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Data-Engineer-Associate최고품질시험덤프공부자료 - Data-Engineer-Associate인기자격증덤프자료

Amazon인증 Data-Engineer-Associate시험을 패스하여 자격증을 취득하는게 꿈이라구요? Itexamdump에서 고객님의Amazon인증 Data-Engineer-Associate시험패스꿈을 이루어지게 지켜드립니다. Itexamdump의 Amazon인증 Data-Engineer-Associate덤프는 가장 최신시험에 대비하여 만들어진 공부자료로서 시험패스는 한방에 끝내줍니다.

Amazon인증 Data-Engineer-Associate시험을 패스하여 자격증을 취득하여 승진이나 이직을 꿈구고 있는 분이신가요? 이 글을 읽게 된다면Amazon인증 Data-Engineer-Associate시험패스를 위해 공부자료를 마련하고 싶은 마음이 크다는것을 알고 있어 시장에서 가장 저렴하고 가장 최신버전의 Amazon인증 Data-Engineer-Associate덤프자료를 강추해드립니다. 높은 시험패스율을 자랑하고 있는Amazon인증 Data-Engineer-Associate덤프는 여러분이 승진으로 향해 달리는 길에 날개를 펼쳐드립니다.자격증을 하루 빨리 취득하여 승진꿈을 이루세요.

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Data-Engineer-Associate최고품질 시험덤프 공부자료 덤프로 시험에 도전

Amazon인증Data-Engineer-Associate시험을 위하여 최고의 선택이 필요합니다. Itexamdump 선택으로 좋은 성적도 얻고 하면서 저희 선택을 후회하지 않을것니다.돈은 적게 들고 효과는 아주 좋습니다.우리Itexamdump여러분의 응시분비에 많은 도움이 될뿐만아니라Amazon인증Data-Engineer-Associate시험은 또 일년무료 업데이트서비스를 제공합니다.작은 돈을 투자하고 이렇게 좋은 성과는 아주 바람직하다고 봅니다.

최신 AWS Certified Data Engineer Data-Engineer-Associate 무료샘플문제 (Q128-Q133):

질문 # 128
A company has a production AWS account that runs company workloads. The company's security team created a security AWS account to store and analyze security logs from the production AWS account. The security logs in the production AWS account are stored in Amazon CloudWatch Logs.
The company needs to use Amazon Kinesis Data Streams to deliver the security logs to the security AWS account.
Which solution will meet these requirements?

A. Create a destination data stream in the security AWS account. Create an IAM role and a trust policy to grant CloudWatch Logs the permission to put data into the stream. Create a subscription filter in the security AWS account.
B. Create a destination data stream in the production AWS account. In the security AWS account, create an IAM role that has cross-account permissions to Kinesis Data Streams in the production AWS account.
C. Create a destination data stream in the security AWS account. Create an IAM role and a trust policy to grant CloudWatch Logs the permission to put data into the stream. Create a subscription filter in the production AWS account.
D. Create a destination data stream in the production AWS account. In the production AWS account, create an IAM role that has cross-account permissions to Kinesis Data Streams in the security AWS account.

정답：C

설명：
Amazon Kinesis Data Streams is a service that enables you to collect, process, and analyze real-time streaming data. You can use Kinesis Data Streams to ingest data from various sources, such as Amazon CloudWatch Logs, and deliver it to different destinations, such as Amazon S3 or Amazon Redshift. To use Kinesis Data Streams to deliver the security logs from the production AWS account to the security AWS account, you need to create a destination data stream in the security AWS account. This data stream will receive the log data from the CloudWatch Logs service in the production AWS account. To enable this cross- account data delivery, you need to create an IAM role and a trust policy in the security AWS account. The IAM role defines the permissions that the CloudWatch Logs service needs to put data into the destination data stream. The trust policy allows the production AWS account to assume the IAM role. Finally, you need to create a subscription filter in the production AWS account. A subscription filter defines the pattern to match log events and the destination to send the matching events. In this case, the destination is the destination data stream in the security AWS account. This solution meets the requirements of using Kinesis Data Streams to deliver the security logs to the security AWS account. The other options are either not possible or not optimal.
You cannot create a destination data stream in the production AWS account, as this would not deliver the data to the security AWS account. You cannot create a subscription filter in the security AWS account, as this would not capture the log events from the production AWS account. References:
* Using Amazon Kinesis Data Streams with Amazon CloudWatch Logs
* AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 3: Data Ingestion and Transformation, Section 3.3: Amazon Kinesis Data Streams

