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Google Data Engineer Sample Questions:

1. Which of the following is NOT true about Dataflow pipelines?

A) Dataflow pipelines can consume data from other Google Cloud services
B) Dataflow pipelines are tied to Dataflow, and cannot be run on any other runner
C) Dataflow pipelines can be programmed in Java
D) Dataflow pipelines use a unified programming model, so can work both with streaming and batch data sources

2. You launched a new gaming app almost three years ago. You have been uploading log files from the previous day to a separate Google BigQuery table with the table name format LOGS_yyyymmdd. You have been using table wildcard functions to generate daily and monthly reports for all time ranges. Recently, you discovered that some queries that cover long date ranges are exceeding the limit of 1,000 tables and failing. How can you resolve this issue?

A) Create separate views to cover each month, and query from these views
B) Convert all daily log tables into date-partitioned tables
C) Enable query caching so you can cache data from previous months
D) Convert the sharded tables into a single partitioned table

3. You are building a new data pipeline to share data between two different types of applications: jobs generators and job runners. Your solution must scale to accommodate increases in usage and must accommodate the addition of new applications without negatively affecting the performance of existing ones. What should you do?

A) Create a table on Cloud SQL, and insert and delete rows with the job information
B) Use a Cloud Pub/Sub topic to publish jobs, and use subscriptions to execute them
C) Create a table on Cloud Spanner, and insert and delete rows with the job information
D) Create an API using App Engine to receive and send messages to the applications

4. Which of the following is NOT one of the three main types of triggers that Dataflow supports?

A) Trigger based on time
B) Trigger that is a combination of other triggers
C) Trigger based on element count
D) Trigger based on element size in bytes

5. You are planning to use Google's Dataflow SDK to analyze customer data such as displayed below. Your project requirement is to extract only the customer name Passing Certification Exams Made Easy visit - https://www.2PassEasy.com from the data source and then write to an output PCollection.
Tom,555 X street Tim,553 Y street Sam, 111 Z street
Which operation is best suited for the above data processing requirement?

A) Source API
B) Sink API
C) Data extraction
D) ParDo

Solutions: