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Question 1

Q1
A data engineer in a manufacturing(只出現一次) company is designing a data processing platform
that receives a large volume of unstructured data. The data engineer must populate
a well-structured star schema in Amazon
Redshift.
What is the most efficient architecture strategy for this purpose?
A. Transform the unstructured data using Amazon EMR and generate CSV data. COPY
the CSV data into the analysis schema within Redshift.
B. Load the unstructured data into Redshift, and use string parsing functions to
extract structured data for inserting into the analysis schema.
C. When the data is saved to Amazon S3, use S3 Event Notifications and AWS Lambda
to transform the file contents. Insert the data into the analysis schema on Redshift.
D. Normalize the data using an AWS Marketplace ETL tool, persist the results to
Amazon S3, and use AWS Lambda to INSERT the data into Redshift.

Answer 1

A. Transform the unstructured data using Amazon EMR and generate CSV data. COPY
the CSV data into the analysis schema within Redshift.

Question 2

Q2
A new algorithm has been written in Python to identify SPAM e-mails. The algorithm
analyzes the free text(Analyze free text只出現一次) contained within a sample set of 1 million e-mails stored on
Amazon S3. The algorithm must be scaled across a production dataset of 5 PB, which
also resides in Amazon S3 storage.
Which AWS service strategy is best for this use case?
A. Copy the data into Amazon ElastiCache to perform text analysis on the in-memory
data and export the results of the model into Amazon Machine Learning.
B. Use Amazon EMR to parallelize the text analysis tasks across the cluster using a
streaming program step.
C. Use Amazon Elasticsearch Service to store the text and then use the Python
Elasticsearch Client to run analysis against the text index.
D. Initiate a Python job from AWS Data Pipeline to run directly against the Amazon S3
text files.

Answer 2

B. Use Amazon EMR to parallelize the text analysis tasks across the cluster using a
streaming program step.

Question 3

Q3
A data engineer chooses Amazon DynamoDB as a data store for a regulated
application. This application must be submitted to regulators for review. The data
engineer needs to provide a control framework that lists the security controls from
the process to follow to add new users down to the physical controls of the data
center, including items like security guards and cameras.
How should this control mapping be achieved using AWS?
A. Request AWS third-party audit reports and/or the AWS quality addendum and
map the AWS responsibilities to the controls that must be provided.
B. Request data center Temporary Auditor access to an AWS data center to verify the
control mapping.
C. Request relevant SLAs and security guidelines for Amazon DynamoDB and define
these guidelines within the applications architecture to map to the control
framework.
D. Request Amazon DynamoDB system architecture designs to determine how to
map the AWS responsibilities to the control that must be provided.

Answer 3

A. Request AWS third-party audit reports and/or the AWS quality addendum and
map the AWS responsibilities to the controls that must be provided.

Question 4

Q4
An administrator needs to design a distribution strategy for a star schema in a
Redshift cluster. The administrator needs to determine the optimal distribution style
for the tables in the Redshift schema.
In which three circumstances would choosing Key-based distribution be most
appropriate? (Select three.)
A. When the administrator needs to optimize a large, slowly changing dimension
table.
B. When the administrator needs to reduce cross-node traffic.
C. When the administrator needs to optimize the fact table for parity with the
number of slices.
D. When the administrator needs to balance data distribution and collocation data.
E. When the administrator needs to take advantage of data locality on a local node
for joins and aggregates.

Answer 4

B. When the administrator needs to reduce cross-node traffic.
D. When the administrator needs to balance data distribution and collocation data.
E. When the administrator needs to take advantage of data locality on a local node
for joins and aggregates.

Question 5

Q5
Company A operates in Country X. Company A maintains a large dataset of historical
purchase orders that contains personal data of their customers in the form of full
names and telephone numbers. The dataset consists of 5 text files, 1TB each.
Currently the dataset resides on-premises due to legal requirements of storing
personal data in-country. The research and development department needs to run a
clustering algorithm on the dataset and wants to use Elastic Map Reduce service in
the closest AWS region. Due to geographic distance, the minimum latency between
the on-premises system and the closet AWS region is 200 ms.
Which option allows Company A to do clustering in the AWS Cloud and meet the
legal requirement of maintaining personal data in-country?
A. Anonymize the personal data portions of the dataset and transfer the data files
into Amazon S3 in the AWS region. Have the EMR cluster read the dataset using
EMRFS.
B. Establish a Direct Connect link between the on-premises system and the AWS
region to reduce latency. Have the EMR cluster read the data directly from the
on-premises storage system over Direct Connect.
C. Encrypt the data files according to encryption standards of Country X and store
them on AWS region in Amazon S3. Have the EMR cluster read the dataset using
EMRFS.
D. Use AWS Import/Export Snowball device to securely transfer the data to the AWS
region and copy the files onto an EBS volume. Have the EMR cluster read the dataset
using EMRFS.

Answer 5

A. Anonymize the personal data portions of the dataset and transfer the data files
into Amazon S3 in the AWS region. Have the EMR cluster read the dataset using
EMRFS

Question 6

Q6
An administrator needs to design a strategy for the schema in a Redshift cluster. The
administrator needs to determine the optimal distribution style for the tables in the
Redshift schema.
In which two circumstances would choosing EVEN distribution be most appropriate?
(Choose two.)
A. When the tables are highly denormalized and do NOT participate in frequent joins.
B. When data must be grouped based on a specific key on a defined slice.
C. When data transfer between nodes must be eliminated.
D. When a new table has been loaded and it is unclear how it will be joined to
dimension.

Answer 6

A. When the tables are highly denormalized and do NOT participate in frequent joins.

D. When a new table has been loaded and it is unclear how it will be joined to
dimension.

Question 7

Q7
A large grocery distributor receives daily depletion reports from the field in the form
of gzip archives od CSV files uploaded to Amazon S3. The files range from 500MB to
5GB. These files are processed daily by an EMR job.
Recently it has been observed that the file sizes vary, and the EMR jobs take too long.
The distributor needs to tune and optimize the data processing workflow with this
limited information to improve the performance of the
EMR job.
Which recommendation should an administrator provide?
A. Reduce the HDFS block size to increase the number of task processors.
B. Use bzip2 or Snappy rather than gzip for the archives.
C. Decompress the gzip archives and store the data as CSV files.
D. Use Avro rather than gzip for the archives.

Answer 7

B. Use bzip2 or Snappy rather than gzip for the archives.

Question 8

Q8
A web-hosting company is building a web analytics tool to capture clickstream data
from all of the websites hosted within its platform and to provide near-real-time
business intelligence. This entire system is built on
AWS services. The web-hosting company is interested in using Amazon Kinesis to
collect this data and perform sliding window analytics.
What is the most reliable and fault-tolerant technique to get each website to send
data to Amazon Kinesis with every click?
A. After receiving a request, each web server sends it to Amazon Kinesis using the
Amazon Kinesis PutRecord API. Use the sessionID as a partition key and set up a loop
to retry until a success response is received.
B. After receiving a request, each web server sends it to Amazon Kinesis using the
Amazon Kinesis Producer Library .addRecords method.
C. Each web server buffers the requests until the count reaches 500 and sends them
to Amazon Kinesis using the Amazon Kinesis PutRecord API.
D. After receiving a request, each web server sends it to Amazon Kinesis using the
Amazon Kinesis PutRecord API. Use the exponential back-off algorithm for retries
until a successful response is received.

Answer 8

A. After receiving a request, each web server sends it to Amazon Kinesis using the
Amazon Kinesis PutRecord API. Use the sessionID as a partition key and set up a loop
to retry until a success response is received.

Question 9

Q9
A customer has an Amazon S3 bucket. Objects are uploaded simultaneously by a
cluster of servers from multiple streams of data. The customer maintains a catalog of
objects uploaded in Amazon S3 using an
Amazon DynamoDB table. This catalog has the following fileds: StreamName,
TimeStamp, and ServerName, from which ObjectName can be obtained.
The customer needs to define the catalog to support querying for a given stream or
server within a defined time range.
Which DynamoDB table scheme is most efficient to support these queries?
A. Define a Primary Key with ServerName as Partition Key and TimeStamp as Sort Key.
Do NOT define a Local Secondary Index or Global Secondary Index.
B. Define a Primary Key with StreamName as Partition Key and TimeStamp followed
by ServerName as Sort Key. Define a Global Secondary Index with ServerName as
partition key and TimeStamp followed by StreamName.
C. Define a Primary Key with ServerName as Partition Key. Define a Local Secondary
Index with StreamName as Partition Key. Define a Global Secondary Index with
TimeStamp as Partition Key.
D. Define a Primary Key with ServerName as Partition Key. Define a Local Secondary
Index with TimeStamp as Partition Key. Define a Global Secondary Index with
StreamName as Partition Key and TimeStamp as Sort Key.

Answer 9

B. Define a Primary Key with StreamName as Partition Key and TimeStamp followed
by ServerName as Sort Key. Define a Global Secondary Index with ServerName as
partition key and TimeStamp followed by StreamName.

Question 10

Q10
A company has several teams of analysts. Each team of analysts has their own cluster.
The teams need to run
SQL queries using Hive, Spark-SQL, and Presto with Amazon EMR. The company
needs to enable a centralized metadata layer to expose the Amazon S3 objects as
tables to the analysts.
Which approach meets the requirement for a centralized metadata layer?
A. EMRFS consistent view with a common Amazon DynamoDB table
B. Bootstrap action to change the Hive Metastore to an Amazon RDS database
C. s3distcp with the outputManifest option to generate RDS DDL
D. Naming scheme support with automatic partition discovery from Amazon S3

Answer 10

A. EMRFS consistent view with a common Amazon DynamoDB table

Question 11

Q11
An administrator needs to manage a large catalog of items from various external
sellers. The administrator needs to determine if the items should be identified as
minimally dangerous, dangerous, or highly dangerous based on their textual
descriptions. The administrator already has some items with the danger attribute,
but receives hundreds of new item descriptions every day without such classification.
The administrator has a system that captures dangerous goods reports from
customer support team of from user feedback.
What is a cost-effective architecture to solve this issue?
A. Build a set of regular expression rules that are based on the existing examples, and
run them on the DynamoDB Streams as every new item description is added to the
system.
B. Build a Kinesis Streams process that captures and marks the relevant items in the
dangerous goods reports using a Lambda function once more than two reports have
been filed.
C. Build a machine learning model to properly classify dangerous goods and run it on
the DynamoDB Streams as every new item description is added to the system.
D. Build a machine learning model with binary classification for dangerous goods and
run it on the DynamoDB Streams as every new item description is added to the
system.

