Consulta de JSONB com JSONPath
Aplique expressões de caminho SQL/JSON para filtrar e extrair valores aninhados com suporte de índice.
Consulta de JSONB com JSONPath é uma aula grátis de PostgreSQL Performance & Query Optimization no CoddyKit. Esta é a aula 3 de 4. Você pode ler a aula completa abaixo gratuitamente — depois pratica ao vivo no navegador com um editor de código integrado e um tutor de IA 24/7. Faz parte do caminho de aprendizado de PostgreSQL Performance & Query Optimization, e seu progresso é sincronizado entre a web e o app CoddyKit. O curso de PostgreSQL Performance & Query Optimization inclui 4 aulas no total.
Partes desta aula ainda não foram traduzidas e aparecem em inglês.
Why JSONPath for JSONB
PostgreSQL stores semi-structured data in the jsonb type. Pulling nested values with the classic -> and ->> operators works, but gets clumsy fast for deep paths, arrays, and conditional filters.
The SQL/JSON path language (added in PostgreSQL 12) gives you a compact, expressive way to navigate and filter JSON. It powers two key functions:
jsonb_path_query/jsonb_path_query_array— extract matching valuesjsonb_path_existsand the@?/@@operators — test predicates
Best of all, those operators can be accelerated by a GIN index, which is exactly what this lesson is about.
A sample JSONB document
Imagine an orders table with a data jsonb column. A single row might hold a document like the one below.
Throughout this lesson we will navigate into customer, iterate over the items array, and filter by numeric and string conditions.
SELECT '{
"id": 1042,
"status": "shipped",
"customer": { "name": "Mara", "tier": "gold" },
"items": [
{ "sku": "A-1", "qty": 2, "price": 19.90 },
{ "sku": "B-7", "qty": 1, "price": 4.50 }
]
}'::jsonb AS data;The $ root and dot navigation
Every JSONPath expression starts at $, the context item (the whole document). From there you use dot notation for object keys.
$.status→ the value of thestatuskey$.customer.name→ a nested value
jsonb_path_query returns each match as a jsonb value. Note that string results keep their quotes; use jsonb_path_query_first(...) #>> '{}' or a cast if you need plain text.
SELECT jsonb_path_query(
'{"status":"shipped","customer":{"name":"Mara"}}'::jsonb,
'$.customer.name'
) AS name;Walking into arrays
To reach array elements, use square brackets. Indexes are zero-based.
$.items[0]→ the first element$.items[*]→ the wildcard, every element$.items[*].sku→ theskuof every element
When a path matches many values, jsonb_path_query returns one row per match. Wrap the call in jsonb_path_query_array to collect them into a single JSON array instead.
SELECT jsonb_path_query_array(
'{"items":[{"sku":"A-1"},{"sku":"B-7"}]}'::jsonb,
'$.items[*].sku'
) AS skus;Filter expressions with ? ( )
The real power of JSONPath is the filter expression: ? ( predicate ). Inside a filter, @ refers to the current item being tested.
To get every item whose quantity is at least 2:
$.items[*] ? (@.qty >= 2)
The filter keeps only the array elements that satisfy the predicate. You can then keep navigating, e.g. $.items[*] ? (@.qty >= 2).sku to return just their SKUs.
SELECT jsonb_path_query(
'{"items":[{"sku":"A-1","qty":2},{"sku":"B-7","qty":1}]}'::jsonb,
'$.items[*] ? (@.qty >= 2).sku'
) AS heavy_skus;Combining predicates and operators
Filter predicates support the usual comparison operators (==, !=, <, <=, >, >=) and the boolean connectives && and ||.
Note the equality operator inside JSONPath is ==, not the SQL single =. Strings are written with double quotes.
$.items[*] ? (@.qty > 1 && @.price < 10)$ ? (@.customer.tier == "gold")
Parentheses let you group complex logic just like in SQL.
