{ { identifier | [ field ] | [ * ] | [ index ] }
  [ . identifier | [ field ] | [ * ] | [ index ] ] [...] }
field、* 和 index 周围的括号是实际括号，并不表示可选语法。
parameters
标识符：JSON 字段的不区分大小写的标识符。
[ field ]：括号中区分大小写的 STRING 文本，用于标识 JSON 字段。
[ * ]：用于标识 JSON 数组中的所有元素。
[ index ]：一个整数文本，用于标识基于 0 的 JSON 数组中的特定元素。
一个 STRING。
如果存在具有未分隔的 null 值的 JSON 字段，则会收到该列的 SQL NULL 值，而不是 null 文本值。
可以使用 :: 运算符将值转换为基本数据类型。
使用 from_json 函数将嵌套结果转换为更复杂的数据类型，例如数组或结构。
如果名称不包含空格或特殊字符，并且不存在不同大小写的同名字段，则可以使用未分隔的标识符来引用 JSON 字段。
如果不存在不同大小写的同名字段，请使用分隔标识符。
[ field ] 表示法始终可以使用，但需要与字段的大小写完全匹配。
如果 Databricks SQL 无法唯一地标识字段，则会返回错误。 如果未找到任何字段的匹配项，Databricks SQL 将返回 NULL。
下面的示例使用在示例数据中通过语句创建的数据。
本节内容：
使用标识符和分隔符进行提取
提取嵌套字段
从数组中提取值
NULL 行为
强制转换值
使用标识符和分隔符进行提取
> SELECT raw:owner, raw:OWNER, raw:['owner'], raw:['OWNER'] FROM store_data;
  amy  amy  amy  NULL
-- Use backticks to escape special characters. References are case insensitive when you use backticks.
-- Use brackets to make them case sensitive.
> SELECT raw:`zip code`, raw:`Zip Code`, raw:['fb:testid'] FROM store_data;
  94025      94025      1234
提取嵌套字段
-- Use dot notation
> SELECT raw:store.bicycle FROM store_data;
  '{ "price":19.95, "color":"red" }'
-- Use brackets
> SELECT raw:['store']['bicycle'] FROM store_data;
  '{ "price":19.95, "color":"red" }'
从数组中提取值
-- Index elements
> SELECT raw:store.fruit[0], raw:store.fruit[1] FROM store_data;
  '{ "weight":8, "type":"apple" }'  '{ "weight":9, "type":"pear" }'
-- Extract subfields from arrays
> SELECT raw:store.book[*].isbn FROM store_data;
  '[ null, "0-553-21311-3", "0-395-19395-8" ]'
-- Access arrays within arrays or structs within arrays
> SELECT raw:store.basket[*],
         raw:store.basket[*][0] first_of_baskets,
         raw:store.basket[0][*] first_basket,
         raw:store.basket[*][*] all_elements_flattened,
         raw:store.basket[0][2].b subfield
  FROM store_data;
  basket                       first_of_baskets   first_basket          all_elements_flattened            subfield
 ---------------------------- ------------------ --------------------- --------------------------------- ----------
  [                            [                  [                     [1,2,{"b":"y","a":"x"},3,4,5,6]   y
    [1,2,{"b":"y","a":"x"}],     1,                 1,
    [3,4],                       3,                 2,
    [5,6]                        5                  {"b":"y","a":"x"}
  ]                            ]                  ]
NULL 行为
> SELECT '{"key":null}':key IS NULL sql_null, '{"key":"null"}':key IS NULL;
  true          false
强制转换值
-- price is returned as a double, not a string
> SELECT raw:store.bicycle.price::double FROM store_data
  19.95
-- use from_json to cast into more complex types
> SELECT from_json(raw:store.bicycle, 'price double, color string') bicycle FROM store_data
  '{ "price":19.95, "color":"red" }'
-- the column returned is an array of string arrays
> SELECT from_json(raw:store.basket[*], 'array<array<string>>') baskets FROM store_data
    ["1","2","{\"b\":\"y\",\"a\":\"x\"}]",
    ["3","4"],
    ["5","6"]
CREATE TABLE store_data AS SELECT
   "store":{
      "fruit": [
        {"weight":8,"type":"apple"},
        {"weight":9,"type":"pear"}
      "basket":[
        [1,2,{"b":"y","a":"x"}],
        [3,4],
        [5,6]
      "book":[
          "author":"Nigel Rees",
          "title":"Sayings of the Century",
          "category":"reference",
          "price":8.95
          "author":"Herman Melville",
          "title":"Moby Dick",
          "category":"fiction",
          "price":8.99,
          "isbn":"0-553-21311-3"
          "author":"J. R. R. Tolkien",
          "title":"The Lord of the Rings",
          "category":"fiction",
          "reader":[
            {"age":25,"name":"bob"},
            {"age":26,"name":"jack"}
          "price":22.99,
          "isbn":"0-395-19395-8"
      "bicycle":{
        "price":19.95,
        "color":"red"
    "owner":"amy",
    "zip code":"94025",
    "fb:testid":"1234"
 }' as raw
: 运算符