no manage the information. 

The TK (Toolkit extension for Scripts) has methods that allow for easy copying between DataTables (query results) and Template Tags, like TK.CopyTagToDataTable().

Monitoring Databases Connection Status

Monitoring Database Connections is an essential aspect of maintaining a reliable operation of the solution. 

This can be accomplished using the Dataset Namespace properties, which provide status for DatasetTables and DatasetQueries operations.

→ Read more about Datasets Runtime Attributes.

During the Development phase, when the Designer tools is connected with a Runtime (the Solution is in execution), the main status conditions can be seen in the monitoring page.

→ Read more about Datasets Monitor

Datasets Advanced Topics

Datasets Module Execution

The Dataset module facilitates efficient database interactions by utilizing TServer services, managing synchronous and asynchronous executions for optimal performance.

→ Read more about Databases Connection And Interactions.

Data Management

The Dataset Module offers versatile methods for managing data and concurrency within solutions, including Data Table tags and Async Contents.

→ Read more about Data Management.

Datasets Runtime Attributes

The Datasets Namespace exposes properties and methods from the .NET objects used by the Historian Module execution. You can use these properties and methods on your Displays or to create Scripts and Alarms.

→ Read more about Datasets Runtime Attributes.

Preventing SQL Injections

→ See page Datasets Advanced Topics

Network Gateway Access And Time Zone Handling

→ See page Datasets Advanced Topics

Backup Of Solutions SQLite Data Bases

→ See page Datasets Advanced Topics

Anchor
BestPractices BestPractices

Best Practices and Troubleshooting

Common Issues and Solutions

Connection loss between project and database

Database Timeout Configuration: The database may have a timeout setting that automatically disconnects idle connections after a certain period. It's recommended to check the database's timeout setting and adjust it, if necessary, to ensure that the connection remains active overnight.

Power Settings: It's also suggested to check the computer's power settings to ensure that it doesn't enter sleep or hibernation mode during idle moments, which could cause a loss of connection to the database. Adjusting these settings to keep the computer active during these idle moments may resolve the issue.

Database Connection Problem

In the DB configuration, there is always a "Test" button to ensure that the connection is happening correctly. When there is a problem, the return of this button is an error message, usually returned by the database provider itself. The most common errors are: invalid user, invalid password, computer without access to the database, incorrect form of authentication.

Issue: Error accessing the Database Table

Once the connection is established, the Table configuration is specific to a table. In the "Table" combobox, the list of available tables automatically appears. It is possible, via script, to change which table will be accessed. However, care must be taken that the table exists and that the configuration is done using the correct name. The same care must be taken when Queries are used, as it is the user's responsibility to type the correct table name, as well as the syntax of the separators.

Error in the Syntax of the Query

It is the user's responsibility to type the correct SQLStatement of a query using the QueryBuilder. Table name, column, values, all can generate an error if used incorrectly. For example: comparing different types may not return the expected result, strings in general should be in single quotes. The separators and clauses available can vary between databases. For example:

SQLServer

SELECT TOP 10 * FROM table WHERE column = value

SQLite

SELECT * FROM table WHERE column = value LIMIT 10;

Oracle

SELECT * FROM table WHERE column = value AND ROWNUM <= 10;

or new Oracle version

SELECT * FROM table WHERE column = value FETCH FIRST 10 ROWS ONLY;

IBM DB2

SELECT * FROM table WHERE column = value FETCH FIRST 10 ROWS ONLY;

ServerIP without TWebServer Running on the Remote Machine

In some cases, the computer may not have access to the database. In this case, it is possible to create a gateway, routing the commands to be executed on the computer that has access to the database. The ServerIP field should be configured with the IP and port (<IP>:<port>), pointing to this computer that has access permission. This computer must have the software with the TWebServer running installed. It will automatically perform this gateway service and send the commands to the database.

DataTable Returned NULL

When a query is returned null, some error has occurred. Some common errors include: connection failure with the database, table not found, Dataset module is not running, incorrect query syntax. Check the return of the method using WithStatus when using a synchronous method or use the LastStatus and LastStatusMessage property when using asynchronous mode.

DataTable Returned with 0 Rows

When this happens, in general, there is a connection with the database and the table name is correct. In this case, the search condition is usually wrong, or the table is really empty. Check if the column names are correct and if the separators and clauses are valid.

Dataset Module is Down

Although the TServer is responsible for forwarding requests to the database, the management and communication with the TServer is done by the Dataset module, as well as the treatment of responses. Therefore, if you are having basic problems with access and execution of database access, the first thing to check is whether the module is set up to run and is actually running.

