我們都清楚的知道，IT行業是個新型產業，它是帶動經濟發展的鏈條之一，所以它的地位也是舉足輕重不可忽視的。IT認證又是IT行業裏競爭的手段之一，通過了認證你的各方面將會得到很好的上升，但是想要通過並非易事，所以建議你利用一下培訓工具，如果要選擇通過這項認證的培訓資源，Goldmile-Infobiz Google的Professional-Data-Engineer題庫考試培訓資料當仁不讓，它的成功率高達100%，能夠保證你通過考試。 如果你不及格，我們會全額退款。在你選擇購買Goldmile-Infobiz的產品之前，你可以在Goldmile-Infobiz的網站上免費下載我們提供的部分關於Google Professional-Data-Engineer題庫認證考試的練習題及答案作為嘗試，那樣你會更有信心選擇Goldmile-Infobiz的產品來準備你的Google Professional-Data-Engineer題庫 認證考試。 言行一致是成功的開始，既然你選擇通過苛刻的IT認證考試，那麼你就得付出你的行動，取得優異的成績獲得認證，Goldmile-Infobiz Google的Professional-Data-Engineer題庫考試培訓資料是通過這個考試的最佳培訓資料，有了它就猶如有了一個成功的法寶，Goldmile-Infobiz Google的Professional-Data-Engineer題庫考試培訓資料是百分百信得過的培訓資料，相信你也是百分百能通過這次考試的。
對於 Google的Professional-Data-Engineer題庫考試認證每個考生都很迷茫。
成千上萬的IT考生通過我們的產品成功通過考試，該Professional-Data-Engineer - Google Certified Professional Data Engineer Exam題庫考古題的品質已被廣大考生檢驗。 但是這並不代表不能獲得高分輕鬆通過考試。那麼，還不知道通過這個考試的捷徑在哪里的你，是不是想知道通過考試的技巧呢？現在我來告訴你，就是利用Goldmile-Infobiz的Professional-Data-Engineer 在線題庫考古題。
成千上萬的IT考生通過使用我們的產品成功通過考試，Google Professional-Data-Engineer題庫考古題質量被廣大考試測試其是高品質的。我們從來不相信第二次機會，因此給您帶來的最好的Google Professional-Data-Engineer題庫考古題幫助您首次就通過考試，并取得不錯的成績。Goldmile-Infobiz網站幫助考生通過Professional-Data-Engineer題庫考試獲得認證，不僅可以節約很多時間，還能得到輕松通過Professional-Data-Engineer題庫考試的保證，這是IT認證考試中最重要的考試之一。
Google的Google Professional-Data-Engineer題庫考試認證將會從遙不可及變得綽手可得。
Goldmile-Infobiz的考古題有两种版本，即PDF版和软件版。這樣可以給你最大的方便。PDF版方便你的使用，你可以下載並且將考古題列印出來以供隨時學習。軟體版類比了真實的考試，可以讓你切身感受到考試的氣氛。这样在考试时你就可以轻松自如地应对了。
它可以讓你得到事半功倍的結果。Goldmile-Infobiz幫助過許多參加IT認定考試的人。
Professional-Data-Engineer PDF DEMO:
QUESTION NO: 1
You have an Apache Kafka Cluster on-prem with topics containing web application logs. You need to replicate the data to Google Cloud for analysis in BigQuery and Cloud Storage. The preferred replication method is mirroring to avoid deployment of Kafka Connect plugins.
What should you do?
A. Deploy the PubSub Kafka connector to your on-prem Kafka cluster and configure PubSub as a Sink connector. Use a Dataflow job to read fron PubSub and write to GCS.
B. Deploy a Kafka cluster on GCE VM Instances. Configure your on-prem cluster to mirror your topics to the cluster running in GCE. Use a Dataproc cluster or Dataflow job to read from Kafka and write to
GCS.
C. Deploy the PubSub Kafka connector to your on-prem Kafka cluster and configure PubSub as a
Source connector. Use a Dataflow job to read fron PubSub and write to GCS.
D. Deploy a Kafka cluster on GCE VM Instances with the PubSub Kafka connector configured as a Sink connector. Use a Dataproc cluster or Dataflow job to read from Kafka and write to GCS.
Answer: B
QUESTION NO: 2
Which Google Cloud Platform service is an alternative to Hadoop with Hive?
A. Cloud Datastore
B. Cloud Bigtable
C. BigQuery
D. Cloud Dataflow
Answer: C
Explanation
Apache Hive is a data warehouse software project built on top of Apache Hadoop for providing data summarization, query, and analysis.
Google BigQuery is an enterprise data warehouse.
Reference: https://en.wikipedia.org/wiki/Apache_Hive
QUESTION NO: 3
You want to use Google Stackdriver Logging to monitor Google BigQuery usage. You need an instant notification to be sent to your monitoring tool when new data is appended to a certain table using an insert job, but you do not want to receive notifications for other tables. What should you do?
A. Using the Stackdriver API, create a project sink with advanced log filter to export to Pub/Sub, and subscribe to the topic from your monitoring tool.
B. In the Stackdriver logging admin interface, enable a log sink export to Google Cloud Pub/Sub, and subscribe to the topic from your monitoring tool.
C. In the Stackdriver logging admin interface, and enable a log sink export to BigQuery.
D. Make a call to the Stackdriver API to list all logs, and apply an advanced filter.
Answer: C
QUESTION NO: 4
You need to create a near real-time inventory dashboard that reads the main inventory tables in your BigQuery data warehouse. Historical inventory data is stored as inventory balances by item and location. You have several thousand updates to inventory every hour. You want to maximize performance of the dashboard and ensure that the data is accurate. What should you do?
A. Use the BigQuery streaming the stream changes into a daily inventory movement table. Calculate balances in a view that joins it to the historical inventory balance table. Update the inventory balance table nightly.
B. Use the BigQuery bulk loader to batch load inventory changes into a daily inventory movement table.
Calculate balances in a view that joins it to the historical inventory balance table. Update the inventory balance table nightly.
C. Leverage BigQuery UPDATE statements to update the inventory balances as they are changing.
D. Partition the inventory balance table by item to reduce the amount of data scanned with each inventory update.
Answer: C
QUESTION NO: 5
For the best possible performance, what is the recommended zone for your Compute Engine instance and Cloud Bigtable instance?
A. Have both the Compute Engine instance and the Cloud Bigtable instance to be in different zones.
B. Have the Compute Engine instance in the furthest zone from the Cloud Bigtable instance.
C. Have the Cloud Bigtable instance to be in the same zone as all of the consumers of your data.
D. Have both the Compute Engine instance and the Cloud Bigtable instance to be in the same zone.
Answer: D
Explanation
It is recommended to create your Compute Engine instance in the same zone as your Cloud Bigtable instance for the best possible performance, If it's not possible to create a instance in the same zone, you should create your instance in another zone within the same region. For example, if your Cloud
Bigtable instance is located in us-central1-b, you could create your instance in us-central1-f. This change may result in several milliseconds of additional latency for each Cloud Bigtable request.
It is recommended to avoid creating your Compute Engine instance in a different region from your
Cloud Bigtable instance, which can add hundreds of milliseconds of latency to each Cloud Bigtable request.
Reference: https://cloud.google.com/bigtable/docs/creating-compute-instance
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Updated: May 27, 2022