如何将从json字符串字段提取的数组转换为bigquery重复字段?

FZF*_*FZF 7 google-bigquery

我们在Bigquery表的String字段中加载了json blob.我需要在表上创建一个视图(使用标准的sql),它将数组字段提取为一个bigquery数组/重复字段"RECORD"类型(它本身包含一个重复的字段).

这是一个示例记录(json_blob):

{"order_id":"123456","customer_id":"2abcd", "items":[{"line":"1","ref_ids":["66b56e60","9e7ca2b7"],"sku":"1111","amount":40 },{"line":"2","ref_ids":["7777h0","8888j0"],"sku":"2222","amount":10 }]}
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我希望最终得到一个具有以下布局的视图:

[
{
    "name": "order_id",
    "type": "STRING",
    "mode": "NULLABLE"
},
{
    "mode": "NULLABLE",
    "name": "customer_id",
    "type": "STRING"
},
{
    "mode": "REPEATED",
    "name": "items",
    "type": "RECORD",
    "fields": [
        {
            "mode": "NULLABLE",
            "name": "line",
            "type": "STRING"
        },
        {
            "mode": "REPEATED",
            "name": "ref_ids",
            "type": "STRING"
        },
        {
            "mode": "NULLABLE",
            "name": "sku",
            "type": "STRING"
        },
        {
            "mode": "NULLABLE",
            "name": "amount",
            "type": "INTEGER"
        }
    ]
}
]
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Json_extract(json_blob,'$ .items')提取项目部分,但是如何将其转换为类型为"RECORD"的bigquery数组,然后可以像普通的bigquery数组/重复STRUCT一样处理?

感谢任何帮助.

Mik*_*ant 10

更粗暴的版本 - 我认为如果需要更容易阅读和修改/调整

#standardSQL
WITH `yourTable` AS (
  SELECT '{"order_id":"123456","customer_id":"2abcd", "items":[{"line":"1","ref_ids":["66b56e60","9e7ca2b7"],"sku":"1111","amount":40 },{"line":"2","ref_ids":["7777h0","8888j0"],"sku":"2222","amount":10 }]}' AS json_blob
)
SELECT 
   JSON_EXTRACT_SCALAR(json_blob, '$.order_id') AS order_id,
   JSON_EXTRACT_SCALAR(json_blob, '$.customer_id') AS customer_id,
   ARRAY(
    SELECT STRUCT(
        JSON_EXTRACT_SCALAR(split_items, '$.line') AS line,
        SPLIT(REGEXP_REPLACE(JSON_EXTRACT (split_items, '$.ref_ids'), r'[\[\]\"]', '')) AS ref_ids,
        JSON_EXTRACT_SCALAR(split_items, '$.sku') AS sku,
        JSON_EXTRACT_SCALAR(split_items, '$.amount') AS amount
      )
    FROM (
      SELECT CONCAT('{', REGEXP_REPLACE(split_items, r'^\[{|}\]$', ''), '}') AS split_items
      FROM UNNEST(SPLIT(JSON_EXTRACT(json_blob, '$.items'), '},{')) AS split_items
    )
   ) AS items
FROM `yourTable` 
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Pen*_*m10 7

截至 2020 年 5 月 1 日,已添加JSON_EXTRACT_ARRAY函数,可用于从 json 检索数组。

#standardSQL
WITH `yourTable` AS (
  SELECT '{"order_id":"123456","customer_id":"2abcd", "items":[{"line":"1","ref_ids":["66b56e60","9e7ca2b7"],"sku":"1111","amount":40 },{"line":"2","ref_ids":["7777h0","8888j0"],"sku":"2222","amount":10 }]}' AS json_blob 
)
SELECT
  json_extract_scalar(json_blob,'$.order_id') AS order_id,
  json_extract_scalar(json_blob,'$.customer_id') AS customer_id,
  ARRAY(
  SELECT
    STRUCT(json_extract_scalar(split_items,'$.line') AS line,
          ARRAY(SELECT json_extract_scalar(ref_element,'$') FROM UNNEST(json_extract_array(split_items, '$.ref_ids')) ref_element) AS ref_ids,
          json_extract_scalar(split_items,'$.sku') AS sku,
          json_extract_scalar(split_items,'$.amount') AS amount 
      )
    FROM UNNEST(json_extract_array(json_blob,'$.items')) split_items 
  ) AS items
FROM
  `yourTable`
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返回:

在此处输入图片说明

要仅获取类型查询将是:

#standardSQL
WITH `yourTable` AS (
  SELECT '{ "firstName": "John", "lastName" : "doe", "age"      : 26, "address"  : {     "streetAddress": "naist street",     "city"         : "Nara",     "postalCode"   : "630-0192" }, "phoneNumbers": [     {       "type"  : "iPhone",       "number": "0123-4567-8888"     },     {       "type"  : "home",       "number": "0123-4567-8910"     } ]}' AS json_blob 
)
  SELECT
    json_extract_scalar(split_items,'$.type') AS type FROM `yourTable`, UNNEST(json_extract_array(json_blob,'$.phoneNumbers')) split_items
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返回:

