Apache Spark SQL查询和DataFrame作为参考数据

Question

我有两个Spark DataFrame：

带有以下列的cities DataFrame：

city
-----
London
Austin

bigCities DataFrame，其中包含以下列：

name
------
London
Cairo

我需要转换DataFrame cities并在其中添加一个附加的布尔列： bigCity必须根据以下条件"cities.city IN bigCities.name"计算该列的值

我可以通过以下方式（使用静态bigCities集合）进行此操作：

cities.createOrReplaceTempView("cities")

var resultDf = spark.sql("SELECT city, CASE WHEN city IN ['London', 'Cairo'] THEN 'Y' ELSE 'N' END AS bigCity FROM cities")

但是我不知道如何在查询中用bigCities DataFrame替换静态的bigCities集合['London', 'Cairo'] 。 我想使用bigCities作为查询中的参考数据。

请告知如何实现此目标。

Answer 1

val df = cities.join(bigCities, $"name".equalTo($"city"), "leftouter").
                withColumn("bigCity", when($"name".isNull, "N").otherwise("Y")).
                drop("name")

Answer 2

您可以在bigCities表上使用collect_list（）。 看一下这个

scala> val df_city = Seq(("London"),("Austin")).toDF("city")
df_city: org.apache.spark.sql.DataFrame = [city: string]

scala> val df_bigCities = Seq(("London"),("Cairo")).toDF("name")
df_bigCities: org.apache.spark.sql.DataFrame = [name: string]

scala> df_city.createOrReplaceTempView("cities")

scala> df_bigCities.createOrReplaceTempView("bigCities")

scala> spark.sql(" select city, case when array_contains((select collect_list(name) from bigcities),city) then 'Y' else 'N' end as bigCity from cities").show(false)
+------+-------+
|city  |bigCity|
+------+-------+
|London|Y      |
|Austin|N      |
+------+-------+


scala>

如果数据集很大，则可以使用collect_set，它将更加高效。

scala> spark.sql(" select city, case when array_contains((select collect_set(name) from bigcities),city) then 'Y' else 'N' end as bigCity from cities").show(false)
+------+-------+
|city  |bigCity|
+------+-------+
|London|Y      |
|Austin|N      |
+------+-------+


scala>