Qlik QREP Qlik Replicate Certification Exam Exam Practice Test

When encountering table errors in Qlik Replicate, the escalation policy is set toStop Taskand cannot be changed. This means that if the number of table errors reaches a specified threshold, the task will automatically stop, requiring manual intervention to resolve the issue.

The escalation action for table errors is specifically designed to halt the task to prevent further errors or data inconsistencies from occurring.This is a safety measure to ensure that data integrity is maintained and that any issues are addressed before replication continues1.

The other options listed are not escalation actions for table errors:

A. Log Record to the Exceptions Table: While logging errors to the exceptions table is a common action, it is not an escalation action.

B. No Escalate Action: This is not a valid option as there is a specific escalation action defined for table errors.

C. Suspend Table: Suspending a table is a different action that can be taken in response to errors, but it is not the defined escalation action for table errors in Qlik Replicate.

For more information on error handling and escalation actions in Qlik Replicate, you can refer to the official Qlik Replicate Help documentation, which provides detailed guidance on configuring error handling policies and actions for various types of errors1.

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.

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

In Qlik Replicate, the options to read the log files are located in the following places:

In Diagnostic package (B): The diagnostic package in Qlik Replicate includes various log files that can be used for troubleshooting and analysis purposes1.

In Data directory of Installation (D): The log files are written to the log directory within the data directory.This is the primary location where Qlik Replicate writes its log files, and it is not possible to change this location2.

In Monitor of Qlik Replicate (E): The Monitor feature of Qlik Replicate allows users to view and manage log files.Users can access the Log Viewer from the Server Logging Levels or File Transfer Service Logging Level sub-tabs1.

The other options provided do not align with the locations where log files can be read in Qlik Replicate:

A. In Windows Event log: This is not a location where Qlik Replicate log files are stored.

C. In External monitoring tool: While external monitoring tools can be used to read log files, they are not a direct feature of Qlik Replicate for reading log files.

F. In Enterprise Manager: The Enterprise Manager is a separate component that may manage and monitor multiple Qlik Replicate instances, but it is not where log files are directly read.

Therefore, the verified answers areB,D, andE, as they represent the locations within Qlik Replicate where log files can be accessed and read21.

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 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.

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.

The ODBC drivers in Qlik Replicate are located in the\Replicate\bindirectory.This is supported by the documentation from Qlik, which indicates that when installing required clients such as the Microsoft ODBC Driver for SQL Server, the working directory should be changed to/bin1.Additionally, for other prerequisites involving driver locations, the instructions also refer to changing the working directory to/bin23. This consistent reference to the\bindirectory across different parts of the Qlik Replicate documentation verifies that the ODBC drivers are indeed located in the\Replicate\bindirectory.

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.

To run Analytics under Qlik Enterprise Manager, it is required to have aPostgreSQL Databaseinstalled. This is because the Analytics data for Qlik Enterprise Manager is stored in a PostgreSQL database.Before using the Analytics feature, you must ensure that PostgreSQL (version 12.16 or later) is installed either on the Enterprise Manager machine or on a machine that is accessible from Enterprise Manager1.

Here are the steps and prerequisites for setting up Analytics in Qlik Enterprise Manager:

Install PostgreSQL: The setup file for PostgreSQL is included with Enterprise Manager, and it must be installed to store the Analytics data1.

Create a dedicated database and user: A dedicated database and user in PostgreSQL should be created, which will own the tables accessed by the Enterprise Manager Analytics module1.

Configure connectivity: Connectivity to the PostgreSQL repository must be configured as described in the Repository connection settings1.

Data collection and purging: Configure data collection and purging settings as described in the Analytics - Data collection and purge settings1.

Register a license: A Replication Analytics license is required to use Analytics.If you have a license, you can register it by following the procedure described in Registering a license1.

The other options provided, such as Qlik Replicate (A), Qlik Compose (B), and both Qlik Compose and Replicate (D), are not components that must be installed to run Analytics under Enterprise Manager.The essential component is the PostgreSQL Database ©, which serves as the backend for storing the Analytics data1.

Therefore, the verified answer isC. PostgreSQL Database, as it is the required component to run Analytics under Qlik Enterprise Manager1.

When the connection to the source endpoint is unavailable for an extended period, and the log files are limited to only 2 hours of data before being deleted, the safest way to ensure a consistent state in the target endpoint is to use theReload Target Run option (A). This approach is recommended because it allows for a complete refresh of the target data, ensuring that it is in sync with the source once the connection is re-established.

