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Monitor and Improve Slow Queries

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The Performance Advisor monitors any operation with a query predicate that MongoDB considers slow and suggests new indexes to improve query performance. For the selected host and time period, the Performance Advisor evaluates up to the 20,000 most recent slow queries found in the logs.

Recommended indexes are accompanied by sample queries, grouped by query shape, that were run against a collection that would benefit from the suggested index. The Performance Advisor does not negatively affect the performance of your Ops Manager clusters.

Note

To view the Performance Advisor, you must:

  • Run MongoDB version 3.2 or later on your cluster.

  • Manage your cluster with MongoDB Agent Automation.

    To learn more about the MongoDB Agent, see MongoDB Agent.

To view the field values in the example queries, you must be an Ops Manager user with one or more of the following roles:

Users without the aforementioned roles cannot see the field values.

Common Reasons for Slow Queries

If a query is slow, common reasons include:

  • The query is unsupported by your current indexes.
  • Some documents in your collection have large array fields that are costly to search and index.
  • One query retrieves information from multiple collections with $lookup.

Index Considerations

Indexes improve read performance, but a large number of indexes can negatively impact write performance since indexes must be updated during writes. If your collection already has several indexes, consider this tradeoff of read and write performance when deciding whether to create new indexes. Examine whether a query for such a collection can be modified to take advantage of existing indexes, as well as whether a query occurs often enough to justify the cost of a new index.

The Performance Advisor can help identify and remove unnecessary indexes. To learn more, see Review Drop Index Recommendations.

Access Performance Advisor

To access the Performance Advisor:

1

Click Deployment.

2

Click the replica set where the collection resides.

If the replica set resides in a sharded cluster, first click the sharded cluster containing the replica set.

3

Click Performance Advisor.

4

Select a collection from the Collections dropdown.

5

Select a time period from the Time Range dropdown.

The Performance Advisor displays up to 20 query shapes across all collections in the cluster and suggested indexes for those shapes. The indexes are ranked according to their Impact score, which estimates the improvement in total operational latency across the cluster that creating the index would cause. For more information on index ranking, see Review Index Ranking.

Index Suggestions

The indexes suggested by the Performance Advisor are ordered by their respective Impact scores. Impact indicates the estimated performance improvement that the suggested index would bring. For more information on how the Performance Advisor ranks indexes, see Review Index Ranking.

The Performance Advisor displays a warning icon next to any index with an Impact score of 5% or greater, indicating indexes with the most potential to improve cluster performance.

To learn how to create indexes suggested by the Performance Advisor, see Create Suggested Indexes.

Index Metrics

Each index suggested by the Performance Advisor contains the following metrics. These metrics apply specifically to queries which would be improved by the index:

Metric Description
Execution Count Number of queries executed per hour which would be improved.
Average Execution Time Current average execution time in milliseconds for affected queries.
Average Query Targeting Average number of documents read per document returned by affected queries. A higher query targeting score indicates a greater degree of inefficiency. For more information on query targeting, see Query Targeting.
In Memory Sort Current number of affected queries per hour that needed to be sorted in memory.

Sample Queries

For each suggested index, the Performance Advisor shows the most commonly executed query shapes which would be improved by index. For each query shape, the Performance Advisor displays the following metrics:

Metric Description
Execution Count Number of queries executed per hour which match the query shape.
Average Execution Time Average execution time in milliseconds for queries which match the query shape.
Average Query Targeting Average number of documents read for every document returned by matching queries. A higher query targeting score indicates a greater degree of inefficiency. For more information on query targeting, see Query Targeting.

The Performance Advisor also shows individual sample queries executed which match the query shape, with specific metrics for that query.

Query Targeting

Each index suggestion includes an Average Query Targeting score indicating how many documents were read for every document returned for the index’s corresponding query shapes. A score of 1 represents very efficient query shapes because every document read matched the query and was returned with the query results. All suggested indexes represent an opportunity to improve query performance.

Filter Index Suggestions

By default, the Performance Advisor suggests indexes for all clusters in the deployment. To only show suggested indexes from a specific collection, use the Collection dropdown at the top of the Performance Advisor.

You can also adjust the time range the Performance Advisor takes into account when suggesting indexes by using the Time Range dropdown at the top of the Performance Advisor.

Limitations of Index Suggestions

Timestamp Format for Indexes

The Performance Advisor can’t suggest indexes for MongoDB databases configured to use the ctime timestamp format. As a workaround, set the timestamp format for such databases to either iso8601-utc or iso8601-local.

Log Size

The Performance Advisor analyzes up to 200,000 of your cluster’s most recent log lines.

Create Suggested Indexes

You can create indexes suggested by the Performance Advisor directly within the Performance Advisor itself. When you create indexes, keep the ratio of reads to writes on the target collection in mind. Indexes come with a performance cost, but are more than worth the cost for frequent queries on large data sets. To learn more about indexing strategies, see Indexing Strategies.

Behavior

  • You can only create one index at a time through the Performance Advisor. If you want to create more simultaneously, you can do so using Data Explorer or the shell
  • Indexes created in the Performance Advisor are always created at the top level of the deployment. If you create an index while viewing the Performance Advisor for a single shard in a sharded cluster, Ops Manager creates that index for the whole sharded cluster.

Procedure

To create a suggested index:

1

For the index you want to create, click Create Index.

The Performance Advisor opens the Create Index dialog and prepopulates the Fields based on the index you selected.

2

(Optional) Specify the index options.

{ <option1>: <value1>, ... }

Example

The following options document specifies the unique option and the name for the index:

copy 
{ unique: true, name: "myUniqueIndex" }
3

(Optional) Set the Collation options.

Use collation to specify language-specific rules for string comparison, such as rules for lettercase and accent marks. The collation document contains a locale field which indicates the ICU Locale code, and may contain other fields to define collation behavior.

Example

The following collation option document specifies a locale value of fr for a French language collation:

copy 
{ "locale": "fr" }

To review the list of locales that MongoDB collation supports, see the list of languages and locales. To learn more about collation options, including which are enabled by default for each locale, see Collation in the MongoDB manual.

4

(Optional) Enable building indexes in a rolling fashion.

Warning

Due to critical issue SERVER-68925, Ops Manager deployments using certain versions of the MongoDB Agent should not perform automated rolling index builds on clusters running the following MongoDB versions:

  • MongoDB 4.2.19-4.2.22
  • MongoDB 4.4.13-4.4.16
  • MongoDB 5.0.6-5.0.11
  • MongoDB 6.0.0-6.0.1

You can continue to perform manual rolling index builds safely on your clusters. To perform automated rolling index builds safely, upgrade your clusters to:

  • MongoDB 4.2.23 or later
  • MongoDB 4.4.17 or later
  • MongoDB 5.0.12 or later
  • MongoDB 6.0.2 or later

Important

Rolling index builds succeed only when they meet certain conditions. To ensure your index build succeeds, avoid the following design patterns that commonly trigger a restart loop:

Note

Data Explorer does not support building indexes in a rolling fashion for standalone deployments.

Building indexes in a rolling fashion reduces the performance impact of building indexes on replica sets and sharded clusters. To maintain cluster availability, Ops Manager removes one node from the cluster at a time starting with a secondary.

After you build an index in a rolling fashion, if your MongoDB database runs with an FCV less than 4.2, resync the head database to ensure that the head database takes the new index into account.

To learn more about rebuilding indexes, see Build Indexes on Replica Sets.

Note

The following index options are incompatible with building indexes in a rolling fashion:

Ops Manager ignores these options if you specify them in the Options pane.

5

Click Review.

6

In the Confirm Operation dialog, confirm your index.

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