Presto is a distributed SQL query engine designed for running interactive analytic queries against data sources of all sizes. It is optimized for low-latency and high-throughput, making it ideal for big data analytics. Presto can query data where it lives, including Hive, Cassandra, relational databases, or even proprietary data stores.
When working with Presto, you might encounter the error code INSUFFICIENT_RESOURCES. This error typically manifests when a query cannot be executed due to a lack of available resources. Users may notice that queries are not completing or are failing with this specific error message.
The INSUFFICIENT_RESOURCES error indicates that the Presto cluster does not have enough resources, such as CPU, memory, or disk space, to execute the query. This can happen if the query is too large or complex for the current cluster configuration or if the cluster is under heavy load.
To resolve the INSUFFICIENT_RESOURCES error, consider the following steps:
Review the query to ensure it is optimized. Consider breaking down complex queries into smaller, more manageable parts. Use Presto's SQL documentation to understand how to optimize your queries effectively.
If the query is optimized but still fails, you may need to increase the resources available to the Presto cluster:
Refer to the Presto deployment guide for instructions on scaling your cluster.
Modify Presto's configuration settings to better handle resource allocation:
query.max-memory and query.max-memory-per-node settings in the config.properties file.query.max-concurrent-queries to limit the number of simultaneous queries.For more details, see the resource management documentation.
By following these steps, you can address the INSUFFICIENT_RESOURCES error in Presto. Ensuring that your queries are optimized and your cluster is adequately resourced will help maintain efficient query execution. For further assistance, consider reaching out to the Presto community.
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