Curated interview practice questions with answers. These are practice scenarios, not a verified list of past interview questions.
About Flipkart hiring for Java roles
Flipkart is an Indian e-commerce company and part of the Walmart group, with businesses including Flipkart, Myntra, Cleartrip and Ekart logistics. Its engineering and analytics teams work on search, recommendations, supply chain, pricing and fraud detection. It hires for software development engineers, SDETs, business analysts, data analysts and data scientists.
For Java roles, this Flipkart practice set focuses most on Multithreading and Concurrency (7), Java 8+ Features and Streams (4), Spring Boot and Microservices (4), JDBC, Hibernate and JPA (4). It has 18 medium, 12 hard questions, so you can start easy and work up to the harder ones.
Company type
E-commerce & consumer tech
Headquarters
Bengaluru, India
Main India offices
Bengaluru, Hyderabad
Flipkart Java interview process
Online coding assessment
Machine coding round
Problem solving and DSA round
Hiring manager round
HR round
Typical pattern based on public candidate experiences. Rounds vary by role, team and year.
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01
Flatten a list of lists of integers and compute the sum of squares of the even numbers.
flatMap then use a primitive stream to avoid boxing.
int result = lists.stream()
.flatMap(List::stream)
.filter(n -> n % 2 == 0)
.mapToInt(n -> n * n)
.sum();
mapToInt returns an IntStream, whose sum() is simpler and faster than reduce on boxed Integers.
02
You must expose configuration that differs between dev, QA and production. How do you manage it?
Use Spring profiles with application-dev.yml and application-prod.yml, and bind settings to typed @ConfigurationProperties classes with validation. Keep secrets out of the repo by injecting them through environment variables, Kubernetes Secrets or a vault. Activate the profile with SPRING_PROFILES_ACTIVE in each environment. Use the same build artefact everywhere and change only configuration.
03
When would you choose ArrayDeque over Stack and LinkedList?
Stack is a legacy synchronized class built on Vector, so it is slow and exposes index methods that break stack rules. LinkedList allocates a node per element. ArrayDeque is a resizable circular array with no per-element allocation, so push, pop, offer and poll are fast amortised O(1). Use ArrayDeque for both stacks and queues in single-threaded code; it does not accept null.
04
Two users booking the last seat both succeed. How do you prevent double booking?
This is a race between read and write. Use a database guarantee: a unique constraint on seat and show, an atomic conditional update like UPDATE seats SET status = 'BOOKED' WHERE id = ? AND status = 'FREE' and check the affected row count, or pessimistic locking with SELECT FOR UPDATE. Optimistic locking with a version column also works, retrying or failing the loser.
05
You need to process a 5 GB file using streams without running out of memory. How?
Use Files.lines(path), which reads lazily line by line, inside try-with-resources. Apply filter and map, then aggregate with a collector that keeps small results such as counts or sums instead of collecting all lines into a list. If the output is large, write it incrementally to a BufferedWriter. Avoid sorted() and distinct() on huge data because they buffer everything.
06
A counter shared between threads shows wrong totals. How do you fix it?
count++ is not atomic; two threads can read the same value and both write the same result, so updates are lost. Use AtomicInteger.incrementAndGet(), which uses CAS, or LongAdder for very high contention, as it spreads updates over cells. A synchronized method also works but is slower. volatile alone does not fix it because it gives visibility, not atomicity.
Access order plus removeEldestEntry gives LRU in a few lines.
class LruCache<K, V> extends LinkedHashMap<K, V> {
private final int capacity;
LruCache(int capacity) {
super(16, 0.75f, true);
this.capacity = capacity;
}
@Override
protected boolean removeEldestEntry(Map.Entry<K, V> e) {
return size() > capacity;
}
}
get and put are O(1).
08
A thread pool fills up and tasks get rejected during traffic spikes. How do you handle it?
First check why tasks are slow, since slow tasks fill pools. Then choose a policy: a bounded queue with CallerRunsPolicy applies backpressure by running the task in the submitting thread; otherwise return a fast 503 so clients retry. Tune pool and queue sizes from load tests. Never use an unbounded queue, because it hides the problem until memory runs out.
The simplest safe options are an enum or the holder idiom.
public class Config {
private Config() {}
private static class Holder {
static final Config INSTANCE = new Config();
}
public static Config getInstance() {
return Holder.INSTANCE;
}
}
The JVM loads Holder lazily and class initialisation is thread safe. An enum singleton also resists reflection and serialization attacks.
10
An API listing 100 orders fires 101 SQL queries. How do you fix it?
