GCP-DE 無料問題集「Google Data Engineer」

（A）Keep your row key as long as the field permits

（B）Include multiple time series values within the row key

（C）Keep your row key reasonably short

（D）Keep the row keep as an 8 bit integer

（A）Use an SSD persistent disk and 50% preemptible worker

（B）Change references in scripts from hdfs:// to gs://

（C）Deploy a Cloud Dataproc cluste

（D）Install Hadoop and Spark on a 10-node Compute Engine instance group with preemptible instances.Store data in HDF

（E）Store data in Cloud Storage, and change references in scripts from hdfs:// to gs://

（F）Use a standard persistent disk and 50% preemptible worker

（G）Change references in scripts from hdfs:// to gs://

（H）Install the Cloud Storage connector, and store the data in Cloud Storag

（I）Deploy a Cloud Dataproc cluste

（J）Store data in Cloud Storage, and change references in scripts from hdfs:// to gs://

（K）Install Hadoop and Spark on a 10-node Compute Engine instance group with standard instance

（A）Change "person" to "city.person".

（B）Add ", UNNEST(person)" before the WHERE clause.

（C）Add ", UNNEST(city)" before the WHERE clause.

（D）Change "person" to "person.city".

（A）Use Cloud Deployment Manager to automate access provision.

（B）Find all the active members who have access to these projects, and create a Cloud IAM policy to grant access to all these users.

（C）Only use service accounts when sharing data for Cloud Storage buckets and BigQuery datasets.

（D）For each Cloud Storage bucket or BigQuery dataset, decide which projects need acces

（E）Create distinct groups for various teams, and specify groups in Cloud IAM policies.

（F）Introduce resource hierarchy to leverage access control policy inheritance.

（A）HTTPS

（B）SOCKS

（C）HTTP

（D）VPN

（A）all data

（B）the last transaction

（C）no data

（D）the time dimension

（A）Create a dummy user and grant dataset access to that use

（B）Create a service account and grant dataset access to that accoun

（C）Integrate with a single sign-on (SSO) platform, and pass each user's credentials along with the query request

（D）Store the username and password for that user in a file on the files system, and use those credentials to access the BigQuery dataset

（E）Use the service account's private key to access the dataset

（F）Create groups for your users and give those groups access to the dataset

（A）Run an UPDATE statement that updates the FullName column for each user with the concatenation of the FirstName and LastName values.

（B）Add a new column called FullName to the Users tabl

（C）Use BigQuery to export the data for the table to a CSV fil

（D）Create a view in BigQuery that concatenates the FirstName and LastName field values to produce the FullName.

（E）Create a Google Cloud Dataflow job that queries BigQuery for the entire Users table, concatenates the FirstName value and LastName value for each user, and loads the proper values for FirstName, LastName, and FullName into a new table in BigQuery.

（F）Create a Google Cloud Dataproc job to process the CSV file and output a new CSV file containing the proper values for FirstName, LastName and FullNam G. Run a BigQuery load job to load the new CSV file into BigQuery.