Скачать или смотреть Best Practices for Updating an Imported CSV File in pgAdmin 4

Learn efficient strategies for regularly updating CSV files in pgAdmin 4 without creating duplicate entries in your database.
---
This video is based on the question https://stackoverflow.com/q/65819168/ asked by the user 'TommyK' ( https://stackoverflow.com/u/13124358/ ) and on the answer https://stackoverflow.com/a/65819592/ provided by the user 'Johnny Fitz' ( https://stackoverflow.com/u/1370053/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Updating an imported CSV file in pgadmin4

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Best Practices for Updating an Imported CSV File in pgAdmin 4

When working with CSV files in PostgreSQL using pgAdmin 4, users often encounter the challenge of updating data without creating duplicates. This issue is particularly common for users who regularly import new data into an existing table. If you've ever found yourself in this situation after re-importing your CSV every week, you're not alone. In this guide, we will walk you through effective strategies to update your imported CSV data while avoiding redundancy.

Understanding the Problem

You successfully created a table and imported data from a CSV file into pgAdmin 4 using the following commands:

[[See Video to Reveal this Text or Code Snippet]]

However, when you update the CSV file and re-run the COPY command, it results in the new data being added alongside the existing data, creating duplicates. This is not only inefficient but can also lead to data integrity issues.

Solution: Using a Staging Table Approach

To maintain a clean and organized database, the best practice for regularly updating imported CSV files is to use a staging table. Here’s how to effectively implement this method:

Step 1: Create a Staging Table

First, create a separate staging table that mimics the structure of your original table. This serves as a temporary storage area for the new data.

[[See Video to Reveal this Text or Code Snippet]]

Step 2: Load Data into the Staging Table

Instead of directly loading data into the JAN21 table, load your updated CSV into the staging table:

[[See Video to Reveal this Text or Code Snippet]]

Step 3: Identify New Data

The next step is to identify new records that are not already present in your main table (JAN21). You can achieve this using a SQL INSERT command with an EXCEPT or JOIN clause. Here’s an example using the EXCEPT clause:

[[See Video to Reveal this Text or Code Snippet]]

Step 4: Clean Up the Staging Table

Once the new data has been successfully inserted into your main table, you can empty or truncate the staging table to prepare for the next update cycle:

[[See Video to Reveal this Text or Code Snippet]]

Step 5: Repeat the Process Weekly

Every time you update your CSV file, simply repeat the steps from loading into the staging table to truncating it. This way, you maintain an updated JAN21 table without duplicates effectively.

Conclusion

Utilizing a staging table is an efficient method for updating your CSV data in pgAdmin 4 without creating duplicates. By separating the loading and inserting of data, you maintain data integrity while streamlining the update process. Implementing these best practices makes your workflow much more manageable, especially with regularly updated data.

If you have any questions or would like further clarification on the process, feel free to leave a comment below. Happy data managing!