- 一、Flink Table 实现架构图:
- 二、Flink Table Conncetor流程解析
- 1、定义动态工厂类
- 2、定义Connector Source/Sink类
- (1)定义Connector Sink类
- (2)定义Connector Source类
- - Scan Table Source
- - Lookup Table Source
- (3)实现Source Function
- 三、flink-sql-connector-mqtt 实例
- 添加环境依赖
- 1、MqttDynamicTableSourceFactory
- 2、MqttDynamicTableSource
- 3、MqttSourceFunction
- ==4、META-INF.services==
- 四、打包(fat)
自定义Factory继承DynamicTableSinkFactory,DynamicTableSourceFactory接口,支持读取和写入两种功能。
拿DynamicTableSourceFactory接口来说,需要实现以下几种方法:
@Override
public DynamicTableSink createDynamicTableSource(Context context) {
return null;
}
@Override
public String factoryIdentifier() {
return null;
}
@Override
public Set> requiredOptions() {
return null;
}
@Override
public Set> optionalOptions() {
return null;
}
1.factoryIdentifier(): 指定工厂类的标识符,该标识符就是建表时必须填写的connector参数的值 2.requiredOptions(): with里面必须要填写的属性配置 (比如URL,TABLE_NAME,USERNAME,PASSWORD) 3.optionalOptions(): with里面非必须填写属性配置(比如提交方式,提交批次等) 4.createDynamicTableSource(): 创建TableSource对象,返回一个 DynamicTableSource2、定义Connector Source/Sink类 (1)定义Connector Sink类
继承DynamicTableSink接口,实现以下方法:
@Override
public ChangelogMode getChangelogMode(ChangelogMode changelogMode) {
return null;
}
@Override
public SinkRuntimeProvider getSinkRuntimeProvider(Context context) {
return null;
}
@Override
public DynamicTableSink copy() {
return null;
}
@Override
public String asSummaryString() {
return null;
}
1.getChangelogMode(): 写入方式默认INSERT_ONLY,里面实现了一个static静态类初始化:INSERT_ONLY =newBuilder().addContainedKind(RowKind.INSERT).build(); 具体实现,看下源码就知道了.... 2.getSinkRuntimeProvider(): Sink端输入的主要提供者,这里可以实现一个自定义的OutputFormat继承,当然也有人直接继承RichSinkFunction..这个和dataStream API实现写入方式就很像了。 RichOutputFormat(2)定义Connector Source类 - Scan Table Source主要是写入逻辑的实现。 3.copy(): 返回一个DynamicTableSink 4.asSummaryString(): 接口功能总结,可以概述下这个spi主要是xxxx Sink
ScanTableSource在运行时扫描来自外部存储系统的所有行。
实现ScanTableSource接口,实现方法如下:
@Override
public ChangelogMode getChangelogMode() {
return null;
}
@Override
public ScanRuntimeProvider getScanRuntimeProvider(ScanContext scanContext) {
return null;
}
@Override
public DynamicTableSource copy() {
return null;
}
@Override
public String asSummaryString() {
return null;
}
- Lookup Table Source
LookupTableSource在运行时通过一个或多个键查找外部存储系统的行。
与ScanTableSource相比,该source不必读取整个表,并且可以在需要时从(可能不断变化的)外部表中延迟获取单个值。
与ScanTableSource相比,LookupTableSource当前仅支持发出仅插入的更改。
这里着重提一下Source端的自定义Connector,它是需要继承LookupTableSource接口,实现Lookup功能才能当做Source端使用。
@Override
public LookupRuntimeProvider getLookupRuntimeProvider(LookupContext lookupContext) {
return null;
}
@Override
public DynamicTableSource copy() {
return null;
}
@Override
public String asSummaryString() {
return null;
}
(3)实现Source FunctiongetLookupRuntimeProvider(): 从社区已经提供的Connector中可以看到如果想实现一个Lookup功能,需要继承TableFunction接口.
