36 practice questions with answers for SQL interviews in Lucknow.
SQL jobs in Lucknow
Lucknow's tech job market is smaller but growing, led by IT-services delivery centres, government-tech projects and start-ups. Many Lucknow candidates target Noida and Gurgaon roles or remote jobs, so interviews follow the NCR pattern.
Below are 36 questions that match the mix of service, product and domain employers hiring data analyst (sql)s in Lucknow.
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01
Average order value looks too low in a report. What could be wrong?
Check the grain: if the query averages order items instead of orders, each line counts separately and the average drops. Joins can also duplicate rows. Verify whether cancelled or zero-value orders are included and how NULL amounts are treated. Compute SUM(amount) / COUNT(DISTINCT order_id) at order level and compare with business definitions before changing the report.
02
What is a deadlock and how do databases handle it?
A deadlock occurs when two transactions each hold a lock the other needs, so both wait forever. For example, T1 locks account A and wants B, while T2 locks B and wants A. The database detects the cycle and kills one transaction as the victim, rolling it back with an error. Applications should retry the victim and access resources in a consistent order.
03
A COUNT(DISTINCT) query on a huge events table is very slow. What options do you have?
Exact distinct counts need sorting or hashing all values, which is expensive. Options are filtering the date range tightly, pre-aggregating daily distinct users into a summary table, indexing the columns involved, or using approximate functions such as APPROX_COUNT_DISTINCT or HyperLogLog where small error is acceptable. Explain the accuracy trade-off to stakeholders before switching to approximations.
A natural key is a real-world identifier like PAN number, email or product code. A surrogate key is a system-generated value, usually an integer or UUID, with no business meaning. Surrogate keys are stable, compact and good for joins, while natural keys can change or be long. A common design uses a surrogate primary key plus a unique constraint on the natural key.
05
What is the CASE expression and where can it be used?
CASE adds conditional logic in SQL, returning a value based on conditions: CASE WHEN marks >= 60 THEN 'First' WHEN marks >= 45 THEN 'Second' ELSE 'Fail' END. It can be used in SELECT, WHERE, ORDER BY, GROUP BY and inside aggregates, for example SUM(CASE WHEN status = 'Paid' THEN amount ELSE 0 END) to pivot data. Conditions are checked in order and the first true one wins.
06
Someone ran an UPDATE without WHERE on production. What would you do?
Stop further changes and inform the lead and DBA immediately. If the session is still in an open transaction, roll back. Otherwise, restore affected rows from the latest backup or point-in-time recovery to a separate database and update the production table from it, or use audit or history tables if available. Afterwards, add safeguards such as safe-update mode, reviews and restricted write access.
07
What is the difference between a correlated and a non-correlated subquery?
A non-correlated subquery runs independently and returns a result once, such as the overall average salary. A correlated subquery references columns from the outer query and logically runs for each outer row, such as comparing each employee's salary with the average of their own department. Correlated subqueries are powerful but may be slow without good indexes, although optimisers often rewrite them as joins.
Normalisation organises data into tables to reduce redundancy and avoid insert, update and delete anomalies. For example, storing customer address in every order row means updating it in many places. By separating customers and orders and linking with keys, each fact is stored once. Common forms are 1NF, 2NF, 3NF and BCNF, and most transactional systems target 3NF.
09
How do you make sure your SQL changes do not break anything?
Situation: in my internship I had to change a report query used by three teams. Task: modify it safely. Action: I tested it on a copy of data, compared row counts and totals with the old version, asked a senior for review, and documented the change. Result: the update went live without issues, and the comparison approach became part of my routine for every change.
10
You need customers who bought both product A and product B. How would you write it?
Group by customer and count distinct matching products: SELECT customer_id FROM order_items WHERE product_id IN ('A', 'B') GROUP BY customer_id HAVING COUNT(DISTINCT product_id) = 2. Alternatively use INTERSECT of two queries, or two EXISTS conditions. The HAVING approach is concise, scans the table once and is easy to extend to three or more products.
11
What is the difference between a stored procedure and a function?
A function must return a value or table and can be used inside SELECT or WHERE, but in most databases cannot change data or manage transactions. A stored procedure is executed independently, can return multiple result sets or output parameters, can modify data and control transactions. Use functions for reusable calculations and procedures for workflows such as month-end processing.
Aggregate functions compute a single value from many rows: COUNT, SUM, AVG, MIN and MAX are standard, and databases add others such as STRING_AGG, GROUP_CONCAT, STDDEV and MEDIAN or PERCENTILE_CONT. Used with GROUP BY they return one value per group; without it they return one value for the whole table. Except COUNT(*), they ignore NULL values.
