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Professional-Data-Engineer PDF DEMO:
QUESTION NO: 1 You work for an economic consulting firm that helps companies identify economic trends as they happen. As part of your analysis, you use Google BigQuery to correlate customer data with the average prices of the 100 most common goods sold, including bread, gasoline, milk, and others. The average prices of these goods are updated every 30 minutes. You want to make sure this data stays up to date so you can combine it with other data in BigQuery as cheaply as possible. What should you do? A. Store and update the data in a regional Google Cloud Storage bucket and create a federated data source in BigQuery B. Store the data in a file in a regional Google Cloud Storage bucket. Use Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Google Cloud Storage. C. Store the data in Google Cloud Datastore. Use Google Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Cloud Datastore D. Load the data every 30 minutes into a new partitioned table in BigQuery. Answer: D
QUESTION NO: 2 Which of these rules apply when you add preemptible workers to a Dataproc cluster (select 2 answers)? A. A Dataproc cluster cannot have only preemptible workers. B. Preemptible workers cannot store data. C. Preemptible workers cannot use persistent disk. D. If a preemptible worker is reclaimed, then a replacement worker must be added manually. Answer: A,B Explanation The following rules will apply when you use preemptible workers with a Cloud Dataproc cluster: Processing only-Since preemptibles can be reclaimed at any time, preemptible workers do not store data. Preemptibles added to a Cloud Dataproc cluster only function as processing nodes. No preemptible-only clusters-To ensure clusters do not lose all workers, Cloud Dataproc cannot create preemptible-only clusters. Persistent disk size-As a default, all preemptible workers are created with the smaller of 100GB or the primary worker boot disk size. This disk space is used for local caching of data and is not available through HDFS. The managed group automatically re-adds workers lost due to reclamation as capacity permits. Reference: https://cloud.google.com/dataproc/docs/concepts/preemptible-vms
QUESTION NO: 3 You have Cloud Functions written in Node.js that pull messages from Cloud Pub/Sub and send the data to BigQuery. You observe that the message processing rate on the Pub/Sub topic is orders of magnitude higher than anticipated, but there is no error logged in Stackdriver Log Viewer. What are the two most likely causes of this problem? Choose 2 answers. A. Publisher throughput quota is too small. B. The subscriber code cannot keep up with the messages. C. The subscriber code does not acknowledge the messages that it pulls. D. Error handling in the subscriber code is not handling run-time errors properly. E. Total outstanding messages exceed the 10-MB maximum. Answer: B,D
QUESTION NO: 4 You have a query that filters a BigQuery table using a WHERE clause on timestamp and ID columns. By using bq query - -dry_run you learn that the query triggers a full scan of the table, even though the filter on timestamp and ID select a tiny fraction of the overall data. You want to reduce the amount of data scanned by BigQuery with minimal changes to existing SQL queries. What should you do? A. Recreate the table with a partitioning column and clustering column. B. Create a separate table for each I C. Use the LIMIT keyword to reduce the number of rows returned. D. Use the bq query - -maximum_bytes_billed flag to restrict the number of bytes billed. Answer: C
QUESTION NO: 5 You are designing the database schema for a machine learning-based food ordering service that will predict what users want to eat. Here is some of the information you need to store: * The user profile: What the user likes and doesn't like to eat * The user account information: Name, address, preferred meal times * The order information: When orders are made, from where, to whom The database will be used to store all the transactional data of the product. You want to optimize the data schema. Which Google Cloud Platform product should you use? A. BigQuery B. Cloud Datastore C. Cloud SQL D. Cloud Bigtable Answer: A
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Updated: May 27, 2022
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Professional-Data-Engineer PDF DEMO:
QUESTION NO: 1 You work for an economic consulting firm that helps companies identify economic trends as they happen. As part of your analysis, you use Google BigQuery to correlate customer data with the average prices of the 100 most common goods sold, including bread, gasoline, milk, and others. The average prices of these goods are updated every 30 minutes. You want to make sure this data stays up to date so you can combine it with other data in BigQuery as cheaply as possible. What should you do? A. Store and update the data in a regional Google Cloud Storage bucket and create a federated data source in BigQuery B. Store the data in a file in a regional Google Cloud Storage bucket. Use Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Google Cloud Storage. C. Store the data in Google Cloud Datastore. Use Google Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Cloud Datastore D. Load the data every 30 minutes into a new partitioned table in BigQuery. Answer: D
