select语句中的spark in/exists谓词

下面是正确的SQL查询:

import sparkSession.implicits._

Seq("france").toDF("country").createOrReplaceTempView("countries")
Seq(("user1", "france"), ("user2", "italy"), ("user2", "usa"))
  .toDF("user", "country").createOrReplaceTempView("users")

val query =
  s"""
     |SELECT
     |  CASE
     |    WHEN u.country = 'italy' THEN 'Italy'
     |    ELSE (
     |      CASE
     |        WHEN u.country = c.country THEN upper(u.country)
     |        ELSE u.country
     |      END
     |    ) END AS country
     |FROM users u
     |LEFT JOIN countries c
     |  ON u.country = c.country
  """.stripMargin
sparkSession.sql(query).show()

结果:

+-------+
|country|
+-------+
| FRANCE|
|  Italy|
|    usa|
+-------+

你可以使用的场景背后的原因 IN/EXISTS 仅谓词中的SQL运算符是:投影中的逻辑( CASE-WHEN 在我们的情况下) 每行评估 在从所选内容返回的数据集中。 考虑到这一点,运行等效于 CASE WHEN country IN (SELECT * FROM countries) 对于来自的每一行 users 表。因此,SQL在语言级别(SQL解析器引擎)上防止了这种情况。

作为替代方案,您可以使用

带列()

和

当()

函数(从 spark.sql.functions ):

val users = Seq(("1", "france"), ("2", "Italy"), ("3", "italy")).toDF("userId", "country")
val countriesList = Seq("france", "italy", "germany").toList

val result = users.withColumn("country", when(col("country") === "italy", "Italy")
  .when(col("country") isin(countriesList:_*), upper(col("country"))).otherwise(col("country")))

result.show()

结果:

+------+-------+
|userId|country|
+------+-------+
|     1| FRANCE|
|     2|  Italy|
|     3|  Italy|
+------+-------+