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Description

Error 24, 'Lock Timeout', occurs when a MongoDB operation fails to acquire a necessary lock within the allowed time limit. This typically indicates contention for a resource, where another operation is holding the required lock for too long, preventing the current operation from proceeding.

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Error Message

Lock Timeout

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Known Causes

3 known causes

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High Concurrency

Many concurrent operations attempting to acquire the same database, collection, or document lock, leading to contention.

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Long-Running Operations

An existing operation holds a lock for an extended period, blocking subsequent operations that require the same resource.

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Inefficient Queries

Poorly optimized queries or missing indexes can cause operations to scan large datasets and hold locks longer than necessary.

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Solutions

4 solutions available

1. Investigate and Optimize Slow Queries medium

Identify and tune queries that are holding locks for extended periods.

1

Enable the slow query log to capture queries exceeding a defined threshold.

db.setProfilingLevel(1, { slowms: 100 }); // Set profiling level to 1 (operations) and slowms to 100ms

2

Analyze the slow query log for queries that are frequently running or taking a long time. Look for queries without appropriate indexes, inefficient join-like operations (e.g., using `$lookup` without optimization), or large data scans.

db.system.profile.find().sort({ ts: -1 }).limit(10)

3

Add or optimize indexes for the fields used in the `WHERE` clauses, `JOIN` conditions, and `ORDER BY` clauses of slow queries. Use `explain()` to understand query execution plans and identify missing indexes.

db.collection.explain().find({ field: 'value' })

4

Rewrite inefficient queries. For example, consider denormalizing data or using more efficient aggregation pipeline stages.

// Example: Refactor a complex aggregation pipeline

2. Increase Lock Timeout Settings easy

Adjust MongoDB's lock timeout configuration to allow operations more time to acquire locks.

1

Modify the `operationTimeoutMillis` setting in your MongoDB configuration file or dynamically using `setParameter`.

## In mongod.conf (YAML format)
storage:
  operationTimeoutMillis: 30000 # Increase to 30 seconds (default is 20s)

2

Alternatively, set it dynamically on a running mongod instance (requires appropriate permissions).

db.adminCommand({ setParameter: 1, operationTimeoutMillis: 30000 })

3

Restart the mongod instance for configuration file changes to take effect.

sudo systemctl restart mongod

3. Monitor and Manage Concurrent Operations medium

Reduce the number of highly concurrent write operations that might contend for locks.

1

Use `db.serverStatus()` and `db.currentOp()` to identify operations that are currently running and potentially causing contention.

db.serverStatus().locks

2

Analyze the output of `db.currentOp()` to see which operations are running and for how long. Look for many write operations happening simultaneously.

db.currentOp()

3

If possible, batch write operations or reduce the frequency of high-volume writes. Consider using bulk operations for efficiency.

// Example using bulkWrite

4

If you have a sharded cluster, ensure your sharding strategy is effective and that shard keys are well-distributed to avoid hot spots and excessive cross-shard operations.

db.adminCommand({ reshards: 'your_collection_name', key: { your_shard_key: 1 } })

4. Review and Optimize Schema Design advanced

Evaluate your data model for potential improvements that can reduce lock contention.

1

Examine collections that are frequently updated. If many documents within a single collection are being modified concurrently, consider if a different schema design could distribute the write load.

// No direct code, requires schema analysis

2

For scenarios with high write contention on a single document or a small set of documents, consider techniques like sharding at the application level or using different collections for frequently updated versus infrequently updated data.

// No direct code, requires application-level design changes

3

If you are using capped collections, ensure that your write patterns are compatible with their fixed-size nature. High insert/delete rates might lead to contention.

db.createCollection('myCappedCollection', { capped: true, size: 1000000 })

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Related Errors

5 related errors

MongoDB Error 24: Operation Lock Timeout