在此处输入图片说明


Ell*_*ard 6

在撰写本文时,除非在JSON数组中强加硬性限制,否则无法在BigQuery中使用SQL函数来执行此操作。请参阅相关的问题跟踪器项。您的选择是:

  • 以不同的方式处理数据(例如,使用Cloud Dataflow或其他工具),以便您可以将以换行符分隔的JSON将其加载到BigQuery中。
  • 使用接收输入JSON并返回所需类型的JavaScript UDF;这非常简单,但是通常使用更多的CPU(因此可能需要更高的计费层)。
  • 使用SQL函数时应了解,如果元素太多,则解决方案会崩溃。

这是使用JavaScript UDF的方法:

#standardSQL
CREATE TEMP FUNCTION JsonToItems(input STRING)
RETURNS STRUCT<order_id INT64, customer_id STRING, items ARRAY<STRUCT<line STRING, ref_ids ARRAY<STRING>, sku STRING, amount INT64>>>
LANGUAGE js AS """
return JSON.parse(input);
""";

WITH Input AS (
  SELECT '{"order_id":"123456","customer_id":"2abcd", "items":[{"line":"1","ref_ids":["66b56e60","9e7ca2b7"],"sku":"1111","amount":40 },{"line":"2","ref_ids":["7777h0","8888j0"],"sku":"2222","amount":10 }]}' AS json
)
SELECT
  JsonToItems(json).*
FROM Input;
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如果您确实想尝试不带JavaScript的基于SQL的方法,那么在上述功能请求得到解决之前,这里有些骇人听闻,其中数组元素的数量不得超过10:

#standardSQL
CREATE TEMP FUNCTION JsonExtractRefIds(json STRING) AS (
  (SELECT ARRAY_AGG(v IGNORE NULLS)
   FROM UNNEST([
     JSON_EXTRACT_SCALAR(json, '$.ref_ids[0]'),
     JSON_EXTRACT_SCALAR(json, '$.ref_ids[1]'),
     JSON_EXTRACT_SCALAR(json, '$.ref_ids[2]'),
     JSON_EXTRACT_SCALAR(json, '$.ref_ids[3]'),
     JSON_EXTRACT_SCALAR(json, '$.ref_ids[4]'),
     JSON_EXTRACT_SCALAR(json, '$.ref_ids[5]'),
     JSON_EXTRACT_SCALAR(json, '$.ref_ids[6]'),
     JSON_EXTRACT_SCALAR(json, '$.ref_ids[7]'),
     JSON_EXTRACT_SCALAR(json, '$.ref_ids[8]'),
     JSON_EXTRACT_SCALAR(json, '$.ref_ids[9]')]) AS v)
);

CREATE TEMP FUNCTION JsonToItem(json STRING)
RETURNS STRUCT<line STRING, ref_ids ARRAY<STRING>, sku STRING, amount INT64>
AS (
  IF(json IS NULL, NULL,
    STRUCT(
      JSON_EXTRACT_SCALAR(json, '$.line'),
      JsonExtractRefIds(json),
      JSON_EXTRACT_SCALAR(json, '$.sku'),
      CAST(JSON_EXTRACT_SCALAR(json, '$.amount') AS INT64)
    )
  )
);

CREATE TEMP FUNCTION JsonToItems(json STRING) AS (
  (SELECT AS STRUCT
    CAST(JSON_EXTRACT_SCALAR(json, '$.order_id') AS INT64) AS order_id,
    JSON_EXTRACT_SCALAR(json, '$.customer_id') AS customer_id,
    (SELECT ARRAY_AGG(v IGNORE NULLS)
     FROM UNNEST([
       JsonToItem(JSON_EXTRACT(json, '$.items[0]')),
       JsonToItem(JSON_EXTRACT(json, '$.items[1]')),
       JsonToItem(JSON_EXTRACT(json, '$.items[2]')),
       JsonToItem(JSON_EXTRACT(json, '$.items[3]')),
       JsonToItem(JSON_EXTRACT(json, '$.items[4]')),
       JsonToItem(JSON_EXTRACT(json, '$.items[5]')),
       JsonToItem(JSON_EXTRACT(json, '$.items[6]')),
       JsonToItem(JSON_EXTRACT(json, '$.items[7]')),
       JsonToItem(JSON_EXTRACT(json, '$.items[8]')),
       JsonToItem(JSON_EXTRACT(json, '$.items[9]'))]) AS v) AS items
  )
);

WITH Input AS (
  SELECT '{"order_id":"123456","customer_id":"2abcd", "items":[{"line":"1","ref_ids":["66b56e60","9e7ca2b7"],"sku":"1111","amount":40 },{"line":"2","ref_ids":["7777h0","8888j0"],"sku":"2222","amount":10 }]}' AS json
)
SELECT
  JsonToItems(json).*
FROM Input;
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