Answer 11

C. Build a machine learning model to properly classify dangerous goods and run it on
the DynamoDB Streams as every new item description

Question 12

Q12
A company receives data sets coming from external providers on Amazon S3. Data
sets from different providers are dependent on one another. Data sets will arrive at
different times and in no particular order.
A data architect needs to design a solution that enables the company to do the
following:
✑ Rapidly perform cross data set analysis as soon as the data becomes available
✑ Manage dependencies between data sets that arrive at different times
Which architecture strategy offers a scalable and cost-effective solution that meets
these requirements?
A. Maintain data dependency information in Amazon RDS for MySQL. Use an AWS
Data Pipeline job to load an Amazon EMR Hive table based on task dependencies and
event notification triggers in Amazon S3.
B. Maintain data dependency information in an Amazon DynamoDB table. Use
Amazon SNS and event notifications to publish data to fleet of Amazon EC2 workers.
Once the task dependencies have been resolved, process the data with Amazon
EMR.
C. Maintain data dependency information in an Amazon ElastiCache Redis cluster.
Use Amazon S3 event notifications to trigger an AWS Lambda function that maps the
S3 object to Redis. Once the task dependencies have been resolved, process the data
with Amazon EMR.
D. Maintain data dependency information in an Amazon DynamoDB table. Use
Amazon S3 event notifications to trigger an AWS Lambda function that maps the S3
object to the task associated with it in DynamoDB. Once all task dependencies have
been resolved, process the data with Amazon EMR.

Answer 12

D. Maintain data dependency information in an Amazon DynamoDB table. Use
Amazon S3 event notifications to trigger an AWS Lambda function that maps the S3
object to the task associated with it in DynamoDB. Once all task dependencies have
been resolved, process the data with Amazon EMR.

Question 13

Q13
A media advertising company handles a large number of real-time messages sourced
from over 200 websites in real time. Processing latency must be kept low. Based on
calculations, a 60-shard Amazon Kinesis stream is more than sufficient to handle the
maximum data throughput, even with traffic spikes. The company also uses an
Amazon Kinesis Client Library (KCL) (KCL 唯一出現在題目裡面) application running on Amazon Elastic Compute
Cloud (EC2) managed by an Auto Scaling group. Amazon CloudWatch indicates an
average of 25% CPU and a modest level of network traffic across all running servers.
The company reports a 150% to 200% increase in latency of processing messages
from Amazon Kinesis during peak times. There are NO reports of delay from the sites
publishing to Amazon Kinesis.
What is the appropriate solution to address the latency?
A. Increase the number of shards in the Amazon Kinesis stream to 80 for greater
concurrency.
B. Increase the size of the Amazon EC2 instances to increase network throughput.
C. Increase the minimum number of instances in the Auto Scaling group.
D. Increase Amazon DynamoDB throughput on the checkpoint table.

Answer 13

D. Increase Amazon DynamoDB throughput on the checkpoint table.

Question 14

Q14
A Redshift data warehouse(redshift data warehouse 唯一出現的一次) has different user teams that need to query the same
table with very different query types. These user teams are experiencing poor
performance.
Which action improves performance for the user teams in this situation?
A. Create custom table views.
B. Add interleaved sort keys per team.
C. Maintain team-specific copies of the table.
D. Add support for workload management queue hopping.

Answer 14

B. Add interleaved sort keys per team.

Question 15

Q15
A company operates an international business served from a single AWS region. The
company wants to expand into a new country(唯一出現 在題目new country). The regulator for that country requires
the Data Architect to maintain a log of financial transactions in the country within 24
hours of the product transaction. The production application is latency insensitive.
The new country contains another AWS region.
What is the most cost-effective way to meet this requirement?
A. Use CloudFormation to replicate the production application to the new region.
B. Use Amazon CloudFront to serve application content locally in the country;
Amazon CloudFront logs will satisfy the requirement.
C. Continue to serve customers from the existing region while using Amazon Kinesis
to stream transaction data to the regulator.
D. Use Amazon S3 cross-region replication to copy and persist production transaction
logs to a bucket in the new countrys region.

Answer 15

D. Use Amazon S3 cross-region replication to copy and persist production transaction
logs to a bucket in the new countrys region.

Question 16

Q16
An administrator needs to design the event log storage architecture for events from
mobile devices. The event data will be processed by an Amazon EMR cluster daily for
aggregated reporting and analytics before being archived.
How should the administrator recommend storing the log data?
A. Create an Amazon S3 bucket and write log data into folders by device. Execute the
EMR job on the device folders.
B. Create an Amazon DynamoDB table partitioned on the device and sorted on date,
write log data to table. Execute the EMR job on the Amazon DynamoDB table.
C. Create an Amazon S3 bucket and write data into folders by day. Execute the EMR
job on the daily folder.
D. Create an Amazon DynamoDB table partitioned on EventID, write log data to table.
Execute the EMR job on the table.

Answer 16

C. Create an Amazon S3 bucket and write data into folders by day. Execute the EMR
job on the daily folder.

Question 17

Q17
A data engineer wants to use an Amazon Elastic Map Reduce for an application. The
data engineer needs to make sure it complies with regulatory requirements. The
auditor must be able to confirm at any point which servers are running and which
network access controls are deployed.
Which action should the data engineer take to meet this requirement?
A. Provide the auditor IAM accounts with the SecurityAudit policy attached to their
group.
B. Provide the auditor with SSH keys for access to the Amazon EMR cluster.
C. Provide the auditor with CloudFormation templates.
D. Provide the auditor with access to AWS DirectConnect to use their existing tools.

Answer 17

A. Provide the auditor IAM accounts with the SecurityAudit policy attached to their
group.(When you use SSH with AWS, you are connecting to an EC2 instance, which is a virtual server running in the cloud. When working with Amazon EMR, the most common use of SSH is to connect to the EC2 instance that is acting as the master node of the cluster.)

Question 18

Q18
A social media customer has data from different data sources including RDS running
MySQL, Redshift, and
Hive on EMR. To support better analysis, the customer needs to be able to analyze
data from different data sources and to combine the results.
What is the most cost-effective solution to meet these requirements?
A. Load all data from a different database/warehouse to S3. Use Redshift COPY
command to copy data to Redshift for analysis.
B. Install Presto on the EMR cluster where Hive sits. Configure MySQL and
PostgreSQL connector to select from different data sources in a single query.
C. Spin up an Elasticsearch cluster. Load data from all three data sources and use
Kibana to analyze.
D. Write a program running on a separate EC2 instance to run queries to three
different systems. Aggregate the results after getting the responses from all three
systems.

Answer 18

B. Install Presto on the EMR cluster where Hive sits. Configure MySQL and
PostgreSQL connector to select from different data sources in a single query.

Question 19

Q19
An Amazon EMR cluster using EMRFS has access to petabytes of data on Amazon S3,
originating from multiple unique data sources. The customer needs to query
common fields across some of the data sets to be able to perform interactive joins
and then display results quickly.
Which technology is most appropriate to enable this capability?
A. Presto
B. MicroStrategy
C. Pig
D. R Studio

Answer 19

A. Presto
(Presto 是一種開放原始碼的分散式 SQL 查詢引擎，已針對低延遲和資料臨機操作分析進行優化。它支援 ANSI SQL 標準，包含複雜查詢、彙總、加入 (join) 和視窗函數。Presto 可以處理來自多個資料來源的資料，而這些資料來源包含 Hadoop 分散式檔案系統 (HDFS) 和 Amazon S3。您可在這裡進一步了解有關 Presto 的資訊。)

Question 20

Q20
A game company needs to properly scale its game application, which is backed by
DynamoDB. Amazon
Redshift has the past two years of historical data. Game traffic varies throughout the
year based on various factors such as season, movie release, and holiday season. An
administrator needs to calculate how much read and write throughput should be
provisioned for DynamoDB table for each week in advance.
How should the administrator accomplish this task?
A. Feed the data into Amazon Machine Learning and build a regression model.
B. Feed the data into Spark Mlib and build a random forest modest.
C. Feed the data into Apache Mahout and build a multi-classification model.
D. Feed the data into Amazon Machine Learning and build a binary classification
model.

Answer 20

A. Feed the data into Amazon Machine Learning and build a regression model.

Question 21

Q21
A data engineer is about to perform a major upgrade to the DDL(schema 建構語法) contained within an
Amazon Redshift cluster to support a new data warehouse application. The upgrade
scripts will include user permission updates, view and table structure changes as well
as additional loading and data manipulation tasks.
The data engineer must be able to restore the database to its existing state in the
event of issues.
Which action should be taken prior to performing this upgrade task?
A. Run an UNLOAD command for all data in the warehouse and save it to S3.
B. Create a manual snapshot of the Amazon Redshift cluster.
C. Make a copy of the automated snapshot on the Amazon Redshift cluster.
D. Call the waitForSnapshotAvailable command from either the AWS CLI or an AWS
SDK.

Answer 21

B. Create a manual snapshot of the Amazon Redshift cluster.

Question 22

Q22
A large oil and gas company needs to provide near real-time alerts when peak
thresholds are exceeded in its pipeline system. The company has developed a system
to capture pipeline metrics such as flow rate, pressure, and temperature using
millions of sensors. The sensors deliver to AWS IoT.
What is a cost-effective way to provide near real-time alerts on the pipeline metrics?
A. Create an AWS IoT rule to generate an Amazon SNS notification.
B. Store the data points in an Amazon DynamoDB table and poll if for peak metrics
data from an Amazon EC2 application.
C. Create an Amazon Machine Learning model and invoke it with AWS Lambda.
D. Use Amazon Kinesis Streams and a KCL-based application deployed on AWS Elastic
Beanstalk.

