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NEW QUESTION: 1
DRAG DROP
You are developing a SQL Server Analysis Services (SSAS) multidimensional project that is configured to source data from a Microsoft Azure SQL Database database. The cube is processed each night at midnight.
The largest partition in the cube takes 12 hours to process, and users are unable to access the cube until noon. The partition must be available for querying as soon as possible after processing commences.
You need to ensure that the partition is available for querying as soon as possible, without using source data to satisfy the query.
Which three actions should you perform in sequence? (To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.)
Answer:
Explanation:
Explanation:
Box 1:
Box 2:
Box 3:
Note:
* Processing mode has two possible options.
Regular. This is the default setting. When set to regular, partitions will be available to users after data has been loaded and aggregations are created completely.
Lazy Aggregations. When set to lazy aggregations, partitions will be available to user queries immediately after data has been loaded. Aggregations will be created as a separate background process while users start to query the partition.
* Lazy processing performs the task of building indexes and aggregations for dimensions and measure group partitions at a lower priority to reduce foreground processing time and to allow users to query the cube sooner. For lazy processing to occur, you must switch the ProcessingMode = LazyAggregations of your measure group partitions; by default this value is Regular (lazy processing is turned off). When processing a dimension with flexible aggregations such as parent-child or virtual dimension by using the processing enumeration of ProcessUpdate (such as to take into account of member name or hierarchy changes), lazy processing is initiated to ensure that the aggregations are rebuilt on the associated measure group partitions.
* Configure Lazy Processing for the cube, measure group, or partition. If you configure Lazy Processing, the dropped aggregations are recalculated as a background task. While the flexible aggregations are being recalculated, users can continue to query the cube (without the benefit of the flexible aggregations). While the flexible aggregations are being recalculated, queries that would benefit from the flexible aggregations run slower because Analysis Services resolves these queries by scanning the fact data and then summarizing the data at query time. As the flexible aggregations are recalculated, they become available incrementally on a partition-by-partition basis. For a given cube, Lazy Processing is not enabled by default. You can configure it for a cube, measure group, or partition by changing the ProcessingMode property from Regular to LazyAggregations. To manage Lazy Processing, there are a series of server properties such as the LazyProcessing \ MaxObjectsInParallel setting, which controls the number of objects that can be lazy processed at a given time. By default it is set to 2. By increasing this number, you increase the number of objects processed in parallel; however, this also impacts query performance and should therefore be handled with care.
* Incorrect: With Bring Online Immediately enabled, during cache refresh all queries are directed to the relational source database to retrieve the latest data for end users. While this provides users with refreshed data, it can also result in reduced query performance given that Analysis Services needs to redirect queries to the relational source database.
NEW QUESTION: 2
You have a set of EC2 Instances hosting an nginx server and a web application that is used by a set of users in your organization. After a recent application version upgrade, the instance runs into technical issues and needs an immediate restart. This does not give you enough time to inspect the cause of the issue on the server. Which of the following options if implemented prior to the incident would have assisted in detecting the underlying cause of the issue?
A. Install Cloudwatch logs agent on the instance and send all the logs to Cloudwatch logs.
B. Enabledetailed monitoring and check the Cloudwatch metrics to see the cause of theissue.
C. Streamall the data to Amazon Kinesis and then analyze the data in real time.
D. Createa snapshot of the EBS volume before restart, attach it to another instance as avolume and then diagnose the issue.
Answer: A
Explanation:
Explanation
The AWS documentation mentions the following
You can publish log data from Amazon CC2 instances running Linux or Windows Server, and logged events from AWS CloudTrail. CloudWatch Logs can consume logs from resources in any region, but you can only view the log data in the CloudWatch console in the regions where CloudWatch Logs is supported.
Option A is invalid as detailed monitoring will only help us to get more information about the performance metrics of the instances, volumes etc and will not be able to provide full information regarding technical issues.
Option B is incorrect if we had created a snapshot prior to the update it might be useful but not after the incident.
Option C is incorrect here we are dealing with an issue concerning the underlying application that handles the data so this solution will not help.
For more information on Cloudwatch logs, please refer to the below link:
* http://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/StartTheCW
LAgent.html
NEW QUESTION: 3
The ________ allows the processor to connect to or communicate with every other device within the server.
A. North Bridge
B. Timing Bus
C. Motherboard
D. South Bridge
Answer: C
Explanation:
For the processor to communicate with the rest of the system, it plugs in or connects to a large circuit board called the motherboard or system board. The motherboard allows the processor to branch out and communicate with all other computer components.