org.apache.kafka.streams.kstream.JoinWindows Java Examples
The following examples show how to use
org.apache.kafka.streams.kstream.JoinWindows.
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Example #1
Source File: KStreamsTopologyDescriptionParserTest.java From netbeans-mmd-plugin with Apache License 2.0 | 6 votes |
@Test public void testKsDsl1() { final StreamsBuilder builder = new StreamsBuilder(); final KStream<String, String> streamOne = builder.stream("input-topic-one"); final KStream<String, String> streamTwo = builder.stream("input-topic-two"); final KStream<String, String> streamOneNewKey = streamOne.selectKey((k, v) -> v.substring(0, 5)); final KStream<String, String> streamTwoNewKey = streamTwo.selectKey((k, v) -> v.substring(4, 9)); streamOneNewKey.join(streamTwoNewKey, (v1, v2) -> v1 + ":" + v2, JoinWindows.of(ofMinutes(5).toMillis())).to("joined-output"); final Topology topology = builder.build(); final String text = topology.describe().toString(); System.out.println(text); final KStreamsTopologyDescriptionParser parsed = new KStreamsTopologyDescriptionParser(text); assertEquals(16, parsed.size()); System.out.println(parsed.toString()); }
Example #2
Source File: StatisticsBuilder.java From football-events with MIT License | 5 votes |
private void buildMatchStatistics(KStream<String, GoalScored> goalStream) { KStream<String, MatchStarted> matchStartedStream = builder .stream(MATCH_STARTED_TOPIC, with(String(), matchStartedSerde)); KStream<String, MatchFinished> matchFinishedStream = builder .stream(MATCH_FINISHED_TOPIC, with(String(), matchFinishedSerde)); KStream<String, MatchScore> scoreStream = matchStartedStream .leftJoin(goalStream, (match, goal) -> new MatchScore(match).goal(goal), JoinWindows.of(maxMatchDuration), with(String(), matchStartedSerde, goalScoredSerde) ); KTable<String, MatchScore> scoreTable = scoreStream .groupByKey() .reduce(MatchScore::aggregate, materialized(MATCH_SCORES_STORE, matchScoreSerde)); scoreTable.toStream().to(MATCH_SCORES_TOPIC, Produced.with(String(), matchScoreSerde)); KStream<String, MatchScore> finalScoreStream = matchFinishedStream .leftJoin(scoreTable, (matchFinished, matchScore) -> matchScore, with(String(), matchFinishedSerde, matchScoreSerde) ); // new key: clubId KStream<String, TeamRanking> rankingStream = finalScoreStream .flatMap((clubId, matchScore) -> { Collection<KeyValue<String, TeamRanking>> result = new ArrayList<>(2); result.add(pair(matchScore.getHomeClubId(), matchScore.homeRanking())); result.add(pair(matchScore.getAwayClubId(), matchScore.awayRanking())); return result; }); KTable<String, TeamRanking> rankingTable = rankingStream .groupByKey(Serialized.with(String(), rankingSerde)) .reduce(TeamRanking::aggregate, materialized(TEAM_RANKING_STORE, rankingSerde)); // publish changes to a view topic rankingTable.toStream().to(TEAM_RANKING_TOPIC, Produced.with(String(), rankingSerde)); }
Example #3
Source File: StreamToTableJoinIntegrationTests.java From spring-cloud-stream-binder-kafka with Apache License 2.0 | 5 votes |
@StreamListener public void testProcessor( @Input(BindingsForTwoKStreamJoinTest.INPUT_1) KStream<String, String> input1Stream, @Input(BindingsForTwoKStreamJoinTest.INPUT_2) KStream<String, String> input2Stream) { input1Stream .join(input2Stream, (event1, event2) -> null, JoinWindows.of(TimeUnit.MINUTES.toMillis(5)), Joined.with( Serdes.String(), Serdes.String(), Serdes.String() ) ); }
Example #4
Source File: NamingChangelogAndRepartitionTopics.java From kafka-tutorials with Apache License 2.0 | 4 votes |
