Spark SQL 的行转列 LATERAL VIEW

提示

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Spark SQL 的 LATERAL VIEW 子句与生成器函数（如 EXPLODE）结合使用，后者将生成包含一行或多行的虚拟表。LATERAL VIEW 将行应用于每个原始输出行。

语法

Spark SQL 的 LATERAL VIEW 子句结构为：

LATERAL VIEW [ OUTER ] generator_function ( expression [ , ... ] ) [ table_alias ] AS column_alias [ , ... ]

参数：

OUTER：如果指定了 OUTER，则如果输入数组/映射为空或 null，则返回 null
generator_function：指定生成器函数（EXPLODE, INLINE, 等）
table_alias：generator_function 的别名，可选
column_alias：列出 generator_function 的列别名，可在输出行中使用。如果 generator_function 有多个输出列，则可能有多个别名on have multiple output columns.

示例

以下是一些示例讲解：

CREATE TABLE person (id INT, name STRING, age INT, class INT, address STRING);
INSERT INTO person VALUES
    (100, 'John', 30, 1, 'Street 1'),
    (200, 'Mary', NULL, 1, 'Street 2'),
    (300, 'Mike', 80, 3, 'Street 3'),
    (400, 'Dan', 50, 4, 'Street 4');

SELECT * FROM person
    LATERAL VIEW EXPLODE(ARRAY(30, 60)) tableName AS c_age
    LATERAL VIEW EXPLODE(ARRAY(40, 80)) AS d_age;
+------+-------+-------+--------+-----------+--------+--------+
|  id  | name  |  age  | class  |  address  | c_age  | d_age  |
+------+-------+-------+--------+-----------+--------+--------+
| 100  | John  | 30    | 1      | Street 1  | 30     | 40     |
| 100  | John  | 30    | 1      | Street 1  | 30     | 80     |
| 100  | John  | 30    | 1      | Street 1  | 60     | 40     |
| 100  | John  | 30    | 1      | Street 1  | 60     | 80     |
| 200  | Mary  | NULL  | 1      | Street 2  | 30     | 40     |
| 200  | Mary  | NULL  | 1      | Street 2  | 30     | 80     |
| 200  | Mary  | NULL  | 1      | Street 2  | 60     | 40     |
| 200  | Mary  | NULL  | 1      | Street 2  | 60     | 80     |
| 300  | Mike  | 80    | 3      | Street 3  | 30     | 40     |
| 300  | Mike  | 80    | 3      | Street 3  | 30     | 80     |
| 300  | Mike  | 80    | 3      | Street 3  | 60     | 40     |
| 300  | Mike  | 80    | 3      | Street 3  | 60     | 80     |
| 400  | Dan   | 50    | 4      | Street 4  | 30     | 40     |
| 400  | Dan   | 50    | 4      | Street 4  | 30     | 80     |
| 400  | Dan   | 50    | 4      | Street 4  | 60     | 40     |
| 400  | Dan   | 50    | 4      | Street 4  | 60     | 80     |
+------+-------+-------+--------+-----------+--------+--------+

SELECT c_age, COUNT(1) FROM person
    LATERAL VIEW EXPLODE(ARRAY(30, 60)) AS c_age
    LATERAL VIEW EXPLODE(ARRAY(40, 80)) AS d_age 
GROUP BY c_age;
+--------+-----------+
| c_age  | count(1)  |
+--------+-----------+
| 60     | 8         |
| 30     | 8         |
+--------+-----------+

SELECT * FROM person
    LATERAL VIEW EXPLODE(ARRAY()) tableName AS c_age;
+-----+-------+------+--------+----------+--------+
| id  | name  | age  | class  | address  | c_age  |
+-----+-------+------+--------+----------+--------+
+-----+-------+------+--------+----------+--------+

SELECT * FROM person
    LATERAL VIEW OUTER EXPLODE(ARRAY()) tableName AS c_age;
+------+-------+-------+--------+-----------+--------+
|  id  | name  |  age  | class  |  address  | c_age  |
+------+-------+-------+--------+-----------+--------+
| 100  | John  | 30    | 1      | Street 1  | NULL   |
| 200  | Mary  | NULL  | 1      | Street 2  | NULL   |
| 300  | Mike  | 80    | 3      | Street 3  | NULL   |
| 400  | Dan   | 50    | 4      | Street 4  | NULL   |
+------+-------+-------+--------+-----------+--------+

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更新时间：2021-08-29 14:48:11 标签：sql spark 行转列