使用 spark scala 从 json 结构中获取电影类别

Question

I have a df_movies and col of geners that look like json format.

|genres |
[{'id': 28, 'name': 'Action'}, {'id': 12, 'name': 'Adventure'}, {'id': 37, 'name': 'Western'}]

How can I extract the first field of 'name': val?

way #1

df_movies.withColumn
    ("genres_extract",regexp_extract(col("genres"),
    """ 'name': (\w+)""",1)).show(false)

way #2

df_movies.withColumn
("genres_extract",regexp_extract(col("genres"),
"""[{'id':\s\d,\s 'name':\s(\w+)""",1))

Excepted: Action

Answer 1

You can use get_json_object function:

  Seq("""[{"id": 28, "name": "Action"}, {"id": 12, "name": "Adventure"}, {"id": 37, "name": "Western"}]""")
    .toDF("genres")
    .withColumn("genres_extract", get_json_object(col("genres"), "$[0].name" ))
    .show()


+--------------------+--------------+
|              genres|genres_extract|
+--------------------+--------------+
|[{"id": 28, "name...|        Action|
+--------------------+--------------+

Answer 2

Another possibility is using the from_json function together with a self defined schema. This allows you to "unwrap" the json structure into a dataframe with all of the data in there, so that you can use it however you want!

Something like the following:

import org.apache.spark.sql.types._

Seq("""[{"id": 28, "name": "Action"}, {"id": 12, "name": "Adventure"}, {"id": 37, "name": "Western"}]""")
  .toDF("genres")


// Creating the necessary schema for the from_json function
val moviesSchema = ArrayType(
  new StructType()
    .add("id", StringType)
    .add("name", StringType)
  )

// Parsing the json string into our schema, exploding the column to make one row
// per json object in the array and then selecting the wanted columns,
// unwrapping the parsedActions column into separate columns
val parsedDf = df
  .withColumn("parsedMovies", explode(from_json(col("genres"), moviesSchema)))
  .select("parsedMovies.*")

parsedDf.show(false)
+---+---------+                                                                                                                                                                                                                                                                 
| id|     name|                                                                                                                                                                                                                                                                 
+---+---------+                                                                                                                                                                                                                                                                 
| 28|   Action|                                                                                                                                                                                                                                                                 
| 12|Adventure|                                                                                                                                                                                                                                                                 
| 37|  Western|                                                                                                                                                                                                                                                                 
+---+---------+