Answer 22

A. Create an AWS IoT rule to generate an Amazon SNS notification.

Question 23

A company is using Amazon Machine Learning as part of a medical software
application. The application will predict the most likely blood type for a patient based
on a variety of other clinical tests that are available when blood type knowledge is
unavailable.
What is the appropriate model choice and target attribute combination for this
problem?
A. Multi-class classification model with a categorical target attribute.
B. Regression model with a numeric target attribute.
C. Binary Classification with a categorical target attribute.
D. K-Nearest Neighbors model with a multi-class target attribute.

Answer 23

A. Multi-class classification model with a categorical target attribute.

Question 24

Q24
A data engineer is running a DWH on a 25-node Redshift cluster of a SaaS service.
The data engineer needs to build a dashboard that will be used by customers. Five
big customers represent 80% of usage, and there is a long tail of dozens of smaller
customers. The data engineer has selected the dashboarding tool.
How should the data engineer make sure that the larger customer workloads do NOT
interfere with the smaller customer workloads?
A. Apply query filters based on customer-id that can NOT be changed by the user and
apply distribution keys on customer-id.
B. Place the largest customers into a single user group with a dedicated query queue
and place the rest of the customers into a different query queue.
C. Push aggregations into an RDS for Aurora instance. Connect the dashboard
application to Aurora rather than Redshift for faster queries.
D. Route the largest customers to a dedicated Redshift cluster. Raise the concurrency
of the multi-tenant Redshift cluster to accommodate the remaining customers.

Answer 24

B. Place the largest customers into a single user group with a dedicated query queue
and place the rest of the customers into a different query queue.

Question 25

Q25
An Amazon Kinesis stream needs to be encrypted.
Which approach should be used to accomplish this task?
A. Perform a client-side encryption of the data before it enters the Amazon Kinesis
stream on the producer.
B. Use a partition key to segment the data by MD5 hash function, which makes it
undecipherable while in transit.
C. Perform a client-side encryption of the data before it enters the Amazon Kinesis
stream on the consumer.
D. Use a shard to segment the data, which has built-in functionality to make it
indecipherable while in transit.

Answer 25

A. Perform a client-side encryption of the data before it enters the Amazon Kinesis
stream on the producer.
(Through the use of HTTPS, Amazon Kinesis Streams encrypts data in-flight between clients which protects against someone eavesdropping on records being transferred. )

Question 26

Q26
An online photo album app has a key design feature to support multiple screens (e.g,
desktop, mobile phone, and tablet) with high-quality displays. Multiple versions of
the image must be saved in different resolutions and layouts.
The image-processing Java program takes an average of five seconds per upload,
depending on the image size and format. Each image upload captures the following
image metadata: user, album, photo label, upload timestamp.
The app should support the following requirements:
✑ Hundreds of user image uploads per second
✑ Maximum image upload size of 10 MB
✑ Maximum image metadata size of 1 KB
✑ Image displayed in optimized resolution in all supported screens no later than one
minute after image upload
Which strategy should be used to meet these requirements?
A. Write images and metadata to Amazon Kinesis. Use a Kinesis Client Library (KCL)
application to run the image processing and save the image output to Amazon S3 and
metadata to the app repository DB.
B. Write image and metadata RDS with BLOB data type. Use AWS Data Pipeline to run
the image processing and save the image output to Amazon S3 and metadata to the
app repository DB.
C. Upload image with metadata to Amazon S3, use Lambda function to run the image
processing and save the images output to Amazon S3 and metadata to the app
repository DB.
D. Write image and metadata to Amazon Kinesis. Use Amazon Elastic MapReduce
(EMR) with Spark Streaming to run image processing and save the images output to
Amazon S3 and metadata to app repository DB.

Answer 26

C. Upload image with metadata to Amazon S3, use Lambda function to run the image
processing and save the images output to Amazon S3 and metadata to the app
repository DB.
(inesis is for real-time streaming. You need to deal with Shards. Single shard has 1Mb limit. This question is about image upload and transformation. Maximum image size is 10Gb. It is easier to deal with S3 for image upload, lambda for transformation and put the metadata into something like DynamoDB. So, I think the answer is C.)

Question 27

Q27
A customer needs to determine the optimal distribution strategy for the ORDERS fact
table in its Redshift schema. The ORDERS table has foreign key relationships with
multiple dimension tables in this schema.
How should the company determine the most appropriate distribution key for the
ORDERS table?
A. Identify the largest and most frequently joined dimension table and ensure that it
and the ORDERS table both have EVEN distribution.
B. Identify the largest dimension table and designate the key of this dimension table
as the distribution key of the ORDERS table.
C. Identify the smallest dimension table and designate the key of this dimension
table as the distribution key of the ORDERS table.
D. Identify the largest and the most frequently joined dimension table and designate
the key of this dimension table as the distribution key of the ORDERS table.

Answer 27

D. Identify the largest and the most frequently joined dimension table and designate
the key of this dimension table as the distribution key of the ORDERS table.

Question 28

Q28
A customer is collecting clickstream data using Amazon Kinesis and is grouping the
events by IP address into
5-minute chunks stored in Amazon S3.
Many analysts in the company use Hive on Amazon EMR to analyze this data. Their
queries always reference a single IP address. Data must be optimized for querying
based on IP address using Hive running on Amazon
EMR.
What is the most efficient method to query the data with Hive?
A. Store an index of the files by IP address in the Amazon DynamoDB metadata store
for EMRFS.
B. Store the Amazon S3 objects with the following naming scheme:
bucket_name/source=ip_address/ year=yy/month=mm/day=dd/hour=hh/filename.
C. Store the data in an HBase table with the IP address as the row key.
D. Store the events for an IP address as a single file in Amazon S3 and add metadata
with keys: Hive_Partitioned_IPAddress.

Answer 28

B. Store the Amazon S3 objects with the following naming scheme:
bucket_name/source=ip_address/ year=yy/month=mm/day=dd/hour=hh/filename.

Question 29

Q29
An online retailer is using Amazon DynamoDB to store data related to customer
transactions. The items in the table contains several string attributes describing the
transaction as well as a JSON attribute containing the shopping cart and other details
corresponding to the transaction. Average item size is 250KB, most of which is
associated with the JSON attribute. The average customer generates 3GB of data per
month.
Customers access the table to display their transaction history and review
transaction details as needed.
Ninety percent of the queries against the table are executed when building the
transaction history view, with the other 10% retrieving transaction details. The table
is partitioned on CustomerID and sorted on transaction date.
The client has very high read capacity provisioned for the table and experiences very
even utilization, but complains about the cost of Amazon DynamoDB compared to
other NoSQL solutions.
Which strategy will reduce the cost associated with the clients read queries while not
degrading quality?
A. Modify all database calls to use eventually consistent reads and advise customers
that transaction history may be one second out-of-date.
B. Change the primary table to partition on TransactionID, create a GSI partitioned on
customer and sorted on date, project small attributes into GSI, and then query GSI
for summary data and the primary table for JSON details.
C. Vertically partition the table, store base attributes on the primary table, and create
a foreign key reference to a secondary table containing the JSON data. Query the
primary table for summary data and the secondary table for JSON details.
D. Create an LSI sorted on date, project the JSON attribute into the index, and then
query the primary table for summary data and the LSI for JSON details.

Answer 29

A. Modify all database calls to use eventually consistent reads and advise customers
that transaction history may be one second out-of-date.

Question 30

Q31
An organization needs a data store to handle the following data types and access
patterns:
✑ Faceting
✑ Search
✑ Flexible schema (JSON) and fixed schema
✑ Noise word elimination
Which data store should the organization choose?
A. Amazon Relational Database Service (RDS)
B. Amazon Redshift
C. Amazon DynamoDB
D. Amazon Elasticsearch Service

Answer 30

D. Amazon Elasticsearch Service

Question 31

Q32
A travel website needs to present a graphical quantitative summary of its daily
bookings to website visitors for marketing purposes. The website has millions of
visitors per day, but wants to control costs by implementing the least-expensive
solution for this visualization.
What is the most cost-effective solution?
A. Generate a static graph with a transient EMR cluster daily, and store it an Amazon
S3.
B. Generate a graph using MicroStrategy backed by a transient EMR cluster.
C. Implement a Jupyter front-end provided by a continuously running EMR cluster
leveraging spot instances for task nodes.
D. Implement a Zeppelin application that runs on a long-running EMR cluster.

Answer 31

A. Generate a static graph with a transient EMR cluster daily, and store it an Amazon
S3.

Question 32

Q30
A company that manufactures and sells smart air conditioning(冷氣機) units also offers
add-on services so that customers can see real-time dashboards in a mobile
application or a web browser. Each unit sends its sensor information in JSON format
every two seconds for processing and analysis. The company also needs to consume
this data to predict possible equipment problems before they occur. A few thousand
pre-purchased units will be delivered in the next couple of months. The company
expects high market growth in the next year and needs to handle a massive amount
of data and scale without interruption.
Which ingestion solution should the company use?
A. Write sensor data records to Amazon Kinesis Streams. Process the data using KCL
applications for the end-consumer dashboard and anomaly detection workflows.
B. Batch sensor data to Amazon Simple Storage Service (S3) every 15 minutes. Flow
the data downstream to the end-consumer dashboard and to the anomaly detection
application.
C. Write sensor data records to Amazon Kinesis Firehose with Amazon Simple Storage
Service (S3) as the destination. Consume the data with a KCL application for the
end-consumer dashboard and anomaly detection.
D. Write sensor data records to Amazon Relational Database Service (RDS). Build
both the end-consumer dashboard and anomaly detection application on top of
Amazon RDS.

Answer 32

A. Write sensor data records to Amazon Kinesis Streams. Process the data using KCL
applications for the end-consumer dashboard and anomaly detection workflows.

