Exam - 5

Question 1

Which is not a valid reason for poor Cloud Bigtable performance?
A. The workload isn’t appropriate for Cloud Bigtable.
B. The table’s schema is not designed correctly.
C. The Cloud Bigtable cluster has too many nodes.
D. There are issues with the network connection.

Answer 1

C. The Cloud Bigtable cluster has too many nodes.

Question 2

Which action can a Cloud Dataproc Viewer perform?
A. Submit a job.
B. Create a cluster.
C. Delete a cluster.
D. List the jobs.

Answer 2

D. List the jobs.
A Cloud Dataproc Viewer is limited in its actions based on its role. A viewer can only list clusters, get cluster details, list jobs, get job details, list operations, and get operation details.

Question 3

Which SQL keyword can be used to reduce the number of columns processed by BigQuery?
A. BETWEEN
B. WHERE
C. SELECT
D. LIMIT

Answer 3

C. SELECT
SELECT allows you to query specific columns rather than the whole table.
LIMIT, BETWEEN, and WHERE clauses will not reduce the number of columns processed by
BigQuery.

Question 4

The _________ for Cloud Bigtable makes it possible to use Cloud Bigtable in a Cloud Dataflow pipeline.
A. Cloud Dataflow connector
B. DataFlow SDK
C. BiqQuery API
D. BigQuery Data Transfer Service

Answer 4

A. Cloud Dataflow connector

Question 5

When you design a Google Cloud Bigtable schema it is recommended that you _________.
A. Avoid schema designs that are based on NoSQL concepts
B. Create schema designs that are based on a relational database design
C. Avoid schema designs that require atomicity across rows
D. Create schema designs that require atomicity across rows

Answer 5

C. Avoid schema designs that require atomicity across rows
All operations are atomic at the row level. For example, if you update two rows in a table, it’s possible that one row will be updated successfully and the other update will fail. Avoid schema designs that require atomicity across rows.

Question 6

When running a pipeline that has a BigQuery source, on your local machine, you continue to get permission denied errors. What could be the reason for that?
A. Your gcloud does not have access to the BigQuery resources
B. BigQuery cannot be accessed from local machines
C. You are missing gcloud on your machine
D. Pipelines cannot be run locally

Answer 6

A. Your gcloud does not have access to the BigQuery resources
When reading from a Dataflow source or writing to a Dataflow sink using DirectPipelineRunner, the Cloud Platform account that you configured with the gcloud executable will need access to the corresponding source/sink

Question 7

Which of the following statements about the Wide & Deep Learning model are true? (Select 2 answers.)
A. The wide model is used for memorization, while the deep model is used for generalization.
B. A good use for the wide and deep model is a recommender system.
C. The wide model is used for generalization, while the deep model is used for memorization.
D. A good use for the wide and deep model is a small-scale linear regression problem.

Answer 7

A. The wide model is used for memorization, while the deep model is used for generalization.
B. A good use for the wide and deep model is a recommender system.

Can we teach computers to learn like humans do, by combining the power of memorization and generalization? It’s not an easy question to answer, but by jointly training a wide linear model (for memorization) alongside a deep neural network (for generalization), one can combine the strengths of both to bring us one step closer. At Google, we call it Wide & Deep Learning. It’s useful for generic large-scale regression and classification problems with sparse inputs (categorical features with a large number of possible feature values), such as recommender systems, search, and ranking problems.

Question 8

How would you query specific partitions in a BigQuery table?
A. Use the DAY column in the WHERE clause
B. Use the EXTRACT(DAY) clause
C. Use the __PARTITIONTIME pseudo-column in the WHERE clause
D. Use DATE BETWEEN in the WHERE clause

Answer 8

C. Use the __PARTITIONTIME pseudo-column in the WHERE clause

Partitioned tables include a pseudo column named _PARTITIONTIME that contains a date-based timestamp for data loaded into the table. To limit a query to particular partitions (such as Jan 1st and 2nd of 2017), use a clause similar to this:
WHERE _PARTITIONTIME BETWEEN TIMESTAMP(‘2017-01-01’) AND TIMESTAMP(‘2017-01-02’)

Question 9

What are the minimum permissions needed for a service account used with Google Dataproc?
A. Execute to Google Cloud Storage; write to Google Cloud Logging
B. Write to Google Cloud Storage; read to Google Cloud Logging
C. Execute to Google Cloud Storage; execute to Google Cloud Logging
D. Read and write to Google Cloud Storage; write to Google Cloud Logging

Answer 9

D. Read and write to Google Cloud Storage; write to Google Cloud Logging

Service accounts authenticate applications running on your virtual machine instances to other Google Cloud Platform services. For example, if you write an application that reads and writes files on Google Cloud Storage, it must first authenticate to the Google Cloud Storage API. At a minimum, service accounts used with Cloud Dataproc need permissions to read and write to Google Cloud Storage, and to write to Google Cloud Logging.

