QREP Qlik Replicate Certification Exam Questions and Answers

When handling data errors in Qlik Replicate, especially when data might be truncated, maintaining full table integrity is crucial. The best approach to handle this situation is to log the record to the exceptions table. Here’s why:

Log record to the exceptions table (D): This option allows the task to continue processing while ensuring that any records that could not be applied due to errors, such as truncation, are captured for review and resolution.The exceptions table serves as a repository for such records, allowing administrators to address the issues without losing the integrity of the full dataset1.

Stop Task (A): While stopping the task will prevent further data processing, it does not provide a mechanism to handle the specific records that caused the error.

Suspend Table (B): Suspending the table will halt processing for that specific table, but again, it does not address the individual records that may be causing truncation issues.

Ignore Record ©: Ignoring the record would mean that the truncated data is not processed, potentially leading to data loss and compromising table integrity.

Therefore, the verified answer isD. Log record to the exceptions table, as it allows for the identification and resolution of specific data errors while preserving the integrity of the overall table data12.

According to the Qlik Replicate documentation, the minimum level of permissions required for a user to delete tasks is the Designer role. The predefined roles in Qlik Replicate come with different sets of permissions. The Admin and Designer roles have the permission to delete tasks, while the Operator and Viewer roles do not1.

Here’s a breakdown of the permissions for each role related to task management:

Admin: Can create, design, and delete tasks.

Designer: Can create, design, and delete tasks.

Operator: Can perform runtime operations like start, stop, or reload targets but cannot delete tasks.

Viewer: Can view task history and other details but cannot perform task management operations like deleting tasks.

The default port for Qlik Replicate Server on Linux is3552. This port is used for outbound and inbound communication unless it is overridden during the installation or configuration process. Here’s a reference to the documentation that confirms this information:

The official Qlik Replicate documentation states that “Port 3552 (the default rest port) needs to be opened for outbound and inbound communication, unless you override it as described below.” This indicates that 3552 is the default port that needs to be considered during the installation and setup of Qlik Replicate on a Linux system1.

The other options provided do not correspond to the default port for Qlik Replicate Server on Linux:

A. 3550: This is not listed as the default port in the documentation.

B. 443: This is commonly the default port for HTTPS traffic, but not for Qlik Replicate Server.

C. 80: This is commonly the default port for HTTP traffic, but not for Qlik Replicate Server.

Therefore, the verified answer isD. 3552, as it is the port designated for Qlik Replicate Server on Linux according to the official documentation1.

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.

In Qlik Replicate, notifications can be set up for various events related to tasks, endpoints, and the server itself. The types of notifications that can be configured include:

Task Events: Notifications for task-based events, such as when a task starts or stops, when latency is too high, or when specific errors occur1.

Endpoint Events: While the search results did not explicitly mention “Endpoint Events,” it is common in replication tools to have notifications related to endpoints, such as connectivity issues or endpoint-specific errors.

Server Events: Notifications related to the server, which could include system state changes, performance issues, or server-level errors2.

Therefore, the correct answer isC. Server Events, Endpoint Events, and Task Events, as Qlik Replicate allows setting up notifications for all these types of events. This ensures that administrators are alerted to a wide range of potential issues, allowing for prompt response and resolution.

For detailed instructions on how to set up each type of notification in Qlik Replicate, you can refer to the official Qlik documentation, which provides step-by-step guidance on defining and managing notifications for task events, server events, and other significant occurrences within the replication environment132.

For replicating columns that contain large PDFs, the appropriate data type to use in Qlik Replicate is:

D. BLOB: This stands for Binary Large Object and is the data type used for storing large binary data such as PDF files.The BLOB data type is suitable for handling the size and binary nature of PDF files1.

The other options are not suitable for the following reasons:

A. DLOB: This is not a recognized data type in Qlik Replicate.

B. NCLOB: NCLOB, or National Character Large Object, is used for storing large text data in the national character set and is not optimal for binary data like PDFs.

C. NVARCHAR(1000): NVARCHAR is a character data type with a specified length, which would not be suitable for large binary objects like PDFs due to size limitations and the nature of the data.

For more information on data types and their usage in Qlik Replicate, you can refer to the official Qlik Replicate documentation onReplicate data types.

Qlik Replicate offers several methods for parallel load during a full load process to accelerate the replication of large tables by splitting the table into segments and loading these segments in parallel. The three primary ways Qlik Replicate allows parallel loading are:

Use Data Ranges:

This method involves defining segment boundaries based on data ranges within the columns. You can select segment columns and then specify the data ranges to define how the table should be segmented and loaded in parallel.

