FLATTEN(Lakehouse v1)
将嵌套的 JSON 数据转换为表格格式,每个元素或字段表示为单独的一行。
SQL 语法
Section titled “SQL 语法”[LATERAL] FLATTEN ( INPUT => <expr> [ , PATH => <expr> ] [ , OUTER => TRUE | FALSE ] [ , RECURSIVE => TRUE | FALSE ] [ , MODE => 'OBJECT' | 'ARRAY' | 'BOTH' ] )| 参数 / 关键字 | 说明 | 默认 |
|---|---|---|
| INPUT | 指定要展平的 JSON 或数组数据。 | - |
| PATH | 指定输入数据中要展平的数组或对象的路径。 | - |
| OUTER | 设为 TRUE 时,结果为零行的输入行仍会包含在输出中,但这些行的 KEY、INDEX 和 VALUE 列的值会设为 NULL。 | FALSE |
| RECURSIVE | 设为 TRUE 时,函数会继续展平嵌套元素。 | FALSE |
| MODE | 控制只展平对象(‘OBJECT’)、只展平数组(‘ARRAY’),还是两者都展平(‘BOTH’)。 | ‘BOTH’ |
| LATERAL | LATERAL 是可选关键字,用于引用 FROM 子句中位于 LATERAL 关键字左侧的列。LATERAL 支持前面的表表达式与该函数之间的交叉引用。 | - |
下表说明 FLATTEN 函数的输出列:
| 列 | 说明 |
|---|---|
| SEQ | 与输入关联的唯一序列号。 |
| KEY | 展开值的键。如果被展平的元素不包含键,则设为 NULL。 |
| PATH | 被展平元素的路径。 |
| INDEX | 如果元素是数组,则此列包含其索引;否则设为 NULL。 |
| VALUE | 被展平元素的值。 |
| THIS | 此列标识当前正在被展平的元素。 |
SQL 示例
Section titled “SQL 示例”SQL 示例 1:演示 PATH、OUTER、RECURSIVE 和 MODE 参数
Section titled “SQL 示例 1:演示 PATH、OUTER、RECURSIVE 和 MODE 参数”此示例演示 FLATTEN 函数在 PATH、OUTER、RECURSIVE 和 MODE 参数下的行为。
SELECT *FROM FLATTEN ( INPUT => PARSE_JSON ( '{"name": "John", "languages": ["English", "Spanish", "French"], "address": {"city": "New York", "state": "NY"}}' ) );
┌────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐│ seq │ key │ path │ index │ value │ this │├────────┼──────────────────┼──────────────────┼──────────────────┼──────────────────────────────────┼───────────────────────────────────────────────────────────────────────────────────────────────────────┤│ 1 │ address │ address │ NULL │ {"city":"New York","state":"NY"} │ {"address":{"city":"New York","state":"NY"},"languages":["English","Spanish","French"],"name":"John"} ││ 1 │ languages │ languages │ NULL │ ["English","Spanish","French"] │ {"address":{"city":"New York","state":"NY"},"languages":["English","Spanish","French"],"name":"John"} ││ 1 │ name │ name │ NULL │ "John" │ {"address":{"city":"New York","state":"NY"},"languages":["English","Spanish","French"],"name":"John"} │└────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘
-- PATH helps in selecting elements at a specific path from the original JSON data.SELECT *FROM FLATTEN ( INPUT => PARSE_JSON ( '{"name": "John", "languages": ["English", "Spanish", "French"], "address": {"city": "New York", "state": "NY"}}' ), PATH => 'languages' );
┌──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐│ seq │ key │ path │ index │ value │ this │├────────┼──────────────────┼──────────────────┼──────────────────┼───────────────────┼────────────────────────────────┤│ 1 │ NULL │ languages[0] │ 0 │ "English" │ ["English","Spanish","French"] ││ 1 │ NULL │ languages[1] │ 1 │ "Spanish" │ ["English","Spanish","French"] ││ 1 │ NULL │ languages[2] │ 2 │ "French" │ ["English","Spanish","French"] │└──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘
-- RECURSIVE enables recursive flattening of nested structures.SELECT *FROM FLATTEN ( INPUT => PARSE_JSON ( '{"name": "John", "languages": ["English", "Spanish", "French"], "address": {"city": "New York", "state": "NY"}}' ), RECURSIVE => TRUE );
┌────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐│ seq │ key │ path │ index │ value │ this │├────────┼──────────────────┼──────────────────┼──────────────────┼──────────────────────────────────┼───────────────────────────────────────────────────────────────────────────────────────────────────────┤│ 1 │ address │ address │ NULL │ {"city":"New York","state":"NY"} │ {"address":{"city":"New York","state":"NY"},"languages":["English","Spanish","French"],"name":"John"} ││ 1 │ city │ address.city │ NULL │ "New York" │ {"city":"New York","state":"NY"} ││ 1 │ state │ address.state │ NULL │ "NY" │ {"city":"New York","state":"NY"} ││ 1 │ languages │ languages │ NULL │ ["English","Spanish","French"] │ {"address":{"city":"New York","state":"NY"},"languages":["English","Spanish","French"],"name":"John"} ││ 1 │ NULL │ languages[0] │ 0 │ "English" │ ["English","Spanish","French"] ││ 1 │ NULL │ languages[1] │ 1 │ "Spanish" │ ["English","Spanish","French"] ││ 1 │ NULL │ languages[2] │ 2 │ "French" │ ["English","Spanish","French"] ││ 1 │ name │ name │ NULL │ "John" │ {"address":{"city":"New York","state":"NY"},"languages":["English","Spanish","French"],"name":"John"} │└────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘
-- MODE specifies whether only objects ('OBJECT'), only arrays ('ARRAY'), or both ('BOTH') should be flattened.-- In this example, MODE => 'ARRAY' is used, which means that only arrays within the JSON data will be flattened.SELECT *FROM FLATTEN ( INPUT => PARSE_JSON ( '{"name": "John", "languages": ["English", "Spanish", "French"], "address": {"city": "New York", "state": "NY"}}' ), MODE => 'ARRAY' );
---
-- OUTER determines the inclusion of zero-row expansions in the output.-- In this first example, OUTER => TRUE is used with an empty JSON array, which results in zero-row expansions.-- Rows are included in the output even when there are no values to flatten.SELECT *FROM FLATTEN (INPUT => PARSE_JSON ('[]'), OUTER => TRUE);
┌─────────────────────────────────────────────────────────────────────────────────────────────────────────┐│ seq │ key │ path │ index │ value │ this │├────────┼──────────────────┼──────────────────┼──────────────────┼───────────────────┼───────────────────┤│ 1 │ NULL │ NULL │ NULL │ NULL │ NULL │└─────────────────────────────────────────────────────────────────────────────────────────────────────────┘
-- In this second example, OUTER is omitted, and the output shows how rows with zero results are not included when OUTER is not specified.SELECT *FROM FLATTEN (INPUT => PARSE_JSON ('[]'));SQL 示例 2:演示 LATERAL FLATTEN
Section titled “SQL 示例 2:演示 LATERAL FLATTEN”此示例演示 FLATTEN 函数与 LATERAL 关键字配合使用时的行为。
-- Create a table for Tim Hortons transactions with multiple itemsCREATE TABLE tim_hortons_transactions ( transaction_id INT, customer_id INT, items VARIANT);
-- Insert data for Tim Hortons transactions with multiple itemsINSERT INTO tim_hortons_transactions (transaction_id, customer_id, items)VALUES (101, 1, parse_json('[{"item":"coffee", "price":2.50}, {"item":"donut", "price":1.20}]')), (102, 2, parse_json('[{"item":"bagel", "price":1.80}, {"item":"muffin", "price":2.00}]')), (103, 3, parse_json('[{"item":"timbit_assortment", "price":5.00}]'));
-- Show Tim Hortons transactions with multiple items using LATERAL FLATTENSELECT t.transaction_id, t.customer_id, f.value:item::STRING AS purchased_item, f.value:price::FLOAT AS priceFROM tim_hortons_transactions t, LATERAL FLATTEN(input => t.items) f;
┌───────────────────────────────────────────────────────────────────────────┐│ transaction_id │ customer_id │ purchased_item │ price │├─────────────────┼─────────────────┼───────────────────┼───────────────────┤│ 101 │ 1 │ coffee │ 2.5 ││ 101 │ 1 │ donut │ 1.2 ││ 102 │ 2 │ bagel │ 1.8 ││ 102 │ 2 │ muffin │ 2 ││ 103 │ 3 │ timbit_assortment │ 5 │└───────────────────────────────────────────────────────────────────────────┘
-- Find maximum, minimum, and average prices of the purchased itemsSELECT MAX(f.value:price::FLOAT) AS max_price, MIN(f.value:price::FLOAT) AS min_price, AVG(f.value:price::FLOAT) AS avg_priceFROM tim_hortons_transactions t, LATERAL FLATTEN(input => t.items) f;
┌───────────────────────────────────────────────────────────┐│ max_price │ min_price │ avg_price │├───────────────────┼───────────────────┼───────────────────┤│ 5 │ 1.2 │ 2.5 │└───────────────────────────────────────────────────────────┘