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NEW QUESTION 36
When you store data in Cloud Bigtable, what is the recommended minimum amount of stored data?

• A. 1 TB
• B. 1 GB
• C. 500 GB
• D. 500 TB

Answer: A

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 37
You are building a data pipeline on Google Cloud. You need to prepare data using a casual method for a machine-learning process. You want to support a logistic regression model. You also need to monitor and adjust for null values, which must remain real-valued and cannot be removed. What should you do?

• A. Use Cloud Dataflow to find null values in sample source data. Convert all nulls to `none' using a Cloud Dataprep job.
• B. Use Cloud Dataprep to find null values in sample source data. Convert all nulls to `none' using a Cloud Dataproc job.
• C. Use Cloud Dataflow to find null values in sample source data. Convert all nulls to using a custom script.
• D. Use Cloud Dataprep to find null values in sample source data. Convert all nulls to 0 using a Cloud Dataprep job.

Answer: A

NEW QUESTION 38
You are building a new application that you need to collect data from in a scalable way. Data arrives continuously from the application throughout the day, and you expect to generate approximately 150 GB of JSON data per day by the end of the year. Your requirements are:
* Decoupling producer from consumer
* Space and cost-efficient storage of the raw ingested data, which is to be stored indefinitely
* Near real-time SQL query
* Maintain at least 2 years of historical data, which will be queried with SQL Which pipeline should you use to meet these requirements?

• A. Create an application that writes to a Cloud SQL database to store the data. Set up periodic exports of the database to write to Cloud Storage and load into BigQuery.
• B. Create an application that provides an API. Write a tool to poll the API and write data to Cloud Storage as gzipped JSON files.
• C. Create an application that publishes events to Cloud Pub/Sub, and create a Cloud Dataflow pipeline that transforms the JSON event payloads to Avro, writing the data to Cloud Storage and BigQuery.
• D. Create an application that publishes events to Cloud Pub/Sub, and create Spark jobs on Cloud Dataproc to convert the JSON data to Avro format, stored on HDFS on Persistent Disk.

Answer: B

NEW QUESTION 39
Your United States-based company has created an application for assessing and responding to user actions. The primary table's data volume grows by 250,000 records per second. Many third parties use your application's APIs to build the functionality into their own frontend applications. Your application's APIs should comply with the following requirements:
* Single global endpoint
* ANSI SQL support
* Consistent access to the most up-to-date data
What should you do?

• A. Implement Cloud SQL for PostgreSQL with the master in Norht America and read replicas in Asia and Europe.
• B. Implement Cloud Spanner with the leader in North America and read-only replicas in Asia and Europe.
• C. Implement Cloud Bigtable with the primary cluster in North America and secondary clusters in Asia and Europe.
• D. Implement BigQuery with no region selected for storage or processing.

Answer: B

NEW QUESTION 40
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