You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Scott Black (Jira)" <ji...@apache.org> on 2019/10/15 18:55:00 UTC
[jira] [Created] (SPARK-29484) Very Poor Performance When Reading
SQL Server Tables Using Active Directory Authentication
Scott Black created SPARK-29484:
-----------------------------------
Summary: Very Poor Performance When Reading SQL Server Tables Using Active Directory Authentication
Key: SPARK-29484
URL: https://issues.apache.org/jira/browse/SPARK-29484
Project: Spark
Issue Type: Bug
Components: Spark Core
Affects Versions: 2.4.3
Environment: Test Case
jars for ms sql client
adal4j 1.6.4
oauth2-oidc-sdk 6.16.2
json-smart 2.3
nimbus-jose-jwt 7.9
mssql-jdbc 7.4.0.jre8
Slow JDBC URL using AD
"jdbc:sqlserver://<SERVER NAME>:1433;database=<DB NAME>;user=<AD USERNAME>;password=<PASSWORD>;encrypt=true;ServerCertificate=false;trustServerCertificate=true;hostNameInCertificate=*.database.windows.net;loginTimeout=30;authentication=ActiveDirectoryPassword"
URL For Expect Performance Using SQL Server Account
"jdbc:sqlserver://<SERVER NAME>:1433;database=<DB NAME>;user=<SS USERNAME>;password=<PASSWORD>;encrypt=true;ServerCertificate=false;trustServerCertificate=true;hostNameInCertificate=*.database.windows.net;loginTimeout=30;authentication=sqlPassword"
Reporter: Scott Black
When creating a dataframe via JDBC from MS SQL Server performance is so bad to be unusable when authentication was performed with Active Directory. When authentication is using SQL Server account performance is as expected. Created a java that that connected to the same Azure SQL database via Active Directory account and performance was the as Sql Server account. When connecting via Active Directory it could 30 minutes to 1 hour to read a 250 row table compared to 5 seconds using SQL Server account or using a console Java app connecting via AD.
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org