# Convert query to objects of key-value pairs With open("student_rowarrays.js", "w") as f: Below, we’ll walk through it step-by-step.Ĭonn_string = "host='localhost' dbname='test' user='me' password='pw'"Ĭursor.execute("SELECT * FROM students_test") One file contains JSON row arrays, and the other has JSON key-value objects. Here’s an example Python script that generates two JSON files from that query. Here’s a script that creates a table and fills it with two rows of data: CREATE TABLE students_test ( Python works well for this, with its JSON encoder/decoder offering a flexible set of tools for converting Python objects to JSON.
I’ve gone this route for a few data-driven visuals, creating JSON files out of large database tables. So, you want flat files, each one small for quick loading. Maybe you want to power a data visualization but have neither the time nor the desire to spin up a server to dynamically generate the data. Let’s say you want to generate a few hundred - or even a thousand - flat JSON files from a SQL database. For more of my writing on SQL, check out my book Practical SQL from No Starch Press. I am always interested in new challenges so if you need consulting help, reach me at all posts by Rajendra GuptaThis post has been updated from its original 2012 version to use PostgreSQL and the Python psycopg2 library.
#Output sql 2017 json query to text file series
I am the creator of one of the biggest free online collections of articles on a single topic, with his 50-part series on SQL Server Always On Availability Groups.īased on my contribution to the SQL Server community, I have been recognized as the prestigious Best Author of the Year continuously in 2019, 2020, and 2021 (2nd Rank) at SQLShack and the MSSQLTIPS champions award in 2020. I published more than 650 technical articles on MSSQLTips, SQLShack, Quest, CodingSight, and SeveralNines. I am the author of the book " DP-300 Administering Relational Database on Microsoft Azure". Hi! I am Rajendra Gupta, Database Specialist and Architect, helping organizations implement Microsoft SQL Server, Azure, Couchbase, AWS solutions fast and efficiently, fix related issues, and Performance Tuning with over 14 years of experience. Let me paste the query again for easiness SQL Command Text: In this section, paste the query we specified earlier for JSON data import. From the drop-down menu, select the data access mode as SQL Command Data access mode: We will use the SQL query specified above section.OLE DB connection Manager: Specify SQL Server instance details in the connection manager.Rename the source and destination as per below:ĭouble-click on the JSON file data and in the OLE DB source editor, do the following tasks: In the data flow tab, drag the OLE DB Source and OLE DB destination as shown below: In this package, drag Data Flow Task in the control flow task and rename it to Data import from the JSON file:ĭouble-click on this data import from the JSON file task and it moves the package in the data flow tab. Open Visual Studio 2019 and create a new integration service project in a suitable directory. I am using Visual Studio 2019 with SSDT package in this article. If you are not much aware of it, I would recommend reading SQLShack articles. You should have basic knowledge of SSIS packages. We can use SQL Server integration package for inserting JSON into the SQL Server table as well. SSIS package for importing JSON data into SQL Server table The following query, imports data from results.json, creates a JSON table automatically using SQL SELECT INTO statement and inserts data into it: We can also create a table using the SQL SELECT INTO statement similar to a relational DB table. We can use the similar t-SQL described earlier for inserting data in an existing table. Import JSON file data into the SQL Server table It seems SQL Server uses a fixed estimate of 50 rows for JSON data import: In this execution plan also, it estimates the number of rows 50 in comparison with the actual 290 rows. Let’s import another JSON file having 290 records and view the actual execution plan. We see a difference between the estimated number of rows (50) and an actual number of rows (10) as query optimizer unable to estimates the correct number of rows for JSON input It uses object for fetching the columns and their values In the above execution plan, note the following: Let’s hover the cursor over it and view the details: In this plan, we can note that it uses a table-valued function for OPENJSON. In SSMS, click on Actual Execution Plan and execute the previous SQL statement. View actual execution plan for JSON data import In this output, we do not see the EmailPromotion column even if it is available in the JSON:
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