無料Snowflake DEA-C01テスト練習問題試験問題集
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質問 # 52
A company uses Amazon S3 to store semi-structured data in a transactional data lake. Some of the data files are small, but other data files are tens of terabytes.
A data engineer must perform a change data capture (CDC) operation to identify changed data from the data source. The data source sends a full snapshot as a JSON file every day and ingests the changed data into the data lake.
Which solution will capture the changed data MOST cost-effectively?
- A. Create an AWS Lambda function to identify the changes between the previous data and the current data. Configure the Lambda function to ingest the changes into the data lake.
- B. Use an open source data lake format to merge the data source with the S3 data lake to insert the new data and update the existing data.
- C. Ingest the data into an Amazon Aurora MySQL DB instance that runs Aurora Serverless. Use AWS Database Migration Service (AWS DMS) to write the changed data to the data lake.
- D. Ingest the data into Amazon RDS for MySQL. Use AWS Database Migration Service (AWS DMS) to write the changed data to the data lake.
正解：B
質問 # 53
Streams cannot be created to query change data on which of the following objects? [Select All that Apply]
- A. Directory tables
- B. Views, including secure views
- C. Query Log Tables
- D. External tables
- E. Standard tables, including shared tables.
正解：C
解説：
Explanation
Streams supports all the listed objects except Query Log tables.
質問 # 54
When using the CURRENT_ROLE and CURRENT_USER functions with secure UDFs that will be shared with Snowflake accounts, Snowflake returns a NULL value for these functions?
- A. FALSE
- B. TRUE
正解：B
解説：
Explanation
When using the CURRENT_ROLE and CURRENT_USER functions with secure UDFs that will be shared with Snowflake accounts, Snowflake returns a NULL value for these functions. The rea-son is that the owner of the data being shared does not typically control the users or roles in the ac-count with which the UDF is being shared.
質問 # 55
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 production AWS account.
- B. 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.
- C. 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.
- D. 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.
正解：A
質問 # 56
A data engineer needs to create an AWS Lambda function that converts the format of data from .csv to Apache Parquet. The Lambda function must run only if a user uploads a .csv file to an Amazon S3 bucket.
Which solution will meet these requirements with the LEAST operational overhead?
- A. Create an S3 event notification that has an event type of s3:ObjectCreated:*. Use a filter rule to generate notifications only when the suffix includes .csv. Set the Amazon Resource Name (ARN) of the Lambda function as the destination for the event notification.
- B. Create an S3 event notification that has an event type of s3:*. Use a filter rule to generate notifications only when the suffix includes .csv. Set the Amazon Resource Name (ARN) of the Lambda function as the destination for the event notification.
- C. Create an S3 event notification that has an event type of s3:ObjectTagging:* for objects that have a tag set to .csv. Set the Amazon Resource Name (ARN) of the Lambda function as the destination for the event notification.
- D. Create an S3 event notification that has an event type of s3:ObjectCreated:*. Use a filter rule to generate notifications only when the suffix includes .csv. Set an Amazon Simple Notification Service (Amazon SNS) topic as the destination for the event notification. Subscribe the Lambda function to the SNS topic.
正解：A
解説：
This solution directly triggers the Lambda function only when a .csv file is uploaded to the S3 bucket, minimizing unnecessary invocations of the Lambda function. It uses a specific event type (s3:ObjectCreated:*) and a filter rule to ensure that the Lambda function is invoked only for relevant events. Additionally, it directly invokes the Lambda function without the need for additional services like Amazon SNS, reducing operational overhead.
質問 # 57
In Which Data Modelling Technique, Data Engineer generally refer the terms Hubs & Satellites?
- A. Data Vault
- B. Star Schema
- C. Data Hub
- D. Snowflake Schema
正解：A
解説：
Explanation
In Data Vault modelling, Hubs are entities of interest to the business.
They contain just a distinct list of business keys and metadata about when each key was first loaded and from where.
In Data Vault modelling, Satellites connect to Hubs or Links. They are Point in Time: so we can ask and answer the question, "what did we know when?" Satellites contain data about their parent Hub or Link and metadata about when the data was load-ed, from where, and a business effectivity date.
質問 # 58
Select the Correct statements with regard to using Federated authentication/SSO?
- A. Snowflake supports multiple audience values (i.e. Audience or Audience Restriction Fields) in the SAML 2.0 assertion from the identity provider to Snowflake.
- B. Snowflake supports using MFA in conjunction with SSO to provide additional levels of security.