继承RichSourceFunction类
@Override
public void run(SourceContext sourceContext) throws Exception {
}
@Override
public void cancel() {
}
1.run(): 连接数据源,编写具体实现方式,数据返回格式 2.cancel(): 断开数据源连接三、flink-sql-connector-mqtt 实例 添加环境依赖
1、MqttDynamicTableSourceFactoryorg.apache.flink flink-table-common 1.13.6 org.apache.flink flink-streaming-java_2.11 1.13.6 org.apache.flink flink-table-api-java-bridge_2.11 1.13.6 compile org.fusesource.mqtt-client mqtt-client 1.12 org.eclipse.paho org.eclipse.paho.client.mqttv3 1.2.0
import org.apache.flink.api.common.serialization.DeserializationSchema;
import org.apache.flink.configuration.ConfigOption;
import org.apache.flink.configuration.ConfigOptions;
import org.apache.flink.configuration.ReadableConfig;
import org.apache.flink.table.api.TableSchema;
import org.apache.flink.table.connector.format.DecodingFormat;
import org.apache.flink.table.connector.source.DynamicTableSource;
import org.apache.flink.table.data.RowData;
import org.apache.flink.table.factories.DeserializationFormatFactory;
import org.apache.flink.table.factories.DynamicTableSourceFactory;
import org.apache.flink.table.factories.FactoryUtil;
import java.util.HashSet;
import java.util.Set;
import static org.apache.flink.table.factories.FactoryUtil.createTableFactoryHelper;
public class MqttDynamicTableSourceFactory implements DynamicTableSourceFactory {
@Override
public DynamicTableSource createDynamicTableSource(Context context) {
//内置工具类校验传入参数
FactoryUtil.TableFactoryHelper helper = createTableFactoryHelper(this, context);
helper.validate();
// 获取有效参数
final ReadableConfig options = helper.getOptions();
final DecodingFormat> decodingFormat = helper.discoverDecodingFormat(
DeserializationFormatFactory.class,
FactoryUtil.FORMAT);
// 获取元数据信息
TableSchema schema = context.getCatalogTable().getSchema();
// 创建并且返回一个动态表源
return new MqttDynamicTableSource(options,decodingFormat,schema);
}
@Override
//TODO 2、指定工厂类的标识符,该标识符就是建表时必须填写的connector参数的值
public String factoryIdentifier() {
return "mqtt";
}
@Override
//TODO 3、with里面必须要填写的属性配置
public Set> requiredOptions() {
final Set> options = new HashSet<>();
options.add(HOSTURL);
options.add(TOPIC);
options.add(FactoryUtil.FORMAT); // use pre-defined option for format
return options;
}
@Override
//TODO 4、with里面非必须填写属性配置
public Set> optionalOptions() {
final Set> options = new HashSet<>();
options.add(USERNAME);
options.add(PASSWORD);
options.add(CLIENTID);
return options;
}
//TODO 5、定义MQTT Connector需要的各项参数
public static final ConfigOption HOSTURL =
ConfigOptions.key("hosturl")
.stringType()
.noDefaultValue()
.withDescription("the mqtt's connect hosturl.");
public static final ConfigOption USERNAME =
ConfigOptions.key("username")
.stringType()
.noDefaultValue()
.withDescription("the mqtt's connect username.");
public static final ConfigOption PASSWORD =
ConfigOptions.key("password")
.stringType()
.noDefaultValue()
.withDescription("the mqtt's connect password.");
public static final ConfigOption TOPIC =
ConfigOptions.key("topic")
.stringType()
.noDefaultValue()
.withDescription("the mqtt's connect topic.");
public static final ConfigOption CLIENTID =
ConfigOptions.key("clientid")
.stringType()
.noDefaultValue()
.withDescription("the mqtt's connect clientId.");
}
2、MqttDynamicTableSource
import org.apache.flink.api.common.serialization.DeserializationSchema;
import org.apache.flink.configuration.ReadableConfig;
import org.apache.flink.streaming.api.functions.source.SourceFunction;
import org.apache.flink.table.api.TableSchema;
import org.apache.flink.table.connector.format.DecodingFormat;
import org.apache.flink.table.connector.source.DynamicTableSource;
import org.apache.flink.table.connector.source.ScanTableSource;
import org.apache.flink.table.connector.source.SourceFunctionProvider;
import org.apache.flink.table.data.RowData;
import org.apache.flink.types.RowKind;
public class MqttDynamicTableSource implements ScanTableSource {
private ReadableConfig options;
private TableSchema schema;
private DecodingFormat> decodingFormat;
public MqttDynamicTableSource(ReadableConfig options,DecodingFormat> decodingFormat, TableSchema schema){
this.options = options;
this.decodingFormat = decodingFormat;
this.schema = schema;
}
@Override
//写入方式默认INSERT_ONLY,里面实现了一个static静态类初始化
public ChangelogMode getChangelogMode() {
// return decodingFormat.getChangelogMode();
return ChangelogMode.newBuilder()
.addContainedKind(RowKind.INSERT)
.addContainedKind(RowKind.UPDATe_BEFORE)
.addContainedKind(RowKind.UPDATE_AFTER)
.addContainedKind(RowKind.DELETE)
.build();
}
@Override
//获取运行时类
public ScanRuntimeProvider getScanRuntimeProvider(ScanContext ctx) {
final DeserializationSchema deserializer = decodingFormat.createRuntimeDecoder(
ctx,
schema.toPhysicalRowDataType());
