NEWEST TDVAN5 TEST SIMULATOR OFFER YOU THE BEST CLEARER EXPLANATION | HCIA-DATACOM V1.0

Newest TDVAN5 Test Simulator Offer You The Best Clearer Explanation | HCIA-Datacom V1.0

Newest TDVAN5 Test Simulator Offer You The Best Clearer Explanation | HCIA-Datacom V1.0

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TeraData TDVAN5 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Security Management & Auditing: This section of the exam measures the skills of such database managers. It covers the features, functionality, and benefits of access logging and advanced security configurations.
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
  • User Administration: This section evaluates the skills of system administrators in meeting user security requirements through roles and proxy access configurations. Candidates will also learn about the functionality and benefits of profiles, as well as the key attributes that should be set for a new user.
Topic 4
  • 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.
Topic 5
  • 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.

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TeraData HCIA-Datacom V1.0 Sample Questions (Q38-Q43):

NEW QUESTION # 38
An application is consuming very high I/O on Teradata Vantage. The Administrator has been asked to identify the queries that are consuming more than 100 million IOs and are suspected of completing Full Table Scans or Large Redistribution.
Which metrics should be examined for high values to identify the queries?

  • A. TOTALIOCOUNT and PJI
  • B. MAXAMPIO and PJI
  • C. REQPHYSIO and UII
  • D. I/O SKEW % and UII

Answer: A

Explanation:
TOTALIOCOUNT represents the total number of I/O operations a query performs, which is crucial when trying to identify queries consuming excessive I/O (in this case, more than 100 million IOs). This directly indicates the amount of I/O a query is generating.
PJI (Product Join Index) measures whether a product join is being performed in the query, which is often associated with inefficient joins that result in large redistributions of data. A high PJI value indicates that the query might be performing a product join, leading to a significant performance hit due to large redistributions.
Option A (MAXAMPIO and PJI): MAXAMPIO refers to the maximum I/O performed by a single AMP, but TOTALIOCOUNT is a more direct indicator of the total I/O performed by a query across all AMPs.
Option C (I/O SKEW % and UII): I/O SKEW % indicates uneven distribution of I/O, which can cause performance issues, but it does not directly measure the total I/O consumption like TOTALIOCOUNT does. UII (Utility Impact Index) is relevant but not as important for identifying large I/O queries.
Option D (REQPHYSIO and UII): REQPHYSIO refers to the number of physical I/Os, but it is not as comprehensive as TOTALIOCOUNT, which includes both logical and physical I/O.
Thus, TOTALIOCOUNT (for total I/O) and PJI (to detect potential large redistributions due to product joins) are the key metrics to identify queries with high I/O and large redistributions.


NEW QUESTION # 39
How can an Administrator monitor the data volume that is transferred for a Data Mover job via Viewpoint?

  • A. By submitting the datamove status -job_name command in the remote console
  • 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 viewing the job statistics tab of the Performance Data Collection portlet

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 # 40
An analytics team uses a multibillion row table that is relevant to a great number of queries with different filters and joins. The Administrator needs to identify an effective strategy to collect statistics on this table.
Which statistics should be collected?

  • A. [Dynamic AMP Sample
  • B. Summary
  • C. Sampled
  • D. Full-table

Answer: A

Explanation:
Dynamic AMP Sample is an efficient method for collecting statistics on large tables. It collects sample statistics from a subset of AMPs (Access Module Processors) in the system, making it much faster and less resource-intensive than collecting full-table statistics, while still providing sufficiently accurate information for the optimizer.
Full-table statistics collection would be too resource-intensive for a multibillion-row table, potentially causing performance issues due to the size of the data.
Sampled statistics might be an option, but Dynamic AMP Sample is generally preferred because it provides a more efficient and balanced approach in large distributed systems like Teradata.
Summary statistics typically apply to aggregate data rather than large, detailed tables, and would not be sufficient for query optimization across different filters and joins.
Hence, Dynamic AMP Sample is the most effective strategy in this scenario.


NEW QUESTION # 41
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. Exceptions to place Python scripts consuming too much memory into a penalty box
  • B. Virtual partitions to assign separate memory space to each Python script
  • C. Throttles to limit the concurrency of Python scripts
  • D. Planned environments to specify periods when data scientists can run Python scripts

Answer: C

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 # 42
An Administrator manages a Vantage system that experiences large loads and updates during the night, on weekdays. On Saturday night, significant analytical processing occurs using the data from the prior weeks. The results of this processing are saved to support rapid reporting in the following week.
The business requires this Vantage system to be available as soon as possible in case of a catastrophic system failure.
Which backup strategy meets this need?

  • A. Daily delta backups
  • B. Weekly cumulative backup on Sunday and Wednesday, and delta backups on the remaining days
  • C. Weekly full backup, cumulative backups on Tuesday and Friday, and delta backups on the remaining days
  • D. Daily full backups

Answer: C

Explanation:
This strategy strikes a balance between minimizing recovery time and reducing the overall storage and performance impact during backups.
Weekly full backup ensures that a complete copy of the data is available at the start of the week, which is critical for quick recovery in the event of a catastrophic system failure.
Cumulative backups on Tuesday and Friday ensure that any changes made since the last full backup are captured without needing to apply multiple delta backups, reducing the time required for restoration.
Delta backups on other days provide incremental backups of the system with minimal performance impact, ensuring the system is consistently backed up without using excessive resources.


NEW QUESTION # 43
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