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100% Pass Quiz 2025 TeraData TDVAN5: HCIA-Datacom V1.0 Marvelous Exam Cram Review

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TeraData TDVAN5 Exam Syllabus Topics:

Topic
Details

Topic 1

Performance Management: This section of the exam evaluates the skills of TeraData database administrators. It focuses on strategies for managing statistics, implementing DBQL logging, and using performance data to troubleshoot and resolve system issues.

Topic 2

Integration: This section tests the skills of database administrators in utilizing integration tools like QueryGrid and NOS. It covers the benefits, features, and functionality of QueryGrid, the database objects supporting its implementation, and the performance implications of accessing NOS and foreign servers.

Topic 3

Database Management: This section tests the skills of database administrators in managing access rights and advanced analytic functions. It covers logging benefits, privilege types, and the impact of changing global parameters on user sessions.

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TeraData HCIA-Datacom V1.0 Sample Questions (Q43-Q48):

NEW QUESTION # 43
How can an Administrator monitor the data volume that is transferred for a Data Mover job via Viewpoint?

A. By viewing the job statistics tab of the Performance Data Collection portlet
B. By accessing the Completed Queries portlet and selecting the Data Mover job
C. By using the Data Mover portlet accessing the log tab
D. By submitting the datamove status -job_name command in the remote console

Answer: C

Explanation:
The Data Mover portlet in Viewpoint provides specific functionality for managing and monitoring Data Mover jobs. By accessing the log tab within the Data Mover portlet, the Administrator can review detailed logs, including the data volume that was transferred during the job execution.
Option A (Completed Queries portlet) focuses on monitoring and analyzing completed queries but does not provide detailed insights into Data Mover jobs.
Option C (Performance Data Collection portlet) is used for monitoring system performance but is not directly related to Data Mover job details or data transfer volumes.
Option D (datamove status command) is a CLI (Command-Line Interface) method to check job status, but it is not related to monitoring the data volume within the Viewpoint environment.

NEW QUESTION # 44
An Administrator notices that a system appears to be near capacity and needs to get information about Input/Output Token Allocations (IOTA) for each workload.
How can this information be obtained?

A. Check DBC.ResSpmaView
B. Check DBC.ResSpsView
C. Check DBC.ResSldvView
D. Check DBC.ResSpdskView

Answer: B

Explanation:
The DBC.ResSpsView view provides resource usage information, including I/O-related metrics for workloads. It includes I/O Token Allocations (IOTA), which are essential for monitoring and managing system capacity.
The other options do not specifically provide I/O Token Allocation data:
DBC.ResSpmaView is used for monitoring memory allocations.
DBC.ResSpdskView focuses on disk space usage.
DBC.ResSldvView is related to logging device information.
Therefore, DBC.ResSpsView is the correct view to check for I/O Token Allocations.

NEW QUESTION # 45
A capacity planner wants to keep a record of the number of rows that are added and deleted from certain tables over time and would like to obtain this information without having to change the application itself.
Which DBQL option should be enabled?

A. USECOUNT
B. VERBOSE XMLPLAN
C. EXPLAIN
D. OBJECTS

Answer: D

Explanation:
The OBJECTS option in DBQL (Database Query Logging) records the tables and other objects that are accessed by queries, including information on how many rows are added, updated, or deleted. This allows the capacity planner to track changes to specific tables without modifying the application itself.
The other options are less relevant to tracking row changes:
USECOUNT records how often specific queries are executed, but not the number of rows affected.
EXPLAIN captures the query execution plan, which doesn't provide details on rows added or deleted.
VERBOSE XMLPLAN gives detailed execution plans in XML format, but it is more focused on query execution and optimization, not tracking row modifications.

NEW QUESTION # 46
The data science team reports that they do not have enough memory to run in-database Python scripts when the scripts operate simultaneously.
Which workload management feature should the Administrator use to resolve this issue?

A. Throttles to limit the concurrency of Python scripts
B. Exceptions to place Python scripts consuming too much memory into a penalty box
C. Planned environments to specify periods when data scientists can run Python scripts
D. Virtual partitions to assign separate memory space to each Python script

Answer: A

Explanation:
Using throttles in workload management allows the Administrator to limit the concurrency of Python scripts running in the system. By controlling the number of Python scripts that can run simultaneously, you can prevent memory exhaustion and ensure that enough resources are available for each script to execute without causing failures due to memory constraints.

NEW QUESTION # 47
After a recent migration, a request has started to take significant time to complete. Upon a detailed investigation of the EXPLAIN plan, it is found that an accidental unconstrained product join on a very uniformly-distributed large table was the prime reason for the issue. The Administrator needs to use workload management to detect when this request is running.
Which criteria should the Administrator select for this issue?

A. CPU Skew
B. CPU Utilization
C. CPU Disk Ratio
D. AWT Wait Time

Answer: A

Explanation:
CPU Skew is a metric that measures the uneven distribution of CPU usage across AMPs (Access Module Processors). In the case of an accidental unconstrained product join on a large, uniformly distributed table, certain AMPs may handle significantly more work than others, leading to high CPU Skew. This skew occurs because the product join results in an inefficient execution plan, where data from the large table is unnecessarily compared row-by-row with another table.
Option A (AWT Wait Time) refers to the time queries spend waiting for available AMP Worker Tasks, but it is not directly related to detecting the inefficiencies caused by product joins.
Option C (CPU Disk Ratio) measures the relationship between CPU usage and disk I/O. While it could indicate inefficiency, it doesn't directly pinpoint product join issues like CPU Skew does.
Option D (CPU Utilization) reflects overall CPU usage but doesn't indicate imbalance across AMPs, which is critical for detecting issues like product joins.

NEW QUESTION # 48
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