Configuring node stores and data stores in AEM 6

Introduction

In Adobe Experience Manager (AEM), binary data can be stored independently from the content nodes. The binary data is stored in a data store, whereas content nodes are stored in a node store.

Both data stores and node stores can be configured using OSGi configuration. Each OSGi configuration is referenced using a persistent identifier (PID).

Configuration steps

To configure both the node store and the data store, perform these steps:

1. Copy the AEM quickstart JAR file to its installation directory.

2. Create a folder crx-quickstart/install in the installation directory.

3. First, configure the node store by creating a configuration file with the name of the node store option you want to use in the crx-quickstart/install directory.

   For example, the Document node store (which is the basis for AEM’s MongoMK implementation) uses the file org.apache.jackrabbit.oak.plugins.document.DocumentNodeStoreService.config.

4. Edit the file, and set your configuration options.

5. Create a configuration file with the PID of the data store you want to use. Edit the file to set the configuration options.

   NOTE

   See Node Store Configurations and Data Store Configurations for configuration options.

6. Start AEM.

Node Store Configurations

Segment Node Store

The segment node store is the basis of Adobe’s TarMK implementation in AEM6. It uses the org.apache.jackrabbit.oak.segment.SegmentNodeStoreService PID for configuration.

You can configure the following options:

• repository.home: Path to repository home under which repository-related data is stored. By default, segment files are stored under the crx-quickstart/segmentstore directory.

• tarmk.size: Maximum size of a segment in MB. The default maximum is 256MB.

• customBlobStore: Boolean value indicating that a custom data store is used. The default value is true for AEM 6.3 and later versions. Prior to AEM 6.3 the default was false.

The following is a sample org.apache.jackrabbit.oak.segment.SegmentNodeStoreService.config file:

#Path to repo
repository.home="crx-quickstart/repository"

#Max segment size
tarmk.size=I"256"

#Custom data store
customBlobStore=B"true"

Document Node Store

The document node store is the basis of AEM’s MongoMK implementation. It uses the org.apache.jackrabbit.oak.plugins.document.DocumentNodeStoreService* *PID. The following configuration options are available:

• mongouri: The MongoURI required to connect to Mongo Database. The default is mongodb://localhost:27017

• db: Name of the Mongo database. The default is Oak . However, new AEM 6 installations use **aem-author** as the default database name.

• cache: The cache size in MB. This is distributed among various caches used in DocumentNodeStore. The default is 256

• changesSize: Size in MB of capped collection used in Mongo for caching the diff output. The default is 256

• customBlobStore: Boolean value indicating that a custom data store will be used. The default is false.

The following is a sample org.apache.jackrabbit.oak.plugins.document.DocumentNodeStoreService.config file:

#Mongo server details
mongouri="mongodb://localhost:27017"

#Name of Mongo database to use
db="aem-author"

#Store binaries in custom BlobStore
customBlobStore=B"false"

Data Store Configurations

When dealing with large number of binaries, it is recommended that an external data store be used instead of the default node stores to maximize performance.

For example, if your project requires many media assets, storing them under the File or S3 Data Store makes accessing them faster than storing them directly inside a MongoDB.

The File Data Store provides better performance than MongoDB, and Mongo backup and restore operations are also slower with large number of assets.

Details on the different data stores and configurations are described below.

File Data Store

This is the implementation of FileDataStore present in Jackrabbit 2. It provides a way to store the binary data as normal files on the file system. It uses the org.apache.jackrabbit.oak.plugins.blob.datastore.FileDataStore PID.

These configuration options are available:

• repository.home: Path to repository home under which various repository related data is stored. By default, binary files would be stored under crx-quickstart/repository/datastore directory

• path: Path to the directory under which the files would be stored. If specified then it takes precedence over repository.home value

• minRecordLength: The minimum size in bytes of a file stored in the data store. Binary content less than this value would be inlined.

Amazon S3 Data Store

AEM can be configured to store data in Amazon’s Simple Storage Service (S3). It uses the org.apache.jackrabbit.oak.plugins.blob.datastore.S3DataStore.config PID for configuration.

