Interactive queries in Kafka - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to start a Kafka Streams application.

Kafka

KafkaStreams streams = new KafkaStreams(builder, [1]);

Drag options to blanks, or click blank then click option'

Aproperties

Bconfig

CstreamsConfig

Dsettings

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong variable name for configuration properties.

Passing an incorrect object type instead of Properties.

The KafkaStreams constructor requires a Properties object named config that contains the configuration settings.

2fill in blank

medium

Complete the code to query the local state store named "counts-store".

Kafka

ReadOnlyKeyValueStore<String, Long> store = streams.store(StoreQueryParameters.fromNameAndType("counts-store", [1]));

Drag options to blanks, or click blank then click option'

AQueryableStoreTypes.timestampedKeyValueStore()

BQueryableStoreTypes.windowStore()

CQueryableStoreTypes.sessionStore()

DQueryableStoreTypes.keyValueStore()

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong store type for querying.

Confusing window stores with key-value stores.

The keyValueStore() type is used to query a key-value store in Kafka Streams.

3fill in blank

hard

Fix the error in the code to get a value from the store by key.

Kafka

Long count = store.[1]("myKey");

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Aget

Bfetch

Cretrieve

DgetValue

Attempts:

3 left

💡 Hint

Common Mistakes

Using non-existent methods like fetch or retrieve.

Confusing with other API methods.

The correct method to get a value by key from a ReadOnlyKeyValueStore is get().

4fill in blank

hard

Fill both blanks to create a queryable store parameter for a window store named "window-store".

Kafka

StoreQueryParameters<String, Long> params = StoreQueryParameters.fromNameAndType("window-store", [1]); // store type

QueryableStoreType<WindowStore<String, Long>> storeType = [2];

Drag options to blanks, or click blank then click option'

AQueryableStoreTypes.windowStore()

BQueryableStoreTypes.keyValueStore()

CQueryableStoreTypes.sessionStore()

DQueryableStoreTypes.timestampedKeyValueStore()

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing store types between key-value and window stores.

Using incorrect store type constants.

Both blanks require the window store type, which is QueryableStoreTypes.windowStore().

5fill in blank

hard

Fill all three blanks to create a map of key-value pairs from a store with a condition.

Kafka

Map<String, Long> result = new HashMap<>();
KeyValueIterator<String, Long> iter = store.all();
while (iter.hasNext()) {
    String key = iter.[1]().getKey();
    Long value = store.get(key);
    if (value [2] 10) {
        result.put(key, [3]);
    }
}
iter.close();

Drag options to blanks, or click blank then click option'

Aiterator

B>

Cvalue

Dnext

Attempts:

3 left

💡 Hint

Common Mistakes

Using iterator() instead of next() on the iterator.

Using wrong comparison operators.

Putting the wrong variable into the map.

The all() method returns an iterator, so we use next() to get keys. The condition checks if the value is greater than 10, and then puts the value into the result map.

Practice

1.

What is the main purpose of interactive queries in Kafka Streams?

easy

A. To create new Kafka topics dynamically

B. To write data back to Kafka topics

C. To read live state data directly from the Kafka Streams application

D. To monitor Kafka broker health status

Solution

1. Step 1: Understand interactive queries concept

   Interactive queries allow reading live state from Kafka Streams state stores.

2. Step 2: Identify the main use case

   The main use is to get real-time data from the app without extra databases.

3. Final Answer:

   To read live state data directly from the Kafka Streams application -> Option C

4. Quick Check:

   Interactive queries = read live state [OK]

Hint: Interactive queries read live state, not write or monitor [OK]

Common Mistakes:

• Confusing interactive queries with writing data
• Thinking it creates topics
• Assuming it monitors brokers

2.

Which of the following is the correct way to get a state store named myStore of type ReadOnlyKeyValueStore in Kafka Streams?

easy

A. store = streams.store("myStore", ReadOnlyKeyValueStore.class);

B. store = streams.getStore("myStore", ReadOnlyKeyValueStore);

C. store = streams.getStore("myStore", ReadOnlyKeyValueStore.class);

D. store = streams.store("myStore", ReadOnlyKeyValueStore);

Solution

1. Step 1: Recall Kafka Streams store retrieval syntax

   The correct method is streams.store(storeName, storeType.class) in Java.

2. Step 2: Match the correct syntax

   store = streams.store("myStore", ReadOnlyKeyValueStore.class); uses streams.store with class type, which is correct method name and syntax.

3. Final Answer:

   store = streams.store("myStore", ReadOnlyKeyValueStore.class); -> Option A

4. Quick Check:

   Use streams.store with class type [OK]

Hint: Use streams.store("name", StoreClass.class) syntax [OK]

Common Mistakes:

• Using streams.getStore instead of streams.store
• Omitting .class for type
• Passing type without .class

3.

Given the following code snippet in a Kafka Streams app, what will be the output if the key "user123" exists with value "active" in the state store?

var store = streams.store("userStatusStore", ReadOnlyKeyValueStore.class);
var status = store.get("user123");
System.out.println(status);

medium

A. null

B. "active"

C. Throws NullPointerException

D. Compilation error

Solution

1. Step 1: Understand store.get(key) behavior

   The get method returns the value for the key if it exists, else null.

2. Step 2: Check given key and value

   Since "user123" exists with value "active", store.get("user123") returns "active".

3. Final Answer:

   "active" -> Option B

4. Quick Check:

   store.get(existingKey) = value [OK]

Hint: store.get(key) returns value or null if missing [OK]

Common Mistakes:

• Assuming null is returned even if key exists
• Expecting exceptions on missing keys
• Confusing syntax causing compile errors

4.

Identify the error in this Kafka Streams interactive query code snippet:

var store = streams.store("ordersStore", ReadOnlyKeyValueStore.class);
var order = store.get(12345);
System.out.println(order);

medium

A. Passing integer key instead of string key

B. Missing try-catch block for exceptions

C. Using streams.store instead of streams.getStore

D. Incorrect store type ReadOnlyKeyValueStore

Solution

1. Step 1: Check method to get state store

   The method streams.store is correct.

2. Step 2: Validate key type and store type

   Key type mismatch: passing integer 12345 instead of string key (common for ordersStore).

3. Final Answer:

   Passing integer key instead of string key -> Option A

4. Quick Check:

   Key type must match store definition [OK]

Hint: Use correct key type in store.get(key) [OK]

Common Mistakes:

• Passing int literal without quotes for string keys
• Assuming key type must be string always
• Ignoring exception handling (not mandatory here)

5.

You want to build a real-time dashboard that shows the current count of active users using Kafka Streams interactive queries. Which approach best fits this requirement?

hard

A. Write user statuses to a separate database and query it periodically

B. Store counts in a local variable updated by Kafka Streams processors

C. Use Kafka consumer to read all user status events and aggregate externally

D. Use a ReadOnlyKeyValueStore to store user statuses and query counts live

Solution

1. Step 1: Identify real-time state storage method

   Kafka Streams state stores hold live data accessible via interactive queries.

2. Step 2: Choose best approach for live dashboard

   Using ReadOnlyKeyValueStore allows querying current counts directly without extra DB.

3. Final Answer:

   Use a ReadOnlyKeyValueStore to store user statuses and query counts live -> Option D

4. Quick Check:

   Interactive queries + state store = real-time dashboard [OK]

Hint: Use state store with interactive queries for live data [OK]

Common Mistakes:

• Relying on external DB instead of state store
• Polling Kafka consumer instead of querying store
• Using local variables which are not shared state