在 Amazon Redshift 中使用半結構化資料的範例 - Amazon Redshift
載入半結構化資料查詢巢狀半結構化資料使用 enable_case_sensitive_identifier和 enable_case_sensitive_super_attribute搭配半結構化資料篩選半結構化資料解除半結構化資料的巢狀化解除巢狀陣列巢狀在子查詢中使用半結構化資料使用半結構化資料彙總查詢在具體化視觀表中使用半結構化資料 搭配半結構化資料使用 PIVOT 和 UNPIVOT

從 2025 年 11 月 1 日起，Amazon Redshift 將不再支援建立新的 Python UDFs。如果您想要使用 Python UDFs，請在該日期之前建立 UDFs。現有的 Python UDFs將繼續如常運作。如需詳細資訊，請參閱部落格文章 。

本文為英文版的機器翻譯版本，如內容有任何歧義或不一致之處，概以英文版為準。

在 Amazon Redshift 中使用半結構化資料的範例

下列範例示範如何使用 PartiQL 語法在 Amazon Redshift 中使用半結構化資料。您將建立範例資料表以載入一組半結構化資料，然後在各種使用案例中查詢半結構化資料物件。

注意

建議您先設定 enable_case_sensitive_identifier和 enable_case_sensitive_super_attribute組態選項，再使用 SUPER 資料類型。如需詳細資訊，請參閱enable_case_sensitive_identifier及enable_case_sensitive_super_attribute。

載入半結構化資料

下列陳述式會建立範例資料表，並將範例 JSON 物件載入 SUPER all_data 資料欄。

DROP TABLE IF EXISTS test_json;

SET enable_case_sensitive_super_attribute TO true;
SET enable_case_sensitive_identifier TO true;

CREATE TABLE test_json (all_data SUPER);

INSERT INTO test_json VALUES (JSON_PARSE('
{
   "data":{
      "pnr":{
         "type":"pnr",
         "pnrid":"123PQRS-2024-09-20",
         "bookingIdentifier":"123PQRS",
         "version":"5",
         "triggerType":"",
         "events":[
            {
               "eventType":"UPDATED",
               "type":"PART",
               "id":"123PQRS-2024-09-20-HO-1"
            },
            {
               "eventType":"CREATED",
               "type":"ABC",
               "id":"123PQRS-2024-09-20-OT-38"
            }
         ],
         "create":{
            "pnrCreateDate":"2024-09-20T16:56:00Z",
            "officeID":"OFFCID1234",
            "officeIDCategory":"Email"
         },
         "lastModification":{
            "dateTime":"2024-09-20T17:09:00Z"
         },
         "PARTDetails":[
            {
               "path":"1",
               "TrainPARTs":[
                  {
                     "PARTID":"123PQRS-2024-09-20-HO-1",
                     "departure":{
                        "departureStation":"XYZ",
                        "departureTimeLocal":"2024-10-03T06:30:00",
                        "departureTimeGMT":"2024-10-03T10:30:00Z"
                     },
                     "arrival":{
                        "arrivalStation":"ABC",
                        "arrivalTimeLocal":"2024-10-03T08:20:00",
                        "arrivalTimeGMT":"2024-10-03T15:20:00Z"
                     },
                     "marketing":{
                        "carrierCode":"XX",
                        "TrainNumber":"100"
                     },
                     "operating":{
                        "carrierCode":"YY",
                        "TrainNumber":"100-A"
                     },
                     "status":"ON",
                     "aircraft":{
                        "code":"222"
                     },
                     "class":"WC",
                     "first":"Y",
                     "seating":[
                        
