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NEW QUESTION 23
What is the HBase Shell for Cloud Bigtable?

• A. The HBase shell is a command-line tool that performs administrative tasks, such as creating and deleting tables.
• B. The HBase shell is a GUI based interface that performs administrative tasks, such as creating and deleting tables.
• C. The HBase shell is a hypervisor based shell that performs administrative tasks, such as creating and deleting new virtualized instances.
• D. The HBase shell is a command-line tool that performs only user account management functions to grant access to Cloud Bigtable instances.

Answer: A

Explanation:
The HBase shell is a command-line tool that performs administrative tasks, such as creating and deleting tables. The Cloud Bigtable HBase client for Java makes it possible to use the HBase shell to connect to Cloud Bigtable.
Reference: https://cloud.google.com/bigtable/docs/installing-hbase-shell

NEW QUESTION 24
Your company is streaming real-time sensor data from their factory floor into Bigtable and they have
noticed extremely poor performance. How should the row key be redesigned to improve Bigtable
performance on queries that populate real-time dashboards?

• A. Use a row key of the form >#<sensorid>#<timestamp>.
• B. Use a row key of the form <timestamp>.
• C. Use a row key of the form <sensorid>.
• D. Use a row key of the form <timestamp>#<sensorid>.

Answer: B

NEW QUESTION 25
You are designing the database schema for a machine learning-based food ordering service that will predict what users want to eat. Here is some of the information you need to store:
The user profile: What the user likes and doesn't like to eat The user account information: Name, address, preferred meal times The order information: When orders are made, from where, to whom The database will be used to store all the transactional data of the product. You want to optimize the data schema. Which Google Cloud Platform product should you use?

• A. Cloud Datastore
• B. BigQuery
• C. Cloud Bigtable
• D. Cloud SQL

Answer: B

NEW QUESTION 26
Which of the following is NOT a valid use case to select HDD (hard disk drives) as the storage for Google Cloud Bigtable?

• A. You will mostly run batch workloads with scans and writes, rather than frequently executing random reads of a small number of rows.
• B. You need to integrate with Google BigQuery.
• C. You will not use the data to back a user-facing or latency-sensitive application.
• D. You expect to store at least 10 TB of data.

Answer: B

Explanation:
Explanation
For example, if you plan to store extensive historical data for a large number of remote-sensing devices and then use the data to generate daily reports, the cost savings for HDD storage may justify the performance tradeoff. On the other hand, if you plan to use the data to display a real-time dashboard, it probably would not make sense to use HDD storage-reads would be much more frequent in this case, and reads are much slower with HDD storage.
Reference: https://cloud.google.com/bigtable/docs/choosing-ssd-hdd

NEW QUESTION 27
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. 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
• B. Increase the number of max workers
• C. 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
• D. Use a larger instance type for your Cloud Dataflow workers
• E. Change the zone of your Cloud Dataflow pipeline to run in us-central1

Answer: C,D

NEW QUESTION 28
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