To enable the S3 data store functionality, a feature pack containing the S3 Datastore Connector must be downloaded and installed. Go to the Adobe Repository and download the latest version from the 1.10.x versions of the feature pack (for example, com.adobe.granite.oak.s3connector-1.10.0.zip). Also, you must download and install the latest AEM service pack as listed on the AEM 6.5 Release Notes page.

java -jar <aem-jar-file>.jar -r crx3tar-nofds

Once downloaded, you can install and configure the S3 Connector as follows:

1. Extract the contents of the feature pack zip file to a temporary folder.

2. Go to the temporary folder and navigate to the following location:

   jcr_root/libs/system/install
   

   Copy all the contents from the above location to <aem-install>/crx-quickstart/install.

3. If AEM is already configured to work with the Tar or MongoDB storage, remove any existing configuration files from the <aem-install>/crx-quickstart/install folder before proceeding. The files that must be removed are:

   • For MongoMK: org.apache.jackrabbit.oak.plugins.document.DocumentNodeStoreService.config
   • For TarMK: org.apache.jackrabbit.oak.segment.SegmentNodeStoreService.config

4. Return to the temporary location where the feature pack has been extracted, and copy the contents of the following folder:

   • jcr_root/libs/system/config

   to

   • <aem-install>/crx-quickstart/install

   Make sure you only copy the configuration files needed by your current configuration. For both a dedicated data store and a shared data store setup copy the org.apache.jackrabbit.oak.plugins.blob.datastore.S3DataStore.config file.

   NOTE

   In a cluster setup, perform above steps on all nodes of cluster one by one. Also, make sure to use same S3 settings for all nodes.

5. Edit the file and add the configuration options required by your setup.

6. Start AEM.

Upgrading to a new version of the 1.10.x S3 Connector

To upgrade to a new version of the 1.10.x S3 connector (for example, from 1.10.0 to 1.10.4) follow these steps:

1. Stop the AEM instance.

2. Navigate to <aem-install>/crx-quickstart/install/15 in the AEM installation folder and make a backup of its contents.

3. After the backup, delete the old version of the S3 Connector and its dependencies by deleting all the jar files in the <aem-install>/crx-quickstart/install/15 folder, for example:

   • oak-blob-cloud-1.6.1.jar
   • aws-java-sdk-osgi-1.10.76.jar
   NOTE

   The file names presented above are used for illustration purposes only.

4. Download the latest version of the 1.10.x feature pack from the Adobe Repository.

5. Unzip the contents to a separate folder, then navigate to jcr_root/libs/system/install/15.

6. Copy the jar files to <aem-install>/crx-quickstart/install/15 in the AEM installation folder.

7. Start AEM and check the connector functionality.

You can use the configuration file with the options detailed below.

S3 Connector Configuration File Options

DataStore Caching

When upgrading from an older cache implementation (pre Oak 1.6) there is a difference in the structure of the local file system cache directory. In the old cache structure, both the downloaded and the uploaded files were put directly under the cache path. The new structure segregates the downloads and uploads and stores them in two directories named upload and download under cache path. The upgrade process should be seamless and any pending uploads should be scheduled for upload and any previously downloaded files in the cache are put in the cache on initialization.

You can also upgrade the cache offline by using the datastorecacheupgrade command of oak-run. For details on how to execute the command, check the readme for the oak-run module.

The cache has a size limit and it can be configured by using the cacheSize parameter.

Downloads

The local cache is checked for the record of the requested file/blob before accessing it from the DataStore. When the cache exceeds the configured limit (see the cacheSize parameter) while adding a file into the cache, then some of the files are evicted to reclaim space.

Asynchronous Upload

The cache supports asynchronous uploads to the DataStore. The files are staged locally, in the cache (on the file system), and an asynchronous job starts to upload the file. The number of asynchronous uploads is limited by the size of the staging cache. The size of the staging cache is configured by using the stagingSplitPercentage parameter. This parameter defines the percentage of cache size to be used for the staging cache. Also, the percentage of cache available for downloads is calculated as (100 - stagingSplitPercentage) * cacheSize.

The asynchronous uploads are multi-threaded and the number of threads is configured by using the uploadThreads parameter.

The files are moved to the main download cache after the uploads are complete. When the staging cache size exceeds its limit, the files are uploaded synchronously to the DataStore until the previous asynchronous uploads are complete and space is again available in the staging cache. The uploaded files are removed from the staging area by a periodic job whose interval is configured by the stagingPurgeInterval parameter.