Question 10

When a Cloud Bigtable node fails, ____ is lost.
A. all data
B. no data
C. the last transaction
D. the time dimension

Answer 10

B. no data
A Cloud Bigtable table is sharded into blocks of contiguous rows, called tablets, to help balance the workload of queries. Tablets are stored on Colossus, Google’s file system, in SSTable format. Each tablet is associated with a specific Cloud Bigtable node.
Data is never stored in Cloud Bigtable nodes themselves; each node has pointers to a set of tablets that are stored on Colossus. As a result:
Rebalancing tablets from one node to another is very fast, because the actual data is not copied. Cloud Bigtable simply updates the pointers for each node.
Recovery from the failure of a Cloud Bigtable node is very fast, because only metadata needs to be migrated to the replacement node.
When a Cloud Bigtable node fails, no data is lost

Question 11

Which of the following statements is NOT true regarding Bigtable access roles?
A. Using IAM roles, you cannot give a user access to only one table in a project, rather than all tables in a project.
B. To give a user access to only one table in a project, grant the user the Bigtable Editor role for that table.
C. You can configure access control only at the project level.
D. To give a user access to only one table in a project, you must configure access through your application.

Answer 11

B. To give a user access to only one table in a project, grant the user the Bigtable Editor role for that table.
Reason: there is no Editor role

Question 12

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

Answer 12

A. A sequential numeric ID
B. A timestamp followed by a stock symbol
Reason: Similar row keys at the same time

Question 13

Which is the preferred method to use to avoid hotspotting in time series data in Bigtable?
A. Field promotion
B. Randomization
C. Salting
D. Hashing

Answer 13

A. Field promotion
Reason: Include a field such as user id into the row key to reduce hotspotting. B works but not as good for query.

Question 14

Which of the following statements about Legacy SQL and Standard SQL is not true?
A. Standard SQL is the preferred query language for BigQuery.
B. If you write a query in Legacy SQL, it might generate an error if you try to run it with Standard SQL.
C. One difference between the two query languages is how you specify fully-qualified table names (i.e. table names that include their associated project name).
D. You need to set a query language for each dataset and the default is Standard SQL.

Answer 14

D. You need to set a query language for each dataset and the default is Standard SQL.

You do not set a query language for each dataset. It is set each time you run a query and the default query language is Legacy SQL.
Standard SQL has been the preferred query language since BigQuery 2.0 was released.
In legacy SQL, to query a table with a project-qualified name, you use a colon, :, as a separator. In standard SQL, you use a period, ., instead.
Due to the differences in syntax between the two query languages (such as with project-qualified table names), if you write a query in Legacy SQL, it might generate an error if you try to run it with Standard SQL.

Question 15

Which of the following is NOT a valid use case to select HDD (hard disk drives) as the storage for Google Cloud Bigtable?
A. You expect to store at least 10 TB of data.
B. You will mostly run batch workloads with scans and writes, rather than frequently executing random reads of a small number of rows.
C. You need to integrate with Google BigQuery.
D. You will not use the data to back a user-facing or latency-sensitive application.

Answer 15

C. You need to integrate with Google BigQuery.

For example, if you plan to store extensive historical data for a large number of remote-sensing devices and then use the data to generate daily reports, the cost savings for HDD storage may justify the performance tradeoff. On the other hand, if you plan to use the data to display a real-time dashboard, it probably would not make sense to use HDD storagereads would be much more frequent in this case, and reads are much slower with HDD storage.

Question 16

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. Transform
C. Pipeline
D. Sink API

Answer 16

B. Transform
In Google Cloud, the Dataflow SDK provides a transform component. It is responsible for the data processing operation. You can use conditional, for loops, and other complex programming structure to create a branching pipeline.

