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NEW QUESTION 46
Your financial services company is moving to cloud technology and wants to store 50 TB of financial timeseries data in the cloud. This data is updated frequently and new data will be streaming in all the time.
Your company also wants to move their existing Apache Hadoop jobs to the cloud to get insights into this data.
Which product should they use to store the data?
- A. Google Cloud Datastore
- B. Google Cloud Storage
- C. Google BigQuery
- D. Cloud Bigtable
Answer: D
Explanation:
Reference: https://cloud.google.com/bigtable/docs/schema-design-time-series
NEW QUESTION 47
When you store data in Cloud Bigtable, what is the recommended minimum amount of stored data?
- A. 500 TB
- B. 500 GB
- C. 1 GB
- D. 1 TB
Answer: D
Explanation:
Explanation
Cloud Bigtable is not a relational database. It does not support SQL queries, joins, or multi-row transactions. It is not a good solution for less than 1 TB of data.
Reference: https://cloud.google.com/bigtable/docs/overview#title_short_and_other_storage_options
NEW QUESTION 48
You are running a pipeline in Cloud Dataflow that receives messages from a Cloud Pub/Sub topic and writes the results to a BigQuery dataset in the EU. Currently, your pipeline is located in europe-west4 and has a maximum of 3 workers, instance type n1-standard-1. You notice that during peak periods, your pipeline is struggling to process records in a timely fashion, when all 3 workers are at maximum CPU utilization. Which two actions can you take to increase performance of your pipeline? (Choose two.)
- A. Increase the number of max workers
- B. Create a temporary table in Cloud Spanner that will act as a buffer for new data. Create a new step in your pipeline to write to this table first, and then create a new pipeline to write from Cloud Spanner to BigQuery
- C. Change the zone of your Cloud Dataflow pipeline to run in us-central1
- D. Use a larger instance type for your Cloud Dataflow workers
- E. Create a temporary table in Cloud Bigtable that will act as a buffer for new data. Create a new step in your pipeline to write to this table first, and then create a new pipeline to write from Cloud Bigtable to BigQuery
Answer: B,D
NEW QUESTION 49
If you’re running a performance test that depends upon Cloud Bigtable, all the choices except one below are recommended steps. Which is NOT a recommended step to follow?
- A. Before you test, run a heavy pre-test for several minutes.
- B. Run your test for at least 10 minutes.
- C. Use at least 300 GB of data.
- D. Do not use a production instance.
Answer: D
Explanation:
If you’re running a performance test that depends upon Cloud Bigtable, be sure to follow these steps as you plan and execute your test:
Use a production instance. A development instance will not give you an accurate sense of how a production instance performs under load.
Use at least 300 GB of data. Cloud Bigtable performs best with 1 TB or more of data. However, 300 GB of data is enough to provide reasonable results in a performance test on a 3-node cluster. On larger clusters, use 100 GB of data per node.
Before you test, run a heavy pre-test for several minutes. This step gives Cloud Bigtable a chance to balance data across your nodes based on the access patterns it observes. Run your test for at least 10 minutes. This step lets Cloud Bigtable further optimize your data, and it helps ensure that you will test reads from disk as well as cached reads from memory.
Reference: https://cloud.google.com/bigtable/docs/performance
NEW QUESTION 50
Cloud Dataproc is a managed Apache Hadoop and Apache _____ service.
- A. Spark
- B. Blaze
- C. Fire
- D. Ignite
Answer: A
Explanation:
Cloud Dataproc is a managed Apache Spark and Apache Hadoop service that lets you use open source data tools for batch processing, querying, streaming, and machine learning.
Reference: https://cloud.google.com/dataproc/docs/
NEW QUESTION 51
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