질문 # 129
A data engineer wants to orchestrate a set of extract, transform, and load (ETL) jobs that run on AWS. The ETL jobs contain tasks that must run Apache Spark jobs on Amazon EMR, make API calls to Salesforce, and load data into Amazon Redshift.
The ETL jobs need to handle failures and retries automatically. The data engineer needs to use Python to orchestrate the jobs.
Which service will meet these requirements?

A. Amazon Managed Workflows for Apache Airflow (Amazon MWAA)
B. AWS Step Functions
C. AWS Glue
D. Amazon EventBridge

정답：A

설명：
The data engineer needs to orchestrate ETL jobs that include Spark jobs on Amazon EMR, API calls to Salesforce, and loading data into Redshift. They also need automatic failure handling and retries. Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is the best solution for this requirement.
* Option A: Amazon Managed Workflows for Apache Airflow (Amazon MWAA)Apache Airflow is designed for complex job orchestration, allowing users to define workflows (DAGs) in Python. MWAA manages Airflow and its integrations with other AWS services, including Amazon EMR, Redshift, and external APIs like Salesforce. It provides automatic retry handling, failure detection, and detailed monitoring, which fits the use case perfectly.
* Option B (AWS Step Functions) can orchestrate tasks but doesn't natively support complex workflow definitions with Python like Airflow does.
* Option C (AWS Glue) is more focused on ETL and doesn't handle the orchestration of external systems like Salesforce as well as Airflow.
* Option D (Amazon EventBridge) is more suited for event-driven architectures rather than complex workflow orchestration.
References:
* Amazon Managed Workflows for Apache Airflow
* Apache Airflow on AWS

질문 # 130
A banking company uses an application to collect large volumes of transactional data. The company uses Amazon Kinesis Data Streams for real-time analytics. The company's application uses the PutRecord action to send data to Kinesis Data Streams.
A data engineer has observed network outages during certain times of day. The data engineer wants to configure exactly-once delivery for the entire processing pipeline.
Which solution will meet this requirement?

A. Design the data source so events are not ingested into Kinesis Data Streams multiple times.
B. Design the application so it can remove duplicates during processing by embedding a unique ID in each record at the source.
C. Update the checkpoint configuration of the Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) data collection application to avoid duplicate processing of events.
D. Stop using Kinesis Data Streams. Use Amazon EMR instead. Use Apache Flink and Apache Spark Streaming in Amazon EMR.

정답：B

설명：
For exactly-once delivery and processing in Amazon Kinesis Data Streams, the best approach is to design the application so that it handles idempotency. By embedding a unique ID in each record, the application can identify and remove duplicate records during processing.
* Exactly-Once Processing:
* Kinesis Data Streams does not natively support exactly-once processing. Therefore, idempotency should be designed into the application, ensuring that each record has a unique identifier so that the same event is processed only once, even if it is ingested multiple times.
* This pattern is widely used for achieving exactly-once semantics in distributed systems.

질문 # 131
A technology company currently uses Amazon Kinesis Data Streams to collect log data in real time. The company wants to use Amazon Redshift for downstream real-time queries and to enrich the log data.
Which solution will ingest data into Amazon Redshift with the LEAST operational overhead?

A. Set up an Amazon Data Firehose delivery stream to send data to a Redshift provisioned cluster table.
B. Configure Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to send data directly to a Redshift provisioned cluster table.
C. Use Amazon Redshift streaming ingestion from Kinesis Data Streams and to present data as a materialized view.
D. Set up an Amazon Data Firehose delivery stream to send data to Amazon S3. Configure a Redshift provisioned cluster to load data every minute.

