ms orchestrator get lines activity example

3 min read 29-08-2025
ms orchestrator get lines activity example


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ms orchestrator get lines activity example

Microsoft Orchestrator (now known as Azure Logic Apps) offers a powerful suite of activities for automating workflows. One crucial activity is the "Get Lines" activity, essential for processing data that's structured line by line, commonly found in text files or other delimited data sources. This post delves into the functionality of the "Get Lines" activity, providing practical examples and addressing common questions.

What is the "Get Lines" Activity in MS Orchestrator?

The "Get Lines" activity in Azure Logic Apps (formerly MS Orchestrator) is designed to retrieve and process individual lines from a text-based input. This input could be the content of a file, the output of another activity, or a string variable. The activity efficiently splits the input into separate lines, enabling line-by-line processing within your workflow. This is invaluable when dealing with data formatted with line breaks (e.g., CSV files, log files, or simple text files). Each line is then treated as a separate item, making it easier to manipulate and analyze individual records.

How Does the "Get Lines" Activity Work?

The "Get Lines" activity functions by taking a single input (a string containing multiple lines) and splitting it based on newline characters. These characters typically represent line breaks (\r, \n, or \r\n). The output is an array, where each element in the array represents a single line from the original input. This array can then be iterated through using a "For each" loop, enabling you to process each line individually within the logic app.

Example: Processing a CSV File with "Get Lines"

Let's illustrate how to use "Get Lines" to process a simple CSV file containing product information:

Sample CSV (products.csv):

Product Name,Price,Quantity
Laptop,1200,5
Keyboard,75,10
Mouse,25,20

Logic App Workflow:

  1. Content Connector: Begin by using a connector to read the products.csv file. This could be a File System connector, an FTP connector, or any other appropriate connector depending on where your file is stored. The output of this connector is a string containing the entire CSV file content.

  2. Get Lines: Next, use the "Get Lines" activity. Provide the output of the Content Connector as the input to the "Get Lines" activity.

  3. For each: Use a "For each" loop to iterate through the array of lines returned by "Get Lines." Within the loop:

    • Split: Use the "Split" action to split each line into its component parts (Product Name, Price, Quantity) using the comma (,) as the delimiter.

    • Data Operations: Perform operations on each individual product data point. For instance, you might calculate the total value for each product (Price * Quantity) or add the product details to a database.

This approach allows you to efficiently process each product entry from the CSV file individually.

How to Handle Different Line Endings?

Different operating systems use different newline characters. Windows uses \r\n, while macOS and Linux typically use \n. The "Get Lines" activity generally handles these automatically. However, in cases where the file's line endings are inconsistent or unexpected, you might need to pre-process the string using string manipulation activities to ensure consistent line breaks before feeding it to "Get Lines".

Can I use "Get Lines" with JSON data?

While the "Get Lines" activity primarily targets line-delimited text data, it's not directly suitable for JSON data. JSON is structured differently, with key-value pairs enclosed in curly braces. Using the "Get Lines" activity with JSON will not yield meaningful results. To process JSON data, employ dedicated JSON parsing activities within Azure Logic Apps. These activities can parse the JSON and extract specific data elements based on their paths.

What are the limitations of the "Get Lines" activity?

The main limitation is that it's designed for relatively simple, line-based text files. It's not optimized for complex data structures or very large files. For extremely large files, consider alternative approaches like using Azure Data Factory or other more robust data processing services for improved scalability and performance.

This comprehensive guide provides a solid understanding of the "Get Lines" activity in Azure Logic Apps, equipping you with the knowledge and examples to effectively leverage it in your workflow automation tasks. Remember to choose the most appropriate data processing tools based on the complexity, size, and structure of your data.