今すぐDEA-C01問題を使おうDEA-C01問題集PDF [Q33-Q58]

今すぐDEA-C01問題を使おうDEA-C01問題集PDF

問題集練習試験問題学習ガイドはDEA-C01試験合格させます

質問 # 33
Which callback function is required within a JavaScript User-Defined Function (UDF) for it to execute successfully?

A. initialize ()
B. handler
C. processRow ()
D. finalize ()

正解：C

解説：
Explanation
The processRow () callback function is required within a JavaScript UDF for it to execute successfully. This function defines how each row of input data is processed and what output is returned. The other callback functions are optional and can be used for initialization, finalization, or error handling.

質問 # 34
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. Use Snowpipe to ingest the files that land in an external stage into a Snowflake table
B. Use a COPY INTO command to ingest the PDF files in an external stage into a Snowflake table with a VARIANT column.
C. Create an external table on the PDF files that are stored in a stage and parse the data nto structured data
D. Create a Java User-Defined Function (UDF) that leverages Java-based PDF parser libraries to parse PDF data into structured data

正解：D

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 # 35
Which property can be used with ALTER USER command to temporarily disable MFA for the user so that they can log in?

A. MINS_TO_SKIP_MFA
B. HOURS_TO_BYPASS_MFA
C. SECS_TO_BYPASS_MFA
D. MINS_TO_BYPASS_MFA

正解：D

解説：
Explanation
You can use the following properties for the ALTER USER command to perform these tasks:
MINS_TO_BYPASS_MFA
Specifies the number of minutes to temporarily disable MFA for the user so that they can log in. Af-ter the time passes, MFA is enforced and the user cannot log in without the temporary token gener-ated by the Duo Mobile application.

質問 # 36
A table is loaded using Snowpipe and truncated afterwards Later, a Data Engineer finds that the table needs to be reloaded but the metadata of the pipe will not allow the same files to be loaded again.
How can this issue be solved using the LEAST amount of operational overhead?

A. Set the FORCE=TRUE option in the Snowpipe COPY INTO command
B. Recreate the pipe by using the create or replace pipe command
C. Modify the file by adding a blank row to the bottom and re-stage the file
D. Wait until the metadata expires and then reload the file using Snowpipe

正解：A

解説：
Explanation
The FORCE=TRUE option in the Snowpipe COPY INTO command allows Snowpipe to load files that have already been loaded before, regardless of the metadata. This is the easiest way to reload the same files without modifying them or recreating the pipe.

質問 # 37
Data Engineer try to load data from external stage using Snowpipe & later find out that some Set of Files Not Loaded. To debug the issue, she used COPY_HISTORY function & cross verified that its output indicates a subset of files was not loaded. What is possible reason of arising this situation in both REST API call and Auto-Ingest methods? [Select 2]

A. A backlog of data files already existed in the external stage do not have any impact on Load failure, as this is well managed by serverless SnowPipe
B. An event notification failure prevented a set of files from getting queued.
C. External event-driven functionality is used to call the REST APIs, and a backlog of da-ta files already existed in the external stage before the events were configured.
D. Files modified and staged again after 14 days and Snowpipe ignores modified files that are staged again.

正解：B、C

解説：
Explanation
COPY_HISTORY Record Indicates Unloaded Subset of Files:
If the COPY_HISTORY function output indicates a subset of files was not loaded, you may try to "refresh" the pipe.
This situation can arise in any of the following situations:
The external stage was previously used to bulk load data using the COPY INTO table command.
REST API:
o External event-driven functionality is used to call the REST APIs, and a backlog of data files al-ready existed in the external stage before the events were configured.
Auto-ingest:
o A backlog of data files already existed in the external stage before event notifications were con-figured.
o An event notification failure prevented a set of files from getting queued.
To load the data files in your external stage using the configured pipe, execute an ALTER PIPE ... REFRESH statement.

質問 # 38
Michael, a Data Engineer Running a Data query to achieve Union of Data sets coming from Multi-ple data sources, later he figured out that Data processing query is taking more time than expected. He started analyzing the Query performance using query profile interface. He discovered & realized that he used UNION when the UNION ALL semantics was sufficient.
Which Extra Data Processing Operator Michael figured out while doing query profile analysis in this case which helps him to identify this performance bottlenecks?

A. Flatten
B. Filter
C. Aggregate
D. UNION ALL
E. Join

正解：C

解説：
Explanation
In SQL, it is possible to combine two sets of data with either UNION or UNION ALL constructs. The difference between them is that UNION ALL simply concatenates inputs, while UNION does the same, but also performs duplicate elimination.
A common mistake is to use UNION when the UNION ALL semantics are sufficient. These que-ries show in Query Profile as a UnionAll operator with an extra Aggregate operator on top (which performs duplicate elimination).
To Know more about Data Processing Operators, please do refer:
https://docs.snowflake.com/en/user-guide/ui-query-profile#operator-types

質問 # 39
Which ones are the false statements about Materialized Views?

