Indexing and Customizing Indexes in Adobe Experience Manager

Adobe Experience Manager (AEM) is a powerful tool for managing and delivering digital experiences. One of the keys to maintaining optimal performance in AEM applications is efficient query execution, but like any complex system, its performance can be greatly impacted by inefficient processes—chief among them, query execution. Queries within AEM can become a bottleneck, slowing down website performance, increasing server load, and affecting user experience if not handled correctly.

One key element to ensure fast, scalable, and efficient query execution in AEM is indexing. Indexing is a technique that speeds up the retrieval of content from the repository by allowing AEM to access information quickly without scanning the entire dataset. While AEM provides default indexes, there are many cases where creating custom indexes will vastly improve the efficiency of your queries. In this blog post, we will explore the importance of indexing in AEM, the process of creating custom indexes, and best practices for maintaining an efficient query environment.

Background

Adobe Experience Manager operates on top of the Oak repository, which is an integral part of AEM’s JCR (Java Content Repository). The Oak repository stores all content, assets, and other data within AEM, and queries are executed when the system retrieves content from this repository. While Oak is highly scalable, its performance heavily relies on effective indexing. Without proper indexing, AEM queries can become slow, especially as the volume of content grows.

While AEM does offer default indexes, which work well for many out-of-the-box use cases, they may not cover the unique needs of custom content or complex querying. This is where custom indexes come in—providing more targeted indexing rules to cater to specific data requirements.

Proper indexing in AEM results in faster queries, reduced server load, improved user experiences, and scalability as your content grows.

Key Concepts in AEM Indexing

Before diving into the step-by-step process of creating custom indexes in AEM, let’s first go over some key concepts that will help you understand the importance and application of indexing.

1. Indexes and Query Performance

Indexes allow queries to be executed faster by organizing data in a way that enables quick retrieval. In AEM, when you run a query, the Oak repository checks whether the query can be answered using an existing index. If it can, the index is used, and the query returns results faster.

2. Default vs. Custom Indexes

• Default Indexes: AEM comes with built-in indexes for common query patterns. These are useful for standard queries but might not be sufficient for more complex or specific needs.
• Custom Indexes: Custom indexes are defined by users to optimize query performance for specific content structures or types of queries. These indexes allow you to specify which content to index based on custom paths or properties.

3. Types of Indexes in AEM

There are different types of indexes that AEM supports:

• Node Type Indexes: These indexes target specific node types within the repository and are often used to optimize queries filtering by node type.
• Property Indexes: These indexes optimize queries filtering by specific properties, such as jcr:title or jcr:description.
• Full-Text Search Indexes: Aimed at indexing text properties for full-text search queries.

4. Reindexing

When new content is added, modified, or deleted, AEM might require a reindex to update the indexes to reflect these changes. Reindexing ensures that the index remains accurate and up-to-date. However, it can be a resource-intensive process, which is why it is important to only reindex when necessary.

5. Asynchronous Indexing

For large datasets, indexing operations can take significant time and may impact performance. Asynchronous indexing allows you to index data in the background, ensuring that it doesn’t block other operations or affect user experience.

Detailed Explanation of Indexing in AEM

Why Indexing is Crucial for Performance

AEM applications can house a vast amount of data, including web content, digital assets, and more. As the repository grows, queries against this data can slow down without proper indexing. Slow queries can affect the performance of both the AEM server and the end-user experience. By implementing proper indexes, you are essentially ensuring that queries will return results much faster, making your system more responsive and scalable.

How Indexes Work in AEM

AEM uses the Oak Query Engine to execute queries on its underlying repository. When a query is run, Oak tries to match the query’s criteria with an appropriate index, thereby optimizing how the data is retrieved. If no index is found or the query is not optimized, Oak performs a full scan of the repository, which significantly slows down query execution.

For example, if you perform a query that searches for all content nodes under a specific path, AEM will benefit from an index on that path, which allows it to directly return the relevant content rather than scanning the entire repository.

Creating Custom Indexes

Let’s dive deeper into how you can create custom indexes that cater to your specific application needs. Custom indexing in AEM is done through index definition XML files, which define the parameters and rules for what gets indexed.