This is the N+1 problem from a lazy association loaded in a loop or by JSON serialisation. Fetch what the endpoint needs in one query with JOIN FETCH or @EntityGraph(attributePaths = "items"), or use a DTO projection query. For collections with pagination, fetch ids first, then fetch associations in a second query to avoid in-memory paging. Add a test that asserts the query count.
11
Your service throws OutOfMemoryError: Java heap space in production. How do you investigate?
First capture evidence: enable -XX:+HeapDumpOnOutOfMemoryError and check GC logs to see if heap grows steadily, which signals a leak, or spikes, which signals a large request. Analyse the heap dump in Eclipse MAT or VisualVM and look at the dominator tree for big retainers like static maps or caches. Fix the leak or bound the cache, then increase -Xmx only if the real workload needs it.
12
What is CompletableFuture and how is it better than Future?
Future only lets you block with get() to obtain a result. CompletableFuture supports non-blocking composition: thenApply to transform, thenCompose to chain async calls, thenCombine or allOf to join several, and exceptionally or handle for errors. It runs on the common ForkJoinPool by default, but pass your own executor for blocking I/O to avoid starving the pool.
13
toMap() throws Duplicate key exception in production. How do you fix it?
The data has repeated keys that the developer assumed were unique. Decide the business rule, then pass a merge function, for example toMap(User::email, u -> u, (a, b) -> a) to keep the first, or use groupingBy if all values are needed. Also check upstream data quality, since duplicates may signal a deeper bug such as missing unique constraints.
A deadlock happens when two or more threads each hold a lock and wait for a lock held by the other, so none can continue. It needs mutual exclusion, hold and wait, no preemption and circular wait. Prevent it by always acquiring locks in the same global order, using tryLock with a timeout, holding locks briefly and avoiding calls to unknown code while holding a lock.
15
An API calls three independent downstream services one after another and takes 900 ms. How would you speed it up?
Since the calls are independent, run them in parallel with CompletableFuture.supplyAsync on a dedicated executor or with virtual threads, then join with allOf. Total latency becomes roughly the slowest call, about 300 ms. Add a timeout per call with orTimeout and a fallback for failures so one slow service does not block the whole response. Structured concurrency is another option in newer Java.
16
Users report the app is slow for the first few minutes after every deployment. Why might this happen?
This is usually JVM warm-up. Code runs in the interpreter until the JIT compiles hot paths, and caches, connection pools and class loading are also cold. Fixes include warm-up traffic before adding the instance to the load balancer, pre-initialising pools, class data sharing (AppCDS) to reduce start time, or newer options like CRaC or GraalVM native image when fast start is critical.
17
How do you take a thread dump and a heap dump of a running Java process?
Find the process id with jps or ps, then use jcmd, which is the recommended tool.
jps -l
jcmd <pid> Thread.print > threads.txt
jcmd <pid> GC.heap_dump /tmp/heap.hprof
Older tools jstack and jmap do the same. Take three thread dumps a few seconds apart to spot stuck threads, and analyse heap dumps in Eclipse MAT.
18
Which JVM flags would you set to start a production service with a 4 GB heap, G1 and a heap dump on OOM?
Production has more data, so check the execution plan with EXPLAIN ANALYZE on production-like data. Look for full table scans, missing indexes on filter or join columns, functions on indexed columns and poor statistics. Check if Hibernate generates the SQL you expect. Add a suitable composite index, rewrite the query or paginate, and verify the plan improves before release.
20
A @Transactional method is not rolling back after an exception. What could be wrong?
Check that the exception is unchecked, since checked exceptions do not roll back unless rollbackFor is set. Check that the method is called through the Spring proxy, not from another method in the same class. Make sure the method is public and the exception is not caught and swallowed inside. Also confirm the database engine supports transactions and the right transaction manager is used.
21
Your application hangs and CPU is near zero. How do you find out why?
Low CPU with a hang suggests threads are blocked, often a deadlock or waiting on a slow resource. Take several thread dumps with jcmd pid Thread.print. The JVM reports detected deadlocks at the end of the dump. Otherwise look for many threads BLOCKED on the same lock or WAITING on a connection pool or socket read, then fix lock order, add timeouts or increase the pool.
At startup Spring Boot reads auto-configuration classes listed in META-INF/spring/org.springframework.boot.autoconfigure.AutoConfiguration.imports. Each class uses conditions like @ConditionalOnClass, @ConditionalOnMissingBean and @ConditionalOnProperty, so it creates beans only when the library is on the classpath and you have not defined your own. Run with --debug to see the condition report showing what was applied and why.
23
How would you write a simple thread safe rate limiter in Java?
