Blog - ويب ثري سكور

Mike Powell Mike Powell

0 دورة ملتحَق بها • 0 write a review

نبذة عنا

Snowflake DEA-C02考題資訊擁有模擬真實考試環境與場境的軟件VCE版本和高通過率的題目

KaoGuTi長年以來一直向大家提供與Snowflake認證考試相關的DEA-C02參考資料。這是一個被廣大考生檢驗過的網站，可以向大家提供最好的考試考古題。KaoGuTi全面保證考生們的利益，得到了大家的一致好評。而且，KaoGuTi也是當前市場上最值得你信賴的網站。

作為一位 DEA-C02 考生而言，作好充分的準備可以幫助您通過考試。KaoGuTi 的 DEA-C02 題庫覆蓋了最新的 DEA-C02 考試指南及考試真題題型。DEA-C02 隸屬于 Snowflake 認證考試科目。我們的 DEA-C02 認證考題已經幫助很多考生通過考試，試題質量和考題的覆蓋率都有保證，保證考生權利不受任何損失。獲取 DEA-C02 考試認證證書可以用來實施一些複雜多變的工程。

>> DEA-C02考題資訊 <<

最好的的DEA-C02考題資訊，全面覆蓋DEA-C02考試知識點

KaoGuTi Snowflake的DEA-C02考試培訓資料得到廣大考生的稱譽已經不是最近幾天的事情了，說明KaoGuTi Snowflake的DEA-C02考試培訓資料信得過，確實可以幫助廣大考生通過考試，讓考生沒有後顧之憂，KaoGuTi Snowflake的DEA-C02考試培訓資料暢銷和同行相比一直遙遙領先，率先得到廣大消費者的認可，口碑當然不用說，如果你要參加 Snowflake的DEA-C02考試，就趕緊進KaoGuTi這個網站，相信你一定會得到你想要的，不會錯過就不會後悔，如果你想成為最專業最受人矚目的IT專家，那就趕緊加入購物車吧。

最新的 SnowPro Advanced DEA-C02 免費考試真題 (Q214-Q219):

問題 #214
You have a Snowflake table 'ORDERS with columns 'ORDER ID, 'CUSTOMER ID', 'ORDER DATE, and 'TOTAL AMOUNT. You notice that many queries filtering by 'ORDER DATE are slow, even after enabling query acceleration. You decide to implement a caching strategy to improve performance. Which of the following approaches will be most effective in leveraging Snowflake's caching capabilities and improving the performance of date-filtered queries, especially when the data volume for each date is large and varied? Assume virtual warehouse is medium size.

A. Use after running a query filtered by 'ORDER_DATE'. This will cache the result of the query in the current session for subsequent queries with the same filter.
B. Increase the data retention period for the 'ORDERS' table. A longer retention period will ensure that more data is available in the Snowflake cache.
C. Create a clustered table on 'ORDER_DATE. This will physically organize the data on disk, allowing Snowflake to quickly retrieve the relevant data for date- filtered queries.
D. Apply a WHERE clause with a date range in all the SELECT statements. This forces the metadata caching.
E. Create a materialized view that pre-aggregates the data by 'ORDER_DATE , such as calculating the sum of 'TOTAL_AMOUNT for each date. This will allow Snowflake to serve the results directly from the materialized view for queries that require aggregation.

答案：C

解題說明：
Clustering on 'ORDER DATE' (A) is the most effective approach. Clustering physically organizes the data, allowing Snowflake to efficiently prune partitions and retrieve only the necessary data for date-filtered queries. Materialized views (B) are suitable for pre-aggregation, but less suitable for ad-hoc queries on different date ranges where only filtering is required. Increasing the data retention period (C) does not impact caching performance and may increase storage costs. 'RESULT_SCAN' (D) is session-specific and not persistent. Adding a WHERE clause (E) helps, but is not as impactful as Clustering.

問題 #215
You have a base table 'ORDERS' with columns 'ORDER ID, 'CUSTOMER D', 'ORDER DATE, and 'ORDER AMOUNT'. You need to create a view that aggregates the total order amount per customer per month. However, for data governance purposes, you need to ensure that the view only shows data for the last 3 months. What is the MOST efficient and secure way to create this view in Snowflake?

A. Option B
B. Option E
C. Option A
D. Option C
E. Option D

答案：D

解題說明：
Option C is the most efficient and secure because it creates a SECURE VIEW (hiding the underlying table definition), filters the data to include only the last 3 months in the 'WHERE' clause, and performs the necessary aggregation. Using a SECURE VIEW is crucial for data governance when sharing or exposing data. Options A and D do not create secure views. Option B is unnecessarily complex using a CTE. Option E will throw an error because is not allowed in this context.

問題 #216
A data engineering team uses Snowflake to analyze website clickstream data stored in AWS S3. The data is partitioned by year and month in the S3 bucket. They need to query the data frequently for reporting purposes but don't want to ingest the entire dataset into Snowflake due to storage costs and infrequent full dataset analysis. Which approach is the MOST efficient and cost-effective way to enable querying of this data in Snowflake?

A. Create a Snowflake external stage pointing to the S3 bucket, define an external table on the stage, and use partitioning metadata to optimize queries.
B. Create a Snowpipe pointing to the S3 bucket and ingest the data continuously into a Snowflake table.
C. Load all the data into a Snowflake table and create a materialized view on top of the table to pre-aggregate the data for reporting.
D. Create a Snowflake internal stage, copy the necessary files into the stage, and then load the data into a Snowflake table.
E. Use Snowflake's COPY INTO command to ingest data directly from S3 into a Snowflake table on a scheduled basis.

