Qlik QREP Exam Questions

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

Questions no: 17 Verified Answer: = A. IBM IMS & E. HP NonStop

Explanation: Step by Step Comprehensive and Detailed Explanation with all Reference: = 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 are A. IBM IMS and E. HP NonStop, as they are the endpoints that utilize ARC CDC agents for capturing changes1.

The ODBC drivers in Qlik Replicate are located in the \Replicate\bin directory. 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 <Replicate-Install-Dir>/bin23. This consistent reference to the \bin directory across different parts of the Qlik Replicate documentation verifies that the ODBC drivers are indeed located in the \Replicate\bin directory.

In the Qlik Enterprise Manager Analytics GUI, users can view messages related to both server and task trends. This includes:

Server-specific trends: These are metrics and trends related to the performance and usage of the servers, such as memory consumption and disk usage1.

Task-specific trends: These include metrics and trends specific to individual tasks, such as the number of tables and records processed, throughput, and the number of changes applied1.

Therefore, the correct answer is D. Server and task trends, as the Analytics tab in Qlik Enterprise Manager allows users to review trends over a specific time period for both servers and tasks. Users can filter the data to show information for a particular timeframe and for particular tasks, Replicate servers, source databases, and target databases2.

For more detailed information on the types of messages and trends that can be viewed in the Qlik Enterprise Manager Analytics GUI, you can refer to the official Qlik documentation on Analytics dashboards and Analytics.

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.