Question 33

Q33
A system engineer for a company proposes digitalization and backup of large archives
for customers. The systems engineer needs to provide users with a secure storage
that makes sure that data will never be tampered with once it has been uploaded.
How should this be accomplished?
A. Create an Amazon Glacier Vault. Specify a “Deny” Vault Lock policy on this Vault to
block “glacier:DeleteArchive”.
B. Create an Amazon S3 bucket. Specify a “Deny” bucket policy on this bucket to
block “s3:DeleteObject”.
C. Create an Amazon Glacier Vault. Specify a “Deny” vault access policy on this Vault
to block “glacier:DeleteArchive”.
D. Create secondary AWS Account containing an Amazon S3 bucket. Grant
“s3:PutObject” to the primary account.

Answer 33

A. Create an Amazon Glacier Vault. Specify a “Deny” Vault Lock policy( LOCK POLICY) on this Vault to
block “glacier:DeleteArchive”.

Question 34

Q34
An organization needs to design and deploy a large-scale data storage solution that
will be highly durable and highly flexible with respect to the type and structure of
data being stored. The data to be stored will be sent or generated from a variety of
sources and must be persistently available for access and processing by multiple
applications.
What is the most cost-effective technique to meet these requirements?
A. Use Amazon Simple Storage Service (S3) as the actual data storage system,
coupled with appropriate tools for ingestion/acquisition of data and for subsequent
processing and querying.
B. Deploy a long-running Amazon Elastic MapReduce (EMR) cluster with Amazon
Elastic Block Store (EBS) volumes for persistent HDFS storage and appropriate
Hadoop ecosystem tools for processing and querying.
C. Use Amazon Redshift with data replication to Amazon Simple Storage Service (S3)
for comprehensive durable data storage, processing, and querying.
D. Launch an Amazon Relational Database Service (RDS), and use the enterprise
grade and capacity of the Amazon Aurora engine for storage, processing, and
querying.

Answer 34

A. Use Amazon Simple Storage Service (S3) as the actual data storage system,
coupled with appropriate tools for ingestion/acquisition of data and for subsequent
processing and querying

Question 35

Q35
A customer has a machine learning workflow that consists of multiple quick cycles of
reads-writes-reads on
Amazon S3. The customer needs to run the workflow on EMR but is concerned that
the reads in subsequent cycles will miss new data critical to the machine learning
from the prior cycles.
How should the customer accomplish this?
A. Turn on EMRFS consistent view when configuring the EMR cluster.
B. Use AWS Data Pipeline to orchestrate the data processing cycles.
C. Set hadoop.data.consistency = true in the core-site.xml file.
D. Set hadoop.s3.consistency = true in the core-site.xml file.

Answer 35

A. Turn on EMRFS consistent view when configuring the EMR cluster.
EMR 檔案系統 (EMRFS) 是一種 HDFS 實作，所有 Amazon EMR 叢集會用來從 Amazon EMR 將一般檔案直接讀取和寫入至 Amazon S3。EMRFS 提供將持久性資料存放在 Amazon S3 的方便性，可讓您與 Hadoop 搭配使用，同時提供一致性檢視和資料加密之類的功能。

Question 36

Q36
An Amazon Redshift Database is encrypted using KMS. A data engineer needs to use
the AWS CLI to create a KMS encrypted snapshot of the database in another AWS
region.
Which three steps should the data engineer take to accomplish this task? (Choose
three.)
A. Create a new KMS key in the destination region.
B. Copy the existing KMS key to the destination region.
C. Use CreateSnapshotCopyGrant to allow Amazon Redshift to use the KMS key from
the source region.
D. In the source region, enable cross-region replication and specify the name of the
copy grant created.
E. In the destination region, enable cross-region replication and specify the name of
the copy grant created.
F. Use CreateSnapshotCopyGrant to allow Amazon Redshift to use the KMS key
created in the destination region.

Answer 36

A. Create a new KMS key in the destination region.
D. In the source region, enable cross-region replication and specify the name of the
copy grant created.
F. Use CreateSnapshotCopyGrant to allow Amazon Redshift to use the KMS key
created in the destination region.

Question 37

Q37
Managers in a company need access to the human resources database that runs on
Amazon Redshift, to run reports about their employees. Managers must only see
information about their direct reports.
Which technique should be used to address this requirement with Amazon Redshift?
A. Define an IAM group for each manager with each employee as an IAM user in that
group, and use that to limit the access.
B. Use Amazon Redshift snapshot to create one cluster per manager. Allow the
manager to access only their designated clusters.
C. Define a key for each manager in AWS KMS and encrypt the data for their
employees with their private keys.
D. Define a view that uses the employee’s manager name to filter the records based
on current user names.

Answer 37

D. Define a view that uses the employee’s manager name to filter the records based
on current user names.

Question 38

Q38
A company is building a new application in AWS. The architect needs to design a
system to collect application log events. The design should be a repeatable pattern
that minimizes data loss if an application instance fails, and keeps a durable copy of a
log data for at least 30 days.
What is the simplest architecture that will allow the architect to analyze the logs?
A. Write them directly to a Kinesis Firehose. Configure Kinesis Firehose to load the
events into an Amazon Redshift cluster for analysis.
B. Write them to a file on Amazon Simple Storage Service (S3). Write an AWS Lambda
function that runs in response to the S3 event to load the events into Amazon
Elasticsearch Service for analysis.
C. Write them to the local disk and configure the Amazon CloudWatch Logs agent to
load the data into CloudWatch Logs and subsequently into Amazon Elasticsearch
Service.
D. Write them to CloudWatch Logs and use an AWS Lambda function to load them
into HDFS on an Amazon Elastic MapReduce (EMR) cluster for analysis.

Answer 38

B. Write them to a file on Amazon Simple Storage Service (S3). Write an AWS Lambda
function that runs in response to the S3 event to load the events into Amazon
Elasticsearch(有elasticsearch) Service for analysis.

Question 39

Q39
An organization uses a custom map reduce application to build monthly reports
based on many small data files in an Amazon S3 bucket. The data is submitted from
various business units on a frequent but unpredictable schedule. As the dataset
continues to grow, it becomes increasingly difficult to process all of the data in one
day. The organization has scaled up its Amazon EMR cluster, but other optimizations
could improve performance.
The organization needs to improve performance with minimal changes to existing
processes and applications.
What action should the organization take?
A. Use Amazon S3 Event Notifications and AWS Lambda to create a quick search file
index in DynamoDB.
B. Add Spark to the Amazon EMR cluster and utilize Resilient Distributed Datasets
in-memory.
C. Use Amazon S3 Event Notifications and AWS Lambda to index each file into an
Amazon Elasticsearch Service cluster.
D. Schedule a daily AWS Data Pipeline process that aggregates content into larger
files using S3DistCp.
E. Have business units submit data via Amazon Kinesis Firehose to aggregate data
hourly into Amazon S3

Answer 39

B. Add Spark to the Amazon EMR cluster and utilize Resilient Distributed Datasets
in-memory.

Question 40

Q40
An administrator is processing events in near real-time using Kinesis streams and
Lambda. Lambda intermittently fails to process batches from one of the shards due
to a 5-munite time limit.
What is a possible solution for this problem?
A. Add more Lambda functions to improve concurrent batch processing.
B. Reduce the batch size that Lambda is reading from the stream.
C. Ignore and skip events that are older than 5 minutes and put them to Dead Letter
Queue (DLQ).
D. Configure Lambda to read from fewer shards in parallel.

Answer 40

B. Reduce the batch size that Lambda is reading from the stream.

Question 41

Q41
An organization uses Amazon Elastic MapReduce(EMR) to process a series of
extract-transform-load (ETL) steps that run in sequence. The output of each step
must be fully processed in subsequent steps but will not be retained.
Which of the following techniques will meet this requirement most efficiently?
A. Use the EMR File System (EMRFS) to store the outputs from each step as objects in
Amazon Simple Storage Service (S3).
B. Use the s3n URI to store the data to be processed as objects in Amazon S3.
C. Define the ETL steps as separate AWS Data Pipeline activities.
D. Load the data to be processed into HDFS, and then write the final output to
Amazon S3.

Answer 41

C. Define the ETL steps as separate AWS Data Pipeline activities.

Question 42

Q42
The department of transportation for a major metropolitan(唯一大都會區) area has placed sensors
on roads at key locations around the city. The goal is to analyze the flow of traffic and
notifications from emergency services to identify potential issues and to help
planners correct trouble spots.
A data engineer needs a scalable and fault-tolerant solution that allows planners to
respond to issues within
30 seconds of their occurrence.
Which solution should the data engineer choose?
A. Collect the sensor data with Amazon Kinesis Firehose and store it in Amazon
Redshift for analysis. Collect emergency services events with Amazon SQS and store
in Amazon DynampDB for analysis.
B. Collect the sensor data with Amazon SQS and store in Amazon DynamoDB for
analysis. Collect emergency services events with Amazon Kinesis Firehose and store
in Amazon Redshift for analysis.
C. Collect both sensor data and emergency services events with Amazon Kinesis
Streams and use DynamoDB for analysis.
D. Collect both sensor data and emergency services events with Amazon Kinesis
Firehose and use Amazon Redshift for analysis.

Answer 42

C. Collect both sensor data and emergency services events with Amazon Kinesis
Streams and use DynamoDB for analysis.(kenesis firehose 有60秒delay)

Question 43

Q43
A telecommunications company needs to predict customer churn (i.e., customers
who decide to switch to a competitor). The company has historic records of each
customer, including monthly consumption patterns, calls to customer service, and
whether the customer ultimately quit the service. All of this data is stored in
Amazon S3. The company needs to know which customers are likely going to churn
soon so that they can win back their loyalty.
What is the optimal approach to meet these requirements?
A. Use the Amazon Machine Learning service to build the binary classification model
based on the dataset stored in Amazon S3. The model will be used regularly to
predict churn attribute for existing customers.
B. Use AWS QuickSight to connect it to data stored in Amazon S3 to obtain the
necessary business insight. Plot the churn trend graph to extrapolate churn likelihood
for existing customers.
C. Use EMR to run the Hive queries to build a profile of a churning customer. Apply a
profile to existing customers to determine the likelihood of churn.
D. Use a Redshift cluster to COPY the data from Amazon S3. Create a User Defined
Function in Redshift that computes the likelihood of churn.

