Troubleshooting Slow Queries

Slow Query Classifications

There are 3 main classifications of slow queries in AEM, listed by severity:

  1. Index-less queries

    • Queries that do not resolve to an index and traverse the JCR’s contents to collect results

  2. Poorly restricted (or scoped) queries

    • Queries that resolve to an index, but must traverse all index entries to collect results

  3. Large result set queries

    • Queries that return very large numbers of results

The first 2 classifications of queries (index-less and poorly restricted) are slow, because they force the Oak query engine to inspect each potential result (content node or index entry) to identify which belong in the actual result set.

The act of inspecting each potential result is what is referred to as Traversing.

Since each potential result must be inspected, the cost to determine the actual result set grows linearly with the number of potentials results.

Adding query restrictions and tuning indexes allows the index data to be stored in an optimized format affording fast result retrieval and, reduces or eliminates the need for the linear inspection of potential result sets.

In AEM 6.3, by default, when a traversal of 100,000 is reached, the query fails and throws an exception. This limit does not exist by default in AEM versions prior to AEM 6.3, but can be set via the Apache Jackrabbit Query Engine Settings OSGi configuration and QueryEngineSettings JMX bean (property LimitReads).

Detecting Index-less Queries

During Development

Explain all queries and ensure their query plans do not contain the /* traverse explanation in them. Example traversing query plan:

  • PLAN: [nt:unstructured] as [a] /* traverse "/content//*" where ([a].[unindexedProperty] = 'some value') and (isdescendantnode([a], [/content])) */

Post-Deployment

  • Monitor the error.log for index-less traversal queries:

    • *INFO* org.apache.jackrabbit.oak.query.QueryImpl Traversal query (query without index) ... ; consider creating and index
    • This message is only logged if no index is available, and if the query potentially traverses many nodes. Messages are not logged if an index is available, but amount to traversing is small, and thus fast.

  • Visit the AEM Query Performance operations console and Explain slow queries looking for traversal or no index query explanations.

Detecting Poorly Restricted Queries

During Development

Explain all queries and ensure they resolve to an index tuned to match the query’s property restrictions.

  • Ideal query plan coverage has indexRules for all property restrictions, and at a minimum for the tightest property restrictions in the query.
  • Queries that sort results, should resolve to a Lucene Property Index with index rules for the sorted by properties that set orderable=true.

For example, the default cqPageLucene does not have an index rule for jcr:content/cq:tags

Before adding the cq:tags index rule

  • cq:tags Index Rule

    • Does not exist out of the box

  • Query Builder query

    type=cq:Page
property=jcr:content/cq:tags
property.value=my:tag

  • Query plan

    [cq:Page] as [a] /* lucene:cqPageLucene(/oak:index/cqPageLucene?lang=en) *:* where [a].[jcr:content/cq:tags] = 'my:tag' */

This query resolves to the cqPageLucene index, but because no property index rule exists for jcr:content or cq:tags, when this restriction is evaluated, every record in the cqPageLucene index is checked to determine a match. This means that if the index contains 1 million cq:Page nodes, then 1 million records are checked to determine the result set.

After adding the cq:tags index rule

  • cq:tags Index Rule

    /oak:index/cqPageLucene/indexRules/cq:Page/properties/cqTags
@name=jcr:content/cq:tags
@propertyIndex=true

  • Query Builder query

    type=cq:Page
property=jcr:content/cq:tags
property.value=myTagNamespace:myTag

  • Query plan

    [cq:Page] as [a] /* lucene:cqPageLucene(/oak:index/cqPageLucene?lang=en) jcr:content/cq:tags:my:tag where [a].[jcr:content/cq:tags] = 'my:tag' */

The addition of the indexRule for jcr:content/cq:tags in the cqPageLucene index allows cq:tags data to be stored in an optimized way.

