Concurrent vs MPP — Learn free

Self-check

Questions 1–10 of 10

1. What does MPP stand for?
Question 1A. Multiple Process PipelineB. Massive Parallel ProcessingC. Managed Performance PlatformD. Master Partition ProtocolE. Memory Paging Processor
2. What is the major difference between concurrent processing and MPP?
Question 2A. Concurrent processing depends on developers, whereas MPP depends on hardwareB. Concurrent processing is only for NoSQL databases, whereas MPP is only for SQLC. Concurrent processing is faster in every case than MPPD. MPP runs on a single core, whereas concurrent processing needs manyE. There is no difference; the terms mean the same thing
3. What does concurrent processing mean in simple words?
Question 3A. A single job is split into pieces that run on many nodesB. Jobs are queued and run one after anotherC. More than one job runs in parallel, executing some code sets at the same timeD. A job is paused until hardware becomes availableE. Code is compiled before it is executed
4. On what does concurrent query capability most often depend?
Question 4A. The number of users logged inB. The size of the hard diskC. The version of the operating systemD. The cores handling the queriesE. The colour scheme of the dashboard
5. How does MPP execute a single job?
Question 5A. It runs the job on one node and caches the resultB. It waits for all other jobs to finish firstC. It converts the job into a batch to run overnightD. It sends the job to a cloud provider for approvalE. It divides the job into multiple pieces that run in parallel across multiple nodes
6. Why is a job running under MPP much faster?
Question 6A. Because a single job utilises multiple nodes to execute the same code set instead of one node at a timeB. Because MPP skips validation stepsC. Because MPP compresses the data before processingD. Because MPP only processes a sample of the dataE. Because MPP runs the job in memory only
7. What benefit do concurrent and MPP capabilities give a data solution?
Question 7A. Lower licensing costsB. A huge benefit when it comes to meeting SLAsC. Automatic data quality fixesD. Elimination of the need for backupsE. Guaranteed regulatory compliance
8. In the Big Data era, how are concurrent and MPP capabilities described?
Question 8A. As optional luxuriesB. As obsolete techniquesC. As a must-haveD. As relevant only for small datasetsE. As a security risk
9. Which statement about MPP is NOT correct?
Question 9A. MPP uses hardware-level concurrencyB. MPP divides one code set into multiple piecesC. MPP runs those pieces in parallel across nodesD. MPP depends on developers writing many separate jobsE. MPP helps a solution meet its SLAs
10. Which scenario is an example of concurrent processing rather than MPP?
Question 10A. One large report query split across ten nodesB. A single job divided into pieces at the hardware levelC. A node executing one piece of a larger code setD. Hardware partitioning a single queryE. Several different jobs running in parallel on the available cores at the same time