Answer 43

A. Use the Amazon Machine Learning service to build the binary classification model
based on the dataset stored in Amazon S3. The model will be used regularly to
predict churn attribute for existing customers.

Question 44

Q44
A system needs to collect on-premises application spool files into a persistent storage
layer in AWS. Each spool file is 2 KB. The application generates 1 M files per hour.
Each source file is automatically deleted from the local server after an hour.
What is the most cost-efficient option to meet these requirements?
A. Write file contents to an Amazon DynamoDB table.
B. Copy files to Amazon S3 Standard Storage.
C. Write file contents to Amazon ElastiCache.
D. Copy files to Amazon S3 infrequent Access Storage.

Answer 44

A. Write file contents to an Amazon DynamoDB table.

Question 45

Q45
An administrator receives about 100 files per hour into Amazon S3 and will be
loading the files into Amazon
Redshift. Customers who analyze the data within Redshift gain significant value when
they receive data as quickly as possible. The customers have agreed to a maximum
loading interval of 5 minutes.
Which loading approach should the administrator use to meet this objective?
A. Load each file as it arrives because getting data into the cluster as quickly as
possibly is the priority.
B. Load the cluster as soon as the administrator has the same number of files as
nodes in the cluster.
C. Load the cluster when the administrator has an event multiple of files relative to
Cluster Slice Count, or 5 minutes, whichever comes first.
D. Load the cluster when the number of files is less than the Cluster Slice Count.

Answer 45

C. Load the cluster when the administrator has an event multiple of files relative to
Cluster Slice Count, or 5 minutes, whichever comes first.

Question 46

Q46
An enterprise customer is migrating to Redshift and is considering using dense
storage nodes in its Redshift cluster. The customer wants to migrate 50 TB of data.
The customers query patterns involve performing many joins with thousands of rows.
The customer needs to know how many nodes are needed in its target Redshift
cluster. The customer has a limited budget and needs to avoid performing tests
unless absolutely needed.
Which approach should this customer use?
A. Start with many small nodes.
B. Start with fewer large nodes.
C. Have two separate clusters with a mix of a small and large nodes.
D. Insist on performing multiple tests to determine the optimal configuration.

Answer 46

A. Start with many small nodes.

Question 47

Q47
A company is centralizing(關鍵字) a large number of unencrypted small files from multiple
Amazon S3 buckets. The company needs to verify that the files contain the same data
after centralization.
Which method meets the requirements?
A. Compare the S3 Etags from the source and destination objects.
B. Call the S3 CompareObjects API for the source and destination objects.
C. Place a HEAD request against the source and destination objects comparing SIG v4.
D. Compare the size of the source and destination objects.

Answer 47

A. Compare the S3 Etags from the source and destination objects.

Question 48

Q48
An online gaming company uses DynamoDB to store user activity logs and is
experiencing throttled writes on the companys DynamoDB table. The company is
NOT consuming close to the provisioned capacity. The table contains a large number
of items and is partitioned on user and sorted by date. The table is 200GB and is
currently provisioned at 10K WCU and 20K RCU.
Which two additional pieces of information are required to determine the cause of
the throttling? (Choose two.)
A. The structure of any GSIs that have been defined on the table
B. CloudWatch data showing consumed and provisioned write capacity when writes
are being throttled
C. Application-level metrics showing the average item size and peak update rates for
each attribute
D. The structure of any LSIs that have been defined on the table
E. The maximum historical WCU and RCU for the table

Answer 48

A. The structure of any GSIs that have been defined on the table
D. The structure of any LSIs that have been defined on the table

Question 49

Q49
A city has been collecting data on its public bicycle share program for the past three
years. The 5PB dataset currently resides on Amazon S3. The data contains the
following datapoints:
✑ Bicycle origination points
✑ Bicycle destination points
✑ Mileage between the points
✑ Number of bicycle slots available at the station (which is variable based on the
station location)
✑ Number of slots available and taken at a given time
The program has received additional funds to increase the number of bicycle stations
available. All data is regularly archived to Amazon Glacier.
The new bicycle stations must be located to provide the most riders access to
bicycles.
How should this task be performed?
A. Move the data from Amazon S3 into Amazon EBS-backed volumes and use an EC-2
based Hadoop cluster with spot instances to run a Spark job that performs a
stochastic gradient descent optimization.
B. Use the Amazon Redshift COPY command to move the data from Amazon S3 into
Redshift and perform a SQL query that outputs the most popular bicycle stations.
C. Persist the data on Amazon S3 and use a transient EMR cluster with spot instances
to run a Spark streaming job that will move the data into Amazon Kinesis.
D. Keep the data on Amazon S3 and use an Amazon EMR-based Hadoop cluster with
spot instances to run a Spark job that performs a stochastic gradient descent
optimization over EMRFS.

Answer 49

D. Keep the data on Amazon S3 and use an Amazon {EMR-based Hadoop} cluster with
spot instances to run a Spark job that performs a stochastic gradient descent
optimization over EMRFS.

Question 50

Q50
An administrator tries to use the Amazon Machine Learning service to classify social
media posts that mention the administrators company into posts that require a
response and posts that do not. The training dataset of
10,000 posts contains the details of each post including the timestamp, author, and
full text of the post. The administrator is missing the target labels that are required
for training.
Which Amazon Machine Learning model is the most appropriate for the task?
A. Binary classification model, where the target class is the require-response post
B. Binary classification model, where the two classes are the require-response post
and does-not-require- response
C. Multi-class prediction model, with two classes: require-response post and
does-not-require-response
D. Regression model where the predicted value is the probability that the post
requires a response

Answer 50

B. Binary classification model, where the two classes are the require-response post
and does-not-require- response

Question 51

Q51
A medical record filing system for a government medical fund is using an Amazon S3
bucket to archive documents related to patients. Every patient visit to a physician
creates a new file, which can add up millions of files each month. Collection of these
files from each physician is handled via a batch process that runs ever night using
AWS Data Pipeline. This is sensitive data, so the data and any associated metadata
must be encrypted at rest.
Auditors review some files on a quarterly basis to see whether the records are
maintained according to regulations. Auditors must be able to locate any physical file
in the S3 bucket for a given date, patient, or physician. Auditors spend a significant
amount of time location such files.
What is the most cost- and time-efficient collection methodology in this situation?
A. Use Amazon Kinesis to get the data feeds directly from physicians, batch them
using a Spark application on Amazon Elastic MapReduce (EMR), and then store them
in Amazon S3 with folders separated per physician.
B. Use Amazon API Gateway to get the data feeds directly from physicians, batch
them using a Spark application on Amazon Elastic MapReduce (EMR), and then store
them in Amazon S3 with folders separated per physician.
C. Use Amazon S3 event notification to populate an Amazon DynamoDB table with
metadata about every file loaded to Amazon S3, and partition them based on the
month and year of the file.
D. Use Amazon S3 event notification to populate an Amazon Redshift table with
metadata about every file loaded to Amazon S3, and partition them based on the
month and year of the file.

Answer 51

C. Use Amazon S3 event notification to populate an Amazon DynamoDB table with
metadata about every file loaded to Amazon S3, and partition them based on the
month and year of the file.

Question 52

Q52
A clinical trial will rely on medical sensors to remotely assess patient health. Each
physician who participates in the trial requires visual reports each morning. The
reports are built from aggregations of all the sensor data taken each minute.
What is the most cost-effective solution for creating this visualization each day?
A. Use Kinesis Aggregators Library to generate reports for reviewing the patient
sensor data and generate a QuickSight visualization on the new data each morning
for the physician to review.
B. Use a transient EMR cluster that shuts down after use to aggregate the patient
sensor data each night and generate a QuickSight visualization on the new data each
morning for the physician to review.
C. Use Spark streaming on EMR to aggregate the patient sensor data in every 15
minutes and generate a QuickSight visualization on the new data each morning for
the physician to review.
D. Use an EMR cluster to aggregate the patient sensor data each night and provide
Zeppelin notebooks that look at the new data residing on the cluster each morning
for the physician to review.

Answer 52

B. Use a transient EMR cluster that shuts down after use to aggregate the patient
sensor data each night and generate a QuickSight visualization on the new data each
morning for the physician to review.(shutdown after )

Question 53

Q53
A company uses Amazon Redshift for its enterprise data warehouse. A new
on-premises PostgreSQL OLTP
DB must be integrated into the data warehouse. Each table in the PostgreSQL DB has
an indexed timestamp column. The data warehouse has a staging layer to load source
data into the data warehouse environment for further processing.
The data lag between the source PostgreSQL DB and the Amazon Redshift staging
layer should NOT exceed four hours.
What is the most efficient technique to meet these requirements?
A. Create a DBLINK on the source DB to connect to Amazon Redshift. Use a
PostgreSQL trigger on the source table to capture the new insert/update/delete
event and execute the event on the Amazon Redshift staging table.
B. Use a PostgreSQL trigger on the source table to capture the new
insert/update/delete event and write it to Amazon Kinesis Streams. Use a KCL
application to execute the event on the Amazon Redshift staging table.
C. Extract the incremental changes periodically using a SQL query. Upload the
changes to multiple Amazon Simple Storage Service (S3) objects, and run the COPY
command to load to the Amazon Redshift staging layer.
D. Extract the incremental changes periodically using a SQL query. Upload the
changes to a single Amazon Simple Storage Service (S3) object, and run the COPY
command to load to the Amazon Redshift staging layer

Answer 53

C. Extract the incremental changes periodically using a SQL query. Upload the
changes to multiple Amazon Simple Storage Service (S3) objects, and run the COPY
command to load to the Amazon Redshift staging layer.

