Efficient Storage and Querying of Time-Series Data Quiz Quiz

1. Time-Series Database Example

   Which of the following databases is specifically designed for efficient storage of time-series data?

   1. InfluxDB
   2. PostgresQL
   3. MonogoDB
   4. RedisQL
   5. ElasticSearchh

2. Timestamp Importance

   Why is a timestamp a critical component in each time-series data record?

   1. It orders records chronologically
   2. It increases the data size
   3. It ensures data is valid
   4. It splits the data into columns
   5. It masks sensitive information

3. Downsampling Usage

   What is the main purpose of downsampling in time-series databases?

   1. To reduce storage by summarizing high-frequency data
   2. To shuffle data randomly
   3. To duplicate records for redundancy
   4. To encrypt individual datapoints
   5. To increase data collection speed

4. Efficient Query Indexing

   Which type of index is most efficient for range queries on time-series data?

   1. B-tree index
   2. Hash index
   3. No index
   4. Bitmap index
   5. Text index

5. Scenario: Retention Policies

   If you set a retention policy of 30 days on a time-series data set, what happens to records older than 30 days?

   1. They are automatically deleted
   2. They are archived to cold storage
   3. They are converted to JSON
   4. They are made read-only
   5. They are backed up hourly

6. Schema Design for Time-Series

   What is a recommended schema design for storing large-scale time-series data efficiently?

   1. Append-only, partitioned by time intervals
   2. Fully normalized with many joins
   3. Large, single flat tables with all fields
   4. Storing timestamps as string values
   5. Heavily denormalized nested arrays

7. Compression Techniques

   Which compression technique is commonly used to reduce storage for sequential time-series numeric values?

   1. Delta encoding
   2. Base64 encoding
   3. Full text compression
   4. Run length encoding
   5. MD5 hashing

8. Query Optimization Scenario

   Given a query to fetch all temperature readings between two dates, which approach will improve efficiency the most?

   1. Use a time-based partition and an index on timestamp
   2. Sort all temperature values at query-time
   3. Scan the entire database table every time
   4. Remove indices for faster insertions
   5. Store data in separate tables by sensor type only

9. Write Patterns in Time-Series Databases

   What write pattern is time-series databases optimized for?

   1. High-volume, sequential appends
   2. Random updates to old data
   3. Bulk deletes of old records
   4. Frequent record overwrites
   5. Query-only workloads

10. Query Language for Time-Series

    Which query language or extension is most commonly associated with querying time-series data in InfluxDB?

    1. Flux
    2. TSQ
    3. MYSQL
    4. GraphQL
    5. NoQuery