Here’s an example of a basic custom index definition:

xmlCopy code<?xml version="1.0" encoding="UTF-8"?>

<index oak:indexDefinition="{Name}CustomIndex" xmlns:oak="http://jackrabbit.apache.org/oak/query/1.0">
    
    <indexRules>
        <include>
            <pattern>/content/myapp/.*</pattern>
        </include>
        <include>
            <pattern>/content/dam/myassets/.*</pattern>
        </include>
    </indexRules>
    
</index>

Steps to Implement a Custom Index

1. Create the Index Definition File: Start by creating an XML file that contains the index definition.
2. Deploy the Index: Save the XML definition under /oak:index/ within the JCR repository. You can either use the CRXDE Lite interface or a content package to deploy the index.
3. Reindex if Needed: After creating and deploying the index, you may need to trigger a reindex, especially if you’re working with a large amount of content.

Custom Index Rules

Sometimes, you might need to create more specific indexing rules. For example, if you want to index properties like jcr:title or jcr:description, you can define these rules explicitly in the XML.

Example:

xmlCopy code<?xml version="1.0" encoding="UTF-8"?>

<indexDefinition name="customIndex" jcr:primaryType="oak:QueryIndexDefinition" type="property" async="async">
    <property>
        <name>jcr:title</name>
        <propertyIndex>true</propertyIndex>
        <type>String</type>
    </property>
    
    <property>
        <name>jcr:description</name>
        <propertyIndex>true</propertyIndex>
        <type>String</type>
    </property>
</indexDefinition>

This XML snippet will create an index for properties jcr:title and jcr:description, ensuring queries that filter by these properties are optimized.

Monitoring and Maintaining Indexes

It’s essential to keep track of the health and status of your indexes. AEM offers tools for monitoring indexing performance and checking for issues.

AEM Felix Web Console

The AEM Felix Web Console provides visibility into the health of your indexes. You can view the current status of indexes, trigger reindexing, and get statistics on their performance.

You can access the Felix Web Console at:

bashCopy codehttp://localhost:4502/system/console/indexmanager

Query Performance Monitoring

AEM also provides tools for monitoring and profiling queries. Enabling query profiling will allow you to track the performance of each query, showing you execution times and other useful metrics.

Adobe Granite Query Debugger

The Adobe Granite Query Debugger allows you to debug and optimize individual queries, helping you identify performance bottlenecks.

You can access it at:

bashCopy codehttp://localhost:4502/system/console/depfinder/querydebug.html

Best Practices for Indexing in AEM

1. Regularly Review and Update Indexes: As your application grows and your content model changes, it’s important to regularly revisit and update your indexes. This ensures that they stay aligned with your querying needs and help maintain optimal performance.
2. Limit the Use of Full-Text Indexing: While full-text search indexes can be useful, they can also be expensive in terms of performance. Use them only when necessary and consider limiting the scope of full-text queries.
3. Avoid Over-Indexing: Only index the properties and paths that are required for your specific queries. Over-indexing can negatively impact performance and increase storage requirements.
4. Use Property Constraints: Property constraints in your queries can reduce the number of results returned, making them faster. Always use constraints whenever possible.
5. Rebuild Indexes Periodically: Periodic index rebuilding ensures that the indexes remain optimized and up-to-date. Consider scheduling reindexing operations during off-peak hours.
6. Test Index Changes: Before deploying changes to production, thoroughly test new index definitions in a staging environment to ensure they improve performance without introducing issues.

Case Studies and Examples

Let’s take a look at an example of how proper indexing improved query performance in a large-scale AEM deployment.

Example 1: Large Media Asset Repository

In one large e-commerce deployment, the client stored tens of thousands of media assets in AEM’s DAM (Digital Asset Management). Queries for assets by name, type, or metadata were frequently slowing down the system. By introducing custom indexes specifically targeting properties like jcr:title and jcr:description, the response times for these queries were reduced by over 70%, leading to faster content delivery and a better user experience.

FAQ

Q1: What are the most common types of indexes in AEM?

The most common types of indexes are:

• Node Type Indexes
• Property Indexes
• Full-Text Search Indexes

Q2: How often should I rebuild my indexes?

It depends on the size of your repository and how frequently the content changes. As a best practice, schedule regular reindexing during off-peak hours.

Q3: Can I index all properties in AEM?

It’s generally not recommended to index every property in AEM, as this can lead to performance degradation. Focus on indexing properties that are frequently queried.

Conclusion

Mastering indexing in Adobe Experience Manager is crucial for optimizing query performance, improving the user experience, and ensuring scalability as your content grows. By understanding the different types of indexes, creating custom indexes tailored to your needs, and following best practices for monitoring and maintenance, you can unlock AEM’s full potential.

With proper indexing strategies in place, AEM applications can run smoothly, offering fast, responsive, and high-performing digital experiences for users.