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Data Streaming für Cloud Natives
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Nicolas Byl
May 04, 2017
Technology
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Data Streaming für Cloud Natives
Nicolas Byl
May 04, 2017
Transcript
30 slides
1 DATA STREAMING FÜR CLOUD NATIVES building IoT 2017 Nicolas
Byl, codecentric AG
2 . 1 Stream Processing, anyone?
2 . 2 Spring Cloud Dataflow
3 . 1 PROCESSING MODELL
3 . 2 Streams kleinste Einheit von Spring Cloud Dataflow
Verarbeitungsstrecke
3 . 3 Stream Struktur Source als Datenquelle Multiple Processor
Instanzen für nachfolgende Verarbeitungsschritte Sink als Ende der Verarbeitungskette
None
3 . 4 3 . 5 Verarbeitung Jeder Instanz der
Verarbeitungskette ist eine Spring Boot Applikation Pufferung zwischen Verarbeitungsschritten in Queue Pull Mechanismus für nächste Datensatz
3 . 6 Queueing
4 . 1 ARCHITEKTUR
None
4 . 2 4 . 3 Building Blocks Spring Boot
Spring Integration Spring Batch
4 . 4 Deployables Spring Boot Applikationen Spring Cloud Stream
Starters Spring Cloud Stream Spring Cloud Task
4 . 5 Deployer Spring Cloud Deployer - SPI
4 . 6 Interfaces Command Line Interface Dashboard Flo Editor
REST
5 . 1 BUILDING STREAMS
5 . 2 Command Line Interface Definition und Management der
vorhandenen Streams DSL zur Verkettung von Applikation mittels |
5 . 3 Beispiel 1: Ticktack stream create --name ticktock
--definition "time | log" --deploy
5 . 4 Beispiel 2: HTTP-Request stream create --name test
--definition "http | log" stream deploy test --properties "app.http.spring.cloud.deployer.kubernetes.c http post --target http://<IP>:8080 --data "Hello"
5 . 5 Grafischer Editor
6 . 1 CUSTOM APPLICATIONS
6 . 2 Programmiermodell - Spring Cloud Stream Source, Sink
& Processor sind normale Spring Beans Kopplung an Spring Integration Binding an den jeweiligen Typen Abstraktion des Queueing Providers durch das Framework
6 . 3 Beispiel 1: Direkte Bearbeitung in der Beans
@EnableBinding(Processor.class) public class TransformProcessor { @Autowired VotingService votingService; @StreamListener(Processor.INPUT) @SendTo(Processor.OUTPUT) public VoteResult handle(Vote vote) { return votingService.record(vote); } }
6 . 4 Beispiel 2: Spring Integration als Source @EnableBinding(Source.class)
public class TimerSource { @Value("${format}") private String format; @Bean @InboundChannelAdapter(value = Source.OUTPUT, poller = @Poller(fixedDelay public MessageSource<String> timerMessageSource() { return () -> new GenericMessage<>(new SimpleDateFormat(format).format( } }
6 . 5 Beispiel 3: Reative Processor @EnableRxJavaProcessor public class
RxJavaTransformer { private static Logger logger = LoggerFactory.getLogger(RxJavaTransformer @Bean public RxJavaProcessor<String,String> processor() { return inputStream -> inputStream.map(data -> { logger.info("Got data = " + data); return data; }) .buffer(5) .map(data -> String.valueOf(avg(data))); } [...] }
7 . 1 BEISPIELE
7 . 2 Beispiel 3: Twitter Analyse stream create --name
twitter-demo --definition "twitterstream --twitter.credentials.consumer-key=<...> [..] | field-value-counter --field-value-counter.fieldName=entities.hashtags.text --field-value-counter.name=hashtags"
8 . 1 ZUSAMMENFASSUNG
8 . 2 Andere Anwendungen Analytics Monitoring CRM ...
8 . 3 The End Copyright 2017
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