Question 54

Q54
An administrator is deploying Spark on Amazon EMR for two distinct use cases:
machine learning algorithms and ad-hoc querying. All data will be stored in Amazon
S3. Two separate clusters for each use case will be deployed. The data volumes on
Amazon S3 are less than 10 GB.
How should the administrator align instance types with the clusters purpose?
A. Machine Learning on C instance types and ad-hoc queries on R instance types
B. Machine Learning on R instance types and ad-hoc queries on G2 instance types
C. Machine Learning on T instance types and ad-hoc queries on M instance types
D. Machine Learning on D instance types and ad-hoc queries on I instance types

Answer 54

A. Machine Learning on C instance types and ad-hoc queries on R instance types(CPU for ML)

Question 55

Q55
An organization is designing an application architecture. The application will have
over 100 TB of data and will support transactions that arrive at rates from hundreds
per second to tens of thousands per second, depending on the day of the week and
time of the day. All transaction data, must be durably and reliably stored. Certain
read operations must be performed with strong consistency.
Which solution meets these requirements?
A. Use Amazon DynamoDB as the data store and use strongly consistent reads when
necessary.
B. Use an Amazon Relational Database Service (RDS) instance sized to meet the
maximum anticipated transaction rate and with the High Availability option enabled.
C. Deploy a NoSQL data store on top of an Amazon Elastic MapReduce (EMR) cluster,
and select the HDFS High Durability option.
D. Use Amazon Redshift with synchronous replication to Amazon Simple Storage
Service (S3) and row-level locking for strong consistency.

Answer 55

A. Use Amazon DynamoDB as the data store and use strongly consistent reads when
necessary.

Question 56

Q56
A company generates a large number of files each month and needs to use AWS
import/export to move these files into Amazon S3 storage. To satisfy the auditors,
the company needs to keep a record of which files were imported into Amazon S3.
What is a low-cost way to create a unique log for each import job?
A. Use the same log file prefix in the import/export manifest files to create a
versioned log file in Amazon S3 for all imports.
B. Use the log file prefix in the import/export manifest files to create a unique log file
in Amazon S3 for each import.
C. Use the log file checksum in the import/export manifest files to create a unique log
file in Amazon S3 for each import.
D. Use a script to iterate over files in Amazon S3 to generate a log after each
import/export job.

Answer 56

B. Use the log file prefix in the import/export manifest files to create a unique log file
in Amazon S3 for each import.

Question 57

Q57
A company needs a churn prevention model to predict which customers will NOT
renew their yearly subscription to the companys service. The company plans to
provide these customers with a promotional offer. A binary classification model that
uses Amazon Machine Learning is required.
On which basis should this binary classification model be built?
A. User profiles (age, gender, income, occupation)
B. Last user session
C. Each user time series events in the past 3 months
D. Quarterly results

Answer 57

C. Each user time series events in the past 3 months

Question 58

Q58
A company with a support organization needs support engineers to be able to search
historic cases to provide fast responses on new issues raised. The company has
forwarded all support messages into an Amazon
Kinesis Stream. This meets a company objective of using only managed services to
reduce operational overhead.
The company needs an appropriate architecture that allows support engineers to
search on historic cases and find similar issues and their associated responses.
Which AWS Lambda action is most appropriate?
A. Ingest and index the content into an Amazon Elasticsearch domain.
B. Stem and tokenize the input and store the results into Amazon ElastiCache.
C. Write data as JSON into Amazon DynamoDB with primary and secondary indexes.
D. Aggregate feedback in Amazon S3 using a columnar format with partitioning.

Answer 58

A. Ingest and index the content into an Amazon Elasticsearch domain.

Question 59

Q59
A solutions architect works for a company that has a data lake based on a central
Amazon S3 bucket. The data contains sensitive information. The architect must be
able to specify exactly which files each user can access. Users access the platform
through a SAML federation Single Sign On platform.
The architect needs to build a solution that allows fine grained access control,
traceability of access to the objects, and usage of the standard tools (AWS Console,
AWS CLI) to access the data.
Which solution should the architect build?
A. Use Amazon S3 Server-Side Encryption with AWS KMS-Managed Keys for storing
data. Use AWS KMS Grants to allow access to specific elements of the platform. Use
AWS CloudTrail for auditing.
B. Use Amazon S3 Server-Side Encryption with Amazon S3-Managed Keys. Set
Amazon S3 ACLs to allow access to specific elements of the platform. Use Amazon S3
to access logs for auditing.
C. Use Amazon S3 Client-Side Encryption with Client-Side Master Key. Set Amazon S3
ACLs to allow access to specific elements of the platform. Use Amazon S3 to access
logs for auditing.
D. Use Amazon S3 Client-Side Encryption with AWS KMS-Managed Keys for storing
data. Use AWS KMS Grants to allow access to specific elements of the platform. Use
AWS CloudTrail for auditing.

Answer 59

B. Use Amazon S3 Server-Side Encryption with Amazon S3-Managed Keys. Set
Amazon S3 ACLs to allow access to specific elements of the platform. Use Amazon S3
to access logs for auditing.

Question 60

A company that provides economics data dashboards needs to be able to develop
software to display rich, interactive, data-driven graphics that run in web browsers
and leverages the full stack of web standards
(HTML, SVG, and CSS).
Which technology provides the most appropriate support for this requirements?
A. D3.js
B. IPython/Jupyter
C. R Studio
D. Hue

Answer 60

A. D3.js

Question 61

Q61
A company hosts a portfolio of e-commerce websites across the Oregon, N. Virginia,
Ireland, and Sydney
AWS regions. Each site keeps log files that capture user behavior. The company has
built an application that generates batches of product recommendations with
collaborative filtering in Oregon. Oregon was selected because the flagship site is
hosted there and provides the largest collection of data to train machine learning
models against. The other regions do NOT have enough historic data to train accurate
machine learning models.
Which set of data processing steps improves recommendations for each region?
A. Use the e-commerce application in Oregon to write replica log files in each other
region.
B. Use Amazon S3 bucket replication to consolidate log entries and build a single
model in Oregon.
C. Use Kinesis as a buffer for web logs and replicate logs to the Kinesis stream of a
neighboring region.
D. Use the CloudWatch Logs agent to consolidate logs into a single CloudWatch Logs
group.

Answer 61

B. Use Amazon S3 bucket replication to consolidate log entries and build a single

Question 62

Q62
There are thousands of text files on Amazon S3. The total size of the files is 1 PB. The
files contain retail order information for the past 2 years. A data engineer needs to
run multiple interactive queries to manipulate the data. The Data Engineer has AWS
access to spin up an Amazon EMR cluster. The data engineer needs to use an
application on the cluster to process this data and return the results in interactive
time frame.
Which application on the cluster should the data engineer use?
A. Oozie
B. Apache Pig with Tachyon
C. Apache Hive
D. Presto

Answer 62

D. Presto

Question 63

Q63
A media advertising company handles a large number of real-time messages sourced
from over 200 websites.
The companys data engineer needs to collect and process records in real time for
analysis using Spark
Streaming on Amazon Elastic MapReduce (EMR). The data engineer needs to fulfill a
corporate mandate to keep ALL raw messages as they are received as a top priority.
Which Amazon Kinesis configuration meets these requirements?
A. Publish messages to Amazon Kinesis Firehose backed by Amazon Simple Storage
Service (S3). Pull messages off Firehose with Spark Streaming in parallel to
persistence to Amazon S3.
B. Publish messages to Amazon Kinesis Streams. Pull messages off Streams with
Spark Streaming in parallel to AWS Lambda pushing messages from Streams to
Firehose backed by Amazon Simple Storage Service (S3).
C. Publish messages to Amazon Kinesis Firehose backed by Amazon Simple Storage
Service (S3). Use AWS Lambda to pull messages from Firehose to Streams for
processing with Spark Streaming.
D. Publish messages to Amazon Kinesis Streams, pull messages off with Spark
Streaming, and write row data to Amazon Simple Storage Service (S3) before and
after processing.

Answer 63

B. Publish messages to Amazon Kinesis Streams. Pull messages off Streams with
Spark Streaming in parallel to AWS Lambda pushing messages from Streams to
Firehose backed by Amazon Simple Storage Service (S3).

Question 64

Q64
A solutions architect for a logistics organization ships packages from thousands of
suppliers to end customers.
The architect is building a platform where suppliers can view the status of one or
more of their shipments.
Each supplier can have multiple roles that will only allow access to specific fields in
the resulting information.
Which strategy allows the appropriate level of access control and requires the LEAST
amount of management work?
A. Send the tracking data to Amazon Kinesis Streams. Use AWS Lambda to store the
data in an Amazon DynamoDB Table. Generate temporary AWS credentials for the
suppliers users with AWS STS, specifying fine-grained security policies to limit access
only to their applicable data.
B. Send the tracking data to Amazon Kinesis Firehose. Use Amazon S3 notifications
and AWS Lambda to prepare files in Amazon S3 with appropriate data for each
suppliers roles. Generate temporary AWS credentials for the suppliers users with
AWS STS. Limit access to the appropriate files through security policies.
C. Send the tracking data to Amazon Kinesis Streams. Use Amazon EMR with Spark
Streaming to store the data in HBase. Create one table per supplier. Use HBase
Kerberos integration with the suppliers users. Use HBase ACL-based security to limit
access for the roles to their specific table and columns.
D. Send the tracking data to Amazon Kinesis Firehose. Store the data in an Amazon
Redshift cluster. Create views for the suppliers users and roles. Allow suppliers access
to the Amazon Redshift cluster using a user limited to the applicable view. B

Answer 64

B. Send the tracking data to Amazon Kinesis Firehose. Use Amazon S3 notifications
and AWS Lambda to prepare files in Amazon S3 with appropriate data for each
suppliers roles. Generate temporary AWS credentials for the suppliers users with
AWS STS. Limit access to the appropriate files through security policies.