정답：C

설명：
The most efficient and low-operational-overhead solution for ingesting data into Amazon Redshift from Amazon Kinesis Data Streams is to use Amazon Redshift streaming ingestion. This feature allows Redshift to directly ingest streaming data from Kinesis Data Streams and process it in real-time.
Amazon Redshift Streaming Ingestion:
Redshift supports native streaming ingestion from Kinesis Data Streams, allowing real-time data to be queried using materialized views.
This solution reduces operational complexity because you don't need intermediary services like Amazon Kinesis Data Firehose or S3 for batch loading.
Reference:
Alternatives Considered:
A (Data Firehose to Redshift): This option is more suitable for batch processing but incurs additional operational overhead with the Firehose setup.
B (Firehose to S3): This involves an intermediate step, which adds complexity and delays the real-time requirement.
C (Managed Service for Apache Flink): This would work but introduces unnecessary complexity compared to Redshift's native streaming ingestion.
Amazon Redshift Streaming Ingestion from Kinesis
Materialized Views in Redshift

질문 # 132
A company uses an Amazon Redshift provisioned cluster as its database. The Redshift cluster has five reserved ra3.4xlarge nodes and uses key distribution.
A data engineer notices that one of the nodes frequently has a CPU load over 90%. SQL Queries that run on the node are queued. The other four nodes usually have a CPU load under 15% during daily operations.
The data engineer wants to maintain the current number of compute nodes. The data engineer also wants to balance the load more evenly across all five compute nodes.
Which solution will meet these requirements?

A. Change the primary key to be the data column that is most often used in a WHERE clause of the SQL SELECT statement.
B. Upgrade the reserved node from ra3.4xlarqe to ra3.16xlarqe.
C. Change the distribution key to the table column that has the largest dimension.
D. Change the sort key to be the data column that is most often used in a WHERE clause of the SQL SELECT statement.

정답：C

설명：
Changing the distribution key to the table column that has the largest dimension will help to balance the load more evenly across all five compute nodes. The distribution key determines how the rows of a table are distributed among the slices of the cluster. If the distribution key is not chosen wisely, it can cause data skew, meaning some slices will have more data than others, resulting in uneven CPU load and query performance. By choosing the table column that has the largest dimension, meaning the column that has the most distinct values, as the distribution key, the data engineer can ensure that the rows are distributed more uniformly across the slices, reducing data skew and improving query performance.
The other options are not solutions that will meet the requirements. Option A, changing the sort key to be the data column that is most often used in a WHERE clause of the SQL SELECT statement, will not affect the data distribution or the CPU load. The sort key determines the order in which the rows of a table are stored on disk, which can improve the performance of range-restricted queries, but not the load balancing. Option C, upgrading the reserved node from ra3.4xlarge to ra3.16xlarge, will not maintain the current number of compute nodes, as it will increase the cost and the capacity of the cluster. Option D, changing the primary key to be the data column that is most often used in a WHERE clause of the SQL SELECT statement, will not affect the data distribution or the CPU load either. The primary key is a constraint that enforces the uniqueness of the rows in a table, but it does not influence the data layout or the query optimization. Reference:
Choosing a data distribution style
Choosing a data sort key
Working with primary keys

질문 # 133
......

Amazon인증 Data-Engineer-Associate 시험은 최근 제일 인기있는 인증시험입니다. IT업계에 종사하시는 분들은 자격증취득으로 자신의 가치를 업그레이드할수 있습니다. Amazon인증 Data-Engineer-Associate 시험은 유용한 IT자격증을 취득할수 있는 시험중의 한과목입니다. Itexamdump에서 제공해드리는Amazon인증 Data-Engineer-Associate 덤프는 여러분들이 한방에 시험에서 통과하도록 도와드립니다. 덤프를 공부하는 과정은 IT지식을 더 많이 배워가는 과정입니다. 시험대비뿐만아니라 많은 지식을 배워드릴수 있는 덤프를Itexamdump에서 제공해드립니다. Itexamdump덤프는 선택하시면 성공을 선택한것입니다.

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