flink job同时使用BroadcastProcessFunction和KeyedBroadcastProcessFunction例子

背景：

广播状态可以用于规则表或者配置表的实时更新，本文就是用一个欺诈检测的flink作业作为例子看一下BroadcastProcessFunction和KeyedBroadcastProcessFunction的使用

BroadcastProcessFunction和KeyedBroadcastProcessFunction的使用

1.首先看主流程，主流程中使用了两个Broadcast广播的状态，这两个Broadcast广播的状态是独立的

 // 这里面包含规则广播状态的两次使用方法,分别在DynamicKeyFunction处理函数和DynamicAlertFunction处理函数,注意这两个处理函数中的广播状态是独立的，也就是需要分别维度，不能共享// Processing pipeline setupDataStream<Alert> alerts =transactions.connect(rulesStream).process(new DynamicKeyFunction()).uid("DynamicKeyFunction").name("Dynamic Partitioning Function").keyBy((keyed) -> keyed.getKey()).connect(rulesStream).process(new DynamicAlertFunction()).uid("DynamicAlertFunction").name("Dynamic Rule Evaluation Function");

2.BroadcastProcessFunction的处理，这里面会维护这个算子本身的广播状态，并把所有的事件扩散发送到下一个算子

public class DynamicKeyFunctionextends BroadcastProcessFunction<Transaction, Rule, Keyed<Transaction, String, Integer>> {@Overridepublic void open(Configuration parameters) {}// 这里会把每个事件结合上广播状态中的每个规则生成N条记录，流转到下一个算子@Overridepublic void processElement(Transaction event, ReadOnlyContext ctx, Collector<Keyed<Transaction, String, Integer>> out)throws Exception {ReadOnlyBroadcastState<Integer, Rule> rulesState =ctx.getBroadcastState(Descriptors.rulesDescriptor);forkEventForEachGroupingKey(event, rulesState, out);}// 独立维护广播状态,可以在广播状态中新增删除或者清空广播状态@Overridepublic void processBroadcastElement(Rule rule, Context ctx, Collector<Keyed<Transaction, String, Integer>> out) throws Exception {log.info("{}", rule);BroadcastState<Integer, Rule> broadcastState =ctx.getBroadcastState(Descriptors.rulesDescriptor);handleRuleBroadcast(rule, broadcastState);if (rule.getRuleState() == RuleState.CONTROL) {handleControlCommand(rule.getControlType(), broadcastState);}}}static void handleRuleBroadcast(Rule rule, BroadcastState<Integer, Rule> broadcastState)throws Exception {switch (rule.getRuleState()) {case ACTIVE:case PAUSE:broadcastState.put(rule.getRuleId(), rule);break;case DELETE:broadcastState.remove(rule.getRuleId());break;}}

3.KeyedBroadcastProcessFunction的处理,这里面也是会维护这个算子本身的广播状态，此外还有键值分区状态，特别注意的是在处理广播元素时，可以用applyToKeyedState方法对所有的键值分区状态应用某个方法，对于ontimer方法，依然可以访问键值分区状态和广播状态

