You are deploying 10,000 new Internet of Things devices to collect temperature data in your warehouses globally. You need to process, store and analyze these very large datasets in real time. What should you do?
A.
Send the data to Google Cloud Datastore and then export to BigQuery.
B.
Send the data to Google Cloud Pub/Sub, stream Cloud Pub/Sub to Google Cloud Dataflow, and store the data in Google BigQuery.
C.
Send the data to Cloud Storage and then spin up an Apache Hadoop cluster as needed in Google Cloud Dataproc whenever analysis is required.
D.
Export logs in batch to Google Cloud Storage and then spin up a Google Cloud SQL instance, import the data from Cloud Storage, and run an analysis as needed.
B. Send the data to Google Cloud Pub/Sub, stream Cloud Pub/Sub to Google Cloud Dataflow, and store the data in Google BigQuery.
Here's why this approach is preferred:
Google Cloud Pub/Sub allows for efficient ingestion and real-time data streaming.
Google Cloud Dataflow can process and transform the streaming data in real-time.
Google BigQuery is a fully managed, highly scalable data warehouse that is well-suited for real-time analysis and querying of large datasets.
A voting comment increases the vote count for the chosen answer by one.
Upvoting a comment with a selected answer will also increase the vote count towards that answer by one.
So if you see a comment that you already agree with, you can upvote it instead of posting a new comment.
[Removed]
Highly Voted 4 years, 7 months ago[Removed]
4 years, 7 months ago[Removed]
Highly Voted 4 years, 7 months agoAbizi
Most Recent 2 months agoregal_2010
6 months, 3 weeks agoaxantroff
11 months, 2 weeks agortcpost
1 year agoGCP_PDE_AG
1 year, 2 months agoMaurilio_Cardoso
1 year, 5 months agobha11111
1 year, 7 months agoDGames
1 year, 10 months agoNirca
1 year, 10 months agogitaexams
1 year, 11 months agodevaid
2 years agoDip1994
2 years, 2 months agonoob_master
2 years, 4 months agonexus1_
2 years, 4 months agovw13
2 years, 6 months ago