SQLite Interview Questions and Answers for 10 years experience

1. What is SQLite and why is it different from other databases?

   • Answer: SQLite is a self-contained, serverless, embedded, relational database management system (RDBMS). Unlike client-server databases like MySQL or PostgreSQL, SQLite doesn't require a separate server process. Its file-based nature makes it ideal for applications needing a lightweight and easily deployable database, especially in embedded systems, mobile apps, and browser-based applications. Its simplicity comes at the cost of some features found in larger RDBMS systems, particularly in terms of concurrency management and advanced features.

2. Explain the concept of a transaction in SQLite.

   • Answer: A transaction in SQLite is a sequence of one or more SQL statements treated as a single logical unit of work. It ensures data integrity by guaranteeing that either all changes within the transaction are committed (permanently saved) or none are (rolled back). SQLite uses ACID properties (Atomicity, Consistency, Isolation, Durability) to maintain data integrity during transactions. Transactions are controlled using `BEGIN TRANSACTION`, `COMMIT`, and `ROLLBACK` statements.

3. What are the different data types supported by SQLite?

   • Answer: SQLite has a relatively flexible type system. While it has declared types (INTEGER, REAL, TEXT, BLOB, NULL), it doesn't strictly enforce them. All data is ultimately stored as a blob. The declared type primarily influences how data is interpreted and displayed rather than restricting the kind of data stored. For example, you can store numbers as TEXT, but arithmetic operations will likely fail.

4. How do you create and manage indexes in SQLite?

   • Answer: Indexes are created using the `CREATE INDEX` statement, specifying the index name and the table and column(s) to index. For example: `CREATE INDEX idx_name ON mytable (name);`. Indexes speed up data retrieval but can slow down writes. They are managed by dropping them using `DROP INDEX` when no longer needed. SQLite also automatically creates indexes on primary keys.

5. Explain the difference between `LIKE` and `GLOB` operators.

   • Answer: Both `LIKE` and `GLOB` are used for pattern matching in strings. `LIKE` uses SQL's standard `%` (matches any sequence of characters) and `_` (matches any single character). `GLOB` uses Unix shell-style wildcards: `*` (matches any sequence of characters) and `?` (matches any single character). `GLOB` is generally faster than `LIKE` for simple patterns because it doesn't need to interpret SQL-specific wildcard characters.

6. Describe the use of `JOIN` clauses in SQLite queries.

   • Answer: `JOIN` clauses are used to combine rows from two or more tables based on a related column between them. SQLite supports various types of joins: `INNER JOIN` (returns only matching rows), `LEFT JOIN` (returns all rows from the left table and matching rows from the right), `RIGHT JOIN` (returns all rows from the right table and matching rows from the left), and `FULL OUTER JOIN` (returns all rows from both tables, matching where possible). The `ON` clause specifies the join condition.

7. How do you handle NULL values in SQLite?

   • Answer: NULL represents the absence of a value. Comparison with NULL using `=` or `!=` always results in FALSE. The `IS NULL` and `IS NOT NULL` operators should be used to test for NULL values. Functions like `IFNULL` or `COALESCE` can be used to provide a default value if a column contains NULL.

8. Explain the concept of database triggers in SQLite.

   • Answer: Triggers are special stored procedures that automatically execute in response to certain events on a particular table, such as INSERT, UPDATE, or DELETE. They are used to enforce data integrity constraints, audit changes, or perform other actions automatically based on data modifications. They are created using the `CREATE TRIGGER` statement.

9. How do you optimize SQLite database performance?

   • Answer: Optimization strategies include: creating appropriate indexes, using efficient query structures (avoiding `SELECT *`), normalizing the database design to reduce redundancy, using transactions effectively, analyzing query execution plans using the `EXPLAIN QUERY PLAN` statement, and ensuring sufficient memory and disk I/O resources.

10. How do you use SQLite's built-in functions? Give examples.

    • Answer: SQLite provides numerous built-in functions for string manipulation (e.g., `SUBSTR`, `REPLACE`, `UPPER`, `LOWER`), date and time functions (e.g., `DATE`, `STRFTIME`, `JULIANDAY`), mathematical functions (e.g., `ABS`, `ROUND`, `SQRT`), and aggregate functions (e.g., `SUM`, `AVG`, `COUNT`, `MAX`, `MIN`). These are used directly within SQL queries. Example: `SELECT UPPER(name), SUM(price) FROM products;`

11. What is the difference between `AUTOINCREMENT` and `ROWID`?

    • Answer: `ROWID` is a unique 64-bit integer assigned by SQLite to every row in a table. It's automatically generated and serves as a unique identifier. `AUTOINCREMENT` is a keyword used with `INTEGER PRIMARY KEY` to ensure that new rows receive sequentially increasing integer values. While often overlapping in functionality, `ROWID` is fundamental, while `AUTOINCREMENT` offers more control over the sequence generation.

12. Explain how you would handle concurrency issues in an SQLite application.

    • Answer: SQLite's concurrency model is simpler than that of server-based databases. It uses file locking to manage simultaneous access, which can lead to performance bottlenecks under heavy contention. Strategies for mitigating concurrency issues include using transactions extensively, employing appropriate locking mechanisms within the application code (advisory locking), or considering alternative database solutions for high-concurrency environments.

13. How do you perform data backups and restores in SQLite?

    • Answer: The simplest method is to create a copy of the SQLite database file. More robust approaches involve using the `sqlite3` command-line tool or library functions to create backups. For example, `sqlite3 mydatabase.db .dump > backup.sql` creates a SQL dump file. Restoration involves using the `sqlite3` tool or a library to import the dump file (`sqlite3 newdatabase.db < backup.sql`).

14. What are views in SQLite and how are they useful?

    • Answer: A view is a virtual table based on the result-set of an SQL statement. It doesn't store data itself; instead, it provides a customized perspective of the underlying table(s). Views can simplify complex queries, provide access control by restricting what data users can see, and improve data consistency by ensuring data access through a standardized interface.

15. How would you troubleshoot performance issues in an SQLite database?

    • Answer: Troubleshooting involves using tools like the `EXPLAIN QUERY PLAN` statement to analyze query execution, checking for missing indexes, evaluating the database schema for potential inefficiencies, monitoring disk I/O and memory usage, and profiling the application code to identify bottlenecks. Consider using a database profiling tool if available.

16. Describe your experience with using SQLite in different programming languages.

    • Answer: [This answer will be tailored to the candidate's experience. It should mention specific languages like Python, Java, C++, C#, etc., and detail their experience using SQLite libraries in those languages, including examples of projects where they've used SQLite.]

17. Explain your understanding of SQLite's WAL (Write-Ahead Logging) mode.

    • Answer: WAL mode is an alternative to the traditional rollback journal mode. It improves concurrency and performance, especially in multi-process or multi-threaded environments. In WAL mode, changes are written to a separate log file before being applied to the database file, allowing multiple readers to access the database concurrently without blocking writes.

18. How do you handle large datasets in SQLite?

    • Answer: Handling large datasets efficiently requires careful database design, optimization of queries, and potentially utilizing techniques like paging, caching, and potentially external tools for processing or analyzing the data. Using appropriate indexes is crucial, and you might need to split data into multiple smaller tables or consider alternative database technologies better suited for very large datasets.

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