Question 17

Which Java SDK class can you use to run your Dataflow programs locally?
A. LocalRunner
B. DirectPipelineRunner
C. MachineRunner
D. LocalPipelineRunner

Answer 17

B. DirectPipelineRunner
DirectPipelineRunner allows you to execute operations in the pipeline directly, without any optimization. Useful for small local execution and tests

Question 18

Which of these statements about BigQuery caching is true?
A. By default, a query’s results are not cached.
B. BigQuery caches query results for 48 hours.
C. Query results are cached even if you specify a destination table.
D. There is no charge for a query that retrieves its results from cache.

Answer 18

D. There is no charge for a query that retrieves its results from cache.

When query results are retrieved from a cached results table, you are not charged for the query.
BigQuery caches query results for 24 hours, not 48 hours.
Query results are not cached if you specify a destination table.
A query’s results are always cached except under certain conditions, such as if you specify a destination table.

Question 19

Which of these operations can you perform from the BigQuery Web UI?
A. Upload a file in SQL format.
B. Load data with nested and repeated fields.
C. Upload a 20 MB file.
D. Upload multiple files using a wildcard.

Answer 19

B. Load data with nested and repeated fields.

You can load data with nested and repeated fields using the Web UI.
You cannot use the Web UI to:
- Upload a file greater than 10 MB in size
- Upload multiple files at the same time
- Upload a file in SQL format
All three of the above operations can be performed using the “bq” command.

Question 20

What is the general recommendation when designing your row keys for a Cloud Bigtable schema?
A. Include multiple time series values within the row key
B. Keep the row keep as an 8 bit integer
C. Keep your row key reasonably short
D. Keep your row key as long as the field permits

Answer 20

C. Keep your row key reasonably short

A general guide is to, keep your row keys reasonably short. Long row keys take up additional memory and storage and increase the time it takes to get responses from the Cloud Bigtable server.

Question 21

What is the recommended action to do in order to switch between SSD and HDD storage for your Google Cloud Bigtable instance?
A. create a third instance and sync the data from the two storage types via batch jobs
B. export the data from the existing instance and import the data into a new instance
C. run parallel instances where one is HDD and the other is SDD
D. the selection is final and you must resume using the same storage type

Answer 21

B. export the data from the existing instance and import the data into a new instance

When you create a Cloud Bigtable instance and cluster, your choice of SSD or HDD storage for the cluster is permanent. You cannot use the Google Cloud
Platform Console to change the type of storage that is used for the cluster.
If you need to convert an existing HDD cluster to SSD, or vice-versa, you can export the data from the existing instance and import the data into a new instance.

Alternatively, you can write -
a Cloud Dataflow or Hadoop MapReduce job that copies the data from one instance to another.

Question 22

Cloud Dataproc charges you only for what you really use with _____ billing.
A. month-by-month
B. minute-by-minute
C. week-by-week
D. hour-by-hour

Answer 22

B. minute-by-minute
One of the advantages of Cloud Dataproc is its low cost. Dataproc charges for what you really use with minute-by-minute billing and a low, ten-minute-minimum billing period.

Question 23

Which of the following job types are supported by Cloud Dataproc (select 3 answers)?
A. Hive
B. Pig
C. YARN
D. Spark

Answer 23

ABD

Cloud Dataproc provides out-of-the box and end-to-end support for many of the most popular job types, including Spark, Spark SQL, PySpark, MapReduce, Hive, and Pig jobs.

Question 24

Which of the following IAM roles does your Compute Engine account require to be able to run pipeline jobs?
A. dataflow.worker
B. dataflow.compute
C. dataflow.developer
D. dataflow.viewer

Answer 24

A. dataflow.worker

Question 25

Which of these statements about exporting data from BigQuery is false? A. To export more than 1 GB of data, you need to put a wildcard in the destination filename. B. The only supported export destination is Google Cloud Storage. C. Data can only be exported in JSON or Avro format. D. The only compression option available is GZIP.

Answer 25

C. Data can only be exported in JSON or Avro format. You cannot export table data to a local file, to Google Sheets, or to Google Drive. The only supported export location is Cloud Storage. For information on saving query results, see Downloading and saving query results. You can export up to 1 GB of table data to a single file. If you are exporting more than 1 GB of data, use a wildcard to export the data into multiple files. When you export data to multiple files, the size of the files will vary. You cannot export nested and repeated data in CSV format. Nested and repeated data is supported for Avro and JSON exports. When you export data in JSON format, INT64 (integer) data types are encoded as JSON strings to preserve 64-bit precision when the data is read by other systems. You cannot export data from multiple tables in a single export job. You cannot choose a compression type other than GZIP when you export data using the Cloud Console or the classic BigQuery web UI.

Question 26

Which of these numbers are adjusted by a neural network as it learns from a training dataset (select 2 answers)? A. Weights B. Biases C. Continuous features D. Input values

Answer 26

A. Weights B. Biases A neural network is a simple mechanism thats implemented with basic math. The only difference between the traditional programming model and a neural network is that you let the computer determine the parameters (weights and bias) by learning from training datasets.

Question 27

Which of these is not a supported method of putting data into a partitioned table? A. If you have existing data in a separate file for each day, then create a partitioned table and upload each file into the appropriate partition. B. Run a query to get the records for a specific day from an existing table and for the destination table, specify a partitioned table ending with the day in the format “$YYYYMMDD”. C. Create a partitioned table and stream new records to it every day. D. Use ORDER BY to put a table’s rows into chronological order and then change the table’s type to “Partitioned”.

Answer 27

D. Use ORDER BY to put a table’s rows into chronological order and then change the table’s type to “Partitioned”. You cannot change an existing table into a partitioned table. You must create a partitioned table from scratch. Then you can either stream data into it every day and the data will automatically be put in the right partition, or you can load data into a specific partition by using “$YYYYMMDD” at the end of the table name.

Question 28

Which Google Cloud Platform service is an alternative to Hadoop with Hive? A. Cloud Dataflow B. Cloud Bigtable C. BigQuery D. Cloud Datastore

Answer 28

C. BigQuery Apache Hive is a data warehouse software project built on top of Apache Hadoop for providing data summarization, query, and analysis. Google BigQuery is an enterprise data warehouse.

Question 29

For the best possible performance, what is the recommended zone for your Compute Engine instance and Cloud Bigtable instance? A. Have the Compute Engine instance in the furthest zone from the Cloud Bigtable instance. B. Have both the Compute Engine instance and the Cloud Bigtable instance to be in different zones. C. Have both the Compute Engine instance and the Cloud Bigtable instance to be in the same zone. D. Have the Cloud Bigtable instance to be in the same zone as all of the consumers of your data.

Answer 29

C. Have both the Compute Engine instance and the Cloud Bigtable instance to be in the same zone. It is recommended to create your Compute Engine instance in the same zone as your Cloud Bigtable instance for the best possible performance, If it’s not possible to create a instance in the same zone, you should create your instance in another zone within the same region. For example, if your Cloud Bigtable instance is located in us-central1-b, you could create your instance in us-central1-f. This change may result in several milliseconds of additional latency for each Cloud Bigtable request. It is recommended to avoid creating your Compute Engine instance in a different region from your Cloud Bigtable instance, which can add hundreds of milliseconds of latency to each Cloud Bigtable request.

Question 30

Which methods can be used to reduce the number of rows processed by BigQuery? A. Splitting tables into multiple tables; putting data in partitions B. Splitting tables into multiple tables; putting data in partitions; using the LIMIT clause C. Putting data in partitions; using the LIMIT clause D. Splitting tables into multiple tables; using the LIMIT clause

Answer 30

A. Splitting tables into multiple tables; putting data in partitions

Question 31

The Dataflow SDKs have been recently transitioned into which Apache service? A. Apache Spark B. Apache Hadoop C. Apache Kafka D. Apache Beam

Answer 31

D. Apache Beam

Question 32

Cloud Dataproc is a managed Apache Hadoop and Apache _____ service. A. Blaze B. Spark C. Fire D. Ignite

Answer 32

B. Spark Cloud Dataproc is a managed Apache Spark and Apache Hadoop service that lets you use open source data tools for batch processing, querying, streaming, and machine learning.

Question 33

When creating a new Cloud Dataproc cluster with the projects.regions.clusters.create operation, these four values are required: project, region, name, and ____. A. zone B. node C. label D. type

Answer 33

A. zone At a minimum, you must specify four values when creating a new cluster with the projects.regions.clusters.create operation: The project in which the cluster will be created The region to use - The name of the cluster - The zone in which the cluster will be created You can specify many more details beyond these minimum requirements. For example, you can also specify the number of workers, whether preemptible compute should be used, and the network settings.

Question 34

Which of the following is not possible using primitive roles? A. Give a user viewer access to BigQuery and owner access to Google Compute Engine instances. B. Give UserA owner access and UserB editor access for all datasets in a project. C. Give a user access to view all datasets in a project, but not run queries on them. D. Give GroupA owner access and GroupB editor access for all datasets in a project.

