Common scenarios for debugging queries using query profiles The following topics describe common problems that impact Impala query performance and how to resolve them. By: Manish Maheshwari, Data Architect and Data Scientist at Cloudera, Inc. Memory limit exceededThe memory limit exceeded error typically occurs when no memory limit has been set.Query runs slowlyImpala queries can run slowly for a number of reasons, which are explained in this topic.Admission controlIncreasing memory for resource pools can increase query concurrency that is under admission control.Client fetch wait timerThe client fetch wait timer determines how long a query is kept open waiting for a client action. Tuning the timer settings as described here can improve Impala performance.Wrong join orderAdjusting query join order or join type can improve Impala performance.Time and data skewsSkews in Avg Time and Max Time, which are listed in the Exec Summary section of the query profile, are possible due to either data skews or workload skews:
