In today’s data-driven world, handling data efficiently is essential. Enter dsq, a command line interface (CLI) tool that lets you run SQL queries against various data formats like JSON, CSV, Excel, and Parquet. While it might seem complex at first glance, this guide will help you navigate through its functionalities with ease.

About dsq

dsq serves as a CLI companion to DataStation, a GUI designed for data queries. It allows you to interact with your data files through SQL queries seamlessly.

Installation

Installing dsq is simple and can be achieved using several methods:

• macOS Homebrew:

  bash$ brew install dsq

• Binaries on macOS, Linux, WSL:

  bash
  $ VERSION=v0.23.0
  $ FILE=dsq-$(uname -s | awk '{print tolower($0)}')-x64-$VERSION.zip
  $ curl -LO https://github.com/multiprocessiodsq/releases/download/$VERSION/$FILE
  $ unzip $FILE
  $ sudo mv .dsq /usr/local/bin/dsq
  

• Binaries on Windows (not WSL):

  Download the latest Windows release from here, unzip it, and add dsq to your $PATH.

• Build and install from source:

  bash$ go install github.com/multiprocessiodsq@latest

Using dsq

Once dsq is installed, you can begin querying your data files. Here are a few usage scenarios:

Pretty Print

If you want to visualize your query outputs more clearly, consider using the pretty print option:

bash$ dsq testdata/userdata.parquet select count(*) from < 1000

You can also pipe the output to tools like jq for enhanced formatting:

bash$ dsq testdata/userdata.parquet select count(*) from | jq [count(*): 1000]

Piping Data to dsq

For command line data piping (only works outside Windows), you can use the -s flag to specify the file type:

bash$ cat testdata.csv | dsq -s csv SELECT * FROM < LIMIT 1

Multiple Files and Joins

dsq allows running SQL queries across multiple data files. Use the table numbers to reference them:

bash$ dsq testdata/join_users.csv testdata/join_ages.json SELECT 0.name, 1.age FROM 0 JOIN 1 ON 0.id = 1.id

SQL Query from File

For complex queries, you can store them in a file:

bash$ dsq data1.csv data2.csv -f query.sql

Transforming Data

If you need to convert your files into JSON format without running specific queries:

bash$ dsq testdata.csv

A Simple Analogy

Think of dsq as a librarian in a vast library filled with various texts (data files). By issuing specific requests (SQL queries), the librarian can quickly find the relevant information you seek, be it in JSON, CSV, or Excel formats. The librarian can also join books together to give you a more comprehensive understanding of a subject, much like combining multiple datasets!

Troubleshooting

If you run into issues while using dsq, here are some common troubleshooting tips:

• Ensure that your data files are formatted correctly and use the right extensions.
• If you encounter performance issues, check if caching is enabled and functioning correctly.
• Be wary of file types that dsq does not support. Refer to the supported file types section in the documentation if unsure.

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