A. Materialized views can be secure views.
B. Snowflake does not allow standard DML (e.g. INSERT, UPDATE, DELETE) on ma-terialized views.
C. Materialized views are first-class account objects.
D. A materialized view can also be used as the data source for a subquery.
E. Clustering a subset of the materialized views on a table tends to be more cost-effective than clustering the table itself.
F. Snowflake does not allow users to truncate materialized views.

正解：C

解説：
Explanation
Materialized views are first-class Database objects & rest of the understandings are true.

質問 # 40
Steven created the task, what additional privileges required by Steven on the task so that he can suspend or resume the tasks?

A. In addition to the task owner, a Steven Role must have OPERATE privilege on the task so that he can suspend or resume the task.
B. Steven needs to have Global Managed RESUME privilege by TASK administrator.
C. Steven is already owner of the task; he can execute the task & suspend/resume the task without any additional privileges.
D. Steven must have SUSPEND privilege on the task so that he can suspend or resume the task.

正解：A

解説：
Explanation
In addition to the task ownership privilege, a role that has the OPERATE privilege on the task can suspend or resume the task.

質問 # 41
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 # 42
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. 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.
B. Even though Source files are already compressed, Snowflake do apply default gzip2 Compression to optimize the storage cost.
C. When staging 50 compressed files in a Snowflake stage, the files are automatically com-pressed using gzip.
D. Snowflake automatically detect Brotli Compression, will skip further compression of all 50 files.

正解：A

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 # 43
How can the following relational data be transformed into semi-structured data using the LEAST amount of operational overhead?

A. Use the to_json function
B. Use the PAESE_JSON function to produce a variant value
C. Use the OBJECT_CONSTRUCT function to return a Snowflake object
D. Use the TO_VARIANT function to convert each of the relational columns to VARIANT.

正解：C

解説：
Explanation
This option is the best way to transform relational data into semi-structured data using the least amount of operational overhead. The OBJECT_CONSTRUCT function takes a variable number of key-value pairs as arguments and returns a Snowflake object, which is a variant type that can store JSON data. The function can be used to convert each row of relational data into a JSON object with the column names as keys and the column values as values.

質問 # 44
The following is returned fromSYSTEMCLUSTERING_INFORMATION () for a tablenamed orders with adate column named O_ORDERDATE:

What does the total_constant_partition_count value indicate about this table?

A. The data inO_ORDERDATEhas a very low cardinality as there are 493 micro-partitions where there is only a single distinct value in that column for all rows in the micro-partition
B. The table is not clustered well on O_ORDERDATE, as there are 493 micro-partitions where the range of values in that column overlap with every other micro partition in the table.
C. The table is clustered very well on_ORDERDATE, as there are 493 micro-partitions that could not be significantly improved by reclustering
D. The data inO_ORDERDATEdoes not change very often as there are 493 micro-partitionscontaining rows where that column has not been modified since the row was created

正解：B

解説：
Explanation
The total_constant_partition_count value indicates the number of micro-partitions where the clustering key column has a constant value across all rows in the micro-partition. However, this does not necessarily mean that the table is clustered well on that column, as there could be other micro-partitions where the range of values in that column overlap with each other. This is the case for the orders table, as the clustering depth is 1, which means that every micro-partition overlaps with every other micro-partition on O_ORDERDATE. This indicates that the table is not clustered well on O_ORDERDATE and could benefit from reclustering.

質問 # 45
Tasks may optionally use table streams to provide a convenient way to continuously process new or changed data. A task can transform new or changed rows that a stream surfaces. Each time a task is scheduled to run, it can verify whether a stream contains change data for a table and either consume the change data or skip the current run if no change data exists. Which System Function can be used by Data engineer to verify whether a stream contains changed data for a table?

A. SYSTEM$STREAM_HAS_CHANGE_DATA
B. SYSTEM$STREAM_CDC_DATA
C. SYSTEM$STREAM_HAS_DATA
D. SYSTEM$STREAM_DELTA_DATA

正解：C

解説：
Explanation
SYSTEM$STREAM_HAS_DATA
Indicates whether a specified stream contains change data capture (CDC) records.

質問 # 46
Select the incorrect statement while working with warehouses?

A. Resizing a suspended warehouse does not provision any new compute resources for the warehouse.
B. Resizing a warehouse to a larger size is useful while loading and unloading significant amounts of data.
C. Compute resources waiting to shut down are considered to be in "quiesce" mode.
D. Resizing a warehouse will have any immediate impact on statements that are currently being executed by the warehouse.

