triaging-live-sql-activity（triaging live SQL activity 搜索）

Triaging Live SQL Activity

Diagnoses live cluster performance issues by identifying currently active long-running queries, busy sessions, and active transactions. Uses SQL-only interfaces (SHOW statements and crdb_internal views) to provide immediate triage without requiring DB Console, HTTP endpoints, or Prometheus access.

When to Use This Skill

• Users report "the cluster is slow right now"
• High CPU or memory usage on cluster nodes
• Need to identify runaway queries or stuck transactions
• Want to find which applications/users are consuming resources
• Require immediate triage without DB Console access
• Need to generate SQL to cancel problematic sessions/queries

For historical performance analysis: Use profiling-statement-fingerprints to analyze query patterns over time, identify slow fingerprints, and investigate trends without needing live queries. For transaction-level analysis: Use profiling-transaction-fingerprints to analyze historical transaction retry patterns, commit latency trends, and statement composition. For background job monitoring: Use monitoring-background-jobs to monitor schema changes, backups, and automatic jobs that don't appear in SHOW CLUSTER STATEMENTS.

Prerequisites

Required SQL access:

• Connection to any CockroachDB node
• For cluster-wide visibility: VIEWACTIVITY or VIEWACTIVITYREDACTED privilege

- VIEWACTIVITYREDACTED: Redacts constants in other users' queries (recommended for privacy) - VIEWACTIVITY: Shows full query text for all users - Without these: Only see your own sessions/queries

• Basic understanding of SQL query execution
• (Optional) CANCELQUERY / CANCELSESSION privileges for cancellation operations

Check your privileges:

SHOW GRANTS ON ROLE <username>;

See permissions reference for detailed RBAC setup.

Core Diagnostic Approach

CockroachDB provides SQL-only interfaces for live activity triage:

Triage workflow:

1. Identify long-running queries (> 5-10 minutes)
2. Correlate to sessions and applications
3. Check transaction retry counts (high retries = contention)
4. Drill down by app/user/client
5. (Optional) Cancel runaway work

Safety: All diagnostic queries are read-only. Cancellation is opt-in with explicit warnings.

Core Diagnostic Queries

Long-Running Queries

Identify queries running longer than a specified threshold:

-- Queries running longer than 5 minutes
WITH q AS (SHOW CLUSTER STATEMENTS)
SELECT
  query_id,
  node_id,
  session_id,
  user_name,
  client_address,
  application_name,
  start,
  now() - start AS running_for,
  substring(query, 1, 200) AS query_preview,
  distributed,
  phase
FROM q
WHERE start < now() - INTERVAL '5 minutes'
ORDER BY start
LIMIT 50;

Key columns:

• running_for: How long the query has been executing
• query_preview: First 200 characters (protects against massive queries)
• phase: execution phase (preparing, executing, etc.)
• distributed: whether query spans multiple nodes

Customizable thresholds:

• Change INTERVAL '5 minutes' to '10 minutes', '30 seconds', etc.
• Adjust LIMIT based on cluster size and expected load

Active Sessions

Find sessions with long-running active queries:

-- Sessions with active queries running > 5 minutes
WITH s AS (SHOW CLUSTER SESSIONS)
SELECT
  node_id,
  session_id,
  user_name,
  client_address,
  application_name,
  status,
  active_query_start,
  now() - active_query_start AS active_query_for,
  substring(active_queries, 1, 200) AS active_queries_preview,
  substring(last_active_query, 1, 200) AS last_query_preview
FROM s
WHERE active_query_start IS NOT NULL
  AND active_query_start < now() - INTERVAL '5 minutes'
ORDER BY active_query_start
LIMIT 50;

Key columns:

• active_query_for: Duration of current active query
• application_name: Source application for drill-down
• client_address: Client IP/hostname for troubleshooting
• status: Session state (Idle, Active, etc.)

Active Transactions

Identify long-running transactions (potential blockers):

-- Transactions running > 5 minutes
SELECT
  id AS txn_id,
  node_id,
  session_id,
  application_name,
  start,
  now() - start AS running_for,
  num_stmts,
  num_retries,
  num_auto_retries,
  substring(txn_string, 1, 200) AS txn_string_preview
FROM crdb_internal.cluster_transactions
WHERE start < now() - INTERVAL '5 minutes'
ORDER BY start
LIMIT 50;

Key columns:

• num_retries / num_auto_retries: High retry counts indicate contention
• num_stmts: Number of statements in transaction (large = potentially problematic)
• txn_string: Transaction fingerprint

Production safety note: crdb_internal.cluster_transactions is production-approved and safe for triage.

