How mongodb analyzes which indexes are used in query operations

How to analyze the indexes used by MongoDB query operations? Enable index monitoring: Add a configuration line to enable. Execute query: Execute the query to be analyzed. Check the log file: Index monitoring information will be written to the log file. Analyze log files: content includes query execution plans and index statistics. Identify potential problems: such as index misses or low coverage. Tune indexes: Create or tune indexes to optimize performance and resolve identified issues.

How to analyze the indexes used by MongoDB query operations

Analyzing the indexes used by MongoDB query operations is essential for optimizing the database Performance is critical. This can be achieved through the following steps:

1. Enable index monitoring

You can enable index monitoring by adding the following line in the MongoDB configuration file:

<code>setParameter: { featureFlag: "query-traceQueriesWithIndexStats", value: true }</code>

2. Execute the query

After enabling index monitoring, execute the query operation to be analyzed.

3. Check the log file

Index monitoring information will be written to the MongoDB log file. The log file is usually located at /var/log/mongodb/mongod.log.

4. Analyze the log file

The log file will contain the following information:

• Query execution plan: It contains details about how MongoDB executes queries, including the indexes used.

• Index Statistics: Contains statistics about the index used, such as:

  • Index Coverage: The number of documents included in the index.
  • Index skipped: The number of documents skipped through the index.
  • Index hits: Number of index hits.

5. Identify potential problems

By analyzing the index monitoring information in the log file, you can identify potential problems, such as:

• Index miss: If the index is not used, it may cause poor query performance.
• Low index coverage: If the number of documents covered by the index is small, you may need to create a more selective index.
• Poor index selectivity: If the values ​​of the index are evenly distributed, it may lead to a low index hit rate.

6. Create or adjust indexes as needed

Once potential problems are identified, indexes can be created or adjusted to optimize query performance.

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