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NEW QUESTION 20
Your team is responsible for developing and maintaining ETLs in your company. One of your Dataflow jobs is failing because of some errors in the input data, and you need to improve reliability of the pipeline (incl.
being able to reprocess all failing data).
What should you do?

A. Add a try... catch block to your DoFn that transforms the data, use a sideOutput to create a PCollection that can be stored to PubSub later.B. Add a try... catch block to your DoFn that transforms the data, write erroneous rows to PubSub directly from the DoFn.C. Add a filtering step to skip these types of errors in the future, extract erroneous rows from logs.D. Add a try... catch block to your DoFn that transforms the data, extract erroneous rows from logs.

Answer: A

Explanation:
https://cloud.google.com/blog/products/gcp/handling-invalid-inputs-in-dataflow

 

NEW QUESTION 21
You are designing a data processing pipeline. The pipeline must be able to scale automatically as load increases. Messages must be processed at least once and must be ordered within windows of 1 hour. How should you design the solution?

A. Use Apache Kafka for message ingestion and use Cloud Dataflow for streaming analysis.B. Use Cloud Pub/Sub for message ingestion and Cloud Dataflow for streaming analysis.C. Use Apache Kafka for message ingestion and use Cloud Dataproc for streaming analysis.D. Use Cloud Pub/Sub for message ingestion and Cloud Dataproc for streaming analysis.

Answer: D

Explanation:
Explanation

 

NEW QUESTION 22
Which of the following statements about Legacy SQL and Standard SQL is not true?

A. Standard SQL is the preferred query language for BigQuery.B. One difference between the two query languages is how you specify fully-qualified table names (i.e.
table names that include their associated project name).C. You need to set a query language for each dataset and the default is Standard SQL.D. If you write a query in Legacy SQL, it might generate an error if you try to run it with Standard SQL.

Answer: C

Explanation:
Explanation
You do not set a query language for each dataset. It is set each time you run a query and the default query language is Legacy SQL.
Standard SQL has been the preferred query language since BigQuery 2.0 was released.
In legacy SQL, to query a table with a project-qualified name, you use a colon, :, as a separator. In standard SQL, you use a period, ., instead.
Due to the differences in syntax between the two query languages (such as with project-qualified table names), if you write a query in Legacy SQL, it might generate an error if you try to run it with Standard SQL.
Reference:
https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql

 

NEW QUESTION 23
You have Google Cloud Dataflow streaming pipeline running with a Google Cloud Pub/Sub subscription as the source. You need to make an update to the code that will make the new Cloud Dataflow pipeline incompatible with the current version. You do not want to lose any data when making this update. What should you do?

A. Update the current pipeline and use the drain flag.B. Create a new pipeline that has the same Cloud Pub/Sub subscription and cancel the old pipeline.C. Update the current pipeline and provide the transform mapping JSON object.D. Create a new pipeline that has a new Cloud Pub/Sub subscription and cancel the old pipeline.

Answer: D

 

NEW QUESTION 24
Your company's customer and order databases are often under heavy load. This makes performing analytics against them difficult without harming operations. The databases are in a MySQL cluster, with nightly backups taken using mysqldump. You want to perform analytics with minimal impact on operations.
What should you do?

A. Connect an on-premises Apache Hadoop cluster to MySQL and perform ETL.B. Mount the backups to Google Cloud SQL, and then process the data using Google Cloud Dataproc.C. Add a node to the MySQL cluster and build an OLAP cube there.D. Use an ETL tool to load the data from MySQL into Google BigQuery.

Answer: A

 

NEW QUESTION 25
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