QUESTION NO: 2 Which of these rules apply when you add preemptible workers to a Dataproc cluster (select 2 answers)? A. A Dataproc cluster cannot have only preemptible workers. B. Preemptible workers cannot store data. C. Preemptible workers cannot use persistent disk. D. If a preemptible worker is reclaimed, then a replacement worker must be added manually. Answer: A,B Explanation The following rules will apply when you use preemptible workers with a Cloud Dataproc cluster: Processing only-Since preemptibles can be reclaimed at any time, preemptible workers do not store data. Preemptibles added to a Cloud Dataproc cluster only function as processing nodes. No preemptible-only clusters-To ensure clusters do not lose all workers, Cloud Dataproc cannot create preemptible-only clusters. Persistent disk size-As a default, all preemptible workers are created with the smaller of 100GB or the primary worker boot disk size. This disk space is used for local caching of data and is not available through HDFS. The managed group automatically re-adds workers lost due to reclamation as capacity permits. Reference: https://cloud.google.com/dataproc/docs/concepts/preemptible-vms
QUESTION NO: 3 You have Cloud Functions written in Node.js that pull messages from Cloud Pub/Sub and send the data to BigQuery. You observe that the message processing rate on the Pub/Sub topic is orders of magnitude higher than anticipated, but there is no error logged in Stackdriver Log Viewer. What are the two most likely causes of this problem? Choose 2 answers. A. Publisher throughput quota is too small. B. The subscriber code cannot keep up with the messages. C. The subscriber code does not acknowledge the messages that it pulls. D. Error handling in the subscriber code is not handling run-time errors properly. E. Total outstanding messages exceed the 10-MB maximum. Answer: B,D
QUESTION NO: 4 You have a query that filters a BigQuery table using a WHERE clause on timestamp and ID columns. By using bq query - -dry_run you learn that the query triggers a full scan of the table, even though the filter on timestamp and ID select a tiny fraction of the overall data. You want to reduce the amount of data scanned by BigQuery with minimal changes to existing SQL queries. What should you do? A. Recreate the table with a partitioning column and clustering column. B. Create a separate table for each I C. Use the LIMIT keyword to reduce the number of rows returned. D. Use the bq query - -maximum_bytes_billed flag to restrict the number of bytes billed. Answer: C
QUESTION NO: 5 You are designing the database schema for a machine learning-based food ordering service that will predict what users want to eat. Here is some of the information you need to store: * The user profile: What the user likes and doesn't like to eat * The user account information: Name, address, preferred meal times * The order information: When orders are made, from where, to whom The database will be used to store all the transactional data of the product. You want to optimize the data schema. Which Google Cloud Platform product should you use? A. BigQuery B. Cloud Datastore C. Cloud SQL D. Cloud Bigtable Answer: A
Obviously such positive pass rate will establish you confidence as well as strengthen your will to pass your Huawei H25-631_V1.0 exam. You will feel grateful to choose our Microsoft SC-401 learning quiz! Usually you may take months to review a professional exam, but with ARDMS SPI exam guide, you only need to spend 20-30 hours to review before the exam, and with our ARDMS SPI study materials, you will no longer need any other review materials, because our learning dumps have already included all the important test points. Since our Juniper JN0-253 exam torrent is designed on the purpose to be understood by our customers all over the world, it is compiled into the simplest language to save time and efforts. SAP C_S4CPB_2508 - We offer free demos of our for your reference, and send you the new updates if our experts make them freely.
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Besides, the pollster conducted surveys of public opinions of our Professional-Data-Engineer Dumps.Zip study engine and get desirable outcomes that more than 98 percent of exam candidates feel rewarding after using our Professional-Data-Engineer Dumps.Zip actual exam. And we enjoy their warm feedbacks to show and prove that we really did a good job in this career. You can totally rely on us!
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With our professional experts’ unremitting efforts on the reform of our Professional-Data-Engineer Dumps.Zip guide materials, we can make sure that you can be focused and well-targeted in the shortest time when you are preparing a test, simplify complex and ambiguous contents. With the assistance of our Professional-Data-Engineer Dumps.Zip study guide you will be more distinctive than your fellow workers. For all the above services of our Professional-Data-Engineer Dumps.Zip practice engine can enable your study more time-saving and energy-saving.
