GroupBy and aggregation in Kafka - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to group the stream by the 'user' field.

Kafka

KGroupedStream<String, String> groupedStream = stream.[1]();

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Amap

BflatMap

Cfilter

DgroupByKey

Attempts:

3 left

💡 Hint

Common Mistakes

Using filter instead of groupByKey

Using map which transforms records but does not group

Using flatMap which expands records instead of grouping

The groupByKey method groups the stream by its existing key, which is 'user' here.

2fill in blank

medium

Complete the code to count the number of records per key.

Kafka

KTable<String, Long> counts = groupedStream.[1]();

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Aaggregate

Breduce

Ccount

DmapValues

Attempts:

3 left

💡 Hint

Common Mistakes

Using reduce which combines values but does not count

Using aggregate which requires more parameters

Using mapValues which transforms values but does not count

The count method counts the number of records for each key in the grouped stream.

3fill in blank

hard

Fix the error in the aggregation code by completing the missing method.

Kafka

KTable<String, Integer> aggregated = groupedStream.[1](() -> 0, (key, value, aggregate) -> aggregate + Integer.parseInt(value));

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Aaggregate

Bmap

Creduce

Dcount

Attempts:

3 left

💡 Hint

Common Mistakes

Using count which does not take initializer or aggregator

Using reduce which does not take initializer

Using map which transforms but does not aggregate

The aggregate method allows custom aggregation with initializer and aggregator functions.

4fill in blank

hard

Fill both blanks to group the stream by 'category' and sum the values as integers.

Kafka

KTable<String, Integer> summed = stream.mapValues(Integer::parseInt).[1]( (key, value) -> key.split(":")[0] ).[2](Integer::sum);

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AgroupBy

BmapValues

Creduce

Dcount

Attempts:

3 left

💡 Hint

Common Mistakes

Using mapValues instead of groupBy

Using count instead of reduce

Using reduce without grouping first

groupBy groups by a new key extracted from the original key. reduce sums the integer values.

5fill in blank

hard

Fill the blanks to create a grouped stream by 'type', aggregate values starting at 0, and add parsed integers.

Kafka

KTable<String, Integer> result = stream.[1]( (key, value) -> value.split(",")[0] ).[2](() -> 0, (aggKey, newValue, aggValue) -> aggValue + Integer.parseInt(newValue));

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

AgroupBy

Baggregate

CmapValues

Dcount

Attempts:

3 left

💡 Hint

Common Mistakes

Using count instead of aggregate

Using mapValues instead of aggregate

Not grouping before aggregating

groupBy groups by the first part of the value, aggregate initializes and updates the aggregation, and mapValues is not used here but included as a distractor.