When a query with the jcr:content/cq:tags restriction is performed, the index can look up results by value. That means that if 100 cq:Page nodes have myTagNamespace:myTag as a value, only those 100 results are returned, and the other 999,000 are excluded from the restriction checks, improving performance by a factor of 10,000.

Of course, further query restrictions reduce the eligible result sets and further optimize the query optimization.

Similarly, without an additional index rule for the cq:tags property, even a fulltext query with a restriction on cq:tags would perform poorly as results from the index would return all fulltext matches. The restriction on cq:tags would be filtered after it.

Another cause of post-index-filtering is Access Control Lists which often gets missed during development. Try to make sure that the query does not return paths that might be inaccessible to the user. This usually can be done by better content structure along with providing relevant path restriction on the query.

A useful way to identify if the Lucene index is returning a lot of results to return a very small subset as query result is to enable DEBUG logs for org.apache.jackrabbit.oak.plugins.index.lucene.LucenePropertyIndex and see how many documents are being loaded from the index. Number of eventual results versus the number of loaded documents shouldn’t be disproportionate. For more information, see Logging.

Post-Deployment

  • Monitor the error.log for traversal queries:

    • *WARN* org.apache.jackrabbit.oak.spi.query.Cursors$TraversingCursor Traversed ### nodes ... consider creating an index or changing the query

  • Visit the AEM Query Performance operations console and Explain slow queries looking for query plans that do not resolve query property restrictions to index property rules.

Detecting Large Result Set Queries

During Development

Set low threshholds for oak.queryLimitInMemory (eg. 10000) and oak.queryLimitReads (eg. 5000) and optimize the expensive query when hitting an UnsupportedOperationException saying “The query read more than x nodes…”

This helps avoiding resource intensive queries (ie. not backed by any index or backed by less covering index). For example, a query that reads 1M nodes would lead to lots of IO, and negatively impact the overall application performance. So any query which fails due to above limits should be analyzed and optimized.

Post-Deployment

  • Monitor the logs for queries triggering large node traversal or large heap memory consumption : ``

    • *WARN* ... java.lang.UnsupportedOperationException: The query read or traversed more than 100000 nodes. To avoid affecting other tasks, processing was stopped.
    • Optimize the query to reduce the number of traversed nodes

  • Monitor the logs for queries triggering large heap memory consumption :

    • *WARN* ... java.lang.UnsupportedOperationException: The query read more than 500000 nodes in memory. To avoid running out of memory, processing was stopped
    • Optimize the query to reduce the heap memory consumption

For AEM 6.0 - 6.2 versions, you can tune the threshold for node traversal via JVM parameters in the AEM start script to prevent large queries from overloading the environment. The recommended values are :

  • -Doak.queryLimitInMemory=500000
  • -Doak.queryLimitReads=100000

In AEM 6.3, the above 2 parameters are preconfigured by default, and can be modified via the OSGi QueryEngineSettings.

More information available under : https://jackrabbit.apache.org/oak/docs/query/query-engine.html#Slow_Queries_and_Read_Limits

Query Performance Tuning

The motto of query performance optimization in AEM is:

“The more restrictions, the better.”

The following outlines recommended adjustments to ensure query performance. First tune the query, a less obtrusive activity, and then if needed, tune the index definitions.

Adjusting the Query Statement

AEM supports the following query languages:

  • Query Builder
  • JCR-SQL2
  • XPath

The following example uses Query Builder as it’s the most common query language used by AEM developers, however the same principles are applicable to JCR-SQL2 and XPath.

  1. Add a nodetype restriction so the query resolves to an existing Lucene Property Index.

  • Unoptimized query

    property=jcr:content/contentType
property.value=article-page

  • Optimized query

    type=cq:Page
property=jcr:content/contentType
property.value=article-page

    Queries lacking a nodetype restriction force AEM to assume the nt:base nodetype, which every node in AEM is a subtype of, effectively resulting in no nodetype restriction.