                     ]
                  }
               ]
            }
         ],
         "commuterInformation":[
            {
               "commuterID":"2",
               "commuterPNR":"123PQRS-2024-09-20-RO-2",
               "commuterTypeCode":"DOM",
               "firstName":"JOHN",
               "lastName":"MILLER"
            }
         ],
         "contactDetail":[
            {
               "emailContacts":[
                  {
                     "id":"123PQRS-2024-09-20-OT-4",
                     "contact":"JOHNMILLER@EXAMPLE.COM",
                     "purpose":[
                        "BUSINESS"
                     ],
                     "commuter":[
                        "123PQRS-2024-09-20-RO-2"
                     ],
                     "language":"EN"
                  },
                  {
                     "id":"123PQRS-2024-09-20-OT-5",
                     "contact":"HARVEYCORMIER@EXAMPLE.COM",
                     "purpose":[
                        "NOTIFICATION"
                     ],
                     "commuter":[
                        "123PQRS-2024-09-20-RO-2"
                     ],
                     "language":"EN"
                  }
               ]
            },
            {
               "phoneContacts":[
                  {
                     "id":"123PQRS-2024-09-20-OT-3",
                     "contact":"1234567890",
                     "purpose":[
                        "NOTIFICATION"
                     ],
                     "commuter":[
                        "123PQRS-2024-09-20-RO-2"
                     ],
                     "language":""
                  }
               ]
            },
            {
               "addressInfo":[
                  {
                     "id":"123PQRS-2024-09-20-OT-6",
                     "addressline":[
                        "112 PORT STREET"
                     ],
                     "provinceState":"CA",
                     "cityName":"SAN JOSE",
                     "postalCode":"12345",
                     "countryCode":"USA",
                     "purpose":[
                        "MAILING"
                     ],
                     "commuter":[
                        "123PQRS-2024-09-20-RO-2"
                     ]
                  }
               ]
            }
         ],
         "PendingService":[
            {
               "id":"123PQRS-2024-09-20-OT-26",
               "code":"MONO",
               "status":"",
               "text":"Broken Seat at Coach-No XYZ123 Seat-No 567",
               "trainCode":"WC-1",
               "TrainsArray":[
                  "123PQRS-2024-09-20-HO-1"
               ],
               "commuter":[
                  "123PQRS-2024-09-20-RO-2"
               ]
            },
            {
               "id":"123PQRS-2024-09-20-OT-27",
               "code":"OTHS",
               "status":"",
               "text":"Broken Seat at Coach-No XYZ567 Seat-No 111",
               "trainCode":"WC-1",
               "TrainsArray":[
                  "123PQRS-2024-09-20-HO-1"
               ],
               "commuter":[
                  "123PQRS-2024-09-20-RO-2"
               ]
            },
            {
               "id":"123PQRS-2024-09-20-OT-28",
               "code":"OTHS",
               "status":"",
               "text":"Broken Seat at Coach-No XYZ890 Seat-No 123",
               "trainCode":"WC-1",
               "TrainsArray":[
                  "123PQRS-2024-09-20-HO-1"
               ],
               "commuter":[
                  "123PQRS-2024-09-20-RO-2"
               ]
            },
            {
               "id":"123PQRS-2024-09-20-OT-29",
               "code":"OTHS",
               "status":"",
               "text":"Broken Seat at Coach-No XYZ111 Seat-No 333",
               "trainCode":"WC-1",
               "TrainsArray":[
                  "123PQRS-2024-09-20-HO-1"
               ],
               "commuter":[
                  "123PQRS-2024-09-20-RO-2"
               ]
            }            
         ],
         "parts": [
            {
               "partname": "prop",
               "manufacturer": "local parts co",
               "quality": 2,
               "price": 10.00
            },
            {
               "partname": "prop",
               "manufacturer": "big parts co",
               "quality": null,
               "price": 9.00
            },
            {
               "partname": "prop",
               "manufacturer": "small parts co",
               "quality": 1,
               "price": 12.00
            },
            {
               "partname": "rudder",
               "manufacturer": "local parts co",
               "quality": 1,
               "price": 2.50
            },
            {
               "partname": "rudder",
               "manufacturer": "big parts co",
               "quality": 2,
               "price": 3.75
            },
            {
               "partname": "rudder",
               "manufacturer": "small parts co",
               "quality": null,
               "price": 1.90
            },
            {
               "partname": "wing",
               "manufacturer": "local parts co",
               "quality": null,
               "price": 7.50
            },
            {
               "partname": "wing",
               "manufacturer": "big parts co",
               "quality": 1,
               "price": 15.20
            },
            {
               "partname": "wing",
               "manufacturer": "small parts co",
               "quality": null,
               "price": 11.80
            }
         ],
         "count_by_color": [
            {
               "quality": "high",
               "red": 15,
               "green": 20,
               "blue": 7
            },
            {
               "quality": "normal",
               "red": 35,
               "green": null,
               "blue": 40
            },
            {
               "quality": "low",
               "red": 10,
               "green": 23,
               "blue": null
            }
         ]
       }
   },
   "id":"abcdefgh-ijklmnop-qrstuvwxyz123",
   "mainIds":[
      {
         "ID":"pqrstuvwxyz-aabbcc123",
         "Source":"NYC"
      }
   ]
}
'));

