Slow query execution in Bigquery

[kabilanravi]

Hi Team, We are using Bigquery with BI engine enabled. There are multiple occurrence of a simple select query taking more than 5 min to execute. When we run it 2nd time, it runs faster (with in a sec). Some queries even takes more than 30 min to execute. When checked in job explorer, that specific query seems stuck and bytes processed are 0 bytes. 

Any possible reason for this issue? Does anyone has similar issue before?

[ms4446]

There are several potential reasons why a simple select query in Google Cloud BigQuery with BI Engine enabled might take more than 5 minutes to execute on the first run and then execute much faster on subsequent runs:

1. Cold Cache: Initially, BigQuery needs to load the data from disk into the cache, which can be time-consuming, especially for large datasets. Once the data is cached, subsequent query executions are significantly faster.

2. Query Optimization: BigQuery optimizes the query execution plan during the first run. This optimization process can initially take extra time but helps speed up future executions of the same query.

3. Complex Queries and Data Issues: If a query takes an exceptionally long time (e.g., over 30 minutes), it might be due to the complexity of the query or issues with the underlying data. However, other factors such as network latency, server load, and specific BigQuery configurations could also play a role.

To troubleshoot and potentially improve query performance, consider the following steps:

• Examine the Query Plan: The query execution plan can provide insights into why the query is taking a long time. You can view this in the BigQuery web UI or using the bq command-line tool.

• Break Down the Query: Simplify the query by breaking it down into smaller components. This can help identify which part of the query is causing the slowdown.

• Optimize Data Partitioning: Ensure that your query efficiently utilizes partitioned tables, focusing on appropriate columns for partitioning. This can help BigQuery quickly filter out irrelevant data.

Additional Considerations:

• Resource Constraints: Check for any resource limitations or quotas in your BigQuery environment that might be impacting performance.

• Data Skew: Be aware of data skew issues, where operations on unevenly distributed data can affect query performance.

• Maintenance and Updates: Check Google Cloud's status page for any ongoing maintenance or updates that might temporarily affect BigQuery's performance.

• Contact Google Cloud Support: If the performance issues persist and are not explained by common factors, reaching out to Google Cloud Support can be beneficial.

• Understand BigQuery's Data Processing: While BigQuery does not use traditional indexing, understanding how it processes data (such as through the use of partitioned and clustered tables) can be crucial for optimizing query performance.