final SourceFunction sourceFunction = new MqttSourceFunction(options,deserializer);
return SourceFunctionProvider.of(sourceFunction, false);
}
@Override
public DynamicTableSource copy() {
return new MqttDynamicTableSource(options,decodingFormat,schema);
}
@Override
public String asSummaryString() {
return "Mqtt Table Source";
}
}
3、MqttSourceFunction
import org.apache.flink.api.common.serialization.DeserializationSchema; import org.apache.flink.configuration.ReadableConfig; import org.apache.flink.streaming.api.functions.source.RichSourceFunction; import org.apache.flink.table.data.RowData; import org.eclipse.paho.client.mqttv3.*; import org.eclipse.paho.client.mqttv3.persist.MemoryPersistence; import java.io.ByteArrayOutputStream; import java.io.ObjectOutputStream; import java.io.Serializable; import java.util.concurrent.ArrayBlockingQueue; import java.util.concurrent.BlockingQueue; import static org.apache.flink.table.connector.MqttDynamicTableSourceFactory.*; public class MqttSourceFunction extends RichSourceFunction4、META-INF.services{ //MQTT连接配置信息 private ReadableConfig confs; //阻塞队列存储订阅的消息 private BlockingQueue queue = new ArrayBlockingQueue<>(10); //存储服务 private MqttClient client; //存储订阅主题 private DeserializationSchema deserializer; public MqttSourceFunction(ReadableConfig options,DeserializationSchema deserializer) { this.confs = options; this.deserializer = deserializer; } //包装连接的方法 private void connect() throws MqttException { //连接mqtt服务器 client = new MqttClient(confs.get(HOSTURL), confs.get(CLIENTID), new MemoryPersistence()); MqttConnectOptions options = new MqttConnectOptions(); options.setCleanSession(false); options.setUserName(confs.get(USERNAME)); options.setPassword(confs.get(PASSWORD).toCharArray()); options.setCleanSession(false); //是否清除session // 设置超时时间 options.setConnectionTimeout(30); // 设置会话心跳时间 options.setKeepAliveInterval(20); try { String[] topics = confs.get(TOPIC).split(","); //订阅消息 int[] qos = new int[topics.length]; for (int i = 0; i < topics.length; i++) { qos[i] = 0; } client.setCallback(new MsgCallback(client, options, topics, qos) { }); client.connect(options); client.subscribe(topics, qos); System.out.println("MQTT连接成功:" + confs.get(CLIENTID) + ":" + client); } catch (Exception e) { System.out.println("MQTT连接异常:" + e); } } //实现MqttCallback,内部函数可回调 class MsgCallback implements MqttCallback { private MqttClient client; private MqttConnectOptions options; private String[] topic; private int[] qos; public MsgCallback() { } public MsgCallback(MqttClient client, MqttConnectOptions options, String[] topic, int[] qos) { this.client = client; this.options = options; this.topic = topic; this.qos = qos; } //连接失败回调该函数 @Override public void connectionLost(Throwable throwable) { System.out.println("MQTT连接断开,发起重连"); while (true) { try { Thread.sleep(1000); client.connect(options); //订阅消息 client.subscribe(topic, qos); System.out.println("MQTT重新连接成功:" + client); break; } catch (Exception e) { e.printStackTrace(); continue; } } } //收到消息回调该函数 @Override public void messageArrived(String s, MqttMessage message) throws Exception { System.out.println(); //订阅消息字符 queue.put(deserializer.deserialize(message.getPayload())); } //对象转化为字节码 public byte[] getBytesFromObject(Serializable obj) throws Exception { if (obj == null) { return null; } ByteArrayOutputStream bo = new ByteArrayOutputStream(); ObjectOutputStream oo = new ObjectOutputStream(bo); oo.writeObject(obj); return bo.toByteArray(); } @Override public void deliveryComplete(IMqttDeliveryToken iMqttDeliveryToken) { } } //flink线程启动函数 @Override public void run(SourceContext ctx) throws Exception { connect(); //利用死循环使得程序一直监控主题是否有新消息 while (true) { //使用阻塞队列的好处是队列空的时候程序会一直阻塞到这里不会浪费CPU资源 ctx.collect(queue.take()); } } @Override public void cancel() { try { client.disconnect(); } catch (Throwable t) { // ignore } } }
Flink SQL的自定义Connector主要是用Java的SPI方式可以加载到应用服务当中,根据SPI机制的使用机制,需要在resources目录下新建META-INF.services新建文件
org.apache.flink.table.factories.Factory
文件中添加工厂类的路径就行。
Flink使用Java的Service Provider Interfaces (SPI) 机制通过特定标识符加载table的connector/format工厂。由于每个table的connector/format的名为org.apache.flink.table.factories.Factory的SPI资源文件位于同一目录:META-INF/services下,因此在构建使用多个table connector/format的项目的uber jar时,这些资源文件将相互覆盖,这将导致Flink无法正确加载工厂类。
在这种情况下,推荐的方法是通过maven shade插件的ServicesResourceTransformer转换META-INF/services目录下的这些资源文件。
| plugin | function |
|---|---|
| maven-jar-plugin maven | 默认打包插件,用来创建 project jar |
| maven-shade-plugin | 用来打可执行包,executable(fat) jar |
| maven-assembly-plugin | 支持定制化打包方式,例如 apache 项目的打包方式 |
在配置了ServicesResourceTransformer之后, 项目构建uber-jar时,META-INF/services目录下的这些资源文件会被整合在一起而不是相互覆盖。
org.apache.maven.plugins maven-shade-plugin 3.1.1 shade package shade org.apache.maven.plugins maven-compiler-plugin 8 8