A token bucket with synchronized refill is simple and correct.
class RateLimiter {
private final long capacity, refillPerSec;
private double tokens; private long last = System.nanoTime();
RateLimiter(long cap, long rps) { capacity = cap; refillPerSec = rps; tokens = cap; }
synchronized boolean tryAcquire() {
long now = System.nanoTime();
tokens = Math.min(capacity, tokens + (now - last) / 1e9 * refillPerSec);
last = now;
if (tokens >= 1) { tokens--; return true; }
return false;
}
}
Across servers, keep the bucket in Redis.
24
Group a list of orders by city and sum the amount per city.
Use groupingBy with a summing collector.
Map<String, Double> totals = orders.stream()
.collect(Collectors.groupingBy(
Order::city,
TreeMap::new,
Collectors.summingDouble(Order::amount)));
TreeMap keeps cities sorted. For money, store amounts as long paise or BigDecimal and use Collectors.reducing with BigDecimal::add.
25
A deep inheritance hierarchy of six levels is hard to change. How would you refactor it?
I would identify which behaviours actually vary and pull them into small interfaces, then replace inheritance with composition where a class holds strategy objects. Shared helper code can move to separate components. I would refactor step by step behind existing tests, starting from the leaves, so behaviour stays the same. The result is flatter classes that are easier to test and extend.
Transient: a new object not yet linked to a persistence context. Managed (persistent): attached to the context, so changes are tracked and flushed automatically through dirty checking. Detached: was managed but the context closed or it was evicted; changes are not tracked until merge(). Removed: scheduled for deletion on flush. persist, merge, detach and remove move entities between these states.
27
Read a large text file line by line efficiently and count lines containing ERROR.
Stream the file lazily so it never loads fully into memory.
Path p = Path.of("app.log");
try (Stream<String> lines = Files.lines(p)) {
long errors = lines
.filter(l -> l.contains("ERROR"))
.count();
System.out.println(errors);
}
try-with-resources closes the file handle. BufferedReader.readLine() in a loop is an equally good option.
28
Your Spring Boot service takes 40 seconds to start in Kubernetes and pods get killed. How do you fix it?
First set a startupProbe so Kubernetes waits for startup before liveness checks begin. Then reduce start time: remove unused starters, enable lazy initialisation where safe, avoid heavy work in @PostConstruct, give enough CPU at start and consider AppCDS. For very fast startup, a GraalVM native image built with Spring AOT can start in under a second, with some trade-offs.
29
Explain pattern matching for switch and record patterns in Java 21.
Pattern matching for switch lets a case match on type and bind a variable, such as case Circle c -> Math.PI * c.r() * c.r(). Record patterns deconstruct a record directly: case Point(int x, int y). Guards add conditions with when. With sealed types the compiler checks the switch is exhaustive, so adding a new subtype causes a compile error where it is not handled.
Sealed classes and interfaces, final in Java 17, restrict which classes can extend them using the permits clause, for example sealed interface Shape permits Circle, Square. Each subclass must be final, sealed or non-sealed. This models a closed set of types, and with pattern matching for switch in Java 21 the compiler can check that every case is handled without a default branch.
Tips to crack the Flipkart Java interview
Practise machine coding problems where you build a small working system, such as a parking lot or splitwise, in about 90 minutes.
For analyst roles, prepare guesstimates and cases on topics like Big Billion Days sales, returns or delivery delays.
Learn about Flipkart's supply chain and Ekart operations, as many data problems relate to logistics in Indian conditions.
Keep a one-minute story ready for every project on your CV: problem, your part, tools, result.
Practise the hard questions on this page aloud; Flipkart interviewers usually ask follow-ups on your first answer.
Frequently asked questions
How many rounds are there in the Flipkart Java interview?
Candidates usually go through 5 stages: Online coding assessment; Machine coding round; Problem solving and DSA round; Hiring manager round; HR round. The exact rounds change with the role, team, location and your experience, so confirm the process with the recruiter.
Which topics should I prepare for the Flipkart Java interview?
This practice set leans on Multithreading and Concurrency (7), Java 8+ Features and Streams (4), Spring Boot and Microservices (4), JDBC, Hibernate and JPA (4). Revise those first, then practise explaining one or two of your own projects end to end, because most Flipkart interviewers ask you to walk through real work.
Are these the exact questions asked at Flipkart?
No. These are curated practice questions that match the skills and difficulty usually tested in e-commerce & consumer tech interviews like Flipkart's. They are not a leaked or verified list of past questions.
Where does Flipkart hire Java professionals in India?
Flipkart has large teams in Bengaluru, Hyderabad. Openings and locations change often, so check the Flipkart careers page and filter by city and experience.