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NEW QUESTION: 1
Which processor type is used with the HP BL460c G6 Server Blade?
A. AMD Opteron processor
B. Intel@ Xeon@ Processor
C. Dual-Core Intel@ Itanium@ Processor
D. HP PA-RISC FSB, double data rate
Answer: B
NEW QUESTION: 2
Data gathered in support of an audit conclusion can be rated on a continuum of reliability.
The most reliable form of evidence would be an
A. Internal document that has been circulated through an outside party.
B. External document obtained directly from an outside source.
C. Internal document obtained from the auditee.
D. Internal document subject to rigorous internal review procedures.
Answer: B
NEW QUESTION: 3
Refer to the exhibit.
You are trying to police down to 100 Mb/s. While testing, you notice that you rarely exceed 70-80 Mb/s.
What do you need to change in your MQC configuration to allow for 100 Mb/s speeds?
A. Change the QoS queue from default to priority.
B. Change the CIR value from 100 Mb/s to 200 Mb/s.
C. Change the Bc value to allow for a large enough burst.
D. Change the exceed-action to transmit.
Answer: C
Explanation:
Burst size-Also called the Committed Burst (Bc) size, it specifies in bits (or bytes) per burst how
much traffic can be sent within a given unit of time to not create scheduling concerns. (For a shaper, such as GTS, it specifies bits per burst; for a policer, such as CAR, it specifies bytes per burst.)
NEW QUESTION: 4
You need to store and analyze social media postings in Google BigQuery at a rate of 10,000 messages per minute in near real-time. Initially, design the application to use streaming inserts for individual postings.
Your application also performs data aggregations right after the streaming inserts. You discover that the queries after streaming inserts do not exhibit strong consistency, and reports from the queries might miss in-flight data. How can you adjust your application design?
A. Re-write the application to load accumulated data every 2 minutes.
B. Load the original message to Google Cloud SQL, and export the table every hour to BigQuery via streaming inserts.
C. Convert the streaming insert code to batch load for individual messages.
D. Estimate the average latency for data availability after streaming inserts, and always run queries after waiting twice as long.
Answer: D
Explanation:
The data is first comes to buffer and then written to Storage. If we are running queries in buffer we will face above mentioned issues. If we wait for the bigquery to write the data to storage then we won't face the issue. So We need to wait till it's written to storage.