[ozgune]

(Ozgun at Citus Data)

You're right that you need to have Postgres installed. For running SQL over multiple JSON files, we wanted to keep the blog post short and noted several different ways to go over multiple files in our GitHub Readme.

1. You can create a partitioned PostgreSQL table, and declare one child table per JSON file. You can also declare constraints on the child table to filter out irrelevant files to the query.

2. You can create a distributed foreign table on CitusDB, even if you'd like to run on one node. In this case, we'll collect statistics automatically for you, and filter out irrelevant files.

3. If neither of these fit, you could change the source code to scan over one directory instead of a file. We didn't go down this path to be compatible with file_fdw's semantics.

[tracker1]

Just an idea... I had a script doing record dumps at a prior job... (there were about 30 joins for getting a single record (denormalized) into json), so having each one in a separate .json.gz file was a useful backup solution... it was about zero cost when doing mirroring to another system for query/display purposes.

In the file system, to prevent too many records in a single directory it was split up per 1000 records... base/00001000/(1000-1999).json.gz ... this was mainly for being able to navigate this structure via a gui. I would suggest if your system can't do "basepath//*.json.gz" that you consider it.

[neilk]

Okay, so if I understand correctly, the benefit here is that I can run some kinds of SQL queries on a large collection of heterogenous JSON documents. Is that right? You're still speaking Postgres-internals-geek, not I-want-to-get-something-done geek.

That is:

- you can take heterogenous JSON documents, and then make them appear to the Postgres world as separate tables. (Which they have to be, because they're not uniform)

- you can then take some kinds of SQL queries and distribute them among these tables, as if they were one big SQL table. If some pseudo-tables have missing or extra columns, no problem.

[ozgune]

Thanks for the comment. Yes, that's exactly the benefit.

You could in fact have heterogeneous JSON documents within one file, and json_fdw could still handle them. If a field you declared in the table schema doesn't appear in a JSON document, json_fdw would just consider that field to be Null.

The issue is, json_fdw is built such that one table can only associated with one JSON file, and users typically have many JSON files lying around. For example, you'd have one JSON file for each hour's worth of website error logs.

If that's the case, you could create a distributed table. That way, you could run the query one distributed table and have the query run on all your JSON files instead of just one.

That said, it's probably best to associate one type of JSON logs (say your website error logs) with one distributed table. That way, your queries go over your website error logs or your mobile application logs, but not both at the same time.

[knowtheory]

It should be said I think that it's super cool that you guys are putting Postgres to broader use. More stuff can and should be done with it, i'm just not sure what to do with this particular tool :)