Drill-Down by Application, User, or Client

Once you identify suspicious activity, drill down by filtering:

Filter by Application

-- All activity from specific application
WITH q AS (SHOW CLUSTER STATEMENTS)
SELECT query_id, user_name, start, now() - start AS running_for,
       substring(query, 1, 200) AS query_preview
FROM q
WHERE application_name = 'payments-api'
ORDER BY start;

Filter by User

-- All activity from specific user
WITH s AS (SHOW CLUSTER SESSIONS)
SELECT session_id, application_name, client_address,
       active_query_start, substring(active_queries, 1, 200) AS active_queries_preview
FROM s
WHERE user_name = 'app_user'
  AND active_query_start IS NOT NULL
ORDER BY active_query_start;

Filter by Client Address

-- All sessions from specific client IP
WITH s AS (SHOW CLUSTER SESSIONS)
SELECT session_id, user_name, application_name,
       status, substring(active_queries, 1, 200) AS active_queries_preview
FROM s
WHERE client_address LIKE '10.0.1.%'
ORDER BY active_query_start;

Combined Filters

-- Long queries from specific app and user
WITH q AS (SHOW CLUSTER STATEMENTS)
SELECT query_id, node_id, start, now() - start AS running_for,
       substring(query, 1, 200) AS query_preview
FROM q
WHERE application_name = 'payments-api'
  AND user_name = 'app_user'
  AND start < now() - INTERVAL '10 minutes'
ORDER BY start;

Safety Considerations

Read-only operations: All diagnostic queries (SHOW statements, crdb_internal.cluster_transactions) are read-only and safe to run in production.

Cancellation operations (opt-in):

CAUTION: Canceling queries/sessions terminates user work

Only proceed if:

• You've confirmed the query/session is runaway or stuck
• You have authorization to interrupt user workloads
• You've notified stakeholders if appropriate
• You have CANCELQUERY or CANCELSESSION privileges

Canceling Runaway Work (Opt-In)

Cancel a Specific Query

-- 1. Identify the query_id from triage queries above
-- 2. Cancel it
CANCEL QUERY '<query_id>';

Example:

CANCEL QUERY '15f9e0e91f072f0f0000000000000001';

Cancel an Entire Session

-- 1. Identify the session_id from triage queries above
-- 2. Cancel all queries in that session
CANCEL SESSION '<session_id>';

Example:

CANCEL SESSION '15f9e0e91f072f0f';

Verification: After canceling, re-run the triage queries to confirm the query/session is gone.

Required privileges:

• CANCELQUERY system privilege to cancel queries
• CANCELSESSION system privilege to cancel sessions
• Admin role has both by default

See permissions reference for granting these privileges.

Common Triage Workflows

Workflow 1: "Cluster is slow" investigation

Scenario: Users report general slowness.

1. Check for long-running queries: -- Run the "Long-Running Queries" diagnostic -- Look for queries running > 5-10 minutes
2. Identify source applications: -- Group by application to find culprits WITH q AS (SHOW CLUSTER STATEMENTS) SELECT application_name, COUNT(*) AS num_queries, AVG(now() - start) AS avg_duration FROM q WHERE start < now() - INTERVAL '5 minutes' GROUP BY application_name ORDER BY num_queries DESC;
3. Drill down into specific app: -- Filter by top application from step 2 -- Use "Filter by Application" query
4. Decide on action:

- Contact app team to investigate query patterns - Cancel specific runaway queries if critical - Check for schema/index issues if queries are legitimate

Workflow 2: Find high-retry transactions

Scenario: Suspect contention issues.

1. Check for high retry counts: SELECT application_name, AVG(num_retries) AS avg_retries, MAX(num_retries) AS max_retries, COUNT(*) AS num_txns FROM crdb_internal.cluster_transactions WHERE start < now() - INTERVAL '5 minutes' GROUP BY application_name HAVING AVG(num_retries) > 5 ORDER BY avg_retries DESC;
2. Investigate specific transactions: -- Find transactions with >10 retries SELECT id, application_name, num_retries, num_stmts, substring(txn_string, 1, 200) AS txn_preview FROM crdb_internal.cluster_transactions WHERE num_retries > 10 ORDER BY num_retries DESC;
3. Next steps:

- Review transaction patterns for contention - Check for lock conflicts or hotspots - Consider schema changes to reduce contention

Workflow 3: Identify resource hogs by user

Scenario: Need to attribute load to specific users.

1. Count active queries per user: WITH q AS (SHOW CLUSTER STATEMENTS) SELECT user_name, COUNT(*) AS num_active_queries, AVG(now() - start) AS avg_duration FROM q GROUP BY user_name ORDER BY num_active_queries DESC;
2. Drill down to specific user's activity: -- Use "Filter by User" query
3. Take action:

- Contact user if unexpected load - Review user's query patterns - Cancel if clearly runaway

Troubleshooting

Key Considerations

• Privacy: Use VIEWACTIVITYREDACTED instead of VIEWACTIVITY to protect sensitive query constants in multi-tenant environments
• Performance impact: Triage queries are read-only and lightweight, but avoid running them in tight loops during extreme load
• LIMIT clause: Always include LIMIT to prevent overwhelming output on large clusters
• Time thresholds: Adjust INTERVAL based on your workload (5 minutes is a reasonable default, but fast OLTP may need 30 seconds)
• Cancellation is disruptive: Only cancel queries/sessions after confirming they're problematic; coordinate with application teams when possible
• Not for historical analysis: These queries show current state only; for trends over time, use DB Console or Prometheus metrics
• Production-approved sources: Only use SHOW CLUSTER STATEMENTS, SHOW CLUSTER SESSIONS, and crdb_internal.cluster_transactions for production triage

References

Skill references:

• SQL query variations and examples
• RBAC and privilege setup

Related skills:

• profiling-statement-fingerprints - For historical performance pattern analysis and trend identification
• profiling-transaction-fingerprints - For historical transaction-level analysis including retry storms and commit latency

Official CockroachDB Documentation:

• SHOW STATEMENTS
• SHOW SESSIONS
• CANCEL QUERY
• CANCEL SESSION
• crdb_internal
• VIEWACTIVITY privilege