Very High Response Time

Sometimes, it may seem that access to the database is not being made, but what might actually be happening is that some accesses can return a very large amount of data, or the database may be overloaded, or with a bad configuration, causing it to have a low performance. Or even, the network itself can be overloaded and slow, and all these factors can impact the response time. In these cases, it is important to execute the Query directly in the database environment to be sure that the problem is not on the side of the database. Do this and check how long the database itself takes to execute the query. It is also worth checking the volume of data exchanged to have an idea of the related side effects.

Update of a table with the wrong schema (select before update)

The Dataset module uses ADO technology, and many things are resolved at the level of this API. When we are going to perform an Update on a table, the schema of the table and controls in the .NET DataTable type are used. Therefore, if you are going to perform an update passing a Tag or .NET DataTable object as a parameter, it is important that this object respects the schema of the destination Table in the database. Normally, a Select command must have been given at some point to obtain the correct schema used by the bank. After this, it is easy to add, remove, and modify values in this DataTable and update it back to the physical table in the database.

Where condition CaseSensitive

Case sensitivity in a WHERE clause depends on the database and the configuration of the database you are using. For example, in MySQL, queries are case-insensitive by default, which means 'abc' and 'ABC' would be considered equal. However, this can be changed with specific database settings. In SQL Server, case sensitivity is also determined by the database configuration. In PostgreSQL, queries are case-sensitive by default, so 'abc' and 'ABC' would be considered different. Therefore, it really depends on the specific database and the settings of that database. If you need to ensure case-insensitivity in a query, you can use functions like UPPER() or LOWER() to convert all values to upper or lower case before comparison. For example:

SELECT * FROM table WHERE LOWER(column) = LOWER(value);

This query will return records where the column matches the value, regardless of capitalization.

Performance

The Dataset module's performance depends on many factors, including database performance, network latency, and the complexity of executing SQL queries. The platform will minimize overhead and execute queries as efficiently as possible. However, ultimately, the performance of the Dataset module is tied to these external factors. It's essential to design your database schema and queries with performance in mind and consider investing in high-quality hardware and network infrastructure to ensure optimal performance.

Best Practices and Recommendations

Error Handling

Error handling in the Dataset module is straightforward. If an error occurs during the execution of a command, the error message will update the module's Error property (Last Status). You can monitor this property to handle errors in your application. Furthermore, if an error occurs during the execution of a synchronous method, the process will return an empty DataTable and update the Error property. Alternatively, you can call methods like SelectCommandWithStatus, where the status will be an output parameter in the method.

In this section:

Working with the Dataset Module

Runtime Execution

One of the key features of the Dataset Module is the ability to execute SQL queries and retrieve data in real-time. Here are some ways to leverage the runtime execution features of the Dataset Module:

• Create SQL queries to retrieve data from external databases.
• Use query results to trigger events and actions within the platform environment.
• Configure event triggers based on specific query criteria, such as changes to a specific data point or a threshold value being exceeded.

Integration with Other Modules

The Dataset Module can be easily integrated with other modules within the software environment. Here are some examples of how the Dataset Module can be used in conjunction with other modules:

• Alarm Manager: Configure alarms based on query results to trigger notifications and actions.
• Visualization: Display query results on screens and dashboards using DataGrids and other visualization tools.
• Scripting: Use query results to trigger custom scripts and perform complex data processing and analysis.

By leveraging these integration options, users can gain greater insight and control over their data sources within the platform. With the ability to execute SQL queries and trigger actions based on query results, the Dataset Module provides a powerful set of tools for working with data.

DataGrids on Displays

One of the key features of the Dataset Module is the ability to display query results on screens and dashboards using visualization tools like DataGrids. Here are some steps for using DataGrids to display query results:

1. Create a query in the Dataset Module to retrieve the desired data.
2. In the Visualization Module, add a DataGrid control to the screen or dashboard.
3. Configure the DataGrid to display the query results by selecting the data source and column mappings.
4. Save and preview the screen or dashboard to display the query results on the DataGrid.

Using Query Results on Scripts and Tags

Users can use query results to trigger actions in custom scripts and tags. Here are some steps for using query results in scripts and tags:

1. Create a query in the Dataset Module to retrieve the desired data.
2. In the Scripting Module, create a custom script that references the query results.
3. Use the query results to trigger specific actions within the script, such as sending notifications or updating tags.
4. Save and execute the script to perform the desired actions.