TheReload Target Run optionis designed to handle situations where the replication logs are not sufficient to recover the replicated state due to extended outages or log retention policies. Byreloading the target, you can be confident that the data reflects the current state of the source, without relying on potentially incomplete change logs.

Starting processing from a fixed date and time (B) or recovering from a locally stored checkpoint © would not be reliable if the logs do not cover the entire period of the outage. Resuming the task and ignoring warnings (D) could lead to inconsistencies due to missed changes.

Therefore, theReload Target Run optionis the safest method to create a consistent state in the target endpoint under these circumstances1.

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.

When the error message “Cannot create the specific schema” appears during a Qlik Replicate task, it indicates that the task is unable to automatically create the required schema in the target RDBMS. The recommended method to resolve this issue is to:

Create the schema manually in the target ©: This involves accessing the target database and manually creating the schema that Qlik Replicate is attempting to use. This ensures that the necessary database objects are in place for the replication task to proceed.

Test the target endpoint connection (D): Although not the direct solution to the schema creation issue, it is a good practice to test the target endpoint connection to confirm that Qlik Replicate can connect to the target database. This can help rule out any connectivity issues that might be contributing to the problem.

The options to drop and recreate the task (A) or reload the target (B) are less likely to resolve the specific issue of schema creation, as they do not address the underlying problem of the missing schema in the target database.

It’s important to note that the manual creation of the schema should match the expected structure that Qlik Replicate is attempting to replicate to ensure compatibility and successful replication1.

Questions no:38Verified Answer: = B. AdminStep by Step Comprehensive and Detailed Explanation with all References: =In Qlik Replicate, different user roles are assigned specific permissions that dictate what tasks they can perform within the system. To import tasks into Qlik Replicate, a user must have theAdminrole. Here’s the breakdown of permissions for each role related to task management:

Admin: This role has the highest level of permissions, including the ability to import tasks.Users with the Admin role can perform all operations within Qlik Replicate, such as creating, designing, deleting, exporting, and importing tasks1.

Designer: Users with this role can create and design tasks but do not have permission to import tasks.

Operator: This role allows users to perform runtime operations like start, stop, or reload targets but does not include permissions to import tasks.

Viewer: Users with the Viewer role can view task history and other details but cannot perform task management operations like importing tasks.

Therefore, the correct answer isB. Admin, as only users with the Admin role are granted the permission to import tasks into Qlik Replicate1.

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.

In Qlik Replicate, when multiple schema rename rules are applied, the final schema name isdetermined by the last applied setting that affects the schema name directly. Here’s how the process works:

Global Transformationto rename schema to ‘USER1’: This rule will initially rename the schema from ‘HR’ to ‘USER1’.However, this is not the final schema name as further changes are applied later in the task settings1.

Task Settings -> Target Metadatato enter the Target table schema as ‘USER2’: This setting overrides the previous global transformation rule and sets the target schema name to ‘USER2’.This is because the Target Metadata settings are applied after the Global Transformations and directly affect the target schema name1.

Global Transformationto add a new column named ‘SCHEMA’ with expression as ‘USER3’: While this rule adds a new column with a value of ‘USER3’, it does not change the schema name itself.It only affects the content of a column within the tables1.

Therefore, the final target schema name, after considering all the applied settings, isD. USER2.This is because the Target Metadata setting in the task settings has the final say on the target schema name, and it is set to 'USER2’1.

Questions no:21Verified Answer: = C. As close as possible to the source system

Step by Step Comprehensive and Detailed Explanation with all References: =In an on-premises environment, Qlik Replicate should be set up as close as possible to the source system. This is because the source system is where the initial capture of data changes occurs, and having Qlik Replicate close to the source helps to minimize latency and maximize the efficiency of data capture.

C. As close as possible to the source system: Positioning Qlik Replicate near the source system reduces the time it takes to capture and process changes, which is critical for maintaining low latency in replication tasks1.

The other options are not recommended because:

A. As close as possible to the target system: While proximity to the target system can be beneficial for the apply phase, it is more crucial to have minimal latency during the capture phase, which is closer to the source.

B. In the “middle” between the source and target: This does not provide the optimal configuration for either the capture or apply phases and could introduce unnecessary complexity and potential latency.

D. In a cloud environment: This option is not relevant to the question as it specifies an on-premises setup. Additionally, whether to use a cloud environment depends on the specific architecture and requirements of the replication scenario.

For detailed guidance on setting up Qlik Replicate in an on-premises environment, including considerations for placement and configuration to optimize performance and reduce latency, you can refer to the official Qlik Replicate Setup and User Guide1.

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.