Qlik QREP - Qlik Replicate Certification Exam

To export a task using REPCTL in Qlik Replicate, the correct command isrepctlexportrepository task=task_name. Here’s how you would use it for the task named Oracle_2_SS_Target1:

Open the command-line console on the machine where Qlik Replicate is installed.

Use the REPCTL utility with theexportrepositorycommand followed by thetaskparameter and the name of the task you want to export.

The correct syntax for the command is:

repctl exportrepository task=Oracle_2_SS_Target1

This command will create a JSON file containing the exported task settings1.

The other options provided have either incorrect syntax or misspellings:

Ahas a typo in the command (repct1instead ofrepctl).

Buses an incorrect command (export_taskis not a valid REPCTL command).

Dhas a typo in the task name (0racle_2_SS_Target1instead ofOracle_2_SS_Target1) and an incorrect command (exporttaskis not a valid REPCTL command).

Therefore, the verified answer isC, as it correctly specifies the REPCTL command to export the task named Oracle_2_SS_Target11.

Qlik Enterprise Manager provides a centralized command center to configure, execute, and monitor data replication and transformation tasks across the enterprise. It is specifically designed to manage and control Qlik Replicate and Qlik Compose tasks.Additionally, it integrates with Qlik Catalog to automatically catalog data assets generated by Qlik Replicate directly in Qlik Catalog1.This integration allows for tracking end-to-end data lineage, which improves compliance, governance, and trust in the data assets managed within Qlik Catalog1.

The documentation clearly states that Qlik Enterprise Manager is used to design, execute, and monitor Qlik Replicate and Qlik Compose tasks, and it also mentions the integration with QlikCatalog for data asset management2. However, there is no mention of Qlik Sense being controlled by Qlik Enterprise Manager.Qlik Sense is a separate product for data visualization and analytics, and its management is not within the scope of Qlik Enterprise Manager’s functionalities as described in the available resources12.

Therefore, the correct answer isC. Qlik Replicate, Qlik Compose, Qlik Catalog, as these are the components that can be controlled with Qlik Enterprise Manager.

To address the issue of column names in a source endpoint being too long for the target endpoint’s character limit, the Qlik Replicate administrator should:

D. Define a new Global Transformation rule of the Column type: This allows the administrator to create a rule that applies to all affected columns across all tables.By defining a global transformation rule, the administrator can systematically rename all columns that exceed the character limit1.

The process involves:

Going to the Global Transformations section in Qlik Replicate.

Selecting the option to create a new transformation rule of the Column type.

Using the transformation rule to specify the criteria for renaming the columns (e.g., replacing a prefix or suffix or using a pattern).

Applying the rule to ensure that all affected columns are renamed according to the defined criteria.

The other options are not as efficient or appropriate for solving the issue:

A. Open the Windows command line terminal and run the renamecolumn command: This is not a standard method for renaming columns in Qlik Replicate and could lead to errors if not executed correctly.

B. Visit the Table Settings for each table in a task and select the Transform tab: While this could work, it is not as efficient as defining a global transformation rule, especially if there are many tables and columns to update.

C. Visit the Table Settings for each table and select the Filter tab: The Filter tab is used for record selection conditions and not for renaming columns.

For more detailed instructions on how to define and apply global transformation rules in Qlik Replicate, you can refer to the official Qlik documentation onGlobal Transformations.

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.

Questions no:16Verified Answer: = C. Create a task streaming to a streaming target endpoint (e.g., Kafka) and consume that endpoint in the following tasks as a source endpoint

Step by Step Comprehensive and Detailed Explanation with all References: =To deliver data from a source endpoint with minimal impact and distribute it to several target endpoints in Qlik Replicate, the best approach is:

C. Create a task streaming to a streaming target endpoint (e.g., Kafka) and consume that endpoint in the following tasks as a source endpoint: This method allows for efficient data distribution with minimal impact on the source system.By streaming data to a platform like Kafka, which is designed for high-throughput, scalable, and fault-tolerant storage, Qlik Replicate can then use this data stream as a source for multiple downstream tasks12.

The other options are less optimal because:

A. Create a LogStream task followed by multiple tasks using an endpoint that reads changes from the log stream staging folder: While this option involves a LogStream, it does not specify streaming to a target endpoint that can be consumed by multiple tasks, which is essential for minimal impact distribution.

B. Create a task streaming to a dedicated buffer database (e.g., Oracle or MySQL) and consume that database in the following tasks as a source endpoint: This option introduces additional complexity and potential performance overhead by using a buffer database.

D. Create multiple tasks using the same source endpoint: This could lead to increased load and impact on the source endpoint, which is contrary to the requirement of minimal impact.

For more detailed information on how to set up streaming tasks to target endpoints like Kafka and how to configure subsequent tasks to consume from these streaming endpoints, you can refer to the official Qlik documentation onAdding and managing target endpoints.

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.

The Qlik Replicate diagnostic package is designed to assist in troubleshooting task-related issues. When you generate a task-specific diagnostics package, it includes the task log files and various debugging data. The contents of the diagnostics package are crucial for the Qlik Support team to review and diagnose any problems that may arise during replication tasks.

According to the official Qlik documentation, the diagnostics package contains:

Task log files

Various debugging data

While the documentation does not explicitly list “Statistics, Task Status, and Metadata” as part of the diagnostics package, these elements are typically included in the debugging data necessary for comprehensive troubleshooting.Therefore, the closest match to the documented contents of the diagnostics package would be option C, which includes Logs, Statistics, Task Status, and Metadata123.

It’s important to note that the specific contents of the diagnostics package may vary slightly based on the version of Qlik Replicate and the nature of the task being diagnosed. However, the provided answer is based on the most recent and relevant documentation available.

When using LogStream staging for replication in Qlik Replicate, the Staging folder is compressed and stored on the Qlik Replicate server itself. Here’s the process:

A Log Stream Staging task is defined to replicate changes from the source endpoint to the Log Stream Staging folder1.

This task creates a “Staging” file in the Log Stream Staging folder, which contains the changes from the source database transaction log as a compressed binary file1.

The storage path for the streamed data, which includes the Staging folder, must be specified in the Log Stream target endpoint settings, and it is explicitly stated that this path should be located on the Replicate Server machine2.

Therefore, the correct answer isD. On the Qlik Replicate server, as the staging folder is located on the machine where Qlik Replicate server is running, and it is where the compressed staging files are stored12.