正解：D

解説：
Explanation
Resizing a warehouse doesn't have any impact on statements that are currently being executed by the warehouse. When resizing to a larger size, the new compute resources, once fully provisioned, are used only to execute statements that are already in the warehouse queue, as well as all future statements submitted to the warehouse.

質問 # 47
How Data Engineer can do Monitoring of Files which are Staged Internally during Continuous data pipelines loading process? [Select all that apply]

A. She Can Monitor the files using Metadata maintained by Snowflake i.e. file-name,last_modified date etc.
B. Snowflake retains historical data for COPY INTO commands executed within the pre-vious 14 days.
C. She can Monitor the status of each COPY INTO <table> command on the History tab page of the classic web interface.
D. She can use the DATA_VALIDATE function to validate the data files She have loaded and can retrieve any errors encountered during the load.
E. She can use the DATA_LOAD_HISTORY Information Schema view to retrieve the history of data loaded into tables using the COPY INTO command.

正解：A、B、C

解説：
Explanation
Monitoring Files Staged Internally
Snowflake maintains detailed metadata for each file uploaded into internal stage (for users, tables, and stages), including:
File name
File size (compressed, if compression was specified during upload)
LAST_MODIFIED date, i.e. the timestamp when the data file was initially staged or when it was last modified, whichever is later In addition, Snowflake retains historical data for COPY INTO commands executed within the pre-vious 14 days. The metadata can be used to monitor and manage the loading process, including de-leting files after upload completes:
Use the LIST command to view the status of data files that have been staged.
Monitor the status of each COPY INTO <table> command on the History tab page of the classic web interface.
Use the VALIDATE function to validate the data files you've loaded and retrieve any errors en-countered during the load.
Use the LOAD_HISTORY Information Schema view to retrieve the history of data loaded into tables using the COPY INTO command.

質問 # 48
A Data Engineer is trying to load the following rows from a CSV file into a table in Snowflake with the following structure:

....engineer is using the following COPY INTO statement:

However, the following error is received.

Which file format option should be used to resolve the error and successfully load all the data into the table?

A. ERROR_ON_COLUMN_COUKT_MISMATCH = FALSE
B. FIELD_DELIMITER = ","
C. ESC&PE_UNENGLO9ED_FIELD = '\\'
D. FIELD OPTIONALLY ENCLOSED BY = " "

正解：D

解説：
Explanation
The file format option that should be used to resolve the error and successfully load all the data into the table is FIELD_OPTIONALLY_ENCLOSED_BY = '"'. This option specifies that fields in the file may be enclosed by double quotes, which allows for fields that contain commas or newlines within them. For example, in row 3 of the file, there is a field that contains a comma within double quotes: "Smith Jr., John". Without specifying this option, Snowflake will treat this field as two separate fields and cause an error due to column count mismatch. By specifying this option, Snowflake will treat this field as one field and load it correctly into the table.

質問 # 49
As Data Engineer, you have been asked to access data held in AWS Glacier Deep Archive storage class for Historical Data Analysis, which one is the correct statement to recommend?

A. Upload (i.e. stage) files to your cloud storage account using the tools provided by the cloud storage service.
B. We can simply access AWS Glacier Deep Archive storage External Stage data using PUT command.
C. Loading data from AWS cloud storage services is supported regardless of the cloud platform that hosts your Snowflake account.
D. You cannot access data held in archival cloud storage classes that requires restoration before it can be retrieved.
E. Data can be accessed from External stage using AWS Private link in this case.

正解：D

解説：
Explanation
External stage
References data files stored in a location outside of Snowflake. Currently, the following cloud stor-age services are supported:
Amazon S3 buckets
Google Cloud Storage buckets
Microsoft Azure containers
The storage location can be either private/protected or public.
You cannot access data held in archival cloud storage classes that requires restoration before it can be retrieved. These archival storage classes include, for example, the Amazon S3 Glacier Flexible Retrieval or Glacier Deep Archive storage class, or Microsoft Azure Archive Storage.

質問 # 50
Robert, A Data Engineer, found that Pipe become stale as it was paused for longer than the limited retention period for event messages received for the pipe (14 days by default) & also the previous pipe owner transfers the ownership of this pipe to Robert role while the pipe was paused. How Robert in this case, Resume this stale pipe?

A. ALTER PIPES ... RESUME statement will resume the pipe.
B. select sys-tem$pipe_force_resume('mydb.myschema.stalepipe','staleness_check_override, ownership_transfer_check_override');
C. He can apply System function SYSTEM$PIPE_STALE_RESUME with ALTER PIPE statement.
D. PIPE needs to recreate in this scenario, as pipe already past 14 days of period & stale.
E. Robert can use SYSTEM$PIPE_FORCE_RESUME function to resume this stale pipe.