You can have a free try for downloading our Professional-Data-Engineer Dumps.Zip exam demo before you buy our products. What’s more, you can acquire the latest version of Professional-Data-Engineer Dumps.Zip training materials checked and revised by our exam professionals after your purchase constantly for a year.
Professional-Data-Engineer PDF DEMO:
QUESTION NO: 1 You work for an economic consulting firm that helps companies identify economic trends as they happen. As part of your analysis, you use Google BigQuery to correlate customer data with the average prices of the 100 most common goods sold, including bread, gasoline, milk, and others. The average prices of these goods are updated every 30 minutes. You want to make sure this data stays up to date so you can combine it with other data in BigQuery as cheaply as possible. What should you do? A. Store and update the data in a regional Google Cloud Storage bucket and create a federated data source in BigQuery B. Store the data in a file in a regional Google Cloud Storage bucket. Use Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Google Cloud Storage. C. Store the data in Google Cloud Datastore. Use Google Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Cloud Datastore D. Load the data every 30 minutes into a new partitioned table in BigQuery. Answer: D
QUESTION NO: 2 Which of these rules apply when you add preemptible workers to a Dataproc cluster (select 2 answers)? A. A Dataproc cluster cannot have only preemptible workers. B. Preemptible workers cannot store data. C. Preemptible workers cannot use persistent disk. D. If a preemptible worker is reclaimed, then a replacement worker must be added manually. Answer: A,B Explanation The following rules will apply when you use preemptible workers with a Cloud Dataproc cluster: Processing only-Since preemptibles can be reclaimed at any time, preemptible workers do not store data. Preemptibles added to a Cloud Dataproc cluster only function as processing nodes. No preemptible-only clusters-To ensure clusters do not lose all workers, Cloud Dataproc cannot create preemptible-only clusters. Persistent disk size-As a default, all preemptible workers are created with the smaller of 100GB or the primary worker boot disk size. This disk space is used for local caching of data and is not available through HDFS. The managed group automatically re-adds workers lost due to reclamation as capacity permits. Reference: https://cloud.google.com/dataproc/docs/concepts/preemptible-vms
QUESTION NO: 3 You have Cloud Functions written in Node.js that pull messages from Cloud Pub/Sub and send the data to BigQuery. You observe that the message processing rate on the Pub/Sub topic is orders of magnitude higher than anticipated, but there is no error logged in Stackdriver Log Viewer. What are the two most likely causes of this problem? Choose 2 answers. A. Publisher throughput quota is too small. B. The subscriber code cannot keep up with the messages. C. The subscriber code does not acknowledge the messages that it pulls. D. Error handling in the subscriber code is not handling run-time errors properly. E. Total outstanding messages exceed the 10-MB maximum. Answer: B,D
QUESTION NO: 4 You have a query that filters a BigQuery table using a WHERE clause on timestamp and ID columns. By using bq query - -dry_run you learn that the query triggers a full scan of the table, even though the filter on timestamp and ID select a tiny fraction of the overall data. You want to reduce the amount of data scanned by BigQuery with minimal changes to existing SQL queries. What should you do? A. Recreate the table with a partitioning column and clustering column. B. Create a separate table for each I C. Use the LIMIT keyword to reduce the number of rows returned. D. Use the bq query - -maximum_bytes_billed flag to restrict the number of bytes billed. Answer: C
QUESTION NO: 5 You are designing the database schema for a machine learning-based food ordering service that will predict what users want to eat. Here is some of the information you need to store: * The user profile: What the user likes and doesn't like to eat * The user account information: Name, address, preferred meal times * The order information: When orders are made, from where, to whom The database will be used to store all the transactional data of the product. You want to optimize the data schema. Which Google Cloud Platform product should you use? A. BigQuery B. Cloud Datastore C. Cloud SQL D. Cloud Bigtable Answer: A
Obviously such positive pass rate will establish you confidence as well as strengthen your will to pass your Huawei H25-631_V1.0 exam. You will feel grateful to choose our Microsoft SC-401 learning quiz! Usually you may take months to review a professional exam, but with ARDMS SPI exam guide, you only need to spend 20-30 hours to review before the exam, and with our ARDMS SPI study materials, you will no longer need any other review materials, because our learning dumps have already included all the important test points. Since our Juniper JN0-253 exam torrent is designed on the purpose to be understood by our customers all over the world, it is compiled into the simplest language to save time and efforts. SAP C_S4CPB_2508 - We offer free demos of our for your reference, and send you the new updates if our experts make them freely.
