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Title of test: noe da sua conta Description: noe da sua conta Author: noe Other tests from this author Creation Date: 21/07/2024 Category: Personal Number of questions: 72

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1 - A new data engineering team has been assigned to an ELT project. The new data engineering team woll need full privileges on the table sales to fully manage the project. Which of the following commands can be used to grant full permissions on the database to the nem data engeneering team? GRANT ALL PRIVILEGES ON TABLE sales TO team df sadf. 2 - A data engineer is running code in a Databricks Repo that is cloned from a central Git repository. A colleague os the dara engineer informs them that changes have been made and synced to the central Git Repo. The data engineer now needs to sync theis Databricks Repo to get the changes from the central git repository. Which of the following Git operations does the data engineer need to run to accomplish this task? pull get push clone. 3 - Wich of the following is a benefit of the Databricks Lakehouse platform embracing open source technologies? Avoiding vendor lock-in as. 4 - A data engineer needs to use a Delta Table as part os a data pipeline, bit they do not know if they have the appropriate permissions. In which of the following locations can the data enginner review their permissions ion the table? Data Explore asda s. 5 - Wich of the following describe a scenario in which a data engineer will want to use a single node cluster? When they are working interactively with a small amount of data asd. 6 - A data engineer has been given a new record of data: id STRING = 'a1' rank INTEGER = 6 rating FLOAT = 9.4 Wich of the following SQL commands can be used to append the nem record to an existing Delta table my_table? INSERT INTO my_table VALUES ('a1', 6, 9.4) asd . 7 - A data engineer has realized that the data files associated with a Delta table are incredibly small. They want to campact the small files to form larger files to improve performance. Which of the following keywords can be used to compact the small files? REDUCE OPTIMIZE COMPACTION REPARTITION VACCUN. 8 - In which of the following file formats is data from Delta Lake tables primarily stored? Delts CSV Parquet JSON A proprietary, optimized format specific to Databricks. 9 - Which of the following is stored in the Databricks customer's cloud account? Databricks web application Cluster management metadata Repos Data Notebook. 10 - Wich of the following can be used to simplify and unify siloed data architevture that are specialized for specific use case? None of these Data lake Datawarehouse All of these Data lakehouse. 11 - A data architect has determined that a table os the following format is necessary; Which of the following code blocks uses SQL DDL commands to create an empty Delta table in the above format regardless of whether a table already existis with this name? CREATE TABLE IF NOT EXISTS table_name ( employeeid STRING, startDate DATE, avgRating FLOAT ) CREATE OR REPLACE TABLE table_name as SELECT employeeid STRING, startDate DATE, avgRating FLOAT USING DELTA CREATE OR REPLACE TABLE table_name WITH COLUMNS ( employeeid STRING, startDate DATE, avgRating FLOAT ) USING DELTA CREATE OR REPLACE TABLE table_name SELECT employeeid STRING, startDate DATE, avgRating FLOAT CREATE OR REPLACE TABLE table_name ( employeeid STRING, startDate DATE, avgRating FLOAT ). 12 – A data engineer has a Pytjon notebook in Databricks, but they need to use SQL to accomplish a specific task within a cell. They still want all of the other cells to use Python without making any changes to those cells. Which of the following describes how the data engineer can use SQLwithin a cell of theis Python notebook? It is not possible to use SQL in a Python notebook. They can attach the cell to a SQL endpoint rather than a Databricks cluster. They can simply write SQL sintax in the cell They can add %sql to the first line of the cell They can change the default language of the notebook to SQL. 13 – Which of following SQL keywords can be used to convert a table from a long format toa wide format? Pivot Transform. Sum Convert Where. 14 – Which of the following describes a benefit of creating an external table from pParquet rather than CSV when using a CREATE TABLE AS SELECT statement? Parquet files can be partitioned CREATE TABLE AS SELECT statements cannot be used on file Parquet files have a well-defined schema Parquet files have the ability to be optimized Parquet files will become Delta Tables. 15 – A data engineer wants to create a relational object by pulling data from two tables. The relational object does not need to be user by other data engineers in other sessions. In order to save on storage costs, the data engineer wants to avoid copying and storing physical data. Which of the following relational objects should the data engineer create? Spark SQL Table View Database Temporary view Delta table. 16 – A data Analyst has developed a query that runs against Delta table. They want help from the data engineering team to implement a series of testes to ensure the data returned by the wuery is clean. However, the data engineering team uses Python for its tests rather than SQL. Which of the following operations could the data engineering team use to run query and operate the results in PySpark? SELECT * FROM sales Spark.sql There is no way to share data between PySpark and SQL Spark.table. 