答案：A

解題說明：
Using an external table pointing to the S3 bucket is the most efficient and cost-effective approach. It allows you to query the data directly in S3 without ingesting it into Snowflake, saving on storage costs. Partitioning metadata further optimizes query performance by allowing Snowflake to only scan relevant partitions based on the query criteria.

問題 #217
A data engineering team is implementing a change data capture (CDC) process using Snowflake Streams on a table 'CUSTOMER DATA'. After several days, they observe that some records are missing from the target table after the stream is consumed. The stream 'CUSTOMER DATA STREAM' is defined as follows: 'CREATE STREAM CUSTOMER DATA STREAM ON TABLE CUSTOMER DATA;' and the transformation code to process the data is shown below. What could be the possible reasons for the missing records, considering the interaction between Time Travel and Streams? Assume all table sizes are significantly larger than micro-partitions, making full table scans inefficient.

A. The stream's 'AT' or 'BEFORE clause in the consumer query is incorrectly configured, causing it to skip some historical changes.
B. DML operations (e.g., DELETE, UPDATE) performed directly against the target table are interfering with the stream's ability to track changes consistently.
C. The stream's offset persistence is reliant on Time Travel, If the data being ingested is older than the set Time Travel duration, the change may not be seen by the stream.
D. The underlying table 'CUSTOMER DATA' was dropped and recreated with the same name, invalidating the stream's tracking capabilities.
E. The parameter for the database containing 'CUSTOMER_DATR is set to a value lower than the stream's offset persistence, causing some changes to be purged before the stream could consume them.

答案：C,E

解題說明：
Option A is correct: If the 'DATA RETENTION_TIME IN DAYS' is less than the time it takes to consume the stream, Time Travel will not be able to retrieve the changes, leading to missing records. Option E is also correct, as time travel duration plays a significant role.

問題 #218
You are building a data pipeline that extracts data from a REST API, transforms it using Pandas DataFrames, and loads it into Snowflake. You need to implement error handling to gracefully handle network issues and API rate limits. Which of the following code snippets demonstrates the most robust approach to handle potential errors during data loading into Snowflake using the Python connector?

A. Option B
B. Option E
C. Option A
D. Option C
E. Option D

答案：D

解題說明：
Option C provides the most robust error handling. It specifically catches 'snowflake.connector.errors.ProgrammingError' for SQL syntax errors and 'snowflake.connector.errors.OperationalError' for connection errors. Crucially, it includes 'connection.rollback()" in case of errors to maintain data consistency and suggests a retry mechanism (exponential backoff) for connection issues, making it more resilient. Options A and B offer basic error handling but lack granularity and rollback mechanisms. Options D and E have no error handling at all and are therefore inadequate.

問題 #219
......

KaoGuTi為你提供了不同版本的資料以方便你的使用。PDF版的DEA-C02考古題方便你的閱讀，為你真實地再現考試題目。軟體版本的DEA-C02考古題作為一個測試引擎，可以幫助你隨時測試自己的準備情況。如果你想知道你是不是充分準備好了DEA-C02考試，那麼你可以利用軟體版的考古題來測試一下自己的水準。這樣你就可以快速找出自己的弱點和不足，進而有利於你的下一步學習安排。

DEA-C02在線考題: https://www.kaoguti.com/DEA-C02_exam-pdf.html

DEA-C02考試說到底只是對我們的一次測試而已，不管您想參加DEA-C02認證的哪個考試，我們的DEA-C02認證參考資料都可以給您帶來很大的幫助，我们能為很多參加 Snowflake DEA-C02 認證考試的考生提供具有針對性的培訓方案，包括考試之前的模擬測試，針對性教學課程，和與真實考試有95%相似性的練習題及答案，你可以現在網上免費下載我們KaoGuTi為你提供的部分Snowflake DEA-C02認證考試的考試練習題和答案，如果你選擇了DEA-C02考古題,快下載它吧,能100%通過IT認證考試，我們還會不定期的更新所有考試的考古題，想獲得最新的DEA-C02考古題就在我們的網站，確保你成功通過DEA-C02考試，實現夢想，Snowflake DEA-C02考題資訊或者你也可以選擇為你免費更新考試考古題。

王棟的話，讓林夕麒心中壹動，更糟糕的是政府軍陣營的技術人員不斷地倒戈，現在反叛軍大概已經占據了三分之二個星球了，DEA-C02考試說到底只是對我們的一次測試而已，不管您想參加DEA-C02認證的哪個考試，我們的DEA-C02認證參考資料都可以給您帶來很大的幫助。

DEA-C02考題資訊 - 您最聰明的選擇SnowPro Advanced: Data Engineer (DEA-C02)在線考題

我们能為很多參加 Snowflake DEA-C02 認證考試的考生提供具有針對性的培訓方案，包括考試之前的模擬測試，針對性教學課程，和與真實考試有95%相似性的練習題及答案，你可以現在網上免費下載我們KaoGuTi為你提供的部分Snowflake DEA-C02認證考試的考試練習題和答案。

如果你選擇了DEA-C02考古題,快下載它吧,能100%通過IT認證考試。

ويب ثري سكور

ويب ثري سكور

ويب ثري سكور

هل انت بحاجة الى مساعدة ؟

نعم ! إذا ماذا تنتظر انضم الان لاكبر مجتمع في العملات الرقمي واطرح سؤالك

هل انت بحاجة الى مساعدة ؟

نعم ! اطرح سؤالك الان في اكبر مجتمع للعملات الرقمية

مدونة الاستثمار الرقمي

Mike Powell Mike Powell

نبذة عنا

ويب ثري سكور

سياسة الخصوصية

شروط الاستخدام

سياسة الاسترداد

سياسة الخصوصية

شروط الاستخدام

سياسة الاسترداد