Starting the Execution of Store Procedures

In the platform, the Dataset Module can execute stored procedures in external databases. Here are some steps for starting the execution of stored procedures:

1. Create a query in the Dataset Module that references the stored procedure in the external database.
2. Configure the query to pass any necessary input parameters to the stored procedure.
3. Set up event triggers based on the stored procedure execution results, such as to trigger an alarm or update a tag.
4. Save and execute the query to start the execution of the stored procedure.

Advanced Features and Options

Our platform provides many advanced features and options for working with data sources and SQL queries in the Dataset Module. Here are some examples of advanced features and options available:

• Pass input parameters to SQL queries or stored procedures by using tags as input variables.
• Map query or stored procedure output to specific data points or tags within the platform.
• Use event triggers based on query or stored procedure execution results to trigger notifications, alarms, or other actions.
• Use advanced SQL features like joins, subqueries, and aggregate functions to perform complex data processing and analysis.

Troubleshooting and Best Practices

Common Issues and Solutions

• Connection errors: If the connection to an external database is lost or otherwise interrupted, queries and stored procedures may fail to execute.

Solution: To resolve this issue, check the connection settings in the Dataset Module and ensure that the external database is reachable. If the connection settings are correct, try restarting the external database or resetting the connection in the Dataset Module.

• Query performance issues: If a query is taking too long to execute or is consuming too many system resources, it may be necessary to optimize the query or restructure the underlying database schema.

Solution: Some strategies for improving query performance include adding indexes, reducing the number of joins or subqueries, and limiting the amount of data returned by the query. Additionally, consider using the Query Analyzer tool in the Dataset Module to identify specific performance bottlenecks and optimize the query accordingly.

• Data type compatibility issues: If the data types returned by a query or stored procedure are incompatible with the data types expected by the platform, it may be necessary to use data conversion functions to transform the data into a compatible format.

Solution: Check the data type settings in the Dataset Module and ensure that the query or stored procedure is returning data in the correct format. If necessary, use data conversion functions like CAST or CONVERT to transform the data into the correct format.

• Tag mapping issues: If the mapping between query results and tags is not properly configured, tags may not update or display the correct values.

Solution: Review the tag mapping settings in the Dataset Module and ensure that the correct tags are being updated with the correct query results. Additionally, check the data type settings for the tags and ensure that they are compatible with the data types returned by the query or stored procedure.

• Authentication errors: If the authentication credentials for an external database are incorrect or expired, queries and stored procedures may fail to execute.

Solution: Check the authentication settings in the Dataset Module and ensure that the correct credentials are being used to access the external database. If the credentials are correct, check with the database administrator to ensure that the user account has the necessary permissions to execute the query or stored procedure.

Best Practices and Recommendations

• Plan queries carefully: When creating queries, take the time to carefully plan and structure the SQL statement to ensure that it returns the desired data in an efficient manner. Avoid using overly complex SQL statements or joining large tables without first considering the potential impact on system performance.
• Use parameterized queries: Use parameterized queries whenever possible to prevent SQL injection attacks and improve query performance. Parameterized queries use placeholders for input values that are replaced at runtime, rather than directly embedding user input in the SQL statement.
• Validate input values: Always validate user input values before passing them to SQL queries or stored procedures to prevent potential security vulnerabilities. Use input validation functions or regex patterns to ensure that user input values are in the expected format and do not contain malicious code.
• Monitor query performance: Use performance monitoring tools like the Query Analyzer to identify slow-running or resource-intensive queries and optimize them as necessary. Consider using query caching or stored procedures to reduce the overhead of frequently executed queries.
• Secure database connections: Use secure database connections to protect sensitive data and prevent unauthorized access. Use SSL or other encryption protocols to secure database connections, and use strong authentication mechanisms like Kerberos or LDAP to authenticate users.
• Document queries and procedures: Document queries and stored procedures to ensure that other developers and system administrators can understand and maintain the code. Use clear and descriptive comments and document the purpose and expected results of each query or procedure.
• Test queries and procedures thoroughly: Before deploying SQL queries or stored procedures to production environments, thoroughly test them in a development or testing environment to identify potential issues or compatibility problems. Use test data that accurately reflects the expected production data and ensure that the queries or procedures return the desired results.

Dataset Module Runtime Attributes

• ConnectionStatus: indicates whether the database connection is active or inactive.
• QueryStatus: indicates whether the query is currently executing or not.
• QueryLastExecution: indicates the date and time of the last query execution.
• QueryExecutionCount: indicates the number of times the query has been executed.
• DataAcquisitionRate: indicates the rate at which data is being acquired by the Dataset Module.