    Setting type=cq:Page restricts this query to only cq:Page nodes, and resolves the query to AEM’s cqPageLucene, limiting the results to a subset of nodes (only cq:Page nodes) in AEM.

  1. Adjust the query’s nodetype restriction so the query resolves to an existing Lucene Property Index.

  • Unoptimized query

    type=nt:hierarchyNode
property=jcr:content/contentType
property.value=article-page

  • Optimized query

    type=cq:Page
property=jcr:content/contentType
property.value=article-page

    nt:hierarchyNode is the parent nodetype of cq:Page, and assuming jcr:content/contentType=article-page is only applied to cq:Page nodes via our custom application, this query will only return cq:Page nodes where jcr:content/contentType=article-page. This is a suboptimal restriction though, because:

    • Other node inherit from nt:hierarchyNode (eg. dam:Asset) adding unnecessarily to the set of potential results.
    • No AEM-provided index exists for nt:hierarchyNode, however as there a provided index for cq:Page.

    Setting type=cq:Page restricts this query to only cq:Page nodes, and resolves the query to AEM’s cqPageLucene, limiting the results to a subset of nodes (only cq:Page nodes) in AEM.

  1. Or, adjust the property restriction(s) so the query resolves to an existing Property Index.

  • Unoptimized query

    property=jcr:content/contentType
property.value=article-page

  • Optimized query

    property=jcr:content/sling:resourceType
property.value=my-site/components/structure/article-page

    Changing the property restriction from jcr:content/contentType (a custom value) to the well known property sling:resourceType lets the query to resolve to the property index slingResourceType which indexes all content by sling:resourceType.

    Property indexes (opposed to Lucene Property Indexes) are best used when the query does not discern by nodetype, and a single property restriction dominates the result set.

  1. Add the tightest path restriction possible to the query. For example, prefer /content/my-site/us/en over /content/my-site, or /content/dam over /.

  • Unoptimized query

    type=cq:Page
path=/content
property=jcr:content/contentType
property.value=article-page

  • Optimized query

    type=cq:Page
path=/content/my-site/us/en
property=jcr:content/contentType
property.value=article-page

    Scoping the path restriction from path=/contentto path=/content/my-site/us/en allows the indexes to reduce the number of index entries that need to be inspected. When the query can restrict the path very well, beyond just /content or /content/dam, ensure the index has evaluatePathRestrictions=true.

    Note using evaluatePathRestrictions increases the index size.

  1. When possible, avoid query functions/operations suchs as: LIKE and fn:XXXX as their costs scales with the number of restriction-based results.

  • Unoptimized query

    type=cq:Page
property=jcr:content/contentType
property.operation=like
property.value=%article%

  • Optimized query

    type=cq:Page
fulltext=article
fulltext.relPath=jcr:content/contentType

    The LIKE condition is slow to evaluate because no index can be used if the text starts with a wildcard ("%…'). The jcr:contains condition allows using a fulltext index, and is therefore preferred. This requires the resolved Lucene Property Index to have indexRule for jcr:content/contentType with analayzed=true.

    Using query functions like fn:lowercase(..) may be harder to optimize as there are not faster equivalents (outside more complex and obtrusive index analyzer configurations). It is best to identify other scoping restrictions to improve improve the overal query performance, requiring the functions to operate on the smallest set of potential results possible.

  1. This adjustment is Query Builder specific, and does not apply to JCR-SQL2 or XPath.

    Use Query Builder’ guessTotal when the full set of results is not immediately needed.

    • Unoptimized query

      type=cq:Page
path=/content

    • Optimized query

      type=cq:Page
path=/content
p.guessTotal=100

    For cases where query execution is fast but the number of results are large, p. guessTotal is a critical optimization for Query Builder queries.

    p.guessTotal=100 tells Query Builder to only collect only the first 100 results, and set a boolean flag indicating if at least one more results exist (but not how many more, as counting this number would be be result in slowness). This optimization excels for pagination or infinite loading use cases, where only a subset of results are incrementally displayed.

