MCQs on BigQuery APIs and SDKs | Google BigQuery

BigQuery offers powerful APIs and SDKs that enable developers to programmatically interact with its data warehouse capabilities. This chapter covers essential topics such as using the BigQuery REST API, authentication, client libraries for different programming languages, and integrating BigQuery with other Google Cloud Platform services like Cloud Functions, Dataflow, and Dataproc. Test your knowledge with 30 MCQs.


Topic 1: Using the BigQuery REST API

  1. What is the primary purpose of the BigQuery REST API?
    a) To store and retrieve large datasets
    b) To interact programmatically with BigQuery
    c) To create virtual machines in GCP
    d) To monitor BigQuery billing
  2. Which HTTP method is used to run a query using the BigQuery REST API?
    a) GET
    b) POST
    c) PUT
    d) DELETE
  3. Which endpoint is used to run a query in BigQuery via the REST API?
    a) /query
    b) /datasets
    c) /jobs/query
    d) /jobs/run
  4. What does the query job type in the BigQuery REST API represent?
    a) A table creation request
    b) A long-running data processing job
    c) An API call to list datasets
    d) A SQL query execution task
  5. How can you specify the query’s destination in the BigQuery REST API?
    a) By including a destinationTable property in the request body
    b) By setting a destinationUri parameter
    c) By using a storeInBucket field
    d) By passing the table name as a query parameter
  6. Which of the following is a required parameter when sending a query request to the BigQuery REST API?
    a) Project ID
    b) Dataset ID
    c) Table ID
    d) Data format
  7. How do you handle large result sets when using the BigQuery REST API?
    a) Use pagination with the pageToken parameter
    b) Set a larger query timeout
    c) Use data compression in the query
    d) Use larger disk storage
  8. What type of data format does the BigQuery REST API use for responses?
    a) XML
    b) CSV
    c) JSON
    d) Avro
  9. Which API service do you need to enable before using the BigQuery REST API?
    a) Cloud Storage API
    b) BigQuery API
    c) Cloud Pub/Sub API
    d) Cloud Functions API
  10. What is the purpose of the dryRun parameter in the BigQuery REST API?
    a) To preview query results
    b) To perform a cost estimation without executing the query
    c) To test connection speed
    d) To skip error checking

Topic 2: Authentication and API Keys

  1. Which authentication method is required for the BigQuery REST API?
    a) OAuth 2.0
    b) Basic Authentication
    c) API Key only
    d) Client Certificate Authentication
  2. What is the role of an API key in authenticating BigQuery API requests?
    a) It identifies the user to the BigQuery service
    b) It encrypts data before sending to BigQuery
    c) It authorizes the request to access BigQuery resources
    d) It provides a user-specific encryption key
  3. How do you obtain an API key for using the BigQuery REST API?
    a) From the Google Cloud Console under API & Services > Credentials
    b) By sending a request to the BigQuery team
    c) By enabling OAuth 2.0
    d) By signing up for a GCP billing account
  4. Which OAuth 2.0 flow is recommended for server-to-server BigQuery access?
    a) Authorization code flow
    b) Implicit flow
    c) Client credentials flow
    d) Password credentials flow
  5. What should you do to avoid exposing your API key in client-side applications?
    a) Use OAuth 2.0 credentials instead
    b) Store the API key in a Google Cloud Storage bucket
    c) Hardcode the API key in your application
    d) Use an HTTP proxy to secure the key
  6. What type of authentication is recommended for accessing the BigQuery API from a service or application?
    a) API key
    b) Service account with a JSON key file
    c) User login credentials
    d) Static IP addresses
  7. Which of the following is true about the BigQuery API’s quota limits?
    a) They are global for all users
    b) They can be increased by contacting Google Cloud support
    c) They are fixed and cannot be modified
    d) They are applied per user account
  8. How can you ensure that your BigQuery API requests are secure?
    a) Always use HTTPS to encrypt API traffic
    b) Use private IP addresses for API calls
    c) Disable authorization on requests
    d) Use a proxy server
  9. What is the recommended way to authenticate from a Python application using the BigQuery API?
    a) Use the google-auth library
    b) Use the pyodbc library
    c) Use a direct API key in the script
    d) Authenticate with username and password
  10. What should you do if an API key is compromised?
    a) Change the key immediately
    b) Ignore it, as it cannot be used for malicious purposes
    c) Log it to monitor usage
    d) Only change it if there are reports of misuse

