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Google GCP-DE Exam Syllabus Topics:

Google Data Engineer Sample Questions:

1. Which of these sources can you not load data into BigQuery from?

A) Google Drive
B) Google Cloud Storage
C) Google Cloud SQL
D) File upload

2. You work for a large fast food restaurant chain with over 400,000 employees. You store employee information in Google BigQuery in a Users table consisting of a FirstName field and a LastName field. A member of IT is building an application and asks you to modify the schema and data in BigQuery so the application can query a FullName field consisting of the value of the FirstName field concatenated with a space, followed by the value of the LastName field for each employee. How can you make that data available while minimizing cost?

A) Add a new column called FullName to the Users tabl
B) Create a Google Cloud Dataproc job to process the CSV file and output a new CSV file containing the proper values for FirstName, LastName and FullNam G. Run a BigQuery load job to load the new CSV file into BigQuery.
C) Create a Google Cloud Dataflow job that queries BigQuery for the entire Users table, concatenates the FirstName value and LastName value for each user, and loads the proper values for FirstName, LastName, and FullName into a new table in BigQuery.
D) Use BigQuery to export the data for the table to a CSV fil
E) Run an UPDATE statement that updates the FullName column for each user with the concatenation of the FirstName and LastName values.
F) Create a view in BigQuery that concatenates the FirstName and LastName field values to produce the FullName.

3. Which row keys are likely to cause a disproportionate number of reads and/or writes on a particular node in a Bigtable cluster (select 2 answers)?

A) A sequential numeric ID
B) A non-sequential numeric ID
C) A stock symbol followed by a timestamp
D) A timestamp followed by a stock symbol

4. You are developing a software application using Google's Dataflow SDK, and want to use conditional, for loops and other complex programming structures to create a branching pipeline. Which component will be used for the data processing operation?

A) PCollection
B) Sink API
C) Pipeline
D) Transform

5. 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 SQ Which pipeline should you use to meet these requirements?

A) Create an application that provides an AP
B) 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.
C) 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.
D) Set up periodic exports of the database to write to Cloud Storage and load into BigQuery.
E) Write a tool to poll the API and write data to Cloud Storage as gzipped JSON files.
F) Create an application that writes to a Cloud SQL database to store the dat

Solutions: