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Batch processing
Process accumulated requests from EngageOne Interactive, or process your own multiple or individual files, in a scheduled, or ad hoc manner.
NA batch setup and performance optimization
Scaling and performance recommendations

EngageOne Server overview
EngageOne Administration is used to configure and manage operating modes and user roles.
Getting started
Information on creating and configuring communities, running the EngageOne Server Admin and common features available in the web application.
Template management
Template management allows you to create and organize folders that contain templates and Active Content, created in Designer and imported into EngageOne.
External File management
External resources not contained in the template, succh as images (key maps or keyed images), lookup tables, and RTF files.
Delivery management
Before you can use a template in EngageOne Administration you must define a device for viewing and define at least one delivery option.
Community Administration
Features for managing shared community document classes, retention policies, spelling dictionaries, data maps, and diagnostics.
System administration
As an EngageOne Server system administrator you will be responsible for configuration, diagnostics and account activities.
Event Monitor
Events related to the document cycle and administration, these are captured throughout the system and sent to the Event Monitor.
Batch processing
Process accumulated requests from EngageOne Interactive, or process your own multiple or individual files, in a scheduled, or ad hoc manner.
- Accumulated batch
  The process of submitting documents for batch delivery in EngageOne Interactive is referred to as accumulated batch.
- Non-accumulated batch
  In NA batch, which is a traditional batch process, the batch process accepts one or more input files containing document data sets, as well as optional processing instructions.
- NA batch setup and performance optimization
- Purging using batch
  Running purge is an important maintenance activity to prevent gradual performance degradation due to the build-up of data in the database tables. Make sure you implement a purge routine as part of your EngageOne Server maintenance plan.
- Log file location
- Logging information (accumulated and non-accumulated batch)
- Modifying log file count
- Batch error handling
  Error handling for accumulated and non-accumulated batch have some differences.
- Batch threshold settings
  The threshold level is the limit where a running batch will terminate, if the number of processed documents that have errors has been reached.
- Setting up the batch programs on a separate machine
- Running batch with integrated security database connections
Managing your EngageOne environment
Best practices for managing your EngageOne and safeguarding your environment.
EngageOne Server system monitoring
This section describes how to monitor the EngageOne Server system.
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Scaling and performance recommendations

Non-accumulated batch can be configured to maintain the number of threads for scaling and performance tuning of the system. Shown below are the configuration settings in the configuration framework used for tuning performance in batch. These can be modified in config-settings.xml.

Namespace: com.pb.engageone.server.batch.na


Config setting	Description
batch.dca.pool.size.maximum Default value: ${com.pb.dca[pool.size.maximum]}	The number of DCA adapters to use during pre-composition
worker.queue.size Default value: 1000	The maximum number of XML records (not files) that are held in memory at any given time during processing
workerThread.pool.size Default value: 2	The number of active running threads in processing record for partial composition
recomposition.workerThread.pool.size Default value: 2	The number of active running threads in processing record for re-composition/concatenation process
documentInfo.list.page.size Default value: 500	The page cache size for internal DocumentInfo List
sort.db.connection.pool.size Default value: 20	The number of pooled connections to the sort repository database.

These values can be increased depending on the machine's capability (memory and CPU). Increasing both DCA pool size and the batch thread size can increase the rate at which records are processed but should be adjusted with caution, taking CPU capacity into account.

Increasing worker.queue.size increases the number of documents that can be queued up for the partial composition and variable resolution process, but should be limited depending on the memory availability or the specified heap size in the JVM (as discussed in the Java Tuning White Paper link).

Increasing documentInfo.list.page.size increases the number of documents that can be queued up for the concatenation and the report/index generation process but should be limited depending on the memory availability, or the specified heap size in the JVM.