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NEW QUESTION: 1
Shipping Functionアプリを保護する必要があります。
アプリをどのように構成する必要がありますか?回答するには、回答領域で適切なオプションを選択します。
注:それぞれの正しい選択は1ポイントの価値があります。
Answer:
Explanation:
Explanation
Scenario: Shipping Function app: Implement secure function endpoints by using app-level security and include Azure Active Directory (Azure AD).
Box 1: Function
Box 2: JSON based Token (JWT)
Azure AD uses JSON based tokens (JWTs) that contain claims
Box 3: HTTP
How a web app delegates sign-in to Azure AD and obtains a token
User authentication happens via the browser. The OpenID protocol uses standard HTTP protocol messages.
References:
https://docs.microsoft.com/en-us/azure/active-directory/develop/authentication-scenarios
NEW QUESTION: 2
How many bits of a MAC address uniquely identify a vendor, as provided by the IEEE?
A. 24 bits
B. 6 bits
C. 12 bits
D. 16 bits
Answer: A
Explanation:
Explanation/Reference:
The MAC address is 48 bits long, 24 of which identify the vendor, as provided by the IEEE. The other 24 bits are provided by the vendor.
A media access control address (MAC address) is a unique identifier assigned to network interfaces for communications on the physical network segment. MAC addresses are used for numerous network technologies and most IEEE 802 network technologies, including Ethernet. Logically, MAC addresses are used in the media access control protocol sublayer of the OSI reference model.
MAC addresses are most often assigned by the manufacturer of a network interface card (NIC) and are stored in its hardware, such as the card's read-only memory or some other firmware mechanism. If assigned by the manufacturer, a MAC address usually encodes the manufacturer's registered identification number and may be referred to as the burned-in address. It may also be known as an Ethernet hardware address (EHA), hardware address or physical address. This is can be contrasted to a programmed address, where the host device issues commands to the NIC to use an arbitrary address. An example is many SOHO routers, where the ISP grants access to only one MAC address (used previously to inserting the router) so the router must use that MAC address on its Internet-facing NIC. Therefore the router administrator configures a MAC address to override the burned-in one.
A network node may have multiple NICs and each must have one unique MAC address per NIC.
See diagram below from Wikipedia showing the format of a MAC address. :
MAC Address format
Reference(s) used for this question:
http://en.wikipedia.org/wiki/MAC_address
NEW QUESTION: 3
During a recent audit, it was discovered that several user accounts belonging to former employees were still active and had valid VPN permissions. Which of the following would help reduce the amount of risk the organization incurs in this situation in the future?
A. Change management policies
B. Time-of-day restrictions
C. Group-based privileges
D. User access reviews
Answer: D
NEW QUESTION: 4
You observe that the number of spilled records from map tasks for exceeds the number of map output records. You child heap size is 1 GB and your io.sort.mb value is set to 100MB. How would you tune your io.sort.mb value to achieve maximum memory to disk I/O ratio?
A. For 1GB child heap size an io.sort.mb of 128MB will always maximum memory to disk I/O.
B. Tune io.sort.mb value until you observe that the number of spilled records equals (or is as close to equals) the number of map output records.
C. Decrease the io.sort.mb value below 100M
D. Increase the IO.sort.mb as high you can, as close to 1GB as possible.
Answer: B
Explanation:
here are a few tradeoffs to consider.
1.the number of seeks being done when merging files. If you increase the merge factor too high, then the seek cost on disk will exceed the savings from doing a parallel merge (note that OS cache might mitigate this somewhat).
2.Increasing the sort factor decreases the amount of data in each partition. I believe the number is io.sort.mb / io.sort.factor for each partition of sorted data. I believe the general rule of thumb is to have io.sort.mb = 10 * io.sort.factor (this is based on the seek latency of the disk on the transfer speed, I believe. I'm sure this could be tuned better if it was your bottleneck. If you keep these in line with each other, then the seek overhead from merging should be minimized
3.you increase io.sort.mb, then you increase memory pressure on the cluster, leaving less memory available for job tasks. Memory usage for sorting is mapper tasks * io.sort.mb -- so you could find yourself causing extra GCs if this is too high
Essentially,
If you find yourself swapping heavily, then there's a good chance you have set the sort factor too high.
If the ratio between io.sort.mb and io.sort.factor isn't correct, then you may need to change io.sort.mb (if you have the memory) or lower the sort factor.
If you find that you are spending more time in your mappers than in your reducers, then you may want to increase the number of map tasks and decrease the sort factor (assuming there is memory pressure).
Reference: How could I tell if my hadoop config parameter io.sort.factor is too small or too big?
http://stackoverflow.com/questions/8642566/how-could-i-tell-if-my-hadoop-config-parameter-iosort-factor-is-too-small-or-to