- C. Snowflake supports using SSO with organizations, and you can use the corresponding URL in the SAML2 security integration.
- D. Snowflake supports SSO with Private Connectivity to the Snowflake Service for Snow-flake accounts on Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform.
正解：A、B、C、D
質問 # 59
For enabling non-ACCOUNTADMIN Roles to Perform Data Sharing Tasks, which two glob-al/account privileges snowflake provide?
- A. REFERENCE USAGE
- B. CREATE SHARE
- C. IMPORT SHARE
- D. OPERATE
正解：B、C
解説：
Explanation
CREATE SHARE
In a provider account, this privilege enables creating and managing shares (for sharing data with consumer accounts).
IMPORT SHARE
In a consumer account, this privilege enables viewing the inbound shares shared with the account. Also enables creating databases from inbound shares; requires the global CREATE DATABASE privilege.
By default, these privileges are granted only to the ACCOUNTADMIN role, ensuring that only ac-count administrators can perform these tasks. However, the privileges can be granted to other roles, enabling the tasks to be delegated to other users in the account.
質問 # 60
Elon, a Data Engineer, needs to Split Semi-structured Elements from the Source files and load them as an array into Separate Columns.
Source File:
1.+----------------------------------------------------------------------+
2.| $1 |
3.|----------------------------------------------------------------------|
4.| {"mac_address": {"host1": "197.128.1.1","host2": "197.168.0.1"}}, |
5.| {"mac_address": {"host1": "197.168.2.1","host2": "197.168.3.1"}} |
6.+----------------------------------------------------------------------+ Output: Splitting the Machine Address as below.
1.COL1 | COL2 |
2.|----------+----------|
3.| [ | [ |
4.| "197", | "197", |
5.| "128", | "168", |
6.| "1", | "0", |
7.| "1" | "1" |
8.| ] | ] |
9.| [ | [ |
10.| "197", | "197", |
11.| "168", | "168", |
12.| "2", | "3", |
13.| "1" | "1" |
14.| ] | ]
Which SnowFlake Function can Elon use to transform this semi structured data in the output for-mat?
- A. CONVERT_TO_ARRAY
- B. NEST
- C. SPLIT
- D. GROUP_BY_CONNECT
正解：C
質問 # 61
A company has developed several AWS Glue extract, transform, and load (ETL) jobs to validate and transform data from Amazon S3. The ETL jobs load the data into Amazon RDS for MySQL in batches once every day. The ETL jobs use a DynamicFrame to read the S3 data.
The ETL jobs currently process all the data that is in the S3 bucket. However, the company wants the jobs to process only the daily incremental data.
Which solution will meet this requirement with the LEAST coding effort?
- A. Create an ETL job that reads the S3 file status and logs the status in Amazon DynamoDB.
- B. Enable job bookmarks for the ETL jobs to update the state after a run to keep track of previously processed data.
- C. Configure the ETL jobs to delete processed objects from Amazon S3 after each run.
- D. Enable job metrics for the ETL jobs to help keep track of processed objects in Amazon CloudWatch.
正解：B
解説：
AWS Glue job bookmarks are designed to handle incremental data processing by automatically tracking the state.
質問 # 62
If the data retention period for a table is less than 90 days, and a stream has not been consumed, Snowflake temporarily extends this period to prevent it from going stale?
- A. FALSE
- B. TRUE
正解：A
解説：
Explanation
If the data retention period for a table is less than 14 days, and a stream has not been consumed, Snowflake temporarily extends this period to prevent it from going stale. The period is extended to the stream's offset, up to a maximum of 14 days by default, regardless of the Snowflake edition for your account. The maximum number of days for which Snowflake can extend the data retention period is determined by the MAX_DATA_EXTENSION_TIME_IN_DAYS parameter value. When the stream is consumed, the extended data retention period is reduced to the default period for the table.
質問 # 63
A data engineer needs to debug an AWS Glue job that reads from Amazon S3 and writes to Amazon Redshift. The data engineer enabled the bookmark feature for the AWS Glue job.
The data engineer has set the maximum concurrency for the AWS Glue job to 1.
The AWS Glue job is successfully writing the output to Amazon Redshift. However, the Amazon S3 files that were loaded during previous runs of the AWS Glue job are being reprocessed by subsequent runs.
What is the likely reason the AWS Glue job is reprocessing the files?
- A. The AWS Glue job does not have a required commit statement.
- B. The data engineer incorrectly specified an older version of AWS Glue for the Glue job.
- C. The maximum concurrency for the AWS Glue job is set to 1.