Use Partitions - Use all partitions - Use main/sub-partitions:

For tables that are already partitioned, you can choose to load all partitions or use main/sub-partitions to parallelize the data load process. This method ensures that the load is divided based on the existing partitions in the source database.

Use Partitions - Specify partitions/sub-partitions:

This method allows you to specify exactly which partitions or sub-partitions to use for the parallel load. This provides greater control over how the data is segmented and loaded, allowing for optimization based on the specific partitioning scheme of the source table.

These methods are designed to enhance the performance and efficiency of the full load process by leveraging the structure of the source data to enable parallel processing

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.

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 Replicate, when handling data errors, there are specific actions that can be configured to manage such errors. Based on the documentation, the available options for handling data errors include:

C. Log record to a specific table: This option allows for the logging of error records to a designated table for further analysis and troubleshooting1.

E. Log record to the exceptions table: This is the default action for data errors in Qlik Replicate, where the error record is written to the exceptions table, allowing the task to continue while preserving information about the error1.

The other options listed are not directly related to the actions available for data errors in Qlik Replicate:

A. Reload task and Reload table: These actions are more related to resolving issues at the task or table level, rather than handling individual data errors.

B. Update missing target error on target side: This option does not correspond to a standard data error handling action in Qlik Replicate.

D. Suspend table: While suspending a table is an action that can be taken in response to data errors, it is typically used to halt replication for the affected table until the issue is resolved1.

For a detailed understanding of data error handling in Qlik Replicate, you can refer to the official Qlik Replicate Help documentation, which outlines the various error handling strategies and configurations that can be applied to tasks1.

Theattrep_apply_exceptionstable in Qlik Replicate is used for troubleshooting specific issues that occur during the data replication process. Based on the documentation and community discussions, the two situations where this table can be particularly useful are:

Apply conflicts (B): This table records errors related to conflicts that occur when applying changes to the target system.For instance, if there is a primary key violation or a constraint failure, the details of the conflict are logged in this table1.

Data errors (E): The table also captures errors related to the data itself, such as missing data or data type mismatches.If a record cannot be applied due to data-related issues, the error message and the statement that caused the error are stored in theattrep_apply_exceptionstable2.

Theattrep_apply_exceptionstable is not typically used forabnormal termination (A),table errors ©, orenvironment errors (D)as these issues are generally logged elsewhere within the system or require different troubleshooting approaches. For example, abnormalterminations might be logged in system event logs, while environment errors could be related to infrastructure issues outside the scope of Qlik Replicate’s control tables.

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

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

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.

To change the Data Directory location on Windows for Qlik Replicate, the administrator needs to follow these steps after stopping the Qlik Replicate services:

E. Move the data directory to a new location: The first step is to physically move the data directory to the new desired location on the file system1.

A. Update the Windows Registry: After moving the data directory, the next step is to update the Windows Registry to reflect the new location of the data directory.This involves modifying theImagePathstring within theHKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\servicesfor both the Qlik Replicate UI Server and Qlik Replicate Server services1.

F. Start the Attunity Replicate services: Once the data directory has been moved and the Windows Registry has been updated, the final step is to start the Qlik Replicate services again.This will allow Qlik Replicate to operate using the new data directory location1.

The other options are not part of the recommended steps for changing the Data Directory location:

B. Uninstall Qlik Replicate and reinstall: This is not necessary just for changing the data directory location.

C. Copy the data directory to a shared drive and keep all tasks running: It is not recommended to use a shared drive for the data directory, and tasks cannot run during this process since the services need to be stopped.

D. Stop the Attunity Replicate Ul Server and Attunity Replicate Server services: This is a prerequisite step that should have already been completed before proceeding with the data directory change.

For a complete guide on changing the Data Directory location on Windows, the official Qlik documentation provides detailed instructions and considerations1.

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 the “Apply batched changes to multiple tables concurrently” option is enabled in a Qlik Replicate task, theattrep_apply_exceptioncontrol table stores specific information related to change processing errors. The details stored in this table include:

TASK_NAME: The name of the Qlik Replicate task.

TABLE_NAME: The name of the table.

ERROR_TIME (in UTC): The time the exception (error) occurred.

STATEMENT: The statement that was being executed when the error occurred.

ERROR: The actual error message1.

This information is crucial for troubleshooting and resolving issues that may arise during the replication process.The data in theattrep_apply_exceptiontable is never deleted, ensuring a persistent record of all exceptions1.

The other options do not accurately reflect the information stored in theattrep_apply_exceptioncontrol table:

AandBmention “Warning_Time,” which is not a column in the table.

Dis incorrect because the table does store information about errors.

For more detailed information on theattrep_apply_exceptioncontrol table and its role in handling change processing errors, you can refer to the official Qlik Replicate documentation1.