Don’t use JSON for data that can easily be stored in database tables.For example, the majority of questions about PostgreSQL and JSON asked on Stackoverflow are about problems that arise from the use of JSON where it had better been avoided.įollow these guidelines when you consider using JSON in PostgreSQL:
Postgresql json query how to#
It is just that many people don’t understand how to use it right. If all the above is wrong, should we use JSON in PostgreSQL at all?ĭon’t get me wrong: JSON support in PostgreSQL is a wonderful thing. That query can use the GiST index from the exclusion constraint we created above. With our junction table, the query becomes WHERE CAST(elem.j -> 'from' AS timestamp) > 'to' AS timestamp) > TIMESTAMP ' 15:30:00' Imagine we want to search for all rooms that are occupied at 15:30:00. Simple searches for equality can be performed with the JSON containment operator and such searches can be supported by a GIN index. Sixth mistake: complicated searches in JSON The extension is required to create a GiST index on a bigint column. With the junction table, the exercise is simple all we have to do is to add an exclusion constraint that checks for overlaps with the & operator:ĬREATE EXTENSION IF NOT EXISTS btree_gist ĪLTER TABLE reservations ADD EXCLUDE USING gist (
Postgresql json query free#
The best that comes to mind is a constraint trigger, but that would require elaborate locking or the SERIALIZABLE transaction isolation level to be free from race conditions. With JSON, we are pretty much out of luck here. So far, our data model offers no protection against overlapping reservations, which would be good to enforce in the database. Fifth mistake: trying to enforce constraints on JSON This statement will only write a small amount of data.ĭeleting a reservation is just as complicated and expensive, and is left as an exercise to the reader. The whole JSON object has to be read and written, which is more I/O than you would want – particularly if the JSON object is large and stored out of line.Ĭompare how simple the same exercise would be with the junction table: This will fetch the complete JSON object, construct a new JSON from it and store that new object in the table. This data model exemplifies everything that you can do wrong: In this article, I will try to point out good and bad uses of JSON in PostgreSQL, and provide you with guidelines that you can follow. That causes problems and unhappiness in the long run. However, my experience is that the vast majority of people don’t use it correctly. Many people – particularly those with a stronger background in Javascript programming than in relational databases – use it extensively. Row_to_json(record ) : Returns the row as JSON.The comprehensive JSON support in PostgreSQL is one of its best-loved features. Json_agg(expression) : aggregates values as a JSON array. I am doing this using, json_agg and row_to_json function. Sometimes it requires to populate JSON formatted data for a web service purpose. Here, I am sharing one type of utility script to convert PostgreSQL table data into JSON formatted data. Generally, We are storing JSON formatted data into PostgreSQL and access base on the different filters. In this post, I am also going share one of the important query to convert PostgreSQL tabular data into JSON formatted data. PostgreSQL 9.4: Indexing on jsonb Data Type (Part 3/3). PostgreSQL 9.4: Introduced JSON Functions and Operators (Part 2/3). PostgreSQL 9.4: The JSON data type is Awesome (Part 1/3).
Postgresql json query series#
This is one of the interesting topics for us and I have recently published a series of articles on PostgreSQL JSON Data type. It also introduced a variety of new operators and functions related to JSON data type. PostgreSQL 9.4 introduced very powerful data type called JSON data type.
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