- D. The AWS Glue job does not have the s3:GetObjectAcl permission that is required for bookmarks to work correctly.
正解：A
解説：
https://docs.aws.amazon.com/glue/latest/dg/glue-troubleshooting-errors.html#error-job- bookmarks-reprocess-data
質問 # 64
Melissa, Senior Data Engineer, looking out to optimize query performance for one of the Critical Control Dashboard, she found that most of the searches by the users on the control dashboards are based on Equality search on all the underlying columns mostly. Which Best techniques she should consider here?
- A. The search optimization service would best fit here as it can be applied to all underlying columns & speeds up equality searches.
(Correct) - B. She can go for clustering on underlying tables which can speedup Equality searches.
- C. Melissa can create Indexes & Hints on the searchable columns to speed up Equality search.
- D. A materialized view speeds both equality searches and range searches.
正解：A
解説：
Explanation
Clustering a table can speed any of the following, as long as they are on the clustering key:
Range searches.
Equality searches.
However, a table can be clustered on only a single key (which can contain one or more columns or expressions).
The search optimization service speeds equality searches. However, this applies to all the columns of supported types in a table that has search optimization enabled. This is what required here& best fit for purpose.
A materialized view speeds both equality searches and range searches, as well as some sort opera-tions, but only for the subset of rows and columns included in the materialized view.
質問 # 65
While running an external function, me following error message is received:
Error:function received the wrong number of rows
What iscausing this to occur?
- A. External functions do not support multiple rows
- B. The JSON returned by the remote service is not constructed correctly
- C. The return message did not produce the same number of rows that it received
- D. Nested arrays are not supported in the JSON response
正解：C
解説：
Explanation
The error message "function received the wrong number of rows" is caused by the return message not producing the same number of rows that it received. External functions require that the remote service returns exactly one row for each input row that it receives from Snowflake. If the remote service returns more or fewer rows than expected, Snowflake will raise an error and abort the function execution. The other options are not causes of this error message. Option A is incorrect because external functions do support multiple rows as long as they match the input rows. Option B is incorrect because nested arrays are supported in the JSON response as long as they conform to the return type definition of the external function. Option C is incorrect because the JSON returned by the remote service may be constructed correctly but still produce a different number of rows than expected.
質問 # 66
Data Engineer Loading File named snowdata.tsv in the /datadir directory from his local machine to Snowflake stage and try to prefix the file with a folder named tablestage, please mark the correct command which helps him to load the files data into snowflake internal Table stage?
- A. put file://c:\datadir\snowdata.tsv @%tablestage;
- B. put file://c:\datadir\snowdata.tsv @~/tablestage;
- C. put file://c:\datadir\snowdata.tsv @tablestage;
- D. put file:///datadir/snowdata.tsv @%tablestage;
正解：A
解説：
Explanation
Execute PUT to upload (stage) local data files into an internal stage.
@% character combination identifies a table stage.
質問 # 67
A company uses an Amazon QuickSight dashboard to monitor usage of one of the company's applications. The company uses AWS Glue jobs to process data for the dashboard. The company stores the data in a single Amazon S3 bucket. The company adds new data every day.
A data engineer discovers that dashboard queries are becoming slower over time. The data engineer determines that the root cause of the slowing queries is long-running AWS Glue jobs.
Which actions should the data engineer take to improve the performance of the AWS Glue jobs?
(Choose two.)
- A. Partition the data that is in the S3 bucket. Organize the data by year, month, and day.
- B. Convert the AWS Glue schema to the DynamicFrame schema class.
- C. Modify the IAM role that grants access to AWS glue to grant access to all S3 features.
- D. Increase the AWS Glue instance size by scaling up the worker type.
- E. Adjust AWS Glue job scheduling frequency so the jobs run half as many times each day.
正解：A、D
質問 # 68
A Data Engineer needs to ingest invoice data in PDF format into Snowflake so that the data can be queried and used in a forecasting solution.
..... recommended way to ingest this data?
- A. Create a Java User-Defined Function (UDF) that leverages Java-based PDF parser libraries to parse PDF data into structured data
- B. Create an external table on the PDF files that are stored in a stage and parse the data nto structured data
- C. Use Snowpipe to ingest the files that land in an external stage into a Snowflake table
- D. Use a COPY INTO command to ingest the PDF files in an external stage into a Snowflake table with a VARIANT column.
