Spark DataFrame join后移除重复的列

在Spark，两个DataFrame做join操作后，会出现重复的列。例如：

 Dataset moviesWithRating = moviesDF
                .join(averageRatingMoviesDF,
                        moviesDF.col("movieId").equalTo(averageRatingMoviesDF.col("movieId")));

其schema如下：

//moviesWithRating.printSchema();
        /**
         * root
         *  |-- _id: struct (nullable = true)
         *  |    |-- oid: string (nullable = true)
         *  |-- actors: string (nullable = true)
         *  |-- description: string (nullable = true)
         *  |-- directors: string (nullable = true)
         *  |-- genres: string (nullable = true)
         *  |-- issue: string (nullable = true)
         *  |-- language: string (nullable = true)
         *  |-- movieId: integer (nullable = true)
         *  |-- shoot: string (nullable = true)
         *  |-- timeLong: string (nullable = true)
         *  |-- title: string (nullable = true)
         *  |-- movieId: integer (nullable = true)
         *  |-- avgRating: double (nullable = true)
         */

我们在继续操作这个DataFrame时，可能就会报错，如下：org.apache.spark.sql.AnalysisException: Reference ‘movieId’ is ambiguous

解决方案有两种方法可以用来移除重复的列

• 方法一：join表达式使用字符串数组（用于join的列）

  Seq joinColumns = JavaConversions.asScalaBuffer(Arrays.asList("movieId")).toList();
  Dataset moviesWithRating = moviesDF.join(
                          averageRatingMoviesDF,
                          joinColumns,
                          "inner");
  

  这里DataFrame moviesDF和averageRatingMoviesDF使用了movieId和movieId两列来做join，返回的结果会对这两列去重

  如果是scala，解决方案如下：

   val moviesWithRating = moviesDf.join(averageRatingMoviesDF, Seq("movieId")) 
  

  • 方法二：使用select返回指定的列

    Dataset moviesWithRating = moviesDF
                    .join(averageRatingMoviesDF,
                            moviesDF.col("movieId").equalTo(averageRatingMoviesDF.col("movieId")))
                    .select(
                            moviesDF.col("movieId"),
                            col("actors"),
                            col("description"),
                            col("directors"),
                            col("genres"),
                            col("issue"),
                            col("language"),
                            col("shoot"),
                            col("timeLong"),
                            col("title"),
                            col("avgRating")
                    );
    

    说明：

    如果列较少, 推荐使用第二种.

    如果列较多, 推荐使用第一种.