Basics of TimescaleDB and Time-Series Data Quiz

1. Identifying Time-Series Data

   Which of the following is considered time-series data?

   1. Temperature readings collected every minute from sensors
   2. A phone book listing names and addresses
   3. A static image stored in a file
   4. Monthly magazine covers stored as PDF files
   5. An alphabetical list of book titles

2. Time-Series Database Feature

   Which main feature sets time-series databases apart from traditional relational databases?

   1. Efficient storage and querying of time-stamped data
   2. Case-insensitive search by default
   3. Support for only single-table schemas
   4. Data encryption as the primary focus
   5. Ability to execute only plain text queries

3. Understanding Hypertables

   In the context of time-series databases, what is a hypertable?

   1. A logical table optimized for high-volume time-series data
   2. A static table with no indexes
   3. A table limited to 1000 rows
   4. A table used only for text data
   5. A non-relational data structure

4. Data Ingestion Example

   A weather station needs to insert thousands of temperature readings per second. Which database is designed for this high ingestion scenario?

   1. A time-series database
   2. A hierarchical file system
   3. A document database
   4. A spreadsheet application
   5. A transactional queue

5. Typical Use Case Scenario

   Which example best describes a use case for a time-series database?

   1. Monitoring CPU usage data from servers every second
   2. Storing static tax forms for download
   3. Listing available flights alphabetically
   4. Archiving scanned legal documents
   5. Storing product descriptions for an online catalog

6. Role of Timestamps

   Why are timestamps crucial in time-series databases?

   1. They track when each record was collected or created
   2. They ensure all records are encrypted
   3. They generate unique user IDs
   4. They replace the need for primary keys
   5. They allow only string data types

7. Data Retention Example

   What is a common strategy for handling old data in time-series databases?

   1. Regularly deleting or downsampling older records
   2. Copying all records to a separate table daily
   3. Encrypting only old records
   4. Converting old data to images
   5. Exporting data as unstructured blobs

8. Query Optimization

   How do time-series databases optimize queries over large historical datasets?

   1. By partitioning data into smaller chunks based on time intervals
   2. By disabling indexing completely
   3. By storing all data in a single text file
   4. By reformatting queries into binary code
   5. By requiring manual row scanning

9. Data Write Patterns

   What is a typical data write pattern in time-series applications?

   1. Frequent appends of new records as data is generated
   2. Random overwrites of old records based on user input
   3. Bulk deletion every hour
   4. Storing updates as email attachments
   5. Infrequent updates to binary trees

10. Aggregate Query Usage

    Which type of query is most commonly used with time-series data?

    1. Calculating average sensor values over specific time intervals
    2. Finding the maximum length of a paragraph
    3. Sorting images by resolution
    4. Retrieving user passwords
    5. Counting distinct colors in a picture