17 – Wich of the following commands will return the number of null values in the member_id column? SELECT count(member_id) FROM my_table; SELECT count(member_id) – count_null(member_id) FROM my_table; SELECT count_if(member_id IS NULL) FROM my_table; SELECT null(member_id) FROM my_table; SELECT count_null(member_id) FROM my_table;. 18 – A data Engineer needs to apply custom logic to identify employees with more than 5 years of experience in array column employees in table stores. The custom logic should create a new column exp_employees that is an array of all of the employees with more than 5 years of experience for each row. In order to apply this custom logic at scale, the data engineer wants to use the FILTER higher-order function. Which of the following code blocks successfully completes this task? SELECT store_id, employees, FILTER (employees, i -> i.years_exp > 5) AS exp_employees FROM stores; SELECT store_id, employees, FILTER (employees, years_exp > 5) AS exp_employees FROM stores; SELECT store_id, employees, FILTER (employees, years_exp > 5) AS exp_employees FROM stores; SELECT store_id, employees, CASE WHEN employees.years_exp > 5 THEN employees ELSE NULL END AS employees FROM stores; SELECT store_id, employees, FILTER (employees, i -> i.years_exp > 5) AS exp_employees FROM stores;. 19 – A data engineer has a Python variable table_name that they would loke to use in a SQL query. They want to construct a Python code block that will run the query using table_name. They have the following incomplete code clock: --(f”SELECT customer_id, spend FROM {table_name}”) Which of the following can be used to fill in the blank to successfully complete the task? Spark.delta.sql Spark.delta.table Spark.table Dbutils.sql Spark.sql. 20 – A data engineer has created anew database using the following command: CREATE DATABASE ID NOT EXISTIS customer360: In which of the following locations woll the customer360 database be located? dbfs:/user/hive/database/customer360 dbfs:/user/hive/warehouse dbfs:/user/hive/customer360 More information is needed to determine the correct response dbfs:/user/hive/database. 21 - A data engineer is attempting to drop a Spark table my_table and runs the following command: DROP TABLE IF EXISTS my_table; After running this command, the engineer notices that the data files and metadata files have been deleted from the file system. Which of the following describes why all of these files were deleted? The table was managed The table’s data was smaller than 10GB The table’s data was larger than 10GB The table was external The table did not have a location. 22 – A data engineer that is new to using Python needs to create a Python function to add two integers together and return the sum? Which of the following code blocks can the data engineer use to complete this task? function add_integers(x,y): return x + y function add_integers(x,y): x + y def add_integers(x,y): print (x + y ) def add_integers(x,y): return x + y def add_integers(x,y): x + y . 23 – In which of the following scenarios should a data engineer use the MERGE INTO command instead of the INSERT INTO command? When the Location of the data needs to be changed When the target table is an external table When the source table can be deleted When the target table cannot contain duplicate records When the source is not a Delta table. 24 – A data engineer is working with two tables. Each of these tables is displayed below in its entirety. Which of the following will be returned by the above query? A B C D E. none of these lines of code are needed to successfully complete the task USING CSV FROM CSV USING DELTA FROM "path/to/csv". 70. A data engineer has configured a Structured Streaming job to read from a table, manipulate the data, and then perform a streaming write into a new table. The code block used by the data engineer is below: (spark.readStream .table('sales') .withColumn('avg_prince', col('sales') / col('units')) .writeStream .option('checkpointLocation', checkpointPath) .outputMode('complete') .________ .table('new_sales') ) if the data engineer only wants the query to process all of the avaliable data in as many batches as required, which of the following lines of code should the data engineer use to fill in the blank? processingTime(1) trigger(avaliableNow=True) trigger(parallelbatch=True) trigger(processingTime='once') trigger(continuous='once'). A data engineer has developed a data pipeline to ingest data from a JSON source using Auto Loader, but the engineer has not provided any type inference or schema hints in their pipeline. Upon reviewing the data, the data engineer has noticed that all of the columns in the target table are of the string type despite some of the fields only including float or boolean values. Which of the following describes why Auto Loader inferred all of the columns to be the string type? There was a type mismatch between the specific schema and the inferred schema. JSON data is a text-based format. Auto Loader only works with string data. All of the fields had at least one null value. Auto Loader cannot infer