QREP Exam Dumps - Qlik Certification Questions and Answers

Questions no:17Verified Answer: = A. IBM IMS & E. HP NonStopStep by Step Comprehensive and Detailed Explanation with all References: =ARC (Attunity Replicate Connect) CDC agents are used for capturing changes (CDC) and can be utilized with both relational and non-relational endpoints supported by ARC. The endpoints that have ARC CDC agents include:

IBM IMS (A): This is a database and transaction management system, and it is listed as one of the endpoints supported by ARC CDC agents1.

HP NonStop (E): This is a platform for high-availability servers and is also supported by ARC CDC agents1.

The other options provided do not align with the endpoints that have ARC CDC agents:

B. IBMDB2Z/OS: While DB2 for z/OS is a common database system, it is not mentioned in the context of ARC CDC agents.

C. Kafka Source: Kafka is a streaming platform, and while it can be an endpoint for data, it is not listed as having ARC CDC agents.

D. SAPHANA: SAP HANA is an in-memory database, and it is not specified as having ARC CDC agents.

Therefore, the verified answers areA. IBM IMSandE. HP NonStop, as they are the endpoints that utilize ARC CDC agents for capturing changes1.

If a task has missing metadata, you need to first stop the task.

Navigate to the "Advanced Run" options.

Select the option "Metadata Only."

Start the task with this setting to process the missing metadata.

Stop the task again after the metadata is added.

Resume normal task processing. This procedure ensures that only the metadata is processed without affecting the existing data on the target side. This method is recommended in Qlik Replicate documentation for handling missing metadata issues.

To add missing metadata in a Qlik Replicate task after the task has been stopped, the correct approach is to use the Advanced Run option for metadata only. Here’s the process:

Select the task that requires metadata to be added.

Go to theAdvanced Runoptions for the task.

Choose theMetadata Onlyoption, which has two sub-options:

Recreate all tables and then stop: This will rebuild metadata for all available tables in the task.

Create missing tables and then stop: This will rebuild metadata only for the missing tables or the tables that were newly added to the task1.

By selecting theMetadata Onlyoption and choosing to create missing tables, you can ensure that the metadata for the newly added tables is updated without affecting the existing tables and data. After this operation, you can stop the task again and then resume processing.

The other options provided are not the recommended methods for adding missing metadata:

AandDsuggest dropping tables or data, which is not necessary for simply adding metadata.

Bsuggests reloading the target, which is not the same as updating metadata only.

Therefore, the verified answer isC, as it accurately describes the process of adding missing metadata to a Qlik Replicate task using the Advanced Run options1.

When merging databases, especially of such large sizes (12 TB and 15 TB), it is crucial to ensure data integrity and consistency. The recommended approach is to:

Stop the Replication Task: This is important to prevent any changes from being replicated to the target while the IBM load process is ongoing.

Perform the IBM Load: Execute the IBM load to merge the database into the existing database.

Resume the Replication Task: Once the IBM load has been successfully completed, the replication task can be resumed.

This approach ensures that the data loaded via IBM load is not missed or duplicated in the target database. It also allows Qlik Replicate to continue capturing changes from the point where the task was stopped, thus maintaining the continuity of the replication process.

It’s important to note that creating a new task after the IBM load (Option D) could lead to complexities in managing the data consistency and might require additional configuration. Continuing to run the task (Option C) could result in conflicts or data integrity issues during the load process. Therefore, Option B is the safest and most reliable approach to ensure a smooth merge of the databases.

For further details and best practices, you can refer to the official Qlik Replicate documentation and support articles which provide guidance on similar scenarios1234.

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 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.

For stream endpoint types like Kafka or Azure Event Hubs in Qlik Replicate, there are specific limitations that apply to the replication options and target table preparation options:

D. The Store Changes replication option is not supported: This limitation is explicitly mentioned for Kafka1and Azure Event Hubs23. The Store Changes mode is not supported when using these stream endpoints, meaning that changes cannot be stored for later retrieval or reporting.

E. The DROP and CREATE table target table preparation option is not supported: This is also a known limitation for Kafka as a target endpoint1. The Drop and Create table Target Table Preparation option is not supported, which affects how tables are prepared on the target side during replication.

The other options are not correct because:

A. The Apply Changes replication option is not supported: This is not listed as a limitation for Kafka or Azure Event Hubs.

B. The Full Load replication option is not supported: Full Load is supported for Kafka1.

C. Associated tasks filling those endpoint types cannot be stopped: This is not mentioned as a limitation, and tasks can typically be stopped unless otherwise specified.

For more detailed information on the limitations of using Kafka or Azure Event Hubs as target endpoints in Qlik Replicate, you can refer to the official Qlik documentation123.

When performing a Full Load to a target endpoint in Qlik Replicate, the task logging components that are associated with this process areTARGET_LOADandSOURCE_UNLOAD.

TARGET_LOAD: This component is responsible for loading the data into the target endpoint.It represents the process where Qlik Replicate reads all columns/rows from the Source database and creates the exact same copy on the Target database1.

SOURCE_UNLOAD: This component is involved in unloading the data from the source endpoint.It is part of the Full Load process where the data is read from the source and prepared for transfer to the target2.

The other options provided are not directly associated with the Full Load process to a target endpoint:

TARGET_APPLYis related to the Change Data Capture (CDC) phase where changes from the source are applied to the target2.

FILE_TRANSFERis not a term directly associated with Qlik Replicate’s logging components.

STREAMrefers to the Log Stream tasks, which is a different type of task configuration used for saving data changes from the transaction log of a single source database and applying them to multiple targets2.

For a comprehensive understanding of the task types and options in Qlik Replicate, you can refer to the official Qlik community articles onQlik Replicate Task Configuration OptionsandAn Introduction to Qlik Replicate Tasks: Full Load vs CDC.