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NEW QUESTION: 1
You are deploying IS-IS in your network to enable the routing of only IPv6. Assume that the loopback interface has been properly configured.
What is the minimum required configuration to enable only IPv6 routing in IS-IS?
A. user@host# show protocols isis
interface ge-0/0/0.0;
interface lo0.0 {
passive;
}
user@host# show interfaces ge-0/0/0
unit 0 {
family iso;
family inet6 address fd85:5944:1aee:026::1/64;
}
B. user@host# show protocols isis
no-ipv4-routing;
interface ge-0/0/0.0;
interface lo0.0 {
passive;
}
user@host# show interfaces ge-0/0/0
unit 0 {
family iso;
family inet6;
}
C. user@host# show protocols isis
rib-group inet6;
interface ge-0/0/0.0;
interface lo0.0 {
passive;
}
user@host# show interfaces ge-0/0/0
unit 0 {
family inet6 address fd85:5944:1aee:026::1/64;
}
D. user@host# show protocols isis
traffic-engineering {
family inet6 {
shortcuts;
}
}
interface ge-0/0/0.0;
interface lo0.0 {
passive;
}
user@host# show interfaces ge-0/0/0
unit 0 {
family inet6 address fd85:5944:1aee:026::1/64;
family iso;
}
E. user@host# show protocols isis
no-ipv4-routing;
interface ge-0/0/0.0
interface lo0.0 {
passive;
}
user@host# show interfaces ge-0/0/0
unit 0 {
family iso;
family inet6 address fd85:5944:1aee:026::1/64;
}
Answer: E
NEW QUESTION: 2
Welche Objekte sind obligatorisch, wenn Sie einen Transaktionsdatenfluss bei der Bereitstellung von Betriebsdaten erstellen? Hinweis: Auf diese Frage gibt es 2 richtige Antworten.
A. Transformation
B. Echtzeit-Daemon
C. InfoPackage
D. Datenübertragungsprozess
Answer: A,D
NEW QUESTION: 3
How are keys and values presented and passed to the reducers during a standard sort and shuffle phase of MapReduce?
A. Keys are presented to a reducer in random order; values for a given key are sorted in ascending order.
B. Keys are presented to reducer in sorted order; values for a given key are not sorted.
C. Keys are presented to a reducer in random order; values for a given key are not sorted.
D. Keys are presented to reducer in sorted order; values for a given key are sorted in ascending order.
Answer: B
Explanation:
Reducer has 3 primary phases:
1.Shuffle
The Reducer copies the sorted output from each Mapper using HTTP across the network.
2.Sort
The framework merge sorts Reducer inputs by keys (since different Mappers may have output the same key).
The shuffle and sort phases occur simultaneously i.e. while outputs are being fetched they are merged.
SecondarySort
To achieve a secondary sort on the values returned by the value iterator, the application should extend the key with the secondary key and define a grouping comparator. The keys will be sorted using the entire key, but will be grouped using the grouping comparator to decide which keys and values are sent in the same call to reduce.
3. Reduce
In this phase the reduce(Object, Iterable, Context) method is called for each <key, (collection of values)> in the sorted inputs.
The output of the reduce task is typically written to a RecordWriter via TaskInputOutputContext.write(Object, Object).
The output of the Reducer is not re-sorted.
Reference: org.apache.hadoop.mapreduce, Class Reducer<KEYIN,VALUEIN,KEYOUT,VALUEOUT>