the schema of ingested data. A B C D E. Which of the following data workloads will utilize a Gold table as its source? A job that enriches data by parsing its timestamps into a human-readable format. A job that aggregates uncleaned data to create standard summary statistics. A job that cleans data by removing malformatted records. A job that queries aggregated data designed to feed into a dashboard. A job that ingests raw data from a streaming source into de Lakehouse. which of the following must be specified when creating a new Delta live Tables pipeline a Key-value pair configuration the preferred DBU/ hour cost a path to cloud storage location for written data a location of a target database for the written data at least one notebook library to be executed. the stream function is not needed an will couse an error the table being created is a live table the customers table is a streaming live table the customers table is a reference to a structured streaming query on a pyspark dataframe. the data in customers table has been updated since its last run . which of the following describes the type of workloads that are always compatible with auto loader steaming workloads machine learning workloads serverless workloads batch workloads dashboard workloads. none of these changes will need to be made the pipeline will need to stop using the medalion-based multi-hop architecture the pipeline will need to be written entirely in SQL the pipeline will need to use a batch source in place of streaming source the pipeline will need to be written entirely in python . replace predict with a stream-friendly prediction function replace schema(schema) with option ("maxFilesPerTrigger", 1) replace "transactions" with the path to the location of the delta table replace format("delta") with format("stream") replace spark.read with spark.readStream. records that violate the expection are dropped from target dataset and recorded as invalid in the event log Records that violate expectation couse the jog fail records that violate the expectation are dropped from targer dataset and loaded into a quarantine table records that violate the expectation are added to the target dataset and recorded as invalid in the event log. records that violate the expectation are added to the target dataset and flagged as invalid in field added to the target dataset . which of the following statements regarding the relationship between silver tables and bronze tables is always true silver tables contain a less refined, lesse clean view of data than bronze data silver tables contain aggregates while bronze data is unaggregated silver tables contain a more refinerd an cleane view of data than Bronze tables Silver tables contain more data than bronze tables silver tables contain less data than bronze tables . they can turn on the serverless feature for the SQL endpoint and change the spot instance they can turn on the auto stop feature for the sqp endpoint they can increase the cluster size of the sql endpoint they can turn on the serverless feature for the sql endpoint they can increase the maximum bound of the sql endpoint scaling range . pyspark.sql.types.DateType datetime pyspark.sql.types.TimestampType Cron syntax there is no way to represent and submit this information programmatically . which of the following approches should be used to send the databricks job owner an email in the case that the job fails manually progamming in alert system in ech cell of the notebook setting up an alert in the job page setting up an alert in the notebook there is no way to jnotify the job owner in the case of job failure MLflow model Registry webhoocks. they can schedule the query to refresh every 1 day from the SQL endpoint page in databricks sql they can schedule the query to refresh every 12 hours from the SQL endpoint page in databricks sql they can schedule the query to refresh every 1 day from the querys page in databricks SQL they can schedule the query to run every 1 day from Jobs UI they can schedule the query to refresh every 12 hours from the SQL endpoint page in databricks sql . in which of the following scenarios should a data engineer select a task in depends on field of a new databricks job task when anothe task needs to be replaced by the new task when anothe task needs to fail before the new begins when anothe task has the same dependency libraries as the new task when anothe task needs to use as little compute resources as possible when anothe task needs to succesfulle complete before the new task begins . they can set up an alert with a custom template they can set up an alert with a new email destination they can set up an alert with one-time notifications they can set up an alert with a webhook alert destination they can set up an alert without notifications . they can turn on the Auto stop feature for the SQL endpoint they can ensure the dashboard SQL endpoint is not one of the included Querys SQL endpoint They can reduce the cluster size of the SQL endpoint They can ensure the dashboard SQL endpoint matches each of the queries SQL endpoints They Can set up dashboards SQL endpoint Serveless. Review the Permissions tab in the tables page in data explorer all of the options can be used to identify the owner of the table Review the owner field in the tables