与 Spark 数据帧的模式猜测不一致 JSON

Question

正在尝试使用 Spark 1.4.1 数据帧读取 JSON 文件并在其中导航。似乎猜测的架构不正确。

JSON 文件是：

{
    "FILE": {
        "TUPLE_CLI": [{
            "ID_CLI": "C3-00000004",
            "TUPLE_ABO": [{
                "ID_ABO": "T0630000000000004",
                "TUPLE_CRA": {
                    "CRA": "T070000550330",
                    "EFF": "Success"
                },
                "TITRE_ABO": ["Mr",
                "OOESGUCKDO"],
                "DATNAISS": "1949-02-05"
            },
            {
                "ID_ABO": "T0630000000100004",
                "TUPLE_CRA": [{
                    "CRA": "T070000080280",
                    "EFF": "Success"
                },
                {
                    "CRA": "T070010770366",
                    "EFF": "Failed"
                }],
                "TITRE_ABO": ["Mrs",
                "NP"],
                "DATNAISS": "1970-02-05"
            }]
        },
        {
            "ID_CLI": "C3-00000005",
            "TUPLE_ABO": [{
                "ID_ABO": "T0630000000000005",
                "TUPLE_CRA": [{
                    "CRA": "T070000200512",
                    "EFF": "Success"
                },
                {
                    "CRA": "T070010410078",
                    "EFF": "Success"
                }],
                "TITRE_ABO": ["Miss",
                "OB"],
                "DATNAISS": "1926-11-22"
            }]
        }]
    }
}

Spark 代码是：

val j = sqlContext.read.json("/user/arthur/test.json")
j.printSchema

结果是：

root
 |-- FILE: struct (nullable = true)
 |    |-- TUPLE_CLI: array (nullable = true)
 |    |    |-- element: struct (containsNull = true)
 |    |    |    |-- ID_CLI: string (nullable = true)
 |    |    |    |-- TUPLE_ABO: array (nullable = true)
 |    |    |    |    |-- element: struct (containsNull = true)
 |    |    |    |    |    |-- DATNAISS: string (nullable = true)
 |    |    |    |    |    |-- ID_ABO: string (nullable = true)
 |    |    |    |    |    |-- TITRE_ABO: array (nullable = true)
 |    |    |    |    |    |    |-- element: string (containsNull = true)
 |    |    |    |    |    |-- TUPLE_CRA: string (nullable = true)

很明显 TUPLE_CRA 是一个数组。我不明白为什么没有猜到。在我看来，推断模式应该是：

root
 |-- FILE: struct (nullable = true)
 |    |-- TUPLE_CLI: array (nullable = true)
 |    |    |-- element: struct (containsNull = true)
 |    |    |    |-- ID_CLI: string (nullable = true)
 |    |    |    |-- TUPLE_ABO: array (nullable = true)
 |    |    |    |    |-- element: struct (containsNull = true)
 |    |    |    |    |    |-- DATNAISS: string (nullable = true)
 |    |    |    |    |    |-- ID_ABO: string (nullable = true)
 |    |    |    |    |    |-- TITRE_ABO: array (nullable = true)
 |    |    |    |    |    |    |-- element: string (containsNull = true)
 |    |    |    |    |    |-- TUPLE_CRA: array (nullable = true)
 |    |    |    |    |    |    |-- element: struct (containsNull = true)
 |    |    |    |    |    |    |    |-- CRA: string (nullable = true)
 |    |    |    |    |    |    |    |-- EFF: string (nullable = true)

有人有解释吗？如果 JSON 模式更复杂，有没有办法轻松告诉 Spark 实际模式是什么？

Answer 1

嗯，终于明白 JSON 不是预期的了。您会注意到第一个 TUPLE_CRA 是一个没有方括号 [] 的元素。其他 TUPLE_CRA 是带括号的数组，里面有几个元素。这就是为什么 Spark 无法准确猜测结构的原因。所以问题就出在这个JSON的生成上。我需要修改它，使每个 TUPLE_CRA 成为一个数组，即使里面只有一个元素。

与 Spark 数据帧的模式猜测不一致 JSON

Inconsistent JSON schema guess with Spark dataframes

schema

json

scala

spark-dataframe

apache-spark-1.4