Скачать или смотреть How to Read a bytea Type Column in PostgreSQL Line by Line

Discover the steps to read a `bytea` type column in PostgreSQL, extract the data, and insert rows into another table seamlessly.
---
This video is based on the question https://stackoverflow.com/q/62833962/ asked by the user 'xxx_coder_noscope' ( https://stackoverflow.com/u/13677923/ ) and on the answer https://stackoverflow.com/a/62834353/ provided by the user 'Mike Organek' ( https://stackoverflow.com/u/13808319/ ) 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: Read bytea type row by row?

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.
---
How to Read a bytea Type Column in PostgreSQL Line by Line

Do you have a column in your PostgreSQL database of type bytea—perhaps containing a .txt file—and need to read it line by line? This task may seem daunting, but with PostgreSQL's rich set of functions, you can extract the data efficiently and insert it into another table. Let's break down the steps you need to follow to achieve this.

Understanding the Problem

When dealing with a bytea data type, it's important to remember that it stores binary data. In your case, this data is simply text that you would like to manage on a row-by-row basis. The goal is to read the column, parse it, and insert each line into a different table, which could enhance data organization or facilitate further analysis.

Step-by-Step Solution

To accomplish this task, we can utilize several PostgreSQL functions in conjunction. Here’s how you can do it:

1. Encode the bytea Data

First, we need to convert the bytea data into a readable text format. We achieve this by using the encode() function:

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

This function will convert the binary data into an escaped text string, allowing us to handle it more easily.

2. Split the Data into an Array

Next, to handle each line of the text individually, we can use the string_to_array() function. This will split the text into an array based on a specific delimiter—in our case, the newline character (\n):

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

3. Unnest the Array into Rows

Once we have our array of lines, we can use the unnest() function to expand it into rows. This means that each line of the text will now occupy a separate row in our result set.

4. Utilizing CROSS JOIN LATERAL

To maintain the original order of the lines while also generating a row number (rnum), we will employ cross join lateral along with with ordinality. This ensures that every line is numbered as it is extracted:

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

Full Query

Combining all these elements, the full SQL query to read the bytea column line by line would look like this:

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

Explanation of the Query

SELECT id, rnum, tline retrieves the original ID from the table, the row number, and the line content.

FROM your_table specifies the table from which to read the data.

CROSS JOIN LATERAL unnest() applies the unnesting process we discussed, converting the array of text lines into rows.

ORDER BY id, rnum organizes the output based on the ID and the line number to ensure that lines appear in the order they were stored.

Conclusion

Reading a bytea type column in PostgreSQL and processing the data line by line is entirely feasible with the right approach. By following the systematic steps outlined above, you can extract text data efficiently from binary format and make it manageable in your database. Whether for reporting, analysis, or data migration, understanding how to manipulate these types of data is crucial for leveraging the full potential of your PostgreSQL database.

If you need further assistance with SQL queries or database management, feel free to ask!