正解：B

解説：
Explanation
When a pipe is paused, event messages received for the pipe enter a limited retention period. The period is 14 days by default. If a pipe is paused for longer than 14 days, it is considered stale.
To resume a stale pipe, a qualified role must call the SYSTEM$PIPE_FORCE_RESUME function and input the STALENESS_CHECK_OVERRIDE argument. This argument indicates an under-standing that the role is resuming a stale pipe.
For example, resume the stale stalepipe1 pipe in the mydb.myschema database and schema:
SELECT SYS-TEM$PIPE_FORCE_RESUME('mydb.myschema.stalepipe1','staleness_check_override'); While the stale pipe was paused, if ownership of the pipe was transferred to another role, then re-suming the pipe requires the additional OWNERSHIP_TRANSFER_CHECK_OVERRIDE argu-ment. For example, resume the stale stalepipe2 pipe in the mydb.myschema database and schema, which transferred to a new role:
SELECT SYS-TEM$PIPE_FORCE_RESUME('mydb.myschema.stalepipe1','staleness_check_override, own-ership_transfer_check_override');

質問 # 51
Regular views do not cache data, and therefore cannot improve performance by caching?

A. FALSE
B. TRUE

正解：B

解説：
Explanation
Regular views do not cache data, and therefore cannot improve performance by caching.

質問 # 52
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. Nested arrays are not supported in the JSON response
B. The return message did not produce the same number of rows that it received
C. External functions do not support multiple rows
D. The JSON returned by the remote service is not constructed correctly

正解：B

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 # 53
Mark the incorrect statement in case Data engineer using the COPY INTO <table> command to load data from files into Snowflake tables?

A. For Local environment, Files are first copied ("staged") to an internal (Snowflake) stage, then loaded into a table.
B. UTF-32 & UTF-16 both encoding character sets supported for loading data from de-limited files (CSV, TSV, etc.)
C. For loading data from all semi-structured supported file formats (JSON, Avro, etc.), as well as unloading data, UTF-8 is the only supported character set.
D. For Data loading of files with semi-structured file formats (JSON, Avro, etc.), the only supported character set is UTF-16.

正解：D

解説：
Explanation
For Data Loading of delimited files (CSV, TSV, etc.), the default character set is UTF-8. To use any other characters sets, you must explicitly specify the encoding to use for loading.
For semi-structured file formats (JSON, Avro, etc.), the only supported character set is UTF-8.
Rest of the statements are correct.

質問 # 54
Which stages support external tables?

A. External stages only from any region, and any cloud provider
B. Internal stages only; within a single Snowflake account
C. External stages only, only on the same region and cloud provider as the Snowflake account
D. internal stages only from any Snowflake account in the organization

正解：A

解説：
Explanation
External stages only from any region, and any cloud provider support external tables. External tables are virtual tables that can query data from files stored in external stages without loading them into Snowflake tables. External stages are references to locations outside of Snowflake, such as Amazon S3 buckets, Azure Blob Storage containers, or Google Cloud Storage buckets. External stages can be created from any region and any cloud provider, as long as they have a valid URL and credentials. The other options are incorrect because internal stages do notsupport external tables. Internal stages are locations within Snowflake that can store files for loading or unloading data. Internal stages can be user stages, table stages, or named stages.

質問 # 55
Which UDF programming language is not supported with Snowflake Secure Data Sharing feature?

A. JAVA
B. SQL
C. JAVASCRIPT
D. PYTHON

正解：C

質問 # 56
Which Function would Data engineer used to recursively resume all tasks in Chain of Tasks rather than resuming each task individually (using ALTER TASK ... RESUME)?

A. SYSTEM$TASK_RECURSIVE_ENABLE
B. SYSTEM$TASK_DEPENDENTS
C. SYSTEM$TASK_DEPENDENTS_ENABLE
D. SYSTEM$TASK_DEPENDENTS_RESUME

正解：C

解説：
Explanation
To recursively resume all tasks in a DAG(A Directed Acyclic Graph (DAG) is a series of tasks com-posed of a single root task and additional tasks, organized by their dependencies.), query the SYS-TEM$TASK_DEPENDENTS_ENABLE function rather than resuming each task individually (us-ing ALTER TASK ... RESUME).

質問 # 57
Mark the Correct Statements:
Statement 1. Enable failover for a primary database to one or more accounts in your organization using an ALTER DATABASE ... ENABLE FAILOVER TO ACCOUNTS statement.
Statement 2. Enabling failover for a primary database can be done by Data Engineer either before or after a replica of the primary database has been created in a specified account.