Qlik QREP - Qlik Replicate Certification Exam

When a new column is added to one of the tables in a Qlik Replicate task, the administrator should stop and then resume the task to replicate this change. This process allows Qlik Replicate to recognize the structural change and apply it accordingly.

The steps involved in this process are:

Stop the task: This ensures that no data changes are missed during the schema change.

Resume the task: Once the task is resumed, Qlik Replicate will pick up the DDL change and apply the new column to the target system.

This procedure is supported by the Qlik Replicate’s DDL handling policy, which can be set to perform an “alter target table” when the source table is altered.This means that when the task is resumed, the new columns from the source tables will be added to the Replicate target1.

It’s important to note that while stopping and resuming the task is generally the recommended approach, the exact steps may vary depending on the specific configuration and version of Qlik Replicate being used. Therefore, it’s always best to consult the latest official documentation or support resources to ensure the correct procedure for your environment.

To run a Qlik Replicate Task at a high-performance level, the main hardware components that are recommended include:

Cores: A higher number of cores is beneficial for handling many tasks running in parallel and for prioritizing full-load performance1.

SSD (Solid State Drive): SSDs are recommended for optimal performance, especially when using a file-based target or dealing with long-running source transactions that may not fit into memory1.

Network bandwidth: Adequate network bandwidth is crucial to handle the data transfer requirements, with 1 Gbps for basic systems and 10 Gbps for larger systems being recommended1.

The other options do not encompass all the recommended hardware components for high-performance levels in Qlik Replicate tasks:

A. SSD, RAM: While these are important, they do not include the network bandwidth component.

B. Cores, RAM: This option omits the SSD, which is important for disk performance.

D. RAM, Network bandwidth: This option leaves out the cores, which are essential for processing power.

For detailed hardware recommendations for different scales of Qlik Replicate systems, you can refer to the official Qlik documentation onRecommended Hardware Configuration.

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.

ï‚·In Change Data Capture (CDC) mode, Batch optimized apply mode can be set based on time and/or volume.

ï‚·This means that the batching of transactions can be controlled by specifying time intervals or the volume of data changes to be batched together.

ï‚·This optimization helps improve performance by reducing the frequency of writes to the target system and handling large volumes of changes efficiently. The Qlik Replicate documentation outlines this option as a method to enhance the efficiency of data replication in CDC mode by batching transactions based on specific criteria.

In the Change Data Capture (CDC) mode of a Qlik Replicate task, when using the Batch optimized apply mode, the system allows for tuning based on time and/or volume. This setting is designed to optimize the application of changes in batches to the target system. Here’s how it works:

Time: You can set intervals at which batched changes are applied.This includes setting a minimum amount of time to wait between each application of batch changes, as well as a maximum time to wait before declaring a timeout1.

Volume: The system can be configured to force apply a batch when the processing memory exceeds a certain threshold.This allows for the consolidation of operations on the same row, reducing the number of operations on the target to a single transaction2.

The other options provided do not align with the settings for Batch optimized apply mode in CDC tasks:

A. Source connection processes: This is not a setting related to the batch apply mode.

B. Number of changed records: While the number of changed records might affect the batch size, it is not a setting that can be directly configured in this context.

D. Maximum time to batch transactions: This option is related to the time aspect but does not fully capture the essence of the setting, which includes both time and volume considerations.

Therefore, the verified answer isC. Time and/or volume, as it accurately represents the options that can be set for Batch optimized apply mode in the CDC tasks of Qlik Replicate21.

In a scenario where an operative database can commit only two engines to Qlik Replicate for initial loads, the task settings should be modified to ensure that no more than two tables are loaded at any given time. This can be achieved by:

C. Apply Full Load Settings to limit the number of engines to two: This setting allows you to specify the maximum number of concurrent table loads during the Full Load operation.By limiting this number to two, you ensure that the operative database’s capacity is not exceeded1.

The other options are not suitable because:

A. Apply Change Processing Tuning: This option is related to the CDC (Change Data Capture) phase and not the initial Full Load phase. Increasing the apply batched changes interval would not limit the number of engines used during the Full Load.

B. Qlik Replicate tasks only load one table at a time by default: This statement is not accurate as Qlik Replicate can be configured to load multiple tables concurrently, depending on the task settings.

D. Apply Full Load Tuning to read a maximum number of tables not greater than two: While this option seems similar to the correct answer, it is not a recognized setting in Qlik Replicate’s configuration options.

For detailed guidance on configuring task settings in Qlik Replicate, particularly for managing the number of concurrent loads, you can refer to the official Qlik community articles onQlik Replicate Task Configuration Options.

After a Qlik Replicate administrator creates a new task, runs a Full Load test, and turns on Change Processing, the method to test this task would be to:

Stop the task: This ensures that no active processes are running that could interfere with the testing.

Run -> Advanced Run Options: This step allows the administrator to access more specific settings that can control how the task is executed.

Start Change Processing Only: This option will start the Change Data Capture (CDC) phase without re-running the Full Load. It’s used to test the CDC mechanism specifically, ensuring that changes made at the source are captured and applied to the target correctly.

This method is supported by best practices in the Qlik community and documentation, which suggest using the Advanced Run Options to control the task’s behavior for testing purposes1. It allows the administrator to verify that the Change Processing is set up correctly and is functioning as expected without the need to reload the target or recreate the task entirely. This approach is efficient and effective for testing the CDC functionality in isolation.

In Qlik Enterprise Manager, permissions can be managed in a granular way, and one of the key features is the ability to inherit permissions. Here’s how it works:

Inherited permissions for all functions ©: By default, inheritance is enabled for all objects, including users and groups.This means that permissions are automatically carried over from the parent object, ensuring consistency and ease of management across different levels of the organizational structure1.

Using the same permissions as in Qlik Replicate (A)andUsing the same permissions as in Qlik Replicate and Qlik Compose (D): While Qlik Enterprise Manager may integrate with Qlik Replicate and Qlik Compose, the permissions are not directly transferred or used in the same way. Each tool has its own set of permissions and roles that need to be configured separately.

Transfer rights from Qlik Replicate (B): There is no direct option to transfer rights from Qlik Replicate to Qlik Enterprise Manager. Permissions need to be set within the Enterprise Manager itself, although it may be guided by the roles and permissions defined in Qlik Replicate.

Therefore, the verified answer isC. Inherited permissions for all functions, as it reflects the capability of Qlik Enterprise Manager to set permissions based on inheritance, which simplifies the management of user permissions across the system1.

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.

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.