page in data explore Review the owner field in the tables page in the cloud storage solution There is no way to identify the owner of the table . Which of the following describes when to use the CREATE STREAMING LIVE TABLE (formerly CREATE INCREMENTAL LIVE TABLE) syntax over the CREATE LIVE TABLE syntax when creating Delta Live Tables (DLT) tables using SQL? CREATE STREAMING LIVE TABLE should be used when the subsequent step in the DLT pipeline is static CREATE STREAMING LIVE TABLE should be used when data needs to be processed incrementally. CREATE STREAMING LIVE TABLE is redundant for DLT and it does not need to be used. CREATE STREAMING LIVE TABLE should be used when data needs to be processed throught complicated aggregations. CREATE STREAMING LIVE TABLE should be used when the previous step in the DLT pipeline is static. 90. Which of the following queries is performing a streaming hop from raw data to a Bronze table? A. (spark.table('sales') .groupBy('store') .agg(sum('sales')) .writeStream .option('checkpointLocation', checkpointPath) .outputMode('complete') .table('newSales') ) B. (spark.table('sales') .filter(col('units') > 0) .writeStream .option('checkpointLocation', checkpointPath) .outputMode('append') .table('newSales') ) C. (spark.table('sales') withColumn('avgPrice', col('sales') / col('units')) -> nova coluna calculada -> Silver X .writeStream .option('checkpointLocation', checkpointPath) .outputMode('append') .table('newSales') ) D. (spark.table('sales') .write .mode('append') .table('newSales') ) E. (spark.table('sales') .writeStream .option('checkpointLocation', checkpointPath) .outputMode('append') .table('newSales') ). Which data lakehouse feature results inimproved data quality over traditional Data Lake? A data lakehouse stores data in open formats. A data lakehouse allows the use of SQL queries to examine data. A data lakehouse provides storage solutions for structured and unstructured data. A data lakehouse supports ACID-compilant transactions. In which scneario will a data team want to utilize cluster pools? An automated report needs to be version-controlled across multiple collaborators. An automated report needs to be runnable by all stakeholders. An automated report needs to be refreshed as quickly as possible. An automated report needs to be made reproducible. What is hosted completely in the control plane of the classic Databrciks aarchitecture? Worker node Databricks web application Driver node Databricks Filesystem. A data engineer needs to determine whether to use the built-in Databricks Notebooks versioning or version their project using Databricks Repos. What is an advantage of using Databricks Repos over the Databricks Notebooks versioning? Databricks Repos allows users to revert to previous versions of a notebook. Databricks Repos is wholly housed within the Databricks Data Intelligence Plataform. Databricks Repos provides the ability to comment on specific changes. Databricks Repos supports the use of multiple branches. . A data architect has determined that a table of the following format is necessary: employeeId startDate avgRating a1 2009-01-06 5.5 a2 2018-11-21 7.1 Which code block is used by SQL DDL command to create an empty Delta table in the above format regardless of whether a table already existis with this name? CREATE OR REPLACE TABLE table_name (employeeId STRING, startDate DATE, avgRating FLOAT) CREATE OR REPLACE TABLE table_name WITH COLUMNS (employeeId STRING, startDate DATE, avgRating FLOAT) USING Delta CREATE TABLE IF NOT EXISTS table_name (employeeId STRING, startDate DATE, avgRating FLOAT) CREATE TABLE table_name AS SELECT employeeId STRING, startDate DATE, avgRating FLOAT. A data engineer wants to create a data entity from a couple of tables. The data entity must be used by other data engineers in other sessions. It also must be saved to a physical location. Wich of the following data entities should the data engineer create? Table Function View Temporary View. A data engineer runs a statement every day to copy the previous day's sales into the table transactions. Each day's sales are in their own file in location '/trasactions/raw'. Today, the data engineer runs the following command to complete this task: COPY INTO transactions FROM '/transactions/raw' FILEFORMAT = PARQUET; After running the command today, the data engineer notices that the number of records in table transactions has not changed. What explains why the statement might not have copied any new records into the table? The format of the files to be copied were not included with the FORMAT_OPTIONS keyword. The COPY INTO statement requires the table to be refreshed to view the copied rows. The previos days's file has already beem copied into the table. The PARQUET file format does not support COPY INTO. Which command can be used to write data into a Delta table while avoiding the writing of duplicate records? DROP INSERT MERGE APPEND. A data analyst has created a Delta table sales that is used by the entire data analysis team. The want help from the data engineering team to implement a series of tests to ensure the data is clean. However the data engineering team uses Python for its tests rather than SQL. Which command could the data engineering team use to access sales in PySpark? SELECT * FROM sales spark.table('sales') spark.sql('sales') spark.delta.table('sales'). A data engineer has configured a Structured Streaming job to read from a table, manipulate the data, and then perform a streaming write into a new table. The code block used by the data engineer is below: (spark.table('sales) .withColumn('avg_price'), col('sales') / col('units') .writeStream .option('checkpointLocation', 'checkpointPath) .outputMode('complete') .