SparkSQL: Cannot have map type columns in DataFrame which calls set operations(i

更多干货抢先看：大数据干货合集

通过SparkSQL，对两个存在map类型字段的Hive表进行union操作，报如下错误：

org.apache.spark.sql.AnalysisException: Cannot have map type columns in DataFrame which calls set operations(intersect, except, etc.), but the type of column map is map<string,string>;

1. 场景模拟

1）通过函数str_to_map/map生成map类型的字段，然后进行union操作

select 1 id, str_to_map("k1:v1,k2:v2") map

union

select 2 id, map("k1","v1","k2","v2") map

2）报错信息

org.apache.spark.sql.AnalysisException: Cannot have map type columns in DataFrame which calls set operations(intersect, except, etc.), but the type of column map is map<string,string>;;
Distinct
+- Union
   :- Project [1 AS id#116, str_to_map(k1:v1,k2:v2, ,, :) AS map#117]
   :  +- OneRowRelation
   +- Project [2 AS id#118, map(k1, v1, k2, v2) AS map#119]
      +- OneRowRelation

  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.failAnalysis(CheckAnalysis.scala:42)
  at org.apache.spark.sql.catalyst.analysis.Analyzer.failAnalysis(Analyzer.scala:95)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:364)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:85)
  at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:127)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:85)

2. 问题分析

根据报错信息，我们查看org.apache.spark.sql.catalyst.analysis.CheckAnalysis的checkAnalysis方法，第362行源码处理逻辑（错误信息是不是很熟悉呢？）：

关键看mapColumnInSetOperation中对逻辑计划的匹配：

针对逻辑计划中有Intersect、Except、Distinct的output"返回"的属性（Attribute）有map类型，或者Deduplicate的keys（也是Attribute）包含map字段类型，都会导致上述问题。

而union导致上述报错，是因为union会对结果去重，即distinct

3. 解决方案

询问后台小伙伴儿，目前的业务场景是考验不需要去重处理的。

那么我们都知道，union和union all的主要区别就是，前者会对结果去重，后者则不会。那么将union改为union all就好了。 更多干货抢先看：大数据干货合集