Amazon AWS Certified Big Data - Specialty - AWS Certified Big Data - Specialty Exam
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Total 85 questions
Question #6 (Topic: Topic 1)
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.)
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 tables.
Answer: BD
Question #7 (Topic: Topic 1)
A large grocery distributor receives daily depletion reports from the field in the form of gzip archives OF 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?
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: B
Question #8 (Topic: Topic 1)
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?
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 call.
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: A
Question #9 (Topic: Topic 1)
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?
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: A
Question #10 (Topic: Topic 1)
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?
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: A