Failed uploads (for example, because of a network disruption) are put on a retry queue and retried periodically. The retry interval is configured by using the stagingRetryInterval parameter.

Configuring binaryless replication with Amazon S3

To configure binaryless replication with S3, the following steps are required:

1. Install the author and publish instances and make sure they are started properly.

2. Go to the replication agent settings, by opening a page to https://localhost:4502/etc/replication/agents.author/publish.html.

3. Press the Edit button in the Settings section.

4. Change the Serialization type option to Binary less.

5. Add the parameter " binaryless= true" in the transport uri. After the change, the uri should look similar to the following:

   https://localhost:4503/bin/receive?sling:authRequestLogin=1&binaryless=true

6. Restart all author and publish instances to let the changes take effect.

Creating a cluster using S3 and MongoDB

1. Unpack CQ quickstart using the following command:

   java -jar cq-quickstart.jar -unpack

2. After AEM has been unpacked, create a folder inside the installation directory crx-quickstart/install.

3. Create these two files inside the crx-quickstart folder:

   • org.apache.jackrabbit.oak.plugins.document.DocumentNodeStoreService.config

   • org.apache.jackrabbit.oak.plugins.blob.datastore.S3DataStore.config

   After the files have been created, add the configuration options as needed.

4. Install the two bundles required for the S3 data store as explained above.

5. Make sure MongoDB is installed and an instance of mongod is running.

6. Start AEM with the following command:

   java -Xmx1024m -jar cq-quickstart.jar -r crx3,crx3mongo

7. Repeat steps 1 through 4 for the second AEM instance.

8. Start the second AEM instance.

Configuring a Shared Data Store

1. First, create the data store configuration file on each instance that is required to share the data store:

   • If you are using a FileDataStore, create a file named org.apache.jackrabbit.oak.plugins.blob.datastore.FileDataStore.config and place it in the <aem-install>/crx-quickstart/install folder.

   • If using S3 as the data store, create a file named o rg.apache.jackrabbit.oak.plugins.blob.datastore.S3DataStore.config in the <aem-install>/crx-quickstart/install folder as above.

2. Modify the data store configuration files on each instance so they point to the same data store. For more information, see this article.

3. If the instance has been cloned from an existing server, you must remove the clusterId of the new instance by using the latest oak-run tool while the repository is offline. The command you must run is:

   java -jar oak-run.jar resetclusterid < repository path | Mongo URI >
   

   NOTE

   If a Segment node store is configured, then the repository path must be specified. By default, the path is <aem-install-folder>/crx-quickstart/repository/segmentstore. If a Document node store is configured you can use a Mongo Connection String URI.

   NOTE

   The Oak-run tool can be downloaded from this location:

   https://mvnrepository.com/artifact/org.apache.jackrabbit/oak-run/

   Different versions of the tool must be used depending on the Oak version you use with your AEM installation. Check the version requirements list below before using the tool:

   * For Oak versions **1.2.x** use the Oak-run **1.2.12 or newer**
   * For Oak versions **newer than the above**, use the version of Oak-run that matches the Oak core of your AEM installation.
   

4. Lastly, validate the configuration. To validate, look for a unique file added to the data store by each repository that is sharing it. The format of the files is repository-[UUID], where the UUID is a unique identifier of each individual repository.

   Therefore, a proper configuration should have as many unique files as there are repositories sharing the data store.

   The files are stored differently, depending on the data store:

   • For the FileDataStore the files are created under the root path of the data store folder.
   • For the S3DataStore the files are created in the configured S3 bucket under the META folder.

Azure Data Store

AEM can be configured to store data in Microsoft®’s Azure storage service. It uses the org.apache.jackrabbit.oak.plugins.blob.datastore.AzureDataStore.config PID for configuration.

To enable the Azure data store functionality, a feature pack containing the Azure Connector must be downloaded and installed. Go to the Adobe Repository and download the latest version from the 1.6.x versions of the feature pack (for example, com.adobe.granite.oak.azureblobconnector-1.6.3.zip).

java -jar <aem-jar-file>.jar -r crx3tar-nofds

Once downloaded, you can install and configure the Azure connector as follows:

1. Extract the contents of the feature pack zip file to a temporary folder.

2. Go to the temporary folder and copy the contents of jcr_root/libs/system/install to the <aem-install>crx-quickstart/install folder.