public Topology buildTopology(Properties envProps) { final StreamsBuilder builder = new StreamsBuilder(); final String inputTopic = envProps.getProperty("input.topic.name"); final String outputTopic = envProps.getProperty("output.topic.name"); final String joinTopic = envProps.getProperty("join.topic.name"); final Serde<Long> longSerde = Serdes.Long(); final Serde<String> stringSerde = Serdes.String(); final boolean addFilter = Boolean.parseBoolean(envProps.getProperty("add.filter")); final boolean addNames = Boolean.parseBoolean(envProps.getProperty("add.names")); KStream<Long, String> inputStream = builder.stream(inputTopic, Consumed.with(longSerde, stringSerde)) .selectKey((k, v) -> Long.parseLong(v.substring(0, 1))); if (addFilter) { inputStream = inputStream.filter((k, v) -> k != 100L); } final KStream<Long, String> joinedStream; final KStream<Long, Long> countStream; if (!addNames) { countStream = inputStream.groupByKey(Grouped.with(longSerde, stringSerde)) .count() .toStream(); joinedStream = inputStream.join(countStream, (v1, v2) -> v1 + v2.toString(), JoinWindows.of(Duration.ofMillis(100)), StreamJoined.with(longSerde, stringSerde, longSerde)); } else { countStream = inputStream.groupByKey(Grouped.with("count", longSerde, stringSerde)) .count(Materialized.as("the-counting-store")) .toStream(); joinedStream = inputStream.join(countStream, (v1, v2) -> v1 + v2.toString(), JoinWindows.of(Duration.ofMillis(100)), StreamJoined.with(longSerde, stringSerde, longSerde) .withName("join").withStoreName("the-join-store")); } joinedStream.to(joinTopic, Produced.with(longSerde, stringSerde)); countStream.map((k,v) -> KeyValue.pair(k.toString(), v.toString())).to(outputTopic, Produced.with(stringSerde, stringSerde)); return builder.build(); }
Example #5
Source File: KafkaStreamsJoinsApp.java From kafka-streams-in-action with Apache License 2.0 | 4 votes |
public static void main(String[] args) throws Exception { StreamsConfig streamsConfig = new StreamsConfig(getProperties()); StreamsBuilder builder = new StreamsBuilder(); Serde<Purchase> purchaseSerde = StreamsSerdes.PurchaseSerde(); Serde<String> stringSerde = Serdes.String(); KeyValueMapper<String, Purchase, KeyValue<String,Purchase>> custIdCCMasking = (k, v) -> { Purchase masked = Purchase.builder(v).maskCreditCard().build(); return new KeyValue<>(masked.getCustomerId(), masked); }; Predicate<String, Purchase> coffeePurchase = (key, purchase) -> purchase.getDepartment().equalsIgnoreCase("coffee"); Predicate<String, Purchase> electronicPurchase = (key, purchase) -> purchase.getDepartment().equalsIgnoreCase("electronics"); int COFFEE_PURCHASE = 0; int ELECTRONICS_PURCHASE = 1; KStream<String, Purchase> transactionStream = builder.stream( "transactions", Consumed.with(Serdes.String(), purchaseSerde)).map(custIdCCMasking); KStream<String, Purchase>[] branchesStream = transactionStream.selectKey((k,v)-> v.getCustomerId()).branch(coffeePurchase, electronicPurchase); KStream<String, Purchase> coffeeStream = branchesStream[COFFEE_PURCHASE]; KStream<String, Purchase> electronicsStream = branchesStream[ELECTRONICS_PURCHASE]; ValueJoiner<Purchase, Purchase, CorrelatedPurchase> purchaseJoiner = new PurchaseJoiner(); JoinWindows twentyMinuteWindow = JoinWindows.of(60 * 1000 * 20); KStream<String, CorrelatedPurchase> joinedKStream = coffeeStream.join(electronicsStream, purchaseJoiner, twentyMinuteWindow, Joined.with(stringSerde, purchaseSerde, purchaseSerde)); joinedKStream.print(Printed.<String, CorrelatedPurchase>toSysOut().withLabel("joined KStream")); // used only to produce data for this application, not typical usage MockDataProducer.producePurchaseData(); LOG.info("Starting Join Examples"); KafkaStreams kafkaStreams = new KafkaStreams(builder.build(), streamsConfig); kafkaStreams.start(); Thread.sleep(65000); LOG.info("Shutting down the Join Examples now"); kafkaStreams.close(); MockDataProducer.shutdown(); }