Merge 对于databricks delta lake,pyspark的合并等效于什么?
DataRicks描述了如何对增量表进行合并 在SQL语法中Merge 对于databricks delta lake,pyspark的合并等效于什么?,merge,databricks,delta,delta-lake,Merge,Databricks,Delta,Delta Lake,DataRicks描述了如何对增量表进行合并 在SQL语法中 MERGE INTO [db_name.]target_table [AS target_alias] USING [db_name.]source_table [<time_travel_version>] [AS source_alias] ON <merge_condition> [ WHEN MATCHED [ AND <condition> ] THEN <matched_actio
MERGE INTO [db_name.]target_table [AS target_alias]
USING [db_name.]source_table [<time_travel_version>] [AS source_alias]
ON <merge_condition>
[ WHEN MATCHED [ AND <condition> ] THEN <matched_action> ]
[ WHEN MATCHED [ AND <condition> ] THEN <matched_action> ]
[ WHEN NOT MATCHED [ AND <condition> ] THEN <not_matched_action> ]
可以使用。是否有类似python的版本?我在Alexandros Biratsis的帮助下找到了文档。可以找到文档。下面给出了这种合并的一个示例:
deltaTable.alias("events").merge(
source = updatesDF.alias("updates"),
condition = "events.eventId = updates.eventId"
).whenMatchedUpdate(set =
{
"data": "updates.data",
"count": "events.count + 1"
}
).whenNotMatchedInsert(values =
{
"date": "updates.date",
"eventId": "updates.eventId",
"data": "updates.data",
"count": "1"
}
).execute()
我在Alexandros Biratsis的帮助下找到了文档。可以找到文档。下面给出了这种合并的一个示例:
deltaTable.alias("events").merge(
source = updatesDF.alias("updates"),
condition = "events.eventId = updates.eventId"
).whenMatchedUpdate(set =
{
"data": "updates.data",
"count": "events.count + 1"
}
).whenNotMatchedInsert(values =
{
"date": "updates.date",
"eventId": "updates.eventId",
"data": "updates.data",
"count": "1"
}
).execute()
Delta-lake是用脚本编写的,API本身只支持Scalamoment@AlexandrosBiratsis:谢谢你的链接。事实证明有一个pythonapi-available.Delta-lake是用它编写的,并且api本身只支持Scalamoment@AlexandrosBiratsis:谢谢你的链接。事实证明有一个pythonapi可用。