Topic 3: Querying and Managing Tables Programmatically

  1. How can you create a new table in BigQuery using the REST API?
    a) Send a POST request to /projects/{projectId}/datasets/{datasetId}/tables
    b) Use the CREATE TABLE SQL query
    c) Send a PUT request to /tables/create
    d) Use the INSERT INTO query
  2. What parameter must be specified when querying a specific table using the BigQuery REST API?
    a) Project ID and Table ID
    b) Dataset ID and Query ID
    c) Dataset ID and Table ID
    d) Table ID and Query Statement
  3. Which of the following options is used to update an existing table schema in BigQuery?
    a) PATCH request to the /tables/{tableId} endpoint
    b) PUT request with a new schema
    c) Directly modify the table from the BigQuery Console
    d) Use the SQL ALTER TABLE statement
  4. Which of the following BigQuery operations cannot be performed through the REST API?
    a) Data insertion
    b) Data deletion
    c) Schema modifications
    d) Data transformations
  5. How can you manage table data programmatically?
    a) Use the tabledata.insertAll endpoint
    b) Send the data using a POST request to the /tables endpoint
    c) Use the CREATE TABLE statement
    d) Use SELECT INTO queries
  6. How can you export the result of a query into a CSV file using the BigQuery REST API?
    a) Use the export endpoint and specify a destination URI
    b) Use a COPY statement in the query
    c) Send the results to Cloud Storage using a POST request
    d) Use gsutil to manually export results
  7. How do you delete a table in BigQuery programmatically?
    a) Send a DELETE request to /tables/{datasetId}/{tableId}
    b) Use the DROP TABLE SQL statement
    c) Use the BigQuery Console
    d) Send a PUT request to /tables/delete
  8. How do you list all the tables in a dataset using the BigQuery REST API?
    a) Send a GET request to /datasets/{datasetId}/tables
    b) Use the SHOW TABLES SQL query
    c) Use a query to list table names
    d) Access through the table.list endpoint
  9. What parameter is required to create a table in a specified dataset via the REST API?
    a) Table name
    b) Table schema
    c) Table data
    d) Dataset location
  10. Which method is recommended for handling large datasets when querying programmatically?
    a) Use pagination with pageToken for results
    b) Use a single API call to get all results
    c) Use a separate API call for each row
    d) Use the LIMIT clause in the query

Answers

Q NoAnswer
1b) To interact programmatically with BigQuery
2b) POST
3c) /jobs/query
4d) A SQL query execution task
5a) By including a destinationTable property in the request body
6a) Project ID
7a) Use pagination with the pageToken parameter
8c) JSON
9b) BigQuery API
10b) To perform a cost estimation without executing the query
11a) OAuth 2.0
12c) It authorizes the request to access BigQuery resources
13a) From the Google Cloud Console under API & Services > Credentials
14c) Client credentials flow
15a) Use OAuth 2.0 credentials instead
16b) Service account with a JSON key file
17b) They can be increased by contacting Google Cloud support
18a) Always use HTTPS to encrypt API traffic
19a) Use the google-auth library
20a) Change the key immediately
21a) Send a POST request to /projects/{projectId}/datasets/{datasetId}/tables
22c) Dataset ID and Table ID
23a) PATCH request to the /tables/{tableId} endpoint
24d) Data transformations
25a) Use the tabledata.insertAll endpoint
26a) Use the export endpoint and specify a destination URI
27a) Send a DELETE request to /tables/{datasetId}/{tableId}
28a) Send a GET request to /datasets/{datasetId}/tables
29b) Table schema
30a) Use pagination with pageToken for results

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