Question

我有如下数据

+----------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
|asset_id  |chg_log                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
+----------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
|4455628986|[{'oldValues': [], 'newValues': ['COMPO_MAIL'], 'fieldName': 'Communication Type', 'fieldType': 'TEXT', 'lookupInfo': {'fieldType': 'TEXT'}, 'additional': {'GROUP_QUALIFIER': [{'qualifiers': [{'lookupKey': 'Communication_Type', 'value': 'COMPO_MAIL'}]}]}}, {'oldValues': [], 'lookupInfo': {'isClientLevel': False, 'fieldType': 'DATE'}, 'fieldName': 'Delivery Due Date', 'fieldType': 'DATE', 'newValues': ['1601771520000']}, {'oldValues': [], 'lookupInfo': {'lookupType': 'CUST_ID', 'fieldType': 'CUST_ID'}, 'fieldName': 'Customer Id', 'fieldType': 'CUST_ID', 'newValues': ['10486']}, {'oldValues': [], 'lookupInfo': {'isClientLevel': False, 'fieldType': 'DROPDOWN'}, 'fieldName': 'Process_Status', 'fieldType': 'PICKLIST', 'newValues': ['Request Review']}]  |
+----------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

从 chg_log 列的 Json 字符串中，我想提取 fieldName - Process_Status 的值，并将它的 newValues 作为请求审查。预期结果如下。

+----------+---------------+
|asset_id  |Process_Status |
+----------+---------------+
|4455628986|Request Review |
+----------+---------------+

json 每次的顺序都不一样。有时 Process_Status 首先出现在 json 字符串中，然后是 Communication Type 等等...... 我尝试使用函数 json_extract 但无法获得它。
如何在 spark Sql 或 Pyspark 或 Hive 中实现这一点。有人可以帮我吗？？

提前致谢

Answer 1

在 Hive 中，对 JSON 处理的支持非常有限：get_json_object 返回字符串，即使它是 JSON 数组或映射，也是 JSONPath filtering does not work。这就是为什么您需要提取、拆分、分解和过滤查询中的所有内容。

例如这个 get_json_object(chg_log,"$.[].fieldName") 返回：

["Communication Type","Delivery Due Date","Customer Id","Process_Status"]

看起来像数组，但它是一个字符串，需要拆分才能得到数组。

此外，您的 JSON 也无效。而不是单引号，它应该是双引号，False 应该小写："isClientLevel": false，而不是 'isClientLevel': False

使用您的示例进行演示（请参阅代码中的注释）：

with mytable as(
 select 4455628986 asset_id , "[{'oldValues': [], 'newValues': ['COMPO_MAIL'], 'fieldName': 'Communication Type', 'fieldType': 'TEXT', 'lookupInfo': {'fieldType': 'TEXT'}, 'additional': {'GROUP_QUALIFIER': [{'qualifiers': [{'lookupKey': 'Communication_Type', 'value': 'COMPO_MAIL'}]}]}}, {'oldValues': [], 'lookupInfo': {'isClientLevel': False, 'fieldType': 'DATE'}, 'fieldName': 'Delivery Due Date', 'fieldType': 'DATE', 'newValues': ['1601771520000']}, {'oldValues': [], 'lookupInfo': {'lookupType': 'CUST_ID', 'fieldType': 'CUST_ID'}, 'fieldName': 'Customer Id', 'fieldType': 'CUST_ID', 'newValues': ['10486']}, {'oldValues': [], 'lookupInfo': {'isClientLevel': False, 'fieldType': 'DROPDOWN'}, 'fieldName': 'Process_Status', 'fieldType': 'PICKLIST', 'newValues': ['Request Review']}]" chg_log 
)

select s.asset_id, split(s.newValues,'","')[f.pos] as Process_Status
from
(
select asset_id, 
--extract array of fieldName and newValues 
--returned as string, not array
--this is why we need to split and explode it later
--remove [" and "]
regexp_replace(get_json_object(chg_log,"$.[].fieldName"),'^\\["|"\\]$','') fieldName,
regexp_replace(get_json_object(chg_log,"$.[].newValues"),'^\\["|"\\]$','') newValues
from
(
--Fix invalid JSON
--replace single-quotes with double-quotes, convert False to false, etc, add more fixes if necessary here
select asset_id, regexp_replace(regexp_replace(regexp_replace(chg_log, "'",'"'),'False','false'),'True','true') chg_log from mytable
)s 
)s lateral view outer posexplode(split(fieldName,'","'))f as pos, field_name
where f.field_name='Process_Status' --filter

结果：

asset_id    process_status
4455628986  Request Review

Answer 2

您的列 chg_log 似乎是一个字符串化 Python 字典，而不是一个有效的 JSON 字符串。

在 Pyspark 中，您可以使用 UDF 将 dict 转换为 json，然后使用 from_json 将其转换为结构数组，最后过滤该数组以找到字段 Process_Status：

import ast
from pyspark.sql import functions as F

dict_to_json = F.udf(lambda x: json.dumps(ast.literal_eval(x)))

df = df.withColumn("chg_log", dict_to_json(F.col("chg_log")))

df1 = df.withColumn(
    "chg_log",
    F.from_json("chg_log", F.schema_of_json(df.select("chg_log").head()[0]))
).withColumn(
    "chg_log",
    F.expr("filter(chg_log, x -> x.fieldName = 'Process_Status')")[0]
).select(
    F.col("asset_id"), F.col("chg_log.newValues").alias("Process_Status")
)

df1.show()
# +----------+----------------+
# |  asset_id|  Process_Status|
# +----------+----------------+
# |4455628986|[Request Review]|
# +----------+----------------+

直接在 UDF 中进行查找的另一种方法：

parse_status = F.udf(
    lambda x: next(i["newValues"] for i in ast.literal_eval(x) if i["fieldName"] == "Process_Status"),
    ArrayType(StringType())
)

df1 = df.select(F.col("asset_id"), parse_status(F.col("chg_log")).alias("Process_Status"))

从配置单元表中的 json 字符串中提取值

2 个答案: