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NEW QUESTION: 1
Which two statements about the SQL Management Base (SMB) are true? (Choose two.)
A. It contains the statement log, the plan history, plan baselines, and SQL profiles.
B. It stores plans generated by the optimizer using a stored outline.
C. It is part of the data dictionary and stored in the SYSAUX tablespace.
D. It contains only SQL profiles generated by SQL Tuning Advisor.
E. It is part of the data dictionary and stored in the SYSTEM tablespace.
Answer: A,C
NEW QUESTION: 2
An architect proposes an HPE Moonshot 1500 chassis with m710p cartridges, an HPE Moonshot 45XGc Switch, and an HPE 4-QSFP+ Uplink Module. The customer informs the architect that each cartridge requires a redundant 10GbE link.
How should the architect change the proposal?
A. Change the 4-QSFP+ Uplink Module to a 16-SFP+ Uplink Module.
B. Change the HPE Moonshot 45XGc Switch to an HPE Moonshot 180G switch.
C. Add another HPE Moonshot 45XGc Switch and 4-QSFP+ Uplink Module.
D. Add another FlexibleLOM adapter for each cartridge.
Answer: C
NEW QUESTION: 3
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution. Determine whether the solution meets the stated goals.
You deploy a tabular data model to an instance of Microsoft SQL Server Analysis Services
(SSAS). The model uses an in-memory cache to store and query data. The data set is already the same size as the available RAM on the server. Data volumes are likely to continue to increase rapidly.
Your data model contains multiple calculated tables.
The data model must begin processing each day at 2:00 and processing should be complete by 4:00 the same day. You observe that the data processing operation often does not complete before 7:00. This is adversely affecting team members.
You need to improve the performance.
Solution: Install solid-state disk drives to store the tabular data model.
Does the solution meet the goal?
A. No
B. Yes
Answer: A
Explanation:
By default, tabular models use an in-memory cache to store and query data. When tabular models query data residing in-memory, even complex queries can be incredibly fast.
However, there are some limitations to using cached data. Namely, large data sets can exceed available memory, and data freshness requirements can be difficult if not impossible to achieve on a regular processing schedule.
DirectQuery overcomes these limitations while also leveraging RDBMS features making query execution more efficient.
With DirectQuery: +
References:https://docs.microsoft.com/en-us/sql/analysis-services/tabular- models/directquery-mode-ssas-tabular