You are implementing several batch jobs that must be executed on a schedule. These jobs have many interdependent steps that must be executed in a specific order. Portions of the jobs involve executing shell scripts, running Hadoop jobs, and running queries in BigQuery. The jobs are expected to run for many minutes up to several hours. If the steps fail, they must be retried a fixed number of times. Which service should you use to manage the execution of these jobs?

• A. Cloud Composer
• B. Cloud Scheduler
• C. Cloud Dataflow
• D. Cloud Functions

You are designing storage for two relational tables that are part of a 10-TB database on Google Cloud. You want to support transactions that scale horizontally. You also want to optimize data for range queries on nonkey columns. What should you do?

• A. Use Cloud SQL for storag
• B. Use Cloud Spanner for storag
• C. Use Cloud Spanner for storag
• D. Use Cloud Dataflow to transform data to support query patterns.
• E. Add secondary indexes to support query patterns.
• F. Use Cloud SQL for storag
• G. Use Cloud Dataflow to transform data to support query patterns.
• H. Add secondary indexes to support query patterns.

You need to deploy additional dependencies to all of a Cloud Dataproc cluster at startup using an existing initialization action. Company security policies require that Cloud Dataproc nodes do not have access to the Internet so public initialization actions cannot fetch resources. What should you do?

• A. Copy all dependencies to a Cloud Storage bucket within your VPC security perimeter
• B. Deploy the Cloud SQL Proxy on the Cloud Dataproc master
• C. Use Resource Manager to add the service account used by the Cloud Dataproc cluster to the Network User role
• D. Use an SSH tunnel to give the Cloud Dataproc cluster access to the Internet

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. Data extraction
• B. ParDo
• C. Source API
• D. Sink API

You architect a system to analyze seismic dat
a. Your extract, transform, and load (ETL) process runs as a series of MapReduce jobs on an Apache Hadoop cluster. The ETL process takes days to process a data set because some steps are computationally expensive. Then you discover that a sensor calibration step has been omitted. How should you change your ETL process to carry out sensor calibration systematically in the future?

• A. Introduce a new MapReduce job to apply sensor calibration to raw data, and ensure all other MapReduce jobs are chained after this.
• B. Add sensor calibration data to the output of the ETL process, and document that all users need to apply sensor calibration themselves.
• C. Modify the transformMapReduce jobs to apply sensor calibration before they do anything else.
• D. Develop an algorithm through simulation to predict variance of data output from the last MapReduce job based on calibration factors, and apply the correction to all data.