Google Certified Professional Data Engineer Set 1 Welcome to Google Certified Professional Data Engineer Set 1.Click on Next Button to proceed. 1. What is a pipeline in the context of Cloud Dataflow? A pipeline represents the entire series of steps involved in ingesting data, transforming that data and writing output. A pipeline could be any of these. A pipeline represents a collection of data being prepared for transformation.2. Your company stores data in BigQuery for long-term and short-term analytics queries. Most of the jobs only need to study the last 7 days of data. Over time, the cost of queries keeps going up. How can you redesign the database to lower the cost of the most frequent queries? Create a new table every 7 days. Maintain a separate table that duplicates the weekly tables to contain all data. Create a new table every 7 days. Use JOIN statements to conduct long-term analytics queries. Use DATE partitioned tables.3. What method could you use to help compute averages when dealing with unbounded/streaming data? Change the input data to be batched/bounded to make it easier to compute averages Session windows Sliding windows4. If you have 2 replicating clusters in your Bigtable instance, how can you ensure that your application will be guaranteed strong consistency for its transactions? Use an application profile that specifies single-cluster routing. Refactor your application so that strong consistency is no longer required. Use an application profile that specifies multi-cluster routing, but place both clusters within the same region.5. How does Bigtable managed rows, tables and tablets? Tables are sorted into contiguous rows, and stored in a single tablet Tables are sorted into contiguous rows, and sharded into tablets Tables contain unsorted rows, and stored in a single tablet6. Bigtable is compatible with which open source project's client library for Java? Apache HBase Apache Kafka Apache Cassandra7. For what types of data workload would Bigtable *not* be a good fit? (Choose 2) Small datasets below 300GB in size Time-series data Internet of things data Relational data requiring SQL-type queries8. What is the compute model of Cloud Dataflow? Dataflow fully manages Compute Engine services to run jobs. Dataflow manages Cloud Storage but requires a pre-built Kubernetes Engine cluster to run jobs. Dataflow requires a pre-built Cloud Dataproc cluster to run jobs.9. You are required to load a large volume of data into BigQuery that does contain some duplication. What should you do to ensure the best query performance once the data is loaded? Denormalize the data by using nested or repeated fields. Normalize the data to eliminate duplicates from being stored, and reformat the data as JSON. Normalize the data to eliminate duplicates from being stored, and reformat the data as Avro.10. A customer has 90TB of archive data to move to Google Cloud Storage, but has restrictions on connecting their private network to the public Internet. How could you facilitate this? Create bastion hosts that connect to the private network and Google Cloud, and start multiple uploads to GCS using gsutil Use the 100TB Transfer Appliance Create bastion hosts that connect to the private network and Google Cloud, and start a single upload to GCS using gsutil11. Which native output connectors are supported by Dataproc? (Choose 3) BigQuery Cloud Bigtable Cloud Storage Cloud Firestore Cloud SQL12. True of False: Preemptible workers in a Dataproc cluster cannot store HDFS data. True False13. A customer wants to run Spark jobs on a low-cost ephemeral Dataproc cluster, utilizing preemptible workers wherever possible, but needs to store the results of Dataproc jobs persistently. What would you recommend? Do not use preemptible workers at all, it will prevent you from choosing any persistent storage option. Use a secondary group of preemptible worker nodes, but add custom code to a job that copies its results to Cloud Storage. Use the Cloud Storage connector, and specify GCS locations for the input and ouput of jobs.14. What are some ways to help control costs in BigQuery? (Choose 2) There are no ways to control the cost of BigQuery. Preview queries before running them. Use LIMIT clauses in SQL queries. Only query specific columns, avoiding SELECT *.15. Which GCP product implements the Apache Beam SDK and is sometimes recommended as an alternative to Dataproc particularly for streaming data? Cloud Composer Cloud Dataflow Cloud Datalab16. When you run a query in BigQuery, what happens to the results? Query results exist only within the BigQuery UI and are not stored in a table. Query results are either written to a destination table specified by the user, or to a temporary cached results table. Query results exist only in BigQuery memory and are not stored in a table.17. A customer needs a JSON document store NoSQL database to help them develop a new application. Which GCP product should they choose? Cloud SQL Cloud Firestore Cloud Bigtable18. Your customer would like to use Dataproc, but the standard image does not contain some additional Spark components required to run their jobs. What would you recommend? Use a Dataproc cluster, but specify an initialization action that installs all of the additional components. Create custom Dataproc image that fulfils the customer requirements and use it to deploy a Dataproc cluster. Create an image that fulfils the customer requirements and use it to deploy a custom Spark cluster using Compute Engine.19. What is the best way to grant someone temporary access to a file if they do not have a Google account? Use a signed URL with a specific expiry Make the file publicly accessible but ask the user not to share the link Use a long and complex name for the bucket and object20. You are required to share a subset of data from a BigQuery data set with a 3rd party analytics team. The data may change over time, and you should not grant unnecessary projects permissions to this team if you can avoid it. How should you proceed? Create an authorized view based on a specific query for the subset of data, and provide access for the team only to that view. Create an export of the data subset to a Cloud Storage bucket. Provide a signed URL for the team to download the data from the bucket. Add the team to your GCP project and assign them the BigQuery Data Viewer IAM role for the data set.21. How does Bigtable managed the storage of tablets? Tablets are stored on cluster nodes, but storage can dynamically grow as part of the managed service Tablets are stored on cluster nodes, which must be sized accordingly for their storage needs Tablets are stored in Google Colossus, but a cluster node has a limit on how much storage it can process22. What is a federated data source? A BigQuery data set that belongs to a different GCP project, used in an SQL statement. An external data source that can be queried directly even though the data is not stored in BigQuery. A BigQuery table that belongs to a different data set, used in an SQL statement.23. What is the name given to a dataset that can be acted upon within a Cloud Dataflow pipeline? Bucket PCollection Aggregation24. Which primary Apache services does Dataproc run? (Choose 2) Dataflow Cassandra Spark Hadoop25. Using Cloud IAM, what is the most granular level for which you can configure access control for Pub/Sub? Across individual topcis and subscriptions Across individual topics, but not subscriptions Across the entire project, including all topics and subscriptions26 out of 1Please fill in the comment box below. Email
