QUESTION: 9

An Administrator has been asked to improve the response time of the workloads in the tactical tier. Workloads are in all tiers of TASM. They are at CPU and I/O capacity, and they have AWT reserved for tactical. The Administrator begins by analyzing the data and the workload prioritization.
Which action should the Administrator take?

Increase the relative weight of the tactical tier.
Disable the expedite option of the workloads in the SLG Tier level 1.
Increase the number of AWTs.
Adjust the limits of awt concurrency in the tactical tier using DBS control.

Answer(s): A

Explanation:

In a TASM (Teradata Active System Management) environment, the relative weight of different tiers (such as tactical, SLG, or background) determines the amount of CPU and I/O resources allocated to each tier. Increasing the relative weight of the tactical tier would prioritize these workloads, giving them more resources relative to other tiers and improving their response time. Option B (Disable the expedite option of the workloads in the SLG Tier level 1) might alleviate some resource pressure from SLG Tier 1 workloads, but it doesn't directly improve the prioritization or resource allocation for tactical workloads.
Option C (Increase the number of AWTs) is not applicable because the system already has reserved AWTs for tactical workloads, and AWT (AMP Worker Task) availability is likely not the bottleneck here. Simply increasing the number of AWTs without addressing the core CPU and I/O resource allocation will not improve tactical workload response. Option D (Adjust the limits of AWT concurrency in the tactical tier using DBS control) might provide marginal improvements but won't have a significant impact on overall resource prioritization. It focuses more on concurrency management than directly improving workload performance through resource allocation.

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QUESTION: 10

At a large car manufacturer, huge volumes of diagnostic data for cars are collected in the following table:

The master data for each car is stored in the following table:

Many reports require data from both tables by joining via column VehicleId.

A very frequently performed query on the system returns the number of events by FaultCode and ModelType. This query consumes many CPU and I/O resources each day.

Which action should the Administrator take to improve the runtime and resource consumption for this query?

Use an aggregate join index with columns FaultCode, ModelType, as well as an appropriate aggregate function.
Use a sparse join index with columns FaultCode and ModelType, as well as an appropriate filter function.
Use a NUSI on VehicleEvent.FaultCode and a NUSI on Vehicle.ModelType
Use a single table join index on VehicleEvent hashed by FaultCode and another single table join index on Vehicle hashed by ModelType.

Answer(s): A

Explanation:

To improve the runtime and resource consumption for a query that returns the number of events by FaultCode and ModelType from the two tables VehicleEvent and Vehicle, the most appropriate action would be:
A . Use an aggregate join index with columns FaultCode, ModelType, as well as an appropriate aggregate function.
Aggregate Join Index: This type of join index will pre-join the tables VehicleEvent and Vehicle on

VehicleId and store the results of frequently queried aggregations (in this case, counts by FaultCode and ModelType). It would significantly reduce the need to perform full joins and aggregations at query time, saving both CPU and I/O resources.
Option B: A sparse join index is useful for selective filtering but does not offer aggregation. Since the query involves counting (aggregation), the aggregate join index is more suitable. Option C: Creating Non-Unique Secondary Indexes (NUSIs) on FaultCode and ModelType would help speed up searches for those columns, but it won't help with the pre-aggregation or frequent joins that are consuming the majority of the resources.
Option D: Creating separate single table join indexes for FaultCode and ModelType on different tables won't improve the performance of the aggregation and join-heavy query, because the problem stems from the frequent joins and aggregations, not just individual table access.

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QUESTION: 11

An Administrator has been given a task to generate a list of users who have not changed their password in the last 90 days.
Which DBC view should be used to generate this list?

DBC.LOGONOFFV
DBC.USERSV
DBSECURITYDEFAULTSV
DBC.ACCESSLOGV

Answer(s): B

Explanation:

DBC.USERSV contains information about users, including the passwordlastmodified column, which records the date and time the user last changed their password. By querying this view, the Administrator can identify users who have not updated their password within the specified time frame (in this case, 90 days).
Option A (DBC.LOGONOFFV) logs user logon and logoff events, but it does not track password changes.
Option C (DBC.SECURITYDEFAULTSV) contains system-wide security defaults, but it does not track individual user password activity.
Option D (DBC.ACCESSLOGV) logs access control events, like who accessed which database objects, but it doesn't track password changes either.

Therefore, DBC.USERSV is the appropriate view to use for this task.

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QUESTION: 12

A client has a healthy system but often sees delays in some queries because of workload concurrency limits. These limits have been carefully chosen, so the client needs a solution that will not modify them.
What should the Administrator use to assist this client?

Use a system throttle.
Use Query Group Viewpoint gortjet to change the throttle limit temporally.
Use Flex Throttle option.
Use Query Monitor Viewpoint portlet to change query workloads.

Answer(s): C

Explanation:

The Flex Throttle option allows the system to temporarily adjust workload concurrency limits based on system conditions. This provides more flexibility when handling spikes in query concurrency, without permanently modifying the established workload limits. Flex Throttle is ideal for handling temporary peaks in activity, helping to smooth out delays while keeping the core concurrency limits intact.
Option A (Use a system throttle) would enforce strict concurrency limits but doesn't provide the flexibility needed in this scenario, where the client is trying to avoid modifying existing limits. Option B (Use Query Group Viewpoint portlet to change the throttle limit temporarily) suggests manually adjusting the throttle limit, which is not desirable in this case as the limits have been carefully chosen.
Option D (Use Query Monitor Viewpoint portlet to change query workloads) would involve changing the way queries are handled or prioritized but does not address the need to keep concurrency limits unchanged while still dealing with temporary delays.
Thus, Flex Throttle (Option C) provides the best solution to assist the client without altering the concurrency limits permanently.

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