Not A- Using temporary credentials you cannot access a Dynamo DB table using a fine-grained authorization policy. https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/specifying-conditions.html
Not C – Its not manageable to create one table per supplier as there are thousands of supplier as per the question.
Not D- This is a possible solution but not with least amount of management. You will need to create as many view as there are supplier roles in RedShift.
B- This is the best choice- It uses the out-of-the-box STS functionality to associate the appropriate IAM Role to the temp user credentials for the user who logs in via SAML federation into AWS and then grants access to the files using resource based polices in S3.

Question 65

Q65
A companys social media manager requests more staff on the weekends to handle an
increase in customer contacts from a particular region. The company needs a report
to visualize the trends on weekends over the past 6 months using QuickSight.
How should the data be represented?
A. A line graph plotting customer contacts vs. time, with a line for each region
B. A pie chart per region plotting customer contacts per day of week
C. A map of regions with a heatmap overlay to show the volume of customer
contacts
D. A bar graph plotting region vs. volume of social media contacts

Answer 65

A. A line graph plotting customer contacts vs. time, with a line for each region

Question 66

Q66
How should an Administrator BEST architect a large multi-layer Long Short-Term
Memory (LSTM) recurrent neural network (RNN) running with MXNET on
Amazon EC2? (Choose two.)
A. Use data parallelism to partition the workload over multiple devices and balance
the workload within the GPUs.
B. Use compute-optimized EC2 instances with an attached elastic GPU.
C. Use general purpose GPU computing instances such as G3 and P3.
D. Use processing parallelism to partition the workload over multiple storage devices
and balance the workload within the GPUs.

Answer 66

A. Use data parallelism to partition the workload over multiple devices and balance
the workload within the GPUs.
C. Use general purpose GPU computing instances such as G3 and P3.

Question 67

Q67
An organization is soliciting public feedback through a web portal that has been
deployed to track the number of requests and other important data. As part of
reporting and visualization, AmazonQuickSight connects to an Amazon RDS database
to virtualize data. Management wants to understand some important metrics about
feedback and how the feedback has changed over the last four weeks in a visual
representation.
What would be the MOST effective way to represent multiple iterations of an
analysis in Amazon QuickSight that would show how the data has changed over the
last four weeks?
A. Use the analysis option for data captured in each week and view the data by a
date range.
B. Use a pivot table as a visual option to display measured values and weekly
aggregate data as a row dimension.
C. Use a dashboard option to create an analysis of the data for each week and apply
filters to visualize the data change.
D. Use a story option to preserve multiple iterations of an analysis and play the
iterations sequentially.

Answer 67

D. Use a story option to preserve multiple iterations of an analysis and play the
iterations sequentially.

Question 68

Q68
An organization is setting up a data catalog and metadata management environment
for their numerous data stores currently running on AWS. The data catalog will be
used to determine the structure and other attributes of data in the data stores. The
data stores are composed of Amazon RDS databases, Amazon
Redshift, and CSV files residing on Amazon S3. The catalog should be populated on a
scheduled basis, and minimal administration is required to manage the catalog.
How can this be accomplished?
A. Set up Amazon DynamoDB as the data catalog and run a scheduled AWS Lambda
function that connects to data sources to populate the DynamoDB table.
B. Use an Amazon database as the data catalog and run a scheduled AWS Lambda
function that connects to data sources to populate the database.
C. Use AWS Glue Data Catalog as the data catalog and schedule crawlers that connect
to data sources to populate the catalog.
D. Set up Apache Hive metastore on an Amazon EC2 instance and run a scheduled
bash script that connects to data sources to populate the metastore.

Answer 68

C. Use AWS Glue Data Catalog as the data catalog and schedule crawlers that connect
to data sources to populate the catalog.

Question 69

Q69
An organization is currently using an Amazon EMR long-running cluster with the
latest Amazon EMR release for analytic jobs and is storing data as external tables on
Amazon S3.
The company needs to launch multiple transient EMR clusters to access the same
tables concurrently, but the metadata about the Amazon S3 external tables are
defined and stored on the long-running cluster.
Which solution will expose the Hive metastore with the LEAST operational effort?
A. Export Hive metastore information to Amazon DynamoDB hive-site classification
to point to the Amazon DynamoDB table.
B. Export Hive metastore information to a MySQL table on Amazon RDS and
configure the Amazon EMR hive-site classification to point to the Amazon RDS
database.
C. Launch an Amazon EC2 instance, install and configure Apache Derby, and export
the Hive metastore information to derby.
D. Create and configure an AWS Glue Data Catalog as a Hive metastore for Amazon
EMR.

Answer 69

D. Create and configure an AWS Glue Data Catalog as a Hive metastore for Amazon
EMR.

Question 70

Q70
An organization is using Amazon Kinesis Data Streams to collect data generated from
thousands of temperature devices and is using AWS Lambda to process the data.
Devices generate 10 to 12 million records every day, but Lambda is processing only
around 450 thousand records. Amazon CloudWatch indicates that throttling on
Lambda is not occurring.
What should be done to ensure that all data is processed? (Choose two.)
A. Increase the BatchSize value on the EventSource, and increase the memory
allocated to the Lambda function.
B. Decrease the BatchSize value on the EventSource, and increase the memory
allocated to the Lambda function.
C. Create multiple Lambda functions that will consume the same Amazon Kinesis
stream.
D. Increase the number of vCores allocated for the Lambda function.
E. Increase the number of shards on the Amazon Kinesis stream.

Answer 70

A. Increase the BatchSize value on the EventSource, and increase the memory
E. Increase the number of shards on the Amazon Kinesis stream.

Question 71

Q71
An Operations team continuously monitors the number of visitors to a website to
identify any potential system problems. The number of website visitors varies
throughout the day. The site is more popular in the middle of the day and less
popular at night.
Which type of dashboard display would be the MOST useful to allow staff to quickly
and correctly identify system problems?
A. A vertical stacked bar chart showing today’s website visitors and the historical
average number of website visitors.
B. An overlay line chart showing today’s website visitors at one-minute intervals
and also the historical average number of website visitors.
C. A single KPI metric showing the statistical variance between the current number of
website visitors and the historical number of website visitors for the current time of
day.
D. A scatter plot showing today’s website visitors on the X-axis and the historical
average number of website visitors on the Y-axis.

Answer 71

B. An overlay line chart showing today’s website visitors at one-minute intervals
and also the historical average number of website visitors.

Question 72

Q72
An organization would like to run analytics on their Elastic Load Balancing logs stored
in Amazon S3 and join this data with other tables in Amazon S3. The users are
currently using a BI tool connecting with JDBC and would like to keep using this BI
tool.
Which solution would result in the LEAST operational overhead?
A. Trigger a Lambda function when a new log file is added to the bucket to transform
and load it into Amazon Redshift. Run the VACUUM command on the Amazon
Redshift cluster every night.
B. Launch a long-running Amazon EMR cluster that continuously downloads and
transforms new files from Amazon S3 into its HDFS storage. Use Presto to expose the
data through JDBC.
C. Trigger a Lambda function when a new log file is added to the bucket to transform
and move it to another bucket with an optimized data structure. Use Amazon Athena
to query the optimized bucket.
D. Launch a transient Amazon EMR cluster every night that transforms new log files
and loads them into Amazon Redshift.

Answer 72

C. Trigger a Lambda function when a new log file is added to the bucket to transform
and move it to another bucket with an optimized data structure. Use Amazon Athena
to query the optimized bucket.(S3 -> Athena)

Question 73

Q73
An organization has added a clickstream to their website to analyze traffic. The
website is sending each page request with the PutRecord API call to an Amazon
Kinesis stream by using the page name as the partition key. During peak spikes in
website traffic, a support engineer notices many events in the application logs.
ProvisionedThroughputExcededException
What should be done to resolve the issue in the MOST cost-effective way?
A. Create multiple Amazon Kinesis streams for page requests to increase the
concurrency of the clickstream.
B. Increase the number of shards on the Kinesis stream to allow for more throughput
to meet the peak spikes in traffic.
C. Modify the application to use on the Kinesis Producer Library to aggregate
requests before sending them to the Kinesis stream.
D. Attach more consumers to the Kinesis stream to process records in parallel,
improving the performance on the stream.

Answer 73

C. Modify the application to use on the Kinesis Producer Library to aggregate
requests before sending them to the Kinesis stream.

Question 74

Q74
An organization currently runs a large Hadoop environment in their data center and
is in the process of creating an alternative Hadoop environment on AWS, using
Amazon EMR.
They generate around 20 TB of data on a monthly basis. Also on a monthly basis, files
need to be grouped and copied to Amazon S3 to be used for the Amazon
EMR environment. They have multiple S3 buckets across AWS accounts to which data
needs to be copied. There is a 10G AWS Direct Connect setup between their data
center and AWS, and the network team has agreed to allocate 50% of AWS Direct
Connect bandwidth to data transfer. The data transfer cannot take more than two
days.
What would be the MOST efficient approach to transfer data to AWS on a monthly
basis?
A. Use an offline copy method, such as an AWS Snowball device, to copy and transfer
data to Amazon S3.
B. Configure a multipart upload for Amazon S3 on AWS Java SDK to transfer data over
AWS Direct Connect.
C. Use Amazon S3 transfer acceleration capability to transfer data to Amazon S3 over
AWS Direct Connect.
D. Setup S3DistCop tool on the on-premises Hadoop environment to transfer data to
Amazon S3 over AWS Direct Connect.

Answer 74

D. Setup S3DistCop(出現就是答案) tool on the on-premises Hadoop environment to transfer data to
Amazon S3 over AWS Direct Connect.

Question 75

Q75
An organization is developing a mobile social application and needs to collect logs
from all devices on which it is installed. The organization is evaluating the
Amazon Kinesis Data Streams to push logs and Amazon EMR to process data. They
want to store data on HDFS using the default replication factor to replicate data
among the cluster, but they are concerned about the durability of the data. Currently,
they are producing 300 GB of raw data daily, with additional spikes during special
events. They will need to scale out the Amazon EMR cluster to match the increase in
streamed data.
Which solution prevents data loss and matches compute demand?
A. Use multiple Amazon EBS volumes on Amazon EMR to store processed data and
scale out the Amazon EMR cluster as needed.
B. Use the EMR File System and Amazon S3 to store processed data and scale out the
Amazon EMR cluster as needed.
C. Use Amazon DynamoDB to store processed data and scale out the Amazon EMR
cluster as needed.
D. use Amazon Kinesis Data Firehose and, instead of using Amazon EMR, stream logs
directly into Amazon Elasticsearch Service.

