What is Presto QUERY_CANCELED

Resolving QUERY_CANCELED in Presto

Understanding Presto

Presto is an open-source distributed SQL query engine designed for running interactive analytic queries against data sources of all sizes. Developed by Facebook, Presto is optimized for low-latency and high-throughput data processing, making it ideal for big data analytics. It allows users to query data where it lives, including Hive, Cassandra, relational databases, or even proprietary data stores.

Identifying the Symptom

When using Presto, you might encounter the QUERY_CANCELED error. This error indicates that a query was canceled before it could complete. Users typically observe this issue when a query unexpectedly stops running, and the system returns a message indicating the cancellation.

Common Observations

Queries that run for an extended period and then terminate abruptly. Error messages in the Presto UI or logs stating QUERY_CANCELED.

Exploring the Issue

The QUERY_CANCELED error in Presto can occur due to various reasons, such as manual cancellation by a user, timeout settings, or resource constraints. Understanding the root cause is crucial for resolving the issue effectively.

Potential Causes

Manual Cancellation: A user might have manually canceled the query. Timeouts: Presto has timeout settings that might automatically cancel long-running queries. Resource Constraints: Insufficient resources or competing workloads can lead to query cancellations.

Steps to Fix the Issue

To address the QUERY_CANCELED error, follow these steps:

1. Check for Manual Cancellation

Verify if the query was manually canceled by a user. This can be done by checking the query history in the Presto UI or logs. If manual cancellation is confirmed, communicate with the user to understand the reason.

2. Review Timeout Settings

Presto has several timeout configurations that might affect query execution:

query.max-run-time: The maximum time a query is allowed to run. query.max-execution-time: The maximum time a query is allowed to execute.

Adjust these settings in the config.properties file if necessary. For more details, refer to the Presto Deployment Documentation.

3. Monitor Resource Usage

Ensure that your Presto cluster has sufficient resources to handle the workload. Use monitoring tools to track CPU, memory, and network usage. Consider scaling your cluster if resource constraints are identified.

4. Retry the Query

If the issue persists after addressing the above points, attempt to rerun the query. Ensure that the query is optimized for performance to avoid unnecessary resource consumption.

Conclusion

By understanding the potential causes of the QUERY_CANCELED error and following the outlined steps, you can effectively troubleshoot and resolve this issue in Presto. For further assistance, consider visiting the Presto Community for support and resources.