Google GCP-DE Prüfungsthemen:
| Abschnitt | Gewichtung | Ziele |
|---|---|---|
| Speicherung und Verwaltung von Daten | 20% | - Optimierung von Speicherleistung und -kosten
|
| Wartung und Automatisierung von Datenverarbeitungsabläufen | 18% | - Automatisierung und Optimierung
|
| Entwurf von Datenverarbeitungssystemen | 24% | - Planung von Datenlösungen
|
| Vorbereitung von Daten für Analysen und maschinelles Lernen | 13% | - Vorbereitung von Daten für das maschinelle Lernen
|
| Erfassung und Verarbeitung von Daten | 25% | - Transformation von Daten
|
Google Data Engineer GCP-DE Prüfungsfragen mit Lösungen
Frage #1
You are selecting services to write and transform JSON messages from Cloud Pub/Sub to BigQuery for a data pipeline on Google Cloud. You want to minimize service costs. You also want to monitor and accommodate input data volume that will vary in size with minimal manual intervention. What should you do?
A. Use the default autoscaling setting for worker instances.
B. Monitor the total execution time for a sampling of job
C. Configure the job to use non-default Compute Engine machine types when needed.
D. Use Cloud Dataproc to run your transformation
E. Use Cloud Dataflow to run your transformation
F. Use the diagnose command to generate an operational output archiv
G. Locate the bottleneck and adjust cluster resources.
H. Use Cloud Dataproc to run your transformation
I. Monitor CPU utilization for the cluste
J. Use Cloud Dataflow to run your transformation
K. Resize the number of worker nodes in your cluster via the command line.
L. Monitor the job system lag with Stackdrive
Frage #2
By default, which of the following windowing behavior does Dataflow apply to unbounded data sets?
A. Single, Global Window
B. Windows at every 100 MB of data
C. Windows at every 1 minute
D. Windows at every 10 minutes
Frage #3
You are designing storage for two relational tables that are part of a 10-TB database on Google Cloud. You want to support transactions that scale horizontally. You also want to optimize data for range queries on nonkey columns. What should you do?
A. Add secondary indexes to support query patterns.
B. Use Cloud Spanner for storag
C. Use Cloud SQL for storag
D. Add secondary indexes to support query patterns.
E. Use Cloud Dataflow to transform data to support query patterns.
F. Use Cloud SQL for storag
G. Use Cloud Spanner for storag
H. Use Cloud Dataflow to transform data to support query patterns.
Frage #4
You want to process payment transactions in a point-of-sale application that will run on Google Cloud Platform. Your user base could grow exponentially, but you do not want to manage infrastructure scaling.
Which Google database service should you use?
A. Cloud SQL
B. Cloud Bigtable
C. Cloud Datastore
D. BigQuery
Frage #5
Which of these rules apply when you add preemptible workers to a Dataproc cluster (select 2 answers)?
A. Preemptible workers cannot store data.
B. If a preemptible worker is reclaimed, then a replacement worker must be added manually.
C. A Dataproc cluster cannot have only preemptible workers.
D. Preemptible workers cannot use persistent disk.
Fragen und Antworten:
| Frage #1 Antwort: I | Frage #2 Antwort: A | Frage #3 Antwort: H | Frage #4 Antwort: A | Frage #5 Antwort: A,C |
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