Existing Index Tuning

  1. If the optimal query resolves to a Property Index, then there is nothing left to do as Property Indexes are minimally tune-able.

  2. Otherwise, the query should resolve to a Lucene Property Index. If no index can be resolved, jump to Creating a new Index.

  3. As needed, convert the query to XPath or JCR-SQL2.

    • Query Builder query

      query type=cq:Page
path=/content/my-site/us/en
property=jcr:content/contentType
property.value=article-page
orderby=@jcr:content/publishDate
orderby.sort=desc

    • XPath generated from Query Builder query

      /jcr:root/content/my-site/us/en//element(*, cq:Page)[jcr:content/@contentType = 'article-page'] order by jcr:content/@publishDate descending

  4. Provide the XPath (or JCR-SQL2) to Oak Index Definition Generator to generate the optimized Lucene Property Index definition.

    Generated Lucene Property Index definition

    - evaluatePathRestrictions = true
- compatVersion = 2
- type = "lucene"
- async = "async"
- jcr:primaryType = oak:QueryIndexDefinition
    + indexRules
    + cq:Page
        + properties
        + contentType
            - name = "jcr:content/contentType"
            - propertyIndex = true
        + publishDate
            - ordered = true
            - name = "jcr:content/publishDate"

  5. Manually merge the generated definition into the existing Lucene Property Index in an additive fashion. Be careful not to remove existing configurations as they may be used to satisfy other queries.

    1. Locate the existing Lucene Property Index that covers cq:Page (using Index Manager). In this case, /oak:index/cqPageLucene.
    2. Identify the configuration delta between the optimized index definition (Step #4) and the existing index (/oak:index/cqPageLucene?lang=en), and add the missing configurations from the optimized Index to the existing index definition.
    3. Per AEM’s Re-indexing Best Practices, either a refresh or re-index is in order, based on if existing content will be effected by this index configuration change.

Create a New Index

  1. Verify the query does not resolve to an existing Lucene Property Index. If it does, see the above section on tuning and existing index.

  2. As needed, convert the query to XPath or JCR-SQL2.

    • Query Builder query

      type=myApp:Author
property=firstName
property.value=ira

    • XPath generated from Query Builder query

      //element(*, myApp:Page)[@firstName = 'ira']

  3. Provide the XPath (or JCR-SQL2) to Oak Index Definition Generator to generate the optimized Lucene Property Index definition.

    Generated Lucene Property Index definition

    - compatVersion = 2
- type = "lucene"
- async = "async"
- jcr:primaryType = oak:QueryIndexDefinition
    + indexRules
    + myApp:AuthorModel
        + properties
        + firstName
            - name = "firstName"
            - propertyIndex = true

  4. Deploy the generated Lucene Property Index definition.

    Add the XML definition provided by Oak Index Definition Generator for the new index to the AEM project that manages Oak index definitions (remember, treat Oak index definitions as code, since code depends on them).

    Deploy and test the new index following the usual AEM software development lifecycle and verify the query resolves to the index and the query is performant.

    Upon the initial deployment of this index, AEM will populate the index with the requisite data.

When are index-less and traversal queries OK?

Due to AEM’s flexible content architecture, it’s difficult to predict and ensure traversals of content structures will not evolve over time to be unacceptably large.

Therefore, ensure an indexes satisfy queries, except if the combination of path restriction and nodetype restriction guarantees that less than 20 nodes are ever traversed.

Query Development Tools

Adobe Supported

Community Supported

  • Oak Index Definition Generator

    • Generate optimal Lucence Property Index from XPath or JCR-SQL2 query statements.

  • AEM Chrome Plug-in

    • Google Chrome web browser extension that exposes per-request log data, including executed queries and their query plans, in the browser’s dev tools console.
    • Requires Sling Log Tracer 1.0.2+ to be installed and enabled on AEM.

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