13
You added an index but the query still does a full table scan. Why might that be?
Possible reasons: the predicate is not SARGable because of a function or type conversion, the query returns a large share of rows so a scan is cheaper, the composite index column order does not match the filter, statistics are stale, or OR conditions prevent index use. Check the plan, rewrite the predicate, update statistics, or adjust the index to match the query.
A Common Table Expression is a named temporary result defined with WITH before the main query. It improves readability by breaking a complex query into named steps, can be referenced multiple times in the same statement, and supports recursion. Example: WITH high_value AS (SELECT * FROM orders WHERE amount > 10000) SELECT customer_id, COUNT(*) FROM high_value GROUP BY customer_id.
15
What is the difference between UNION and UNION ALL?
UNION combines the results of two queries and removes duplicate rows, which requires sorting or hashing. UNION ALL combines results and keeps all rows, so it is faster. Both need the same number of columns with compatible types in the same order. Use UNION ALL when duplicates are impossible or acceptable, such as stacking monthly tables, and UNION only when deduplication is required.
16
A business user needs a dashboard on a complex 6-table join that runs slowly. Would you use a view or a materialised view?
A normal view only simplifies the query; it still runs the full join every time, so performance does not improve. If the data can be a few minutes or hours old, a materialised view or summary table refreshed on schedule gives fast reads. If real-time data is required, tune the underlying query with indexes or build an incrementally maintained table.
17
How would you design a database for an online food delivery app at a high level?
Core tables are users, addresses, restaurants, menu_items, orders, order_items, payments, delivery_partners and deliveries. Orders reference users, restaurants and addresses, order_items reference orders and menu_items with price at order time, and payments and deliveries reference orders. Add status history tables for tracking and indexes on user_id, restaurant_id and created_at for common queries.
A CROSS JOIN returns the Cartesian product, every row of the first table combined with every row of the second, so 10 rows by 5 rows gives 50 rows. It is useful for generating combinations, such as all stores by all dates to build a calendar grid and then left join actual sales to show zero-sales days. Accidental cross joins from missing conditions produce huge results.
19
A search on name LIKE '%sharma%' is very slow on a 20 million row table. What can you do?
A leading wildcard cannot use a normal B-tree index, so the database scans the table. Options are full-text indexing, trigram indexes in PostgreSQL, a reversed or computed column if the pattern is a suffix, or a search engine for heavy text search. Also limit the result, filter on other indexed columns first, and check whether users really need contains search.
20
What is the difference between OLTP and OLAP databases?
OLTP systems handle many short transactions such as orders and payments, with normalised schemas, row-based storage and focus on fast inserts and updates. OLAP systems support analysis over large history, using denormalised star or snowflake schemas, columnar storage and heavy aggregations. A bank's core system is OLTP, while its data warehouse used for monthly reports is OLAP.
21
You need to delete duplicate rows but keep one copy of each. How do you do it?
Use a CTE with ROW_NUMBER: WITH d AS (SELECT id, ROW_NUMBER() OVER (PARTITION BY email ORDER BY id) AS rn FROM users) DELETE FROM users WHERE id IN (SELECT id FROM d WHERE rn > 1). SQL Server allows DELETE FROM d WHERE rn > 1 directly. Back up the table first, run a SELECT to verify, then add a unique constraint to prevent new duplicates.
DDL (Data Definition Language) defines structure: CREATE, ALTER, DROP, TRUNCATE. DML (Data Manipulation Language) changes data: INSERT, UPDATE, DELETE, and SELECT is often grouped here or as DQL. DCL (Data Control Language) manages access: GRANT and REVOKE. TCL (Transaction Control Language) manages transactions: COMMIT, ROLLBACK and SAVEPOINT. Knowing the categories helps explain behaviour such as auto-commit of DDL in some databases.
It depends on the database. SQL Server and MySQL usually inline CTEs like subqueries. PostgreSQL before version 12 always materialised CTEs, which could hurt performance; since version 12 non-recursive CTEs referenced once are inlined, and you can force behaviour with MATERIALIZED or NOT MATERIALIZED. Referencing a heavy CTE many times may cause repeated work, so check the plan.
24
Describe a time you reviewed someone else's SQL and suggested improvements.
Situation: a teammate's report query took eight minutes and had nested subqueries. Task: help without discouraging him. Action: I reviewed it with him, rewrote parts as CTEs, replaced a correlated subquery with a pre-aggregated join, and explained the execution plan differences. Result: the query ran in 40 seconds, and he later applied the same approach to two other reports.
25
What is the difference between INNER JOIN and LEFT JOIN?
