[英]Convert spark dataframe to nested JSON using pyspark
我正在嘗試將火花 dataframe 轉換為 JSON。 這個 dataframe 大約有 100 萬行,示例代碼如下,但性能真的很差。 所需的 output 將是一個member_id
在 JSON 文件中顯示一次,與一個member_id
下的tag_name
相同。 如果有任何可能的方法可以更快地做到這一點,請告訴我。
示例代碼:
iresult = sdf.groupBy('member_id','tag_name').agg(ch.collect_list(ch.struct('detail_name','detail_value')).alias('detail')).\
groupBy('member_id').agg(ch.collect_list(ch.struct('tag_name','detail')).alias('tag'))\
.agg(ch.to_json(ch.collect_list(ch.struct('member_id','tag'))).alias('result'))
result.show()
詳細信息。csv:
member_id, tag_name, detail_name, detail_value
-------------------------------------------------------
abc123, m1, Service_A, 20
abc123, m1, Service_B, 20
abc123, m2, Service_C, 10
xyz456, m3, Service A, 5
xyz456, m3, Service A, 10
所需的 Output JSON:
{ "member_id": "abc123",
"tag":[ {"tag_name": "m1",
"detail":[{ "detail_name": "Service_A",
"detail_value": "20"},
{ "detail_name": "Service_B",
"detail_value": "20"}]},
{"tag_name": "m2",
"detail":[{ "detail_name": "Service_C",
"detail_value": "10"}]}]},
{ "member_id": "xyz456",
"tag":[{"tag_name": "m3",
"detail":[{ "detail_name": "Service_A",
"detail_value": "5"},
{ "detail_name": "Service_A",
"detail_value": "10"}]}]}
你介意通過 sql 語句來實現它嗎?
逐層構造struct
,最后使用to_json
function生成json字符串。
df.createOrReplaceTempView('tmp')
sql = """
select to_json(collect_list(struct(member_id,tag))) as member
from
(select member_id,collect_list(struct(tag_name,detail)) as tag
from
(select member_id,tag_name,collect_list(struct(detail_name,detail_value)) as detail
from tmp
group by member_id,tag_name)
group by member_id)
"""
df = spark.sql(sql)
df.show(truncate=False)
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