Your company has recently grown rapidly and now ingesting data at a significantly higher rate
than it was previously. You manage the daily batch MapReduce analytics jobs in Apache
Hadoop. However, the recent increase in data has meant the batch jobs are fal ing behind. You
were asked to recommend ways the development team could increase the responsiveness of
the analytics without increasing costs. What should you recommend they do?
A. Rewrite the job in Pig.
B. Rewrite the job in Apache Spark.
C. Increase the size of the Hadoop cluster.
D. Decrease the size of the Hadoop cluster but also rewrite the job in Hive.
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, fol owed by the value of the LastName field for
each employee. How can you make that data available while minimizing cost?
A. Create a view in BigQuery that concatenates the FirstName and LastName field values to
produce the Ful Name.
B. Add a new column called Ful Name to the Users table. Run an UPDATE statement that
updates the Ful Name column for each user with the concatenation of the FirstName and
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 Ful Name into a new table in BigQuery.
D. Use BigQuery to export the data for the table to a CSV file. 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 FullName. Run a BigQuery load job to load the new CSV file into
You are deploying a new storage system for your mobile application, which is a media
streaming service. You decide the best fit is Google Cloud Datastore. You have entities with
multiple properties, some of which can take on multiple values. For example, in the entity
`Movie' the property `actors' and the property `tags' have multiple values but the property `date
released' does not. A typical query would ask for all movies with actor=<actorname> ordered by
date_released or all movies with tag=Comedy ordered by date_released. How should you avoid
a combinatorial explosion in the number of indexes?