Let’s say we have to query a user table with a metadata JSONB column on a PostgreSQL 9.5+ database.
You can query with the @>
operator on metadata. This operator
can compare partial JSON strings against a JSONB column. It’s the
containment operator. For this case you may need to add a GIN index on
metadata column.
SELECT * FROM users WHERE metadata @> '{"country": "Peru"}';
The ->>
operator gets a JSON object field as text. Use it if
you want to query a simple field in a JSONB column. You might add a B-tree
index on metadata->>'country'
.
SELECT * FROM users WHERE metadata->>'country' = 'Peru';
Once again, the ->>
operator gets a JSON object field as
text. Just use directly it in the SELECT
.
SELECT metadata->>'country' FROM users;
You can use the ->>
operator with the classic operator you
use on text: =
, <>
, IS NULL
,
etc. Do not forget to index metadata->>'country'
with a
B-tree index.
SELECT * FROM users WHERE metadata->>'country' IS NOT NULL;
You can use both @>
or ->>
, just like for first
level attribute. Add an index according to your choice.
SELECT * FROM users WHERE metadata->'company'->>'name' = "Mozilla"; SELECT * FROM users WHERE metadata @> '{"company":{"name": "Mozilla"}}';
Remembering @>
operator checks containment in a JSONB column,
you can query on an array like {"x": ["a", "b", "c"]"}
by
just passing {"x":["a"]}
to the WHERE
clause:
SELECT * FROM users WHERE metadata @> '{"companies": ["Mozilla"]}';
Sometimes, we may need to select items where the attributes inside a JSONB column matches a bunch of possible values.
SELECT * FROM users WHERE metadata->>'countries' IN ('Chad', 'Japan');
Use UPDATE ... SET
as usual and pass the whole object as
JSON.
UPDATE users SET metadata = '{"country": "India"}';
Use the ||
operator to concatenate the actual data with the
new data. It will update or insert the value.
UPDATE users SET metadata = metadata || '{"country": "Egypt"}';
The operator -
removes a key from an object.
UPDATE users SET metadata = metadata - 'country';
Querying on JSONB objects is almost as simple as classic SQL queries. I posted only a few examples here, about what seems the most common use cases to me. It’s a note for me, I hope it could help other people too. You may dig in PostgreSQL docs, which has many more examples and more precise explanations :
Feel free to comment with advices, feedback and criticism. I would be really happy to learn more.
Thanks to Emilien Schneider (once again) for his review.
Raphaël Huchet Mar 30, 2017