INNER JOIN keeps only rows where the join condition matches in both tables. LEFT JOIN keeps every row from the left table and fills columns from the right with NULL when there is no match. For customers and orders, INNER JOIN shows only customers who ordered, while LEFT JOIN shows all customers, including those with no orders, which is useful for finding inactive customers.
26
Why is NOT IN dangerous when the subquery contains NULL?
If the subquery returns any NULL, value NOT IN (list) becomes unknown for every row, because comparing with NULL is unknown, so the query returns no rows. For example, NOT IN (SELECT manager_id FROM employees) fails when a manager_id is NULL. Use NOT EXISTS or filter out NULLs in the subquery to get correct results.
Common types are INT, BIGINT and SMALLINT for whole numbers, DECIMAL or NUMERIC for exact values like money, FLOAT for approximate values, CHAR for fixed-length and VARCHAR for variable-length text, DATE, TIME, DATETIME or TIMESTAMP for dates, and BOOLEAN where supported. Choosing correct types saves space, improves performance and prevents errors such as storing amounts in FLOAT and getting rounding issues.
28
What is the difference between ROWS and RANGE frames?
ROWS counts physical rows, so 2 PRECEDING means exactly two rows before. RANGE works on values of the ORDER BY column, so rows with the same value are treated together, and value ranges like INTERVAL '7 days' PRECEDING are possible in some databases. With duplicate dates, a RANGE running total jumps for all ties at once, while ROWS increases row by row.
They produce multiple grouping levels in one query. ROLLUP(region, city) gives city totals, region subtotals and a grand total. CUBE(region, product) gives all combinations of subtotals. GROUPING SETS lets you list exact combinations, such as (region), (product) and (). The GROUPING function identifies subtotal rows, which is useful for labelling them in reports.
1NF: each column holds atomic values and there are no repeating groups, so no comma-separated phone numbers. 2NF: in 1NF and every non-key column depends on the whole composite key, so product name should not sit in an order_items table keyed by order and product. 3NF: in 2NF with no transitive dependency, so city should not determine state inside the employees table.
31
Tell me about a database design decision you made and its outcome.
Situation: our app stored user preferences in a wide table with 60 nullable columns. Task: make it flexible for new settings. Action: I proposed a key-value preferences table with a JSON column for rarely used settings, kept frequently queried fields as columns, and wrote a migration. Result: new settings no longer needed schema changes and query speed for common fields stayed the same.
32
Two users book the last seat at the same time and both succeed. How do you fix it?
This is a race condition. Wrap the check and booking in one transaction and lock the seat row with SELECT ... FOR UPDATE so the second transaction waits and then sees it is taken. Alternatively use an atomic update such as UPDATE seats SET booked_by = :user WHERE seat_id = :id AND booked_by IS NULL and check affected rows, plus a unique constraint as a final safety net.
33
What is the difference between DELETE, TRUNCATE and DROP?
DELETE removes selected rows using a WHERE clause, is logged row by row, fires triggers and can be rolled back inside a transaction. TRUNCATE removes all rows quickly by deallocating pages, usually resets identity values and cannot use WHERE. DROP removes the whole table including structure, indexes and permissions. Use DELETE for selective removal, TRUNCATE to empty staging tables and DROP to remove objects.
LAG returns a value from a previous row in the partition and LEAD from a following row, based on the ORDER BY. LAG(revenue, 1, 0) OVER (ORDER BY month) gives last month's revenue with 0 as default for the first row. They are used for month-over-month change, time between events, and detecting status changes without self joins.
35
What is the difference between a unique index and a normal index?
A unique index enforces that no two rows have the same value in the indexed columns, and it is created automatically for primary keys and unique constraints. A normal index only speeds up lookups and allows duplicates. Both speed up searches, but a unique index also protects data integrity, for example preventing two users from registering with the same email.
36
Join three tables to get total sales by product category.
SELECT cat.category_name,
SUM(oi.quantity * oi.unit_price) AS revenue
FROM order_items oi
JOIN products p ON oi.product_id = p.product_id
JOIN categories cat ON p.category_id = cat.category_id
GROUP BY cat.category_name
ORDER BY revenue DESC;
Join from the most detailed table outward and aggregate at the end.
Which companies hire SQL professionals in Lucknow?
Companies with large offices in Lucknow include HCLTech. Use their company pages below to practise employer-specific sets.
Are SQL interviews in Lucknow different from other cities?
The questions depend more on the company than the city. Lucknow's mix of employers decides the style: Many Lucknow candidates target Noida and Gurgaon roles or remote jobs, so interviews follow the NCR pattern
How do I find SQL jobs in Lucknow?
Shortlist companies with Lucknow offices, keep your CV focused on SQL projects, apply on company career pages and job portals with the Lucknow filter, and practise the questions on this page before each interview.