Exam Associate Cloud Engineer topic 1 question 85 discussion

Breaking down the question into key points - 1. 5-TB AVRO file stored in a Cloud Storage bucket. 2. Analysts are proficient only in SQL 3. cost-effective way to complete their request as soon as possible A. ....Load data in Cloud Datastore... (Not Correct because Cloud Datastore is not a good option to run SQL Queries) B. ...Load data in BigQuery.... (Not Cost Effective because loading the data which is already present in the bucket into BigQuery again is expensive) C. Create external tables in BigQuery that point to Cloud Storage buckets and run a SQL query on these external tables to complete your request. (This is the right answer as it meets all the requirements from the question) D. Create a Hadoop cluster and copy the AVRO file to NDFS by compressing it. Load the file in a hive table and provide access to your analysts so that they can run SQL queries. (Too roundabout and indirect. Not the right option)

C is correct: https://cloud.google.com/bigquery/external-data-sources

D - The ONLY answer that provides data for the analysts is D. The question states that the analysts need access to the data and that they only know SQL (not that *you* only know SQL). The other 3 answers don't provide the data to analysts. You might have to fill in the blanks that you will pass it to them in a spreadsheet format, but that very likely won't satisfy their needs to query the data using SQL and at 5TB size, that isn't ideal. Therefore D is the only answer that satisfies the requirement.

The most cost-effective and efficient option would be Option C: Create external tables in BigQuery that point to Cloud Storage buckets and run a SQL query on these external tables to complete your request. This approach allows you to query data directly from the AVRO file stored in the Cloud Storage bucket without having to load the data into BigQuery first. This saves both time and money as you are not charged for the storage of data within BigQuery. Plus, BigQuery is designed to be able to handle large datasets, making it a suitable choice for a 5-TB AVRO file. Your analysts, who are proficient in SQL, can easily work with BigQuery as it uses a SQL interface.

The correct answer is C

C is the right answer , as

C. Create external tables in BigQuery that point to Cloud Storage buckets and run a SQL query on these external tables to complete your request.

C. Create external tables in BigQuery that point to Cloud Storage buckets and run a SQL query on these external tables to complete your request.

Answer C is the most cost-effective and efficient way to provide analysts access to the data stored in the 5-TB AVRO file in Cloud Storage. Here's why: You can create external tables in BigQuery that point to the 5-TB AVRO file stored in Cloud Storage. External tables allow you to query data stored in Cloud Storage without the need to load the data into BigQuery. This is a cost-effective way to provide your analysts' access to the data they need, and it is also an efficient solution since you can run SQL queries on the data directly in BigQuery.

External tables in BigQuery

C is correct: https://cloud.google.com/bigquery/external-data-sources

external tables in BigQuery

Similar to Athena

C. is correct, An external data source is a data source that you can query directly from BigQuery, even though the data is not stored in BigQuery storage. BigQuery supports the following external data sources: Amazon S3 Azure Storage Cloud Bigtable Cloud Spanner Cloud SQL Cloud Storage Drive

answer is c

mohdafiuddin explanation is very detailed .. C is right

Go for C