In Qlik Replicate, tasks can be exported and imported for various purposes such as remote backup, migration, troubleshooting, and configuration updates. The format used for these operations is the JSON file format. Here’s how the process works:

To export tasks, you can use therepctl exportrepositorycommand, which generates a JSON file containing all task definitions and endpoint information (except passwords)1.

The generated JSON file can then be imported to a new server or instance of Qlik Replicate using therepctl importrepositorycommand, allowing for easy migration or restoration of tasks2.

This JSON file contains everything required to reconstruct the data replication project, making it an essential tool for administrators managing Qlik Replicate tasks3.

Therefore, the correct answer isD. Task JSON files, as they are the files that can be exported and imported in Qlik Replicate for the mentioned purposes123.

To identify the internal commands that Qlik Replicate is executing prior to an error, theTracelogging level should be used.This level provides detailed information about the operations being performed by Qlik Replicate, including the internal commands executed before an error occurs1.

Here’s how the Trace logging level works in Qlik Replicate:

When logging is set toTrace, the log lines are identified with]T:.This indicates that the log will include detailed trace information about the internal workings of Qlik Replicate, such as sending control records to components or waiting for termination of threads1.

The Trace level is more detailed than Warnings (]W:) and Errors (]E:), which only show warning and error messages without the detailed context of the operations leading up to them1.

The Trace level is also distinct from Verbose (]V:), which provides even more detailed logging information but may not be necessary for identifying the commands leading up to an error1.

Therefore, the correct answer isC. Trace, as it is the appropriate logging level to use when you need to analyze the actions performed by Qlik Replicate just before an error occurs1.

When configuring Oracle as a source endpoint for Qlik Replicate, there are several key prerequisites that need to be met:

Enable supplemental logging (A): Supplemental logging is crucial for capturing the changes in the Oracle database accurately, especially for Change Data Capture (CDC) operations.It ensures that all necessary column data is logged for replication purposes1.

Install the Oracle Instant Client (B): The Oracle Instant Client provides the necessary libraries for Qlik Replicate to connect to and interact with the Oracle database.It’s required for the proper functioning of Qlik Replicate2.

Enable ARCHIVELOG mode (D): ARCHIVELOG mode is necessary for the Oracle database to archive redo logs, which Qlik Replicate uses to capture changes.This mode allows the database to continue functioning and preserve the logs even after a log switch, which is essential for CDC1.

The other options provided are not listed as key prerequisites for configuring Oracle as a source endpoint in Qlik Replicate:

C. Complete a full backup of the source: While it’s a good practice to have a backup, it’s not a prerequisite for configuring the source endpoint.

E. Provide Oracle read-only privileges: Read-only privileges might be necessary for certain operations, but they are not listed as a key prerequisite.

F. Configure Oracle Recovery Model: This is not mentioned as a prerequisite in the Qlik Replicate documentation.

Therefore, the verified answers areA,B, andD, as they represent the necessary steps to configure Oracle as a source endpoint in Qlik Replicate12.

For Qlik Replicate’s Change Data Capture (CDC) process, the valid source endpoint types include:

A. Classic Relational RDBMS: These are traditional relational database management systems that support CDC.Qlik Replicate can capture changes from these systems using log-based CDC tools which are integrated to work with most ETL tools1.

C. SAP ECC and Extractors: SAP ECC (ERP Central Component) and its extractors are also supported as source endpoints for CDC in Qlik Replicate.This allows for the replication of data changes from SAP’s complex data structures1.

The other options provided are not typically associated with CDC in Qlik Replicate:

B. MS Dynamics direct access: While Qlik Replicate can connect to various data sources, MS Dynamics is not commonly listed as a direct source for CDC.

D. Generic REST APIs Data Lake file formats: REST APIs and Data Lake file formats are not standard sources for CDC as they do not maintain transaction logs, which are essential for CDC to track changes.

For detailed information on setting up source endpoints and enabling CDC, you can refer to the official Qlik documentation and community articles that discuss the prerequisites and configurations needed for various source endpoints2345.

To batch-load a source automatically on a daily basis in Qlik Replicate, you would typically use a server scheduler. Here’s how it can be done:

Set trigger through server scheduler (A): You can configure a scheduler on the server where Qlik Replicate is running to trigger the batch load process at a specified time each day.This could be done using the operating system’s built-in task scheduler, such as Windows Task Scheduler or cron jobs on Linux systems1.

The scheduler would execute a command or script that starts the Qlik Replicate task configured for batch loading.The command would utilize Qlik Replicate’s command-line interface or API to initiate the task1.

This approach allows for precise control over the timing of the batch load and can be adjusted to meet the specific scheduling requirements of the data replication process1.

The other options provided are not typically used for setting up an automatic daily batch load:

B. Set trigger through Advanced Run options: While Advanced Run options provide various ways to run tasks, they do not include a scheduling function for daily automation.

C. Set trigger through Task Designer: Task Designer is used for designing and configuring tasks, not for scheduling them.

D. Enable task on full load and apply changes: This option would start the task immediately and is not related to scheduling the task on a daily basis.

Therefore, the verified answer isA. Set trigger through server scheduler, as it is the method that allows for the automation of batch loading on a daily schedule1.

The Apply Exceptions data in Qlik Replicate is retained indefinitely by default. This means thatthe data related to apply exceptions, which includes error records and other relevant information, is not automatically purged after a certain period.

The retention of Apply Exceptions data is crucial for ongoing monitoring and troubleshooting of replication tasks. It allows administrators to review and address any issues that have occurred over the life of the task.

According to the Qlik Replicate documentation, theattrep_apply_exceptionstable, which records processing errors, does not have an automated deletion process.This table includes columns for the task name, table owner, table name, error time (in UTC), statement being executed when the error occurred, and the actual error message1.

This indefinite retention policy ensures that administrators have a complete historical record of all exceptions that have occurred, which can be invaluable for diagnosing and resolving issues with replication tasks. However, it’s important for administrators to manage the size of this table manually to prevent it from growing too large, which could potentially impact system performance.

To run daily reports about the changes that have occurred within the past 24 hours using Qlik Replicate, the option that must be set isStore Changes. This feature enables Qlik Replicate to keep a record of the changes that have occurred over a specified period, which in this case is the past 24 hours.

B. Store Changes: This setting allows Qlik Replicate to capture and store the changes made to the data in the source system.These stored changes can then be used to generate reports that reflect the data modifications within the desired timeframe1.

The other options are not specifically designed for the purpose of running daily change reports:

A. Apply Changes: This option is related to applying the captured changes to the target system, which is a different stage of the replication process.

C. Stage Changes: Staging changes involves temporarily storing the changes before they are applied to the target, which is not the same as storing changes for reporting purposes.

D. Full Load: The Full Load option is used to replicate the entire dataset from the source to the target, which is not necessary for generating reports based on changes within a specific timeframe.

For more information on how to configure the Store Changes option and generate reports based on the stored changes, you can refer to the official Qlik documentation and community discussions that provide insights into best practices for setting up replication tasks and managing change data2.