3. If AEM is already configured to work with the Tar or MongoDB storage, remove any existing configuration files from the /crx-quickstart/install folder before proceeding. The files that must be removed are:

   ForMongoMK:

   org.apache.jackrabbit.oak.plugins.document.DocumentNodeStoreService.config

   For TarMK:

   org.apache.jackrabbit.oak.segment.SegmentNodeStoreService.config

4. Return to the temporary location where the feature pack has been extracted and copy the contents of jcr_root/libs/system/config to the <aem-install>/crx-quickstart/install folder.

5. Edit the configuration file and add the configuration options required by your setup.

6. Start AEM.

You can use the configuration file with the following options:

• azureSas=“”: In version 1.6.3 of the connector, Azure Shared Access Signature (SAS) support was added. If both SAS and storage credentials exists in the configuration file, SAS has priority. For more information about SAS see the official documentation. Ensure that the ‘=’ character is escaped like ‘=’.

• azureBlobEndpoint=“”: The Azure Blob Endpoint. For example, https://<storage-account>.blob.core.windows.net.

• accessKey=“”: The storage account name. For more details about the Microsoft® Azure authentication credentials, see the official documentation.

• secretKey=“”: The storage access key. Ensure that the ‘=’ character is escaped like ‘=’.

• container=“”: The Microsoft® Azure blob storage container name. The container is a grouping of a set of blobs. For additional details, read the official documentation.

• maxConnections=“”: The concurrent number of simultaneous requests per operation. The default value is 1.

• maxErrorRetry=“”: Number of retries per request. The default value is 3.

• socketTimeout=“”: The timeout interval, in milliseconds, used for the request. The default value is 5 minutes.

Besides the settings above, the following settings can also be configured:

• path: The path of the data store. The default is <aem-install>/repository/datastore.
• RecordLength: The minimum size of an object that should be stored in the data store. The default is 16 KB.
• maxCachedBinarySize: Binaries with size less than or equal to this size are stored in memory cache. The size is in bytes. The default is 17408 (17 KB).
• cacheSize: The size of the cache. The value is specified in bytes. The default is 64 GB.
• secret: Only to be used if using binaryless replication for shared datastore setup.
• stagingSplitPercentage: The percentage of cache size configured to be used for staging asynchronous uploads. The default value is 10.
• uploadThreads: The number of uploads threads that are used for asynchronous uploads. The default value is 10.
• stagingPurgeInterval: The interval in seconds for purging finished uploads from the staging cache. The default value is 300 seconds (5 minutes).
• stagingRetryInterval: The retry interval in seconds for failed uploads. The default value is 600 seconds (10 minutes).

accessKey="ASDASDERFAERAER"
secretKey="28932hfjlkwdo8fufsdfas\=\="

Data store garbage collection

The data store garbage collection process is used to remove any unused files in the data store, thus freeing up valuable disk space in the process.

You can run data store garbage collection by:

1. Going to the JMX console at https://<serveraddress:port>/system/console/jmx

2. Searching for RepositoryManagement. Once you find the Repository Manager MBean, click it to bring up the available options.

3. Scroll to the end of the page, and click the startDataStoreGC(boolean markOnly) link.

4. In the following dialogue, enter false for the markOnly parameter, then click Invoke:

   

   NOTE

   The markOnly parameter signifies whether the sweep phase of garbage collection runs or not.

Data Store Garbage Collection for a Shared Data Store

With newer versions of AEM, data store garbage collection can also be run on data stores shared by more than one repository. To be able to run data store garbage collection on a shared data store, take the following steps:

1. Make sure that any maintenance tasks configured for the data store garbage collection are disabled on all repository instances sharing the data store.

2. Run the steps mentioned in Binary Garbage Collection individually on all repository instances sharing the data store. However, make sure to enter true for the markOnly parameter before clicking the Invoke button:

   

3. After completing the above procedure on all instances, run the data store garbage collect again from any of the instances:

   1. Go to the JMX console and select the Repository Manager Mbean.
   2. Click the Click startDataStoreGC(boolean markOnly) link.
   3. In the following dialogue, enter false for the markOnly parameter again.

   All the files found are collated using the mark phase used before and delete the rest that are unused from the data store.

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