Java – Use Apache Spark to read JSON files

I’m trying to read a JSON file using Spark v2.0.0. Works very well in the case of simple data codes. If the data is a bit complicated, when I print df.show(), the data is not displayed in the correct way.

Here is my code :

SparkSession session = SparkSession.builder().master("local").appName("jsonreader").getOrCreate();
Dataset<Row> list = session.read().json("/Users/hadoop/Desktop/sample.json");
list.show();

Here is my sample data:

{
    "glossary": {
        "title": "example glossary",
        "GlossDiv": {
            "title": "S",
            "GlossList": {
                "GlossEntry": {
                    "ID": "SGML",
                    "SortAs": "SGML",
                    "GlossTerm": "Standard Generalized Markup Language",
                    "Acronym": "SGML",
                    "Abbrev": "ISO 8879:1986",
                    "GlossDef": {
                        "para": "A meta-markup language, used to create markup languages such as DocBook.",
                        "GlossSeeAlso": ["GML", "XML"]
                    },
                    "GlossSee": "markup"
                }
            }
        }
    }
}

My output is this:

+--------------------+
|     _corrupt_record|
+--------------------+
|                   {|
|       "glossary": {|
|        "title": ...|
|           "GlossDiv": {|
|            "titl...|
|               "GlossList": {|
|                "...|
|                 ...|
|                   "SortAs": "S...|
|                   "GlossTerm":...|
|                   "Acronym": "...|
|                   "Abbrev": "I...|
|                   "GlossDef": {|
|                 ...|
|                       "GlossSeeAl...|
|                 ...|
|                   "GlossSee": ...|
|                   }|
|                   }|
|                   }|
+--------------------+
only showing top 20 rows

If you must read this JSON, you need to format the JSON as a single line. This is a multi-line JSON, so it is not read and loaded correctly (One Object one Row).

Reference JSON API:

Loads a JSON file (one object per line) and returns the result as a
DataFrame.

{"glossary":{"title":"example glossary","GlossDiv":{"title":"S","GlossList":{"GlossEntry":{"ID":"SGML","SortAs":"SGML","GlossTerm":"Standard Generalized Markup Language","Acronym":"SGML","Abbrev":"ISO 8879:1986","GlossDef":{"para":"A meta-markup language, used to create markup languages such as DocBook.","GlossSeeAlso":["GML"," XML"]},"GlossSee":"markup"}}}}}

I

just tried it on the shell and it should work the same way from the code (I get the same broken record error when I read multiple lines of JSON).

scala> val df = spark.read.json("C:/DevelopmentTools/data.json")
df: org.apache.spark.sql.DataFrame = [glossary: struct<GlossDiv: struct<GlossList: struct<GlossEntry: struct<Abbrev: string, Acronym: string ... 5 more fields>>, title: string>, title: string>]

scala>

Edit:

For example, you can use any operation to get values from that data frame

scala> df.select(df("glossary. GlossDiv.GlossList.GlossEntry.GlossTerm")).show()
+--------------------+
|           GlossTerm|
+--------------------+
| Standard Generali...|
+--------------------+

scala>

You should also be able to do this from your code