Answer 34

C. Give a user access to view all datasets in a project, but not run queries on them. Primitive roles can be used to give owner, editor, or viewer access to a user or group, but they can’t be used to separate data access permissions from job-running permissions.

Question 35

If you’re running a performance test that depends upon Cloud Bigtable, all the choices except one below are recommended steps. Which is NOT a recommended step to follow? A. Do not use a production instance. B. Run your test for at least 10 minutes. C. Before you test, run a heavy pre-test for several minutes. D. Use at least 300 GB of data.

Answer 35

A. Do not use a production instance. If you’re running a performance test that depends upon Cloud Bigtable, be sure to follow these steps as you plan and execute your test: Use a production instance. A development instance will not give you an accurate sense of how a production instance performs under load. Use at least 300 GB of data. Cloud Bigtable performs best with 1 TB or more of data. However, 300 GB of data is enough to provide reasonable results in a performance test on a 3-node cluster. On larger clusters, use 100 GB of data per node. Before you test, run a heavy pre-test for several minutes. This step gives Cloud Bigtable a chance to balance data across your nodes based on the access patterns it observes. Run your test for at least 10 minutes. This step lets Cloud Bigtable further optimize your data, and it helps ensure that you will test reads from disk as well as cached reads from memory.

Question 36

Suppose you have a table that includes a nested column called “city” inside a column called “person”, but when you try to submit the following query in BigQuery, it gives you an error. SELECT person FROM project1.example.table1 WHERE city = “London” How would you correct the error? A. Add “, UNNEST(person)” before the WHERE clause. B. Change “person” to “person.city”. C. Change “person” to “city.person”. D. Add “, UNNEST(city)” before the WHERE clause.

Answer 36

A. Add “, UNNEST(person)” before the WHERE clause. To access the person.city column, you need to “UNNEST(person)” and JOIN it to table1 using a comma.

Question 37

Which of these are examples of a value in a sparse vector? (Select 2 answers.) A. [0, 5, 0, 0, 0, 0] B. [0, 0, 0, 1, 0, 0, 1] C. [0, 1] D. [1, 0, 0, 0, 0, 0, 0]

Answer 37

C. [0, 1] D. [1, 0, 0, 0, 0, 0, 0] [0, 0, 0, 1, 0, 0, 1] is not a sparse vector because it has two 1s in it. A sparse vector contains only a single 1. [0, 5, 0, 0, 0, 0] is not a sparse vector because it has a 5 in it. Sparse vectors only contain 0s and 1s.

Question 38

To give a user read permission for only the first three columns of a table, which access control method would you use? A. Primitive role B. Predefined role C. Authorized view D. It’s not possible to give access to only the first three columns of a table.

Answer 38

C. Authorized view An authorized view allows you to share query results with particular users and groups without giving them read access to the underlying tables. Authorized views can only be created in a dataset that does not contain the tables queried by the view. When you create an authorized view, you use the view’s SQL query to restrict access to only the rows and columns you want the users to see.

Question 39

Suppose you have a dataset of images that are each labeled as to whether or not they contain a human face. To create a neural network that recognizes human faces in images using this labeled dataset, what approach would likely be the most effective? A. Use K-means Clustering to detect faces in the pixels. B. Use feature engineering to add features for eyes, noses, and mouths to the input data. C. Use deep learning by creating a neural network with multiple hidden layers to automatically detect features of faces. D. Build a neural network with an input layer of pixels, a hidden layer, and an output layer with two categories.

Answer 39

C. Use deep learning by creating a neural network with multiple hidden layers to automatically detect features of faces.

Question 40

If a dataset contains rows with individual people and columns for year of birth, country, and income, how many of the columns are continuous and how many are categorical? A. 1 continuous and 2 categorical B. 3 categorical C. 3 continuous D. 2 continuous and 1 categorical

Answer 40

D. 2 continuous and 1 categorical

Question 41

Which of these sources can you not load data into BigQuery from? A. File upload B. Google Drive C. Google Cloud Storage D. Google Cloud SQL

Answer 41

D. Google Cloud SQL You can load data into BigQuery from a file upload, Google Cloud Storage, Google Drive, or Google Cloud Bigtable. It is not possible to load data into BigQuery directly from Google Cloud SQL. One way to get data from Cloud SQL to BigQuery would be to export data from Cloud SQL to Cloud Storage and then load it from there.