Redshift Running Slow? Sharpen Your Troubleshooting Skills with This Quiz

Quiz #25 is in our series of quiz questions where we are investigating how to troubleshoot AWS CloudWatch alarms. If this is of interest, also look at our recent quiz on AWS ELB Performance, Debugging Message Queue alert, and Neptune Write IOPS Spiking.

Quiz #25 is:

You’re alerted by a CloudWatch alarm indicating your Redshift cluster’s query execution time has significantly increased in the last hour. What’s the BEST initial troubleshooting step to identify the root cause?

1. Immediately scale the cluster horizontally by adding more nodes.
2. Restart all the Redshift nodes in the cluster.
3. Analyze the slow query logs in Amazon S3 to pinpoint inefficient queries.
4. Disable unused user accounts to potentially reduce overall workload.
5. Terminate any currently running queries to prevent further slowdowns.

Correct Answer: #3, “Analyze the slow query logs in Amazon S3 to pinpoint inefficient queries”

128 people answered this question and 19% got it right.

(1) Horizontal Scaling (Not Ideal Yet):

Adding nodes (horizontal scaling) might seem tempting, but it’s a reactive approach. Scaling up without identifying the cause could be overkill and incur unnecessary costs. Analyze the issue first!

(2) Node Restart (Disruptive and Unnecessary):

Restarting Redshift nodes disrupts ongoing queries and introduces downtime. It’s a heavy-handed tactic unless a node malfunction is suspected.

(3) Analyze Slow Query Logs (The Winner!):

Bingo! Analyzing slow query logs stored in Amazon S3 is the GOLDEN first step. These logs provide invaluable insights:

• Query Details: Identify specific queries taking an unusually long time to execute.
• Execution Plans: Analyze the query plans to pinpoint potential inefficiencies like complex joins or missing indexes.
• Query Times: Compare execution times across different queries to isolate the problematic ones.

Here’s a sample AWS CLI command to access slow query logs for your Redshift cluster named “my-cluster”:

aws redshift get-cluster-diagnostic-information --cluster-identifier my-cluster | jq -r '.ClusterDiagnostics.SlowQueryRecords[].Query'

This retrieves the actual queries flagged as slow. You can then use a tool like Amazon Athena to analyze the query details and execution plans for further investigation.

(4) Disabling Unused Accounts (Not the Root Cause):

Disabling unused accounts might free up some resources, but it’s unlikely to address a sudden surge in slow queries. It’s more suited for long-term workload management.

(5) Terminating Running Queries (Risky Business):

Terminating running queries can be risky. Critical data updates might be interrupted, leading to data inconsistencies. This should only be considered as a last resort after identifying the culprit.

By analyzing slow query logs, you can identify inefficient queries and optimize them for faster execution. This targeted approach minimizes downtime and ensures your Redshift cluster performs optimally.

Bonus Tip: Leverage AWS Redshift Spectrum to offload complex queries to your data lake in Amazon S3, potentially improving query performance for certain workloads.

Stay tuned for future blogs where we’ll delve deeper into advanced Redshift troubleshooting techniques and best practices!

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