How to export Azure machine learning service results into Azure SQL DW? -


i have 3 problems relating azure machine learning service. appreciate if can give me directions or related reference.

(1) regarding result of computation of machine learning, can export sql data warehouse in azure ? format ? can join result existed table in sql db ? exact process ?

i have searched related information [deploy web-service], , found similar issue. however, little confused relationship between web-service , azure sql data warehouse.

[deploy web-service] https://azure.microsoft.com/en-us/documentation/articles/machine-learning-walkthrough-5-publish-web-service/

(2) if need result in machine learning outer sources (ex: outer lpo service), how connect outer source ?

(3) if need connect azure sql data warehouse outer sources, correct need set firewall , offer server address, id , pd , , can connect outer source ?

anticipating response , feedback.

let me try , answer questions.

(1) in order write machine learning output azure sql data warehouse, use 'export data' module (previously known 'writer' module). choose azure sql database option , enter connection string , credentials connect data warehouse. since sql data warehouse sql db underneath covers, both have same format connection string. caution write data data warehouse if you're performing batch execution. recommended approach not stream data azure sql data warehouse, since not transactional store, but, rather analytical store. so, write data data warehouse azureml if use batch execution scoring data. if you're using request/response method, encourage write data sql db , use azure data factory write data sql data warehouse (this lets pause warehouse when it's not in use, saving money).

(2) can please elaborate on this? trying here? if you're trying bring external data azure ml, there multiple ways of doing so.
       (a) azureml natively supports rss data feed , web url via http loads.
       (b) alternatively, use azure data factory or azure functions load data azure blob storage , import data azureml there (azureml natively supports connection blob storage)

(3) yes, if service isn't first-class support paas service in azure, need whitelist ip address of service before can communicate data warehouse (this done security reasons). in order programmatically this, first create service principle in azure active directory , use service principle credentials authenticate azure. here's link create service principle external application: https://azure.microsoft.com/en-us/documentation/articles/resource-group-create-service-principal-portal/.

once authenticated, can use link programmatically add ip address: https://azure.microsoft.com/en-us/documentation/articles/sql-database-firewall-configure/#programmatically-managing-firewall-rules there rest api documentation might started. in order keep database secure, give application static ip address , manually whitelist ip address, ensuring there isn't unauthorized access.

i hope helps! please let me know if have questions!


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