Question 1

How does trdsql compare to other SQL-on-file tools like q or textql?

Accepted Answer

trdsql supports multiple SQL dialects (PostgreSQL, MySQL, SQLite) and more input/output formats, while tools like q typically use only SQLite. It also handles compression natively, making it more versatile for diverse data tasks.

Question 2

How to convert a JSON file to CSV with trdsql?

Accepted Answer

Use the command 'trdsql -ijson -ocsv "SELECT * FROM file.json"' to read JSON and output CSV. For nested JSON, you can use jq expressions with -ijq or SQL JSON functions to flatten data.

Question 3

Can trdsql process data from standard input (stdin)?

Accepted Answer

Yes, trdsql can read from stdin using '-' or 'stdin' as the table name, allowing piped data processing. For example, 'cat file.csv | trdsql "SELECT * FROM -"' works as shown in the README.

Question 4

What SQL functions are available when using the SQLite driver?

Accepted Answer

With the SQLite driver, you can use standard SQL functions and JSON functions from the json1 extension, such as JSON_EXTRACT. The README provides examples for querying nested JSON structures.

Question 5

How to perform a JOIN between a CSV file and a PostgreSQL database table?

Accepted Answer

Specify the PostgreSQL driver with -driver postgres and provide DSN, then use SQL JOIN syntax. The README has an example under PostgreSQL showing how to join a CSV file with an existing database table.

Question 6

Is trdsql good for production ETL pipelines?

Accepted Answer

While trdsql is powerful for ad-hoc queries and quick transformations, it lacks built-in scheduling, error handling, and incremental processing, making it less suitable for robust production ETL without additional scripting.

Question 7

How to output results as a Markdown table?

Accepted Answer

Use the -omd option, e.g., 'trdsql -omd "SELECT * FROM file.csv"' to generate Markdown-formatted output. The README demonstrates this in the ASCII Table & MarkDown output section.

trdsql

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