查詢巢狀半結構化資料

下列陳述式使用 PartiQL 的點表示法來擷取 欄位，該pnrid欄位在最上層all_data物件深處巢狀三層。

select all_data.data.pnr.pnrid::varchar from test_json;

 pnrid
--------------------
 123PQRS-2024-09-20

下列陳述式使用 PartiQL 的括號表示法，只指定和擷取最上層物件內巢狀events陣列的第一個元素。

SELECT
    all_data.data.pnr.events[0]
FROM test_json;

 events
---------------------------------
{
   "eventType":"UPDATED",
   "type":"PART",
   "id":"123PQRS-2024-09-20-HO-1"
}

下列陳述式只會從events陣列中擷取指定元素的 eventType 屬性。

SELECT
    all_data.data.pnr.events[0].eventType
FROM test_json;

 eventtype
-----------
 "UPDATED"

下列陳述式

使用 enable_case_sensitive_identifier和 enable_case_sensitive_super_attribute搭配半結構化資料

下列範例顯示用於查詢半結構化資料時，組態選項 enable_case_sensitive_identifier 和 有何enable_case_sensitive_super_attribute不同。如需這些組態選項的詳細資訊，請參閱 使用大寫和混合大小寫欄位名稱或屬性存取 JSON 欄位。

在下列陳述式中，將兩個組態選項重設為預設值 false 會使查詢傳回 NULL。

RESET enable_case_sensitive_identifier;
RESET enable_case_sensitive_super_attribute;

SELECT
    all_data.data.pnr.events[0].eventType
FROM test_json;

 eventtype
-----------
NULL

在下列範例中，範例查詢會在您以雙引號包裝區分大小寫屬性並enable_case_sensitive_identifier設為 true 之後傳回所需的結果。

RESET enable_case_sensitive_identifier;
RESET enable_case_sensitive_super_attribute;

SELECT
    all_data.data.pnr.events[0]."eventType"
FROM test_json;
         
 eventtype
-----------
NULL

SET enable_case_sensitive_identifier TO true;
         
SELECT
    all_data.data.pnr.events[0]."eventType"
FROM test_json;
         
 eventtype
-----------
 "UPDATED"

在下列範例中，範例查詢會在您將 enable_case_sensitive_super_attribute 設定為 true 之後傳回所需的結果，而不以雙引號括住區分大小寫的屬性。

RESET enable_case_sensitive_identifier;
RESET enable_case_sensitive_super_attribute;

SELECT
    all_data.data.pnr.events[0].eventType
FROM test_json;
         
 eventtype
-----------
NULL
         
SET enable_case_sensitive_super_attribute TO true;
         
SELECT
    all_data.data.pnr.events[0].eventType
FROM test_json;
         
 eventtype
-----------
 "UPDATED"

篩選半結構化資料

下列陳述式使用陳述式 WHERE 子句中的 PartiQL 語法，計算 類型的事件UPDATED，以從陣列中擷取特定屬性的資料。您可以在通常參考資料欄的查詢任何部分使用此語法。

