Azure Synapse Analytics Data Flow: How do the Table Actions and Update Methods work & can you conditionally Truncate with 1 Data Flow?

Question

I am working in Azure Synapse Analytics and making a dataflow, but I'm struggling with understanding some things. (I'm using Azure Data Lake Storage Gen 2 and Delta file for my sink)

1. For the sink activity:
   1. what is the difference between the update method "upsert" and the combination of "insert" and "update"?
   2. How exactly do the 3 table actions function?
      1. None, Overwrite, Truncate
2. And most importantly
   1. Is a way to conditionally truncate a table using a single dataflow. In other words, I'd like to be able to run a dataflow and have it truncate and insert into the sink. Then run that same dataflow later and only upsert.

Answer 1

Hi @Joshua

Thanks for the question and using MS Q&A platform.

As I understand, Working with Data Flows and Delta Lakes in Azure Synapse can involve some specific configurations, especially when choosing the write mode for the sink activity. Here is the detailed information on the mentioned queries.

For the sink activity:

1) What is the difference between the update method "upsert" and the combination of "insert" and "update"?

In Azure Synapse Analytics data flow sink activities, "upsert" and the combination of "insert" and "update" serve the same purpose - to modify data in a target dataset. But there is a key difference between the two approaches, which are as follows:

Upsert: A Single operation thar inserts a new record if it doesn't exist or updates an existing record if it matches the specified conditions. Azure Synapse Analytics performs the necessary insert or update operation automatically. It identifies rows based on a specific column (usually a unique identifier) and performs either an insert for new rows or an update for existing rows with the same identifier. This is useful when you want to merge new data into an existing table.

Insert & Update: These are the two separate operations, using a combination of "insert" and "update" operations requires separate conditions to determine whether to insert or update a row. This approach can be more flexible, but it also requires more complex logic to handle the different scenarios.

Insert: It adds new records to the target dataset.

Update: Modifies existing records in the target dataset. Matches rows in the source data with existing rows in the Delta table based on a unique identifier and updates the existing rows with the new values.

Overall, "upsert" provides a convenient and efficient way to merge new data into an existing table, while using a combination of "insert" and "update" operations provides more flexibility and control over the data merge process.

Feature	Upsert	Insert + Update
Feature	Upsert	Insert + Update
Operation Type	Single (combines insert and update)	Two separate operations (insert & update via Alter Row)
Key Column(s) Required	Yes	Yes (for update condition in Alter Row)
Efficiency	Generally more efficient for large datasets	May be less efficient due to separate operations
Control over Updates	Less granular control	More granular control with conditions in Alter Row

Choosing the Right Approach: If performance is crucial and you have a unique identifier column, upsert is generally preferred. If you need more control over inserts and updates or don't have a unique identifier, use insert + update.

2) How exactly do the 3 table actions function? None, Overwrite, Truncate

In Azure Synapse Analytics Data Flow, the three table actions - None, Overwrite, and Truncate - control how the data is written to the target table. Following is the more detailed information of each action:

None: When "None" is selected, the data flow will not perform any table-level operations before writing data to the target table. That means, if the table does not exist, the data flow will fail and if the table exists, the data will be appended to the existing data. In other words, "None" assumes that the target table already exists and is in the correct state. The data flow will simply add new data to the table without modifying the existing data or table structure.

Overwrite: When Overwrite is selected, the data flow will drop the existing table (if it exists). Recreate the table with the same schema as the incoming data. Write the new data to the recreated table. Overwrite replaces the entire table with the new data. This action is useful when you want to completely refresh the data in the target table.

Truncate: When Truncate is selected, the data flow will remove all existing data from the table (if it exists). Retain the table structure and schema. Write the new data to the truncated table. Truncate is similar to Overwrite, but it preserves the table structure and schema. This action is useful when you want to remove all existing data from the table and replace it with new data, while keeping the table's schema intact.

In Summary:

• None appends data to an existing table without modifying it.
• Overwrite replaces the entire table with new data.
• Truncate removes all existing data from the table and writes new data, while preserving the table structure and schema.

3) Is a way to conditionally truncate a table using a single dataflow. In other words, I'd like to be able to run a dataflow and have it truncate and insert into the sink. Then run that same dataflow later and only upsert.

Currently, Azure Synapse Analytics Data Flow does not support conditional execution of table actions within a single data flow. This means that a data flow can only be configured to perform one type of table action, such as truncate or upsert, and cannot be dynamically switched between the two based on runtime conditions.

To achieve the desired functionality, we suggest you create separate data flows for truncating and upserting, and then control which data flow to run based on the specific requirements.

I hope this helps, please do let us know if you any further queries.

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