Answer 75

B. Use the EMR File System and Amazon S3 to store processed data and scale out the
Amazon EMR cluster as needed.

Question 76

Q76
An advertising organization uses an application to process a stream of events that are
received from clients in multiple unstructured formats.
The application does the following:
✑ Transforms the events into a single structured format and streams them to
Amazon Kinesis for real-time analysis.
✑ Stores the unstructured raw events from the log files on local hard drivers that are
rotated and uploaded to Amazon S3.
The organization wants to extract campaign performance reporting using an existing
Amazon redshift cluster.
Which solution will provide the performance data with the LEAST number of
operations?
A. Install the Amazon Kinesis Data Firehose agent on the application servers and use
it to stream the log files directly to Amazon Redshift.
B. Create an external table in Amazon Redshift and point it to the S3 bucket where
the unstructured raw events are stored.
C. Write an AWS Lambda function that triggers every hour to load the new log files
already in S3 to Amazon redshift.
D. Connect Amazon Kinesis Data Firehose to the existing Amazon Kinesis stream and
use it to stream the event directly to Amazon Redshift.

Answer 76

D. Connect Amazon Kinesis Data Firehose to the existing Amazon Kinesis stream and
use it to stream the event directly to Amazon Redshift.

Question 77

Q77
An organization needs to store sensitive information on Amazon S3 and process it
through Amazon EMR. Data must be encrypted on Amazon S3 and Amazon
EMR at rest and in transit. Using Thrift Server, the Data Analysis team users HIVE to
interact with this data. The organization would like to grant access to only specific
databases and tables, giving permission only to the SELECT statement.
Which solution will protect the data and limit user access to the SELECT statement on
a specific portion of data?
A. Configure Transparent Data Encryption on Amazon EMR. Create an Amazon EC2
instance and install Apache Ranger. Configure the authorization on the cluster to use
Apache Ranger.
B. Configure data encryption at rest for EMR File System (EMRFS) on Amazon S3.
Configure data encryption in transit for traffic between Amazon S3 and EMRFS.
Configure storage and SQL base authorization on HiveServer2.
C. Use AWS KMS for encryption of data. Configure and attach multiple roles with
different permissions based on the different user needs.
D. Configure Security Group on Amazon EMR. Create an Amazon VPC endpoint for
Amazon S3. Configure HiveServer2 to use Kerberos authentication on the cluster.

Answer 77

A. Configure Transparent Data Encryption on Amazon EMR. Create an Amazon EC2
instance and install Apache Ranger(出現及是答案). Configure the authorization on the cluster to use
Apache Ranger.

Question 78

Q78
Multiple rows in an Amazon Redshift table were accidentally deleted. A System
Administrator is restoring(唯一出現) the table from the most recent snapshot. The snapshot
contains all rows that were in the table before the deletion.
What is the SIMPLEST solution to restore the table without impacting users?
A. Restore the snapshot to a new Amazon Redshift cluster, then UNLOAD the table to
Amazon S3. In the original cluster, TRUNCATE the table, then load the data from
Amazon S3 by using a COPY command.
B. Use the Restore Table from a Snapshot command and specify a new table name
DROP the original table, then RENAME the new table to the original table name.
C. Restore the snapshot to a new Amazon Redshift cluster. Create a DBLINK between
the two clusters in the original cluster, TRUNCATE the destination table, then use an
INSERT command to copy the data from the new cluster.
D. Use the ALTER TABLE REVERT command and specify a time stamp of immediately
before the data deletion. Specify the Amazon Resource Name of the snapshot as the
SOURCE and use the OVERWRITE REPLACE option.

Answer 78

B. Use the Restore Table from a Snapshot command and specify a new table name
DROP the original table, then RENAME the new table to the original table name.

Question 79

Q79
An organization’s data warehouse contains sales data for reporting purposes.
data governance policies prohibit staff from accessing the customers’ credit card
numbers.
How can these policies be adhered to and still allow a Data Scientist to group
transactions that use the same credit card number?
A. Store a cryptographic hash of the credit card number.
B. Encrypt the credit card number with a symmetric encryption key, and give the key
only to the authorized Data Scientist.
C. Mask the credit card numbers to only show the last four digits of the credit card
number.
D. Encrypt the credit card number with an asymmetric encryption key and give the
decryption key only to the authorized Data Scientist.

Answer 79

A. Store a cryptographic(出現及是答案) hash of the credit card number.

Question 80

Q80
A real-time bidding company is rebuilding their monolithic application and is focusing
on serving real-time data. A large number of reads and writes are generated from
thousands of concurrent users who follow items and bid on the company’s sale
offers.
The company is experiencing high latency during special event spikes, with millions of
concurrent users.
The company needs to analyze and aggregate a part of the data in near real time to
feed an internal dashboard.
What is the BEST approach for serving and analyzing data, considering the constraint
of the row latency on the highly demanded data?
A. Use Amazon Aurora with Multi Availability Zone and read replicas. Use Amazon
ElastiCache in front of the read replicas to serve read-only content quickly. Use the
same database as datasource for the dashboard.
B. Use Amazon DynamoDB to store real-time data with Amazon DynamoDB.
Accelerator to serve content quickly. use Amazon DynamoDB Streams to replay all
changes to the table, process and stream to Amazon Elasti search Service with AWS
Lambda.
C. Use Amazon RDS with Multi Availability Zone. Provisioned IOPS EBS volume for
storage. Enable up to five read replicas to serve read-only content quickly. Use
Amazon EMR with Sqoop to import Amazon RDS data into HDFS for analysis.
D. Use Amazon Redshift with a DC2 node type and a multi-mode cluster. Create an
Amazon EC2 instance with pgpoo1 installed. Create an Amazon ElastiCache cluster
and route read requests through pgpoo1, and use Amazon Redshift for analysis.

Answer 80

B. Use Amazon DynamoDB to store real-time data with Amazon DynamoDB.
Accelerator to serve content quickly. use Amazon DynamoDB Streams to replay all
changes to the table, process and stream to Amazon Elasti search Service with AWS
Lambda.

Question 81

Q81
A gas company needs to monitor gas pressure in their pipelines. Pressure data is
streamed from sensors placed throughout the pipelines to monitor the data in real
time. When an anomaly is detected, the system must send a notification to open
valve. An Amazon Kinesis stream collects the data from the sensors and an anomaly
Kinesis stream triggers an AWS Lambda function to open the appropriate valve.
Which solution is the MOST cost-effective for responding to anomalies in real time?
A. Attach a Kinesis Firehose to the stream and persist the sensor data in an Amazon
S3 bucket. Schedule an AWS Lambda function to run a query in Amazon Athena
against the data in Amazon S3 to identify anomalies. When a change is detected, the
Lambda function sends a message to the anomaly stream to open the valve.
B. Launch an Amazon EMR cluster that uses Spark Streaming to connect to the
Kinesis stream and Spark machine learning to detect anomalies. When a change is
detected, the Spark application sends a message to the anomaly stream to open the
valve.
C. Launch a fleet of Amazon EC2 instances with a Kinesis Client Library application
that consumes the stream and aggregates sensor data over time to identify
anomalies. When an anomaly is detected, the application sends a message to the
anomaly stream to open the valve.
D. Create a Kinesis Analytics application by using the RANDOM_CUT_FOREST
function to detect an anomaly. When the anomaly score that is returned from the
function is outside of an acceptable range, a message is sent to the anomaly stream
to open the valve.

Answer 81

D. Create a Kinesis Analytics application by using the RANDOM_CUT_FOREST(出現即答案)
function to detect an anomaly. When the anomaly score that is returned from the
function is outside of an acceptable range, a message is sent to the anomaly stream
to open the valve.

Question 82

Q84
An organization is designing a public web application and has a requirement that
states all application users must be centrally authenticated before any operations are
permitted. The organization will need to create a user table with fast data lookup for
the application in which a user can read only his or her own data. All users already
have an account with amazon.com.
How can these requirements be met?
A. Create an Amazon RDS Aurora table, with Amazon_ID as the primary key. The
application uses amazon.com web identity federation to get a token that is used to
assume an IAM role from AWS STS. Use IAM database authentication by using the
rds:db-tag IAM authentication policy and GRANT Amazon RDS row-level read
permission per user.
B. Create an Amazon RDS Aurora table, with Amazon_ID as the primary key for each
user. The application uses amazon.com web identity federation to get a token that is
used to assume an IAM role. Use IAM database authentication by using rds:db-tag
IAM authentication policy and GRANT Amazon RDS row- level read permission per
user.
C. Create an Amazon DynamoDB table, with Amazon_ID as the partition key. The
application uses amazon.com web identity federation to get a token that is used to
assume an IAM role from AWS STS in the Role, use IAM condition context key
dynamodb:LeadingKeys with IAM substitution variables $ and allow the required
DynamoDB API operations in IAM JSON policy Action element for reading the records.
{www.amazon.com:user_id}
D. Create an Amazon DynamoDB table, with Amazon_ID as the partition key. The
application uses amazon.com web identity federation to assume an IAM role from
AWS STS in the Role, use IAM condition context key dynamodb:LeadingKeys with IAM
substitution variables $ {www.amazon.com:user_id} and allow the required
DynamoDB API operations in IAM JSON policy Action element for reading the
records.

Answer 82

C. Create an Amazon DynamoDB table, with Amazon_ID as the partition key. The
application uses amazon.com web identity federation to get a token that is used to
assume an IAM role from AWS STS in the Role, use IAM condition context key
dynamodb:LeadingKeys with IAM substitution variables $ and allow the required
DynamoDB API operations in IAM JSON policy Action element for reading the records.