SELECT COUNT(*)
FROM test_json
WHERE all_data.data.pnr.events[0].eventType = 'UPDATED';

 count
------
 1

下列範例在 GROUP BY 和 ORDER BY 子句中使用 PartiQL 的括號和點語法。

SELECT all_data.data.pnr.events[0].eventType::varchar,
       COUNT(*)
FROM test_json
WHERE all_data.data.pnr.events[0].eventType IS NOT NULL
GROUP BY all_data.data.pnr.events[0].eventType
ORDER BY all_data.data.pnr.events[0].eventType;

 eventtype | count
-----------+-------
 "UPDATED" | 1

解除半結構化資料的巢狀化

下列陳述式使用 PartiQL 聯結來取消events陣列巢狀。請注意，即使陣列的索引數目不是靜態的，此聯結仍然有效。

如需使用 FROM 子句中的 UNNEST 將半結構化資料解除巢狀化的範例，請參閱 UNNEST 範例。

SELECT
a.all_data.data.pnr.type::varchar type_info,
a.all_data.data.pnr.pnrid::varchar pnr_id ,
a.all_data.data.pnr.bookingIdentifier::varchar booking_id,
a.all_data.data.pnr.version::varchar version_info,
b.eventType::varchar event_type,
b.id::varchar event_id
FROM test_json a, 
  a.all_data.data.pnr.events b;

 type_info | pnr_id              | booking_id | version_info | event_type | event_id
-----------+---------------------+------------+--------------+------------+-------------------------
 pnr       | 123PQRS-2024-09-20  | 123PQRS    | 5            | UPDATED    | 123PQRS-2024-09-20-HO-1
 pnr       | 123PQRS-2024-09-20  | 123PQRS    | 5            | CREATED    | 123PQRS-2024-09-20-OT-38

解除巢狀陣列巢狀

下列陳述式使用 PartiQL 聯結來取消巢狀在另一個陣列中的陣列。

如需使用 FROM 子句中的 UNNEST 將半結構化資料解除巢狀化的範例，請參閱 UNNEST 範例。

SELECT
a.all_data.data.pnr.type::varchar type_info,
a.all_data.data.pnr.pnrid::varchar pnr_id ,
a.all_data.data.pnr.bookingIdentifier::varchar booking_id,
a.all_data.data.pnr.version::varchar version_info,
d.id::varchar email_record_id,
d.contact::varchar email_contact,
e::varchar email_purpose,
f::varchar email_commuter
FROM test_json a,
  a.all_data.data.pnr.contactDetail c,
  c."emailContacts" d,
  d.purpose e,
  d.commuter f;

 type_info | pnr_id              | booking_id | version_info | email_record_id         | email_contact             | email_purpose | email_commuter
-----------+---------------------+------------+--------------+-------------------------+---------------------------+---------------+-------------------------
 pnr       | 123PQRS-2024-09-20  | 123PQRS    | 5            | 123PQRS-2024-09-20-OT-4 | JOHNMILLER@EXAMPLE.COM    | BUSINESS      | 123PQRS-2024-09-20-RO-2
 pnr       | 123PQRS-2024-09-20  | 123PQRS    | 5            | 123PQRS-2024-09-20-OT-5 | HARVEYCORMIER@EXAMPLE.COM | NOTIFICATION  | 123PQRS-2024-09-20-RO-2

在子查詢中使用半結構化資料

下列陳述式使用 WHERE 子句中的子查詢，僅傳回先前範例結果的子區段。

SELECT
a.all_data.data.pnr.type::varchar type_info,
a.all_data.data.pnr.pnrid::varchar pnr_id ,
a.all_data.data.pnr.bookingIdentifier::varchar booking_id,
a.all_data.data.pnr.version::varchar version_info,
d.id::varchar email_record_id,
d.contact::varchar email_contact
FROM test_json a,
a.all_data.data.pnr.contactDetail c,
c."emailContacts" d
WHERE (SELECT COUNT(*) FROM d.purpose e WHERE e = 'BUSINESS') > 0;

 type_info | pnr_id              | booking_id | version_info | email_record_id         | email_contact             | email_purpose | email_commuter
-----------+---------------------+------------+--------------+-------------------------+---------------------------+---------------+-------------------------
 pnr       | 123PQRS-2024-09-20  | 123PQRS    | 5            | 123PQRS-2024-09-20-OT-4 | JOHNMILLER@EXAMPLE.COM    | BUSINESS      | 123PQRS-2024-09-20-RO-2