________ .table('new_sales') ) Which line of code should the data engineer use to fill the blank if the data engineer only wants the query to execute a micro-batch to process data every 5 seconds? trigger('5 seconds') trigger(continuous='5 seconds') trigger(once='5 seconds') trigger(processingTime='5 seconds'). A data engineer is maintaining a data pipeline. Upon data ingestion, the data engineer notices that the souce data is starting to have a lowe level of quality. The data engineer would like to automate the processs of monitoring the quality level. Which of the following tools cant he data engineer use to solve this problem? Auto Loader Unity Catalog Delta Lake Delta Live Tables. A data engineer has three tables in a Delta Live Tables (DLT) pipeline. They have configured the pipeline to drop invalid records at each table. They notice that some data is being dropped due to quality concerts at some point the DLT pipeline. They would like to determine at which table in ther pipeline the data is being dropped. Which approach can the data engineer take to identify the table that is dropping the records? They can set up separte expectations for each table when devoloping thei DLT pipeline. They can navigate to the DTLT pipeline page, click on the 'Error' button, and review the present errors. The can set up DLT to notify them via email when records are dropped. They can navigate to the DLT pipeline page, click on each table, and view the data quality statistics. . What is used by Spark to record the offset range of the data being processed in each trigger in order for Structured Streaming to reliably track the exact progress of the processing so that it can handle any kind of failure by restarting and/or reprocessing? Checkpointg and Write-ahead logs (WAL) Replayable Sources and Idempotent Sinks Write-ahead (WAL) Logs and Idempotent Sinks Checkpointing and Idempotent Sinks. What describes the relationship between Gold tables and Silver tables? Gold tables more likely to contain aggregations than Silver tables. Gold tables are more likely to contain valuable data than Silver tables. Gold tables are more likely to contain a less refined view of data than Silver tables Gold tables are more likely to contain truthful data than Silver tables. . Which of the following data workloads will utilize a Gold table as its source? A job that enriches data by parsing its timestamps into a human-readable format. A job that aggregates uncleaned data to create standard summary statistics. A job that queries aggregated data designed to feed into a dashboard. A job that ingests raw data from a streaming source into the Lakehouse. A Delta Live Table pipeline includes two datasets defined using STREAMING LIVE TABLE. Three datasets are defined against Delta Lake table sources using LIVE TABLE. The table is configured to run in Production mode suing the Continuoues Pipeline Mode. What is the expected outcome after clicking Start to update the pipeline assuming previously unprocessed data exists and all definitions are valid? All datasets will be updated at set intervals until the pipeline is shut down. The compute resources will persist to allow for additional testing All datasets will be updated once and the pipeline will shut down. The compute resources will persist to allow for additional testing. All datasets will be updated at set intervals until the pipeline is shut down. The compute resourecs will be deployed for the update and terminated when the pipeline is stopped. All datasets will be updated once and the pipeline will shut down. The compute resources will be terminated. . Which statement regarding the relationship between Silver tables and Bronze tables is always true? Silver tables contain less refined, less clean view of data than Bronze data. Silver tables contain aggregates while Bronze data is unaggregated. Silver tables contain more data thnan Bronze tables. Silver tables contain less data Bronze tables. A dataset has been defined using Delta Live Tables and includes an expectations clause: CONSTRAINT valid_timestamp EXPECT (timestamp > '2020-01-01') ON VIOLATION DROP ROW What is the expected behaivor when a batch of data containing data that biolates these constraints is processed? Records that violate the expectation cause the job to fail. Records that violate the expectation cause the job to fail. Records that violate the expectation are dropped from the target dataset and recorded as invalid in the event log. Records that violate the expectation are added to the target dataset and recorded as invalid in the event log. . A data engineer has a Job with multiple tasks that runs nightly. Each of the tasks runs slowly because the clusters take a long time to start. Which action can the data engineer perform to improve the start up time for the clusters used for the Job? They can use endpoints avaliable in