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/*
* Copyright 2019 Netflix, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package com.netflix.mantis.examples.wordcount;
import com.netflix.mantis.examples.core.WordCountPair;
import com.netflix.mantis.examples.wordcount.sources.TwitterSource;
import io.mantisrx.common.JsonSerializer;
import io.mantisrx.runtime.Job;
import io.mantisrx.runtime.MantisJobProvider;
import io.mantisrx.runtime.Metadata;
import io.mantisrx.runtime.core.MantisStream;
import io.mantisrx.runtime.core.WindowSpec;
import io.mantisrx.runtime.core.functions.SimpleReduceFunction;
import io.mantisrx.runtime.core.sinks.ObservableSinkImpl;
import io.mantisrx.runtime.core.sources.ObservableSourceImpl;
import io.mantisrx.runtime.executor.LocalJobExecutorNetworked;
import io.mantisrx.runtime.parameter.Parameter;
import io.mantisrx.runtime.sink.Sinks;
import java.time.Duration;
import java.util.ArrayList;
import java.util.List;
import java.util.StringTokenizer;
import lombok.extern.slf4j.Slf4j;
/**
* This sample demonstrates connecting to a twitter feed and counting the number of occurrences of words within a 10
* sec hopping window.
* Run the main method of this class and then look for a the SSE port in the output
* E.g
* Serving modern HTTP SSE server sink on port: 8650
* You can curl this port curl localhost:8650 to view the output of the job.
*
* To run via gradle
* ../gradlew execute --args='consumerKey consumerSecret token tokensecret'
*/
@Slf4j
public class TwitterDslJob extends MantisJobProvider {
@Override
public Job getJobInstance() {
final JsonSerializer jsonSerializer = new JsonSerializer();
return MantisStream.create(null)
.source(new ObservableSourceImpl<>(new TwitterSource()))
.map(event -> {
try {
return jsonSerializer.toMap(event);
} catch (Exception e) {
log.error("Failed to deserialize event {}", event, e);
return null;
}
})
// filter out english tweets
.filter((eventMap) -> {
if(eventMap.containsKey("lang") && eventMap.containsKey("text")) {
String lang = (String)eventMap.get("lang");
return "en".equalsIgnoreCase(lang);
}
return false;
}).map((eventMap) -> (String) eventMap.get("text"))
// tokenize the tweets into words
.flatMap(this::tokenize)
.keyBy(WordCountPair::getWord)
// On a hopping window of 10 seconds
.window(WindowSpec.timed(Duration.ofSeconds(10)))
.reduce((SimpleReduceFunction) (acc, item) -> {
if (acc.getWord() != null && !acc.getWord().isEmpty() && !acc.getWord().equals(item.getWord())) {
log.warn("keys dont match: acc ({}) vs item ({})", acc.getWord(), item.getWord());
}
return new WordCountPair(acc.getWord(), acc.getCount() + item.getCount());
})
.map(WordCountPair::toString)
// Reuse built in sink that eagerly subscribes and delivers data over SSE
.sink(new ObservableSinkImpl<>(Sinks.eagerSubscribe(Sinks.sse((String data) -> data))))
.metadata(new Metadata.Builder()
.name("TwitterSample")
.description("Connects to a Twitter feed")
.build())
.create();
}
private List tokenize(String text) {
StringTokenizer tokenizer = new StringTokenizer(text);
List wordCountPairs = new ArrayList<>();
while(tokenizer.hasMoreTokens()) {
String word = tokenizer.nextToken().replaceAll("\\s*", "").toLowerCase();
wordCountPairs.add(new WordCountPair(word,1));
}
return wordCountPairs;
}
public static void main(String[] args) {
String consumerKey = null;
String consumerSecret = null;
String token = null;
String tokenSecret = null;
if(args.length != 4) {
System.out.println("Usage: java com.netflix.mantis.examples.TwitterJob