SELECT jsonb_path_query(
'{"items":[{"sku":"A-1","qty":2,"price":19.9},{"sku":"C-9","qty":3,"price":4.5}]}'::jsonb,
'$.items[*] ? (@.qty > 1 && @.price < 10)'
) AS cheap_bulk;Testing existence: @? and @@
For filtering rows in a WHERE clause you usually want a boolean, not the matched value. Two operators do this:
jsonb @? jsonpath→ true if the path returns any itemjsonb @@ jsonpath→ evaluates a path that itself yields a boolean predicate
Rule of thumb: with @? the filter lives inside the path ($.items[*] ? (@.qty > 5)); with @@ the path is the predicate ($.customer.tier == "gold"). Both are GIN-indexable.
SELECT
data @? '$.items[*] ? (@.qty > 5)' AS has_bulk_item,
data @@ '$.customer.tier == "gold"' AS is_gold
FROM (SELECT '{"customer":{"tier":"gold"},"items":[{"qty":2}]}'::jsonb AS data) t;Filtering rows in a real query
Here is the pattern you will write most often: select rows whose JSONB document satisfies a path predicate. Because @? is indexable, this can run without a sequential scan once the right index exists.
This query finds shipped orders that contain at least one item costing more than 100.
SELECT id, data->>'status' AS status
FROM orders
WHERE data @? '$.items[*] ? (@.price > 100)'
AND data @@ '$.status == "shipped"';Indexing with the default jsonb_ops GIN
A plain GIN index on the column uses the jsonb_ops operator class. It indexes every key and every value, supporting containment (@>), key-existence (?), and the JSONPath operators @? / @@.
It is flexible but larger, because each value gets its own index entry.
CREATE INDEX idx_orders_data ON orders USING gin (data);
-- Now this predicate can use the index:
EXPLAIN ANALYZE
SELECT id FROM orders
WHERE data @? '$.items[*] ? (@.price > 100)';Smaller and faster: jsonb_path_ops
If you only need containment and JSONPath search (not the standalone key-existence ? operator), the jsonb_path_ops operator class is the better choice.
It hashes whole key+value paths into single index entries, so the index is smaller and usually faster for @>, @?, and @@ lookups. The trade-off: it does not support the bare ?, ?|, ?& key-existence operators.
CREATE INDEX idx_orders_data_path
ON orders USING gin (data jsonb_path_ops);
-- Great for: data @? '$.items[*] ? (@.price > 100)'
-- Not for: data ? 'status'Expression indexes for hot scalar paths
GIN is ideal for flexible containment search. But if you constantly filter on one scalar value — say status — a targeted B-tree expression index on the extracted text is smaller and supports ordering and range scans.
- Extract once with
(data->>'status')and index that expression. - The query
WHEREclause must use the same expression for the planner to use it.
Use GIN for "does the document contain X?" and B-tree expression indexes for "equals / ordered-by this one field".
CREATE INDEX idx_orders_status
ON orders ((data->>'status'));
SELECT id FROM orders
WHERE data->>'status' = 'shipped'
ORDER BY (data->>'status');Quick Check
You need a GIN index that accelerates JSONPath predicates like data @? '$.items[*] ? (@.price > 100)' and you want the smallest, fastest index. You do not need the bare key-existence operator ?. Which index should you create?
Recap
You learned how to query JSONB with the SQL/JSON path language and how to make it fast:
- Navigate from
$using dots for keys and[*]for arrays. - Filter with
? (@ ... ), using==for equality and&&/||to combine predicates. - Extract matches with
jsonb_path_query/jsonb_path_query_array. - Test in WHERE clauses with
@?(filter inside the path) and@@(path is the predicate). - Index with GIN: default
jsonb_opsfor full flexibility, orjsonb_path_opsfor smaller, faster containment and path search; reach for a B-tree expression index when you repeatedly filter or sort by a single scalar field.
Pick the index that matches your access pattern, and always confirm with EXPLAIN ANALYZE.
Perguntas Frequentes
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O que vou aprender em “Consulta de JSONB com JSONPath”?
Aplique expressões de caminho SQL/JSON para filtrar e extrair valores aninhados com suporte de índice. Você pratica PostgreSQL Performance & Query Optimization com código prático que executa diretamente no navegador, e um tutor de IA 24/7 responde suas dúvidas enquanto trabalha na aula.
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Todas as aulas deste curso
- Operadores JSONB e consultas de contenção
- GIN versus índices de expressão em JSONB
- Consulta de JSONB com JSONPath
- Quando normalizar dados fora do JSONB