Databricks SQL. They can use jobs clusters instead of all-purpose clusters. They can configure the clusters to autoscale for larger data sized. They can use clusters that are from a cluster pool. . A data engineer has a single-task Job that runs each morning before they begin working. After identifying an upstream data issue, they need to set up another task to run a new notebook prior to the orignal task. Which approach can the data engineer use to set up the new task? They can clone the existing task in the existing Job and update it to run the new notebook. They can create a new task in the existing Job an then add it as a dependency of the orignal task. They can create a new task in the existing Job and then add the original task as a dependency of the new task. They can create a new job from scratch and add both tasks to run concurrently. . A single Job runs two notebooks as two separate tasks. A data engineer has noticed that one of the notebooks is running slowly in the Job's current run. The data engineer asks a tech lead for helpin identifying why this might be the case. Which approach can the tech lead use to identify why the notebook is running slowly as part of the Job? They can navigate to the Runs tab in the Jobs UI to immediately review the processing notebook. They can navigate to the Tasks tab in the JObs UI and click on the active run to review the processing notebook. They can navigate to the Runs tab in the Jobs UI and click on the active run to review the processing notebook. They can navigate to the Tasks tab in the Jobs UI to immediately review the processing notebook. . A data analysis team has noticed that their Databricks SQL queries are running too slowly when connected to their always-on SQL endpoint. They claim that this issue is present when many members of the team are running small queries simultaneously. They ask the data engineering team for a help. The data engineering team notices that each of the team's queries uses the same SQL endpoint. Which approach can the data engineering team use to improve the latency of the team's queries? They can increase the cluster size of the SQL endpoint. They can increase the maximum bound of the SQL endpoint's scaling range. They can turn on the Auto Stop feature for the SQL endpoint. They can turn on the Serverless feature for the SQL Endpoint. . An engineering manager wants to monitor the performance of a recent project using a Databricks SQL query. For the first week following the project's release, the manager wnats the query results to be updated every minute. However, the manager is concerned that the compute resources used for the query will be left running and cost the organization a lot of money beyond the first week of the project's release. Which approach can the engineering team use to ensure the query does not cost the organization any money beyond the first week of the procject's release? They can set a limit to the number of DBUs that are consumed by the SQL endpoint. They can set the query's refresh schedule to end after a certain number of refreshes. They can set the quer's refresh schedule to end on a certain date in the query scheduler. They can set a limit to the number of individuals that are able to amange the query's refresh schedule. . A new data engineering team has been assigned to work on a project. The team will need access to databease customers in order to see what tables already exist. The team has its own group team. Which command can be used to grant the necessary permission on the entire database to the new team? GRANT VIEW ON CATALOG customers TO team; GRANT CREATE ON DATABASE customers TO team; GRANT USAGE ON CATALOG team TO customers; GRANT USAGE ON DATABASE customers TO team;. A new data engineering team has been assigned to an ELT project. The new data engineering team woll need full privileges on the table sales to fully manage the project. Which of the following commands can be used to grant full permissions on the database to the nem data engeneering team? GRANT ALL PRIVILEGES ON TABLE sales TO team; GRANT SELECT CREATE MODIFY ON TABLE sales TO team; GRANT SELECT ON TABLE sales TO team; GRANT ALL PRIVILEGES ON TABLE team TO sales;. 106. A Delta Live Table pipeline includes two datasets defined using STREAMING LIVE TABLE. Three datasets are defined against Delta Lake table sources using LIVE TABLE. The table is configured to run in Developtment mode suing the Continuoues Pipeline Mode. What is the expected outcome after clicking Start to update the pipeline assuming previously unprocessed data exists and all definitions are valid? All datasets will be updated at set intervals until the pipeline is shut down. The compute resources will persist to allow for additional testing. All datasets will be updated once and the pipeline will shut down. The compute resources will persist to allow for additional testing. All datasets will be updated at set intervals until the pipeline is shut down. The compute resourecs will be deployed for the update and terminated when the pipeline is stopped. All datasets will be updated at set intervals until the pipeline is shut down. The compute resourecs will be deployed for the update and terminated when the pipeline is stopped. D. .

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