Help Center> MapReduce Service> Component Operation Guide (Normal)> Using Spark2x> Common Issues About Spark2x> Spark SQL and DataFrame> How Do I Do If I Incidentally Kill the JDBCServer Process During Health Check?
Updated on 2023-08-03 GMT+08:00

How Do I Do If I Incidentally Kill the JDBCServer Process During Health Check?

Question

In the health check solution, when the number of concurrently executed statements reaches the upper limit of the thread pool, the health check command fails to run. As a result, the health check program times out and the Spark JDBCServer process is killed.

Answer

Currently, JDBCServer has two thread pools HiveServer2-Handler-Pool and HiveServer2-Background-Pool. HiveServer2-Handler-Pool is used to process session connections, and HiveServer2-Background-Pool is used to execute SQL statements.

In the current health check mechanism, a session connection is created and the health check command HEALTHCHECK is executed in the thread where the session is located to determine the health status of Spark JDBCServer HiveServer2-Handler-Pool must reserve a thread to process the health check session connection and execute the health check command, otherwise, the health check session cannot be established or the health check command cannot be executed. As a result, Spark JDBCServer is regarded as unhealthy and then killed. That is, if the number of thread pools of HiveServer2-Handler-Pool is 100, a maximum of 99 sessions can be connected.