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TeraData TDVAN5 Exam Syllabus Topics:

Topic
Details

Topic 1

Monitoring Vantage: This section of the exam measures the skills of IT professionals such as system administrators. It covers how to effectively use Viewpoint to investigate system conditions, monitor external queries, and administer both Viewpoint and monitored systems.

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

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 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.

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TeraData HCIA-Datacom V1.0 Sample Questions (Q21-Q26):

NEW QUESTION # 21
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. Summary
B. Sampled
C. Full-table
D. [Dynamic AMP Sample

Answer: D

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 # 22
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 # 23
An Administrator is required to load sensor data from cloud storage. This store contains many numeric columns.
Which strategy should the Administrator use to optimize the data load?

A. Cast column data types to appropriate values in a view of the foreign table.
B. Use a more generic LOCATION string in the USING clause.
C. Collect statistics on all payload attributes.
D. Keep the original VARCHAR data types in JSON or CSV for columns.

Answer: A

Explanation:
When loading sensor data, especially if it involves many numeric columns, casting the data to appropriate types (like INT, FLOAT, etc.) in a view can significantly improve query performance and reduce storage overhead. This approach ensures that the numeric data is handled efficiently, avoiding unnecessary conversions or using inefficient data types such as VARCHAR.

NEW QUESTION # 24
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 # 25
A suite of development jobs have been mistakenly executed at a time when a long-running critical job is being run. The business has decided to allow the development jobs to run if they do not block the critical job. An Administrator has been tasked with recording any delays experienced throughout the execution of this critical job and to abort any of the development jobs if they block it.
Which Viewpoint portlet could the Administrator use for this purpose?

A. Show Locks
B. Query Session
C. Query Monitor
D. Lock Display

Answer: D

Explanation:
The Lock Display portlet in Teradata Viewpoint provides detailed information about database locks. It allows the Administrator to monitor if any queries or jobs are causing lock contention that could block the critical job. Using this portlet, the Administrator can see if the development jobs are creating locks that delay or block the critical job. If such blocking is detected, the Administrator can take action, such as aborting the development jobs.
Option A (Query Session) shows information about active sessions but is not focused on lock contention and blocking.
Option B (Query Monitor) allows the monitoring of query performance and workloads but doesn't specifically focus on lock contention.
Option C (Show Locks) can display current lock information, but Lock Display provides a more comprehensive tool for monitoring and managing lock-related issues.

NEW QUESTION # 26
......

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