使用半結構化資料彙總查詢

下列陳述式使用 COUNT 函數來彙總PendingService陣列中的元素數目。

SELECT
a.all_data.data.pnr.type::varchar type_info,
a.all_data.data.pnr.pnrid::varchar pnr_id ,
a.all_data.data.pnr.bookingIdentifier::varchar booking_id,
a.all_data.data.pnr.version::varchar version_info,
COUNT(*) AS total_pending_service
FROM test_json a, 
  a.all_data.data.pnr.PendingService c
GROUP BY 1,2,3,4;

 type_info | pnr_id             | booking_id | version_info | total_pending_service
-----------+--------------------+------------+--------------+-----------------------
 pnr       | 123PQRS-2024-09-20 | 123PQRS    | 5            | 4

在具體化視觀表中使用半結構化資料

下列陳述式使用上一個範例中的 陳述式來建立具體化視觀表。當基礎資料表取得新資料時，具體化檢視會自動重新整理待定服務的數量。

CREATE MATERIALIZED VIEW mv_total_pending_service
AUTO REFRESH YES
AS
SELECT
a.all_data.data.pnr.type::varchar type_info,
a.all_data.data.pnr.pnrid::varchar pnr_id ,
a.all_data.data.pnr.bookingIdentifier::varchar booking_id,
a.all_data.data.pnr.version::varchar version_info,
COUNT(*) AS total_pending_service
FROM test_json a,
  a.all_data.data.pnr.PendingService c
GROUP BY 1,2,3,4;

搭配半結構化資料使用 PIVOT 和 UNPIVOT

下列陳述式在 partname 欄上使用 PIVOT 來傳回每個部分的平均價格。

SELECT *
FROM 
(
SELECT
c.partname::varchar, c.price
FROM test_json a, 
  a.all_data.data.pnr.parts c) 
PIVOT (AVG(price) for partname IN ('prop', 'rudder', 'wing'));
            
 
 prop       | rudder             |  wing
------------+--------------------+--------
 10.33      | 2.71               |  11.50

在上一個範例中，結果會轉換為資料欄。下列範例顯示 GROUP BY 查詢，以資料列傳回平均價格，而非資料欄。

SELECT partname, avg(price)
FROM (
SELECT
c.partname::varchar, c.price
FROM test_json a, 
  a.all_data.data.pnr.parts c)
WHERE partname IN ('prop', 'rudder', 'wing')
GROUP BY partname;
            
 partname |  avg
----------+-------
 prop     | 10.33
 rudder   |  2.71
 wing     | 11.50

以下是使用 manufacturer做為隱含資料欄的 PIVOT 範例。

SELECT *
FROM (
SELECT
c.quality, c.manufacturer::varchar
FROM test_json a, 
  a.all_data.data.pnr.parts c) PIVOT (
count(*) FOR quality IN (1, 2, NULL)
);
            
 manufacturer      | 1  | 2  | null
-------------------+----+----+------
 local parts co    | 1  | 1  |  1
 big parts co      | 1  | 1  |  1
 small parts co    | 1  | 0  |  2

以下是 quality 欄上的 UNPIVOT 範例。

SELECT *
FROM 
(
SELECT
c.quality as quality
FROM test_json a, 
  a.all_data.data.pnr.parts c) 
UNPIVOT (cnt FOR column_header IN (quality));
            
 column_header   | cnt
-----------------+----
 quality         | 2    
 quality         | 1    
 quality         | 1    
 quality         | 2    
 quality         | 1