正解：A
解説：
Explanation
The recommended way to ingest invoice data in PDF format into Snowflake is to create a Java User-Defined Function (UDF) that leverages Java-based PDF parser libraries to parse PDF data into structured data. This option allows for more flexibility and control over how the PDF data is extracted and transformed. The other options are not suitable for ingesting PDF data into Snowflake. Option A and B are incorrect because Snowpipe and COPY INTO commands can only ingest files that are in supported file formats, such as CSV, JSON, XML, etc. PDF files are not supported by Snowflake and will cause errors or unexpected results.
Option C is incorrect because external tables can only query files that are in supported file formats as well.
PDF files cannot be parsed by external tables and will cause errors or unexpected results.
質問 # 69
Let us say you have List of 50 Source files, which needs to be loaded into Snowflake internal stage. All these Source system files are already Brotli-compressed files. Which statement is correct with respect to Compression of Staged Files?
- A. Snowflake automatically detect Brotli Compression, will skip further compression of all 50 files.
- B. When staging 50 compressed files in a Snowflake stage, the files are automatically com-pressed using gzip.
- C. Even though Source files are already compressed, Snowflake do apply default gzip2 Compression to optimize the storage cost.
- D. Auto-detection is not yet supported for Brotli-compressed files; when staging or loading Brotli-compressed files, you must explicitly specify the compression method that was used.
正解：D
解説：
Explanation
Auto-detection is not yet supported for Brotli-compressed files; when staging or loading Brotli-compressed files, you must explicitly specify the compression method that was used.
To Know more about Compression of Staged Files, please refer the link:
https://docs.snowflake.com/en/user-guide/intro-summary-loading.html#compression-of-staged-files
質問 # 70
A company receives call logs as Amazon S3 objects that contain sensitive customer information.
The company must protect the S3 objects by using encryption. The company must also use encryption keys that only specific employees can access.
Which solution will meet these requirements with the LEAST effort?
- A. Use server-side encryption with AWS KMS keys (SSE-KMS) to encrypt the objects that contain customer information. Configure an IAM policy that restricts access to the KMS keys that encrypt the objects.
- B. Use server-side encryption with Amazon S3 managed keys (SSE-S3) to encrypt the objects that contain customer information. Configure an IAM policy that restricts access to the Amazon S3 managed keys that encrypt the objects.
- C. Use an AWS CloudHSM cluster to store the encryption keys. Configure the process that writes to Amazon S3 to make calls to CloudHSM to encrypt and decrypt the objects. Deploy an IAM policy that restricts access to the CloudHSM cluster.
- D. Use server-side encryption with customer-provided keys (SSE-C) to encrypt the objects that contain customer information. Restrict access to the keys that encrypt the objects.
正解：A
質問 # 71
A Data Engineer needs to know the details regarding the micro-partition layout for a table named invoice using a built-in function.
Which query will provide this information?
- A. SELECT SYSTEM$CLUSTERING_INTFORMATICII ('Invoice' ) ;
- B. SELECT $CLUSTERXNG_INFQRMATION ('Invoice')'
- C. CALL $CLUSTERINS_INFORMATION('Invoice');
- D. CALL SYSTEM$CLUSTERING_INFORMATION ('Invoice');
正解：A
解説：
Explanation
The query that will provide information about the micro-partition layout for a table named invoice using a built-in function is SELECT SYSTEM$CLUSTERING_INFORMATION('Invoice');. The SYSTEM$CLUSTERING_INFORMATION function returns information about the clustering status of a table, such as the clustering key, the clustering depth, the clustering ratio, the partition count, etc. The function takes one argument: the table name in a qualified or unqualified form. In this case, the table name is Invoice and it is unqualified, which means that it will use the current database and schema as the context. The other options are incorrect because they do not use a valid built-in function for providing information about the micro-partition layout for a table. Option B is incorrect because it uses $CLUSTERING_INFORMATION instead of SYSTEM$CLUSTERING_INFORMATION, which is not a valid function name. Option C is incorrect because it uses CALL instead of SELECT, which is not a valid way to invoke a table function.
Option D is incorrect because it uses CALL instead of SELECT and $CLUSTERING_INFORMATION instead of SYSTEM$CLUSTERING_INFORMATION, which are both invalid.
質問 # 72
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Snowflake DEA-C01 認定試験の出題範囲：
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今すぐDEA-C01問題を使おうDEA-C01問題集PDF：https://www.passtest.jp/Snowflake/DEA-C01-shiken.html
問題集練習試験問題学習ガイドはDEA-C01試験にはこれ：https://drive.google.com/open?id=1HUQzPpV-WjJBvhS59peBeCMYb2f241OA