/** Licensed to the Apache Software Foundation (ASF) under one* or more contributor license agreements.  See the NOTICE file* distributed with this work for additional information* regarding copyright ownership.  The ASF licenses this file* to you 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.ververica.field.dynamicrules.functions;import static com.ververica.field.dynamicrules.functions.ProcessingUtils.addToStateValuesSet;
import static com.ververica.field.dynamicrules.functions.ProcessingUtils.handleRuleBroadcast;import com.ververica.field.dynamicrules.Alert;
import com.ververica.field.dynamicrules.FieldsExtractor;
import com.ververica.field.dynamicrules.Keyed;
import com.ververica.field.dynamicrules.Rule;
import com.ververica.field.dynamicrules.Rule.ControlType;
import com.ververica.field.dynamicrules.Rule.RuleState;
import com.ververica.field.dynamicrules.RuleHelper;
import com.ververica.field.dynamicrules.RulesEvaluator.Descriptors;
import com.ververica.field.dynamicrules.Transaction;
import java.math.BigDecimal;
import java.util.*;
import java.util.Map.Entry;
import lombok.extern.slf4j.Slf4j;
import org.apache.flink.api.common.accumulators.SimpleAccumulator;
import org.apache.flink.api.common.state.BroadcastState;
import org.apache.flink.api.common.state.MapState;
import org.apache.flink.api.common.state.MapStateDescriptor;
import org.apache.flink.api.common.typeinfo.BasicTypeInfo;
import org.apache.flink.api.common.typeinfo.TypeHint;
import org.apache.flink.api.common.typeinfo.TypeInformation;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.metrics.Meter;
import org.apache.flink.metrics.MeterView;
import org.apache.flink.streaming.api.functions.co.KeyedBroadcastProcessFunction;
import org.apache.flink.util.Collector;/** Implements main rule evaluation and alerting logic. */
@Slf4j
public class DynamicAlertFunctionextends KeyedBroadcastProcessFunction<String, Keyed<Transaction, String, Integer>, Rule, Alert> {private static final String COUNT = "COUNT_FLINK";private static final String COUNT_WITH_RESET = "COUNT_WITH_RESET_FLINK";private static int WIDEST_RULE_KEY = Integer.MIN_VALUE;private static int CLEAR_STATE_COMMAND_KEY = Integer.MIN_VALUE + 1;private transient MapState<Long, Set<Transaction>> windowState;private Meter alertMeter;private MapStateDescriptor<Long, Set<Transaction>> windowStateDescriptor =new MapStateDescriptor<>("windowState",BasicTypeInfo.LONG_TYPE_INFO,TypeInformation.of(new TypeHint<Set<Transaction>>() {}));@Overridepublic void open(Configuration parameters) {windowState = getRuntimeContext().getMapState(windowStateDescriptor);alertMeter = new MeterView(60);getRuntimeContext().getMetricGroup().meter("alertsPerSecond", alertMeter);}// 键值分区状态和广播状态联合处理，在这个方法中可以更新键值分区状态，然后广播状态只能读取@Overridepublic void processElement(Keyed<Transaction, String, Integer> value, ReadOnlyContext ctx, Collector<Alert> out)throws Exception {long currentEventTime = value.getWrapped().getEventTime();addToStateValuesSet(windowState, currentEventTime, value.getWrapped());long ingestionTime = value.getWrapped().getIngestionTimestamp();ctx.output(Descriptors.latencySinkTag, System.currentTimeMillis() - ingestionTime);Rule rule = ctx.getBroadcastState(Descriptors.rulesDescriptor).get(value.getId());if (noRuleAvailable(rule)) {log.error("Rule with ID {} does not exist", value.getId());return;}if (rule.getRuleState() == Rule.RuleState.ACTIVE) {Long windowStartForEvent = rule.getWindowStartFor(currentEventTime);long cleanupTime = (currentEventTime / 1000) * 1000;ctx.timerService().registerEventTimeTimer(cleanupTime);SimpleAccumulator<BigDecimal> aggregator = RuleHelper.getAggregator(rule);for (Long stateEventTime : windowState.keys()) {if (isStateValueInWindow(stateEventTime, windowStartForEvent, currentEventTime)) {aggregateValuesInState(stateEventTime, aggregator, rule);}}BigDecimal aggregateResult = aggregator.getLocalValue();boolean ruleResult = rule.apply(aggregateResult);ctx.output(Descriptors.demoSinkTag,"Rule "+ rule.getRuleId()+ " | "+ value.getKey()+ " : "+ aggregateResult.toString()+ " -> "+ ruleResult);if (ruleResult) {if (COUNT_WITH_RESET.equals(rule.getAggregateFieldName())) {evictAllStateElements();}alertMeter.markEvent();out.collect(new Alert<>(rule.getRuleId(), rule, value.getKey(), value.getWrapped(), aggregateResult));}}}//维护广播状态，新增/删除或者整个清空,值得注意的是，处理广播元素时可以对所有的键值分区状态应用某个函数，比如这里当收到某个属于控制消息的广播消息时，使用applyToKeyedState方法把所有的键值分区状态都清空@Overridepublic void processBroadcastElement(Rule rule, Context ctx, Collector<Alert> out)throws Exception {log.info("{}", rule);BroadcastState<Integer, Rule> broadcastState =ctx.getBroadcastState(Descriptors.rulesDescriptor);handleRuleBroadcast(rule, broadcastState);updateWidestWindowRule(rule, broadcastState);if (rule.getRuleState() == RuleState.CONTROL) {handleControlCommand(rule, broadcastState, ctx);}}private void handleControlCommand(Rule command, BroadcastState<Integer, Rule> rulesState, Context ctx) throws Exception {ControlType controlType = command.getControlType();switch (controlType) {case EXPORT_RULES_CURRENT:for (Map.Entry<Integer, Rule> entry : rulesState.entries()) {ctx.output(Descriptors.currentRulesSinkTag, entry.getValue());}break;case CLEAR_STATE_ALL:ctx.applyToKeyedState(windowStateDescriptor, (key, state) -> state.clear());break;case CLEAR_STATE_ALL_STOP:rulesState.remove(CLEAR_STATE_COMMAND_KEY);break;case DELETE_RULES_ALL:Iterator<Entry<Integer, Rule>> entriesIterator = rulesState.iterator();while (entriesIterator.hasNext()) {Entry<Integer, Rule> ruleEntry = entriesIterator.next();rulesState.remove(ruleEntry.getKey());log.info("Removed Rule {}", ruleEntry.getValue());}break;}}private boolean isStateValueInWindow(Long stateEventTime, Long windowStartForEvent, long currentEventTime) {return stateEventTime >= windowStartForEvent && stateEventTime <= currentEventTime;}private void aggregateValuesInState(Long stateEventTime, SimpleAccumulator<BigDecimal> aggregator, Rule rule) throws Exception {Set<Transaction> inWindow = windowState.get(stateEventTime);if (COUNT.equals(rule.getAggregateFieldName())|| COUNT_WITH_RESET.equals(rule.getAggregateFieldName())) {for (Transaction event : inWindow) {aggregator.add(BigDecimal.ONE);}} else {for (Transaction event : inWindow) {BigDecimal aggregatedValue =FieldsExtractor.getBigDecimalByName(rule.getAggregateFieldName(), event);aggregator.add(aggregatedValue);}}}private boolean noRuleAvailable(Rule rule) {// This could happen if the BroadcastState in this CoProcessFunction was updated after it was// updated and used in `DynamicKeyFunction`if (rule == null) {return true;}return false;}private void updateWidestWindowRule(Rule rule, BroadcastState<Integer, Rule> broadcastState)throws Exception {Rule widestWindowRule = broadcastState.get(WIDEST_RULE_KEY);if (rule.getRuleState() != Rule.RuleState.ACTIVE) {return;}if (widestWindowRule == null) {broadcastState.put(WIDEST_RULE_KEY, rule);return;}if (widestWindowRule.getWindowMillis() < rule.getWindowMillis()) {broadcastState.put(WIDEST_RULE_KEY, rule);}}// ontimer方法中可以访问/更新键值分区状态，读取广播状态，此外ontimer方法和processElement方法以及processBroadcastElement方法是同步的，不需要考虑并发访问的问题@Overridepublic void onTimer(final long timestamp, final OnTimerContext ctx, final Collector<Alert> out)throws Exception {Rule widestWindowRule = ctx.getBroadcastState(Descriptors.rulesDescriptor).get(WIDEST_RULE_KEY);Optional<Long> cleanupEventTimeWindow =Optional.ofNullable(widestWindowRule).map(Rule::getWindowMillis);Optional<Long> cleanupEventTimeThreshold =cleanupEventTimeWindow.map(window -> timestamp - window);cleanupEventTimeThreshold.ifPresent(this::evictAgedElementsFromWindow);}private void evictAgedElementsFromWindow(Long threshold) {try {Iterator<Long> keys = windowState.keys().iterator();while (keys.hasNext()) {Long stateEventTime = keys.next();if (stateEventTime < threshold) {keys.remove();}}} catch (Exception ex) {throw new RuntimeException(ex);}}private void evictAllStateElements() {try {Iterator<Long> keys = windowState.keys().iterator();while (keys.hasNext()) {keys.next();keys.remove();}} catch (Exception ex) {throw new RuntimeException(ex);}}
}

ps: ontimer方法和processElement方法是同步访问的，没有并发的问题，所以不需要考虑同时更新键值分区状态的线程安全问题

参考文献：
https://flink.apache.org/2020/01/15/advanced-flink-application-patterns-vol.1-case-study-of-a-fraud-detection-system/