Merge remote-tracking branch 'origin/v1.9.0_dev' into v1.10.0_dev

Author: todd5167

kafka-base/kafka-base-sink/src/main/java/com/dtstack/flink/sql/sink/kafka/AbstractKafkaSink.java

@@ -0,0 +1,143 @@
+/*
+ * 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.dtstack.flink.sql.sink.kafka;
+
+import com.dtstack.flink.sql.sink.IStreamSinkGener;
+import com.dtstack.flink.sql.sink.kafka.table.KafkaSinkTableInfo;
+import org.apache.commons.lang3.StringUtils;
+import org.apache.flink.api.common.typeinfo.TypeInformation;
+import org.apache.flink.api.java.tuple.Tuple2;
+import org.apache.flink.api.java.typeutils.RowTypeInfo;
+import org.apache.flink.api.java.typeutils.TupleTypeInfo;
+import org.apache.flink.streaming.api.datastream.DataStream;
+import org.apache.flink.streaming.api.datastream.DataStreamSink;
+import org.apache.flink.streaming.api.functions.sink.SinkFunction;
+import org.apache.flink.streaming.connectors.kafka.partitioner.FlinkKafkaPartitioner;
+import org.apache.flink.table.api.TableSchema;
+import org.apache.flink.table.sinks.RetractStreamTableSink;
+import org.apache.flink.table.sinks.TableSink;
+import org.apache.flink.table.types.DataType;
+import org.apache.flink.types.Row;
+import org.apache.flink.util.Preconditions;
+import org.apache.kafka.clients.consumer.ConsumerConfig;
+
+import java.util.Optional;
+import java.util.Properties;
+import java.util.stream.IntStream;
+
+import static org.apache.flink.table.types.utils.TypeConversions.fromLegacyInfoToDataType;
+
+/**
+ * Date: 2020/3/30
+ * Company: www.dtstack.com
+ * @author maqi
+ */
+public abstract class AbstractKafkaSink implements RetractStreamTableSink<Row>, IStreamSinkGener {
+    public static final String SINK_OPERATOR_NAME_TPL = "${topic}_${table}";
+
+    protected String[] fieldNames;
+    protected TypeInformation<?>[] fieldTypes;
+
+    protected String[] partitionKeys;
+    protected String sinkOperatorName;
+    protected Properties properties;
+    protected int parallelism;
+    protected String topic;
+    protected String tableName;
+
+    protected TableSchema schema;
+    protected SinkFunction<Tuple2<Boolean,Row>> kafkaProducer011;
+
+    protected Optional<FlinkKafkaPartitioner<Tuple2<Boolean,Row>>> partitioner;
+
+    protected Properties getKafkaProperties(KafkaSinkTableInfo KafkaSinkTableInfo) {
+        Properties props = new Properties();
+        props.setProperty(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, KafkaSinkTableInfo.getBootstrapServers());
+
+        for (String key : KafkaSinkTableInfo.getKafkaParamKeys()) {
+            props.setProperty(key, KafkaSinkTableInfo.getKafkaParam(key));
+        }
+        return props;
+    }
+
+    protected TypeInformation[] getTypeInformations(KafkaSinkTableInfo kafka11SinkTableInfo) {
+        Class<?>[] fieldClasses = kafka11SinkTableInfo.getFieldClasses();
+        TypeInformation[] types = IntStream.range(0, fieldClasses.length)
+                .mapToObj(i -> TypeInformation.of(fieldClasses[i]))
+                .toArray(TypeInformation[]::new);
+        return types;
+    }
+
+
+    protected TableSchema buildTableSchema(String[] fieldNames, TypeInformation<?>[] fieldTypes) {
+        Preconditions.checkArgument(fieldNames.length == fieldTypes.length, "fieldNames length must equals fieldTypes length !");
+
+        DataType[] dataTypes = IntStream.range(0, fieldTypes.length)
+                .mapToObj(i -> fromLegacyInfoToDataType(fieldTypes[i]))
+                .toArray(DataType[]::new);
+
+        TableSchema tableSchema = TableSchema.builder()
+                .fields(fieldNames, dataTypes)
+                .build();
+        return tableSchema;
+    }
+
+    protected String[] getPartitionKeys(KafkaSinkTableInfo kafkaSinkTableInfo) {
+        if (StringUtils.isNotBlank(kafkaSinkTableInfo.getPartitionKeys())) {
+            return StringUtils.split(kafkaSinkTableInfo.getPartitionKeys(), ',');
+        }
+        return null;
+    }
+
+    @Override
+    public DataStreamSink<Tuple2<Boolean, Row>> consumeDataStream(DataStream<Tuple2<Boolean, Row>> dataStream) {
+        DataStreamSink<Tuple2<Boolean, Row>> dataStreamSink = dataStream.addSink(kafkaProducer011).name(sinkOperatorName);
+        if (parallelism > 0) {
+            dataStreamSink.setParallelism(parallelism);
+        }
+        return dataStreamSink;
+    }
+
+    @Override
+    public void emitDataStream(DataStream<Tuple2<Boolean, Row>> dataStream) {
+        consumeDataStream(dataStream);
+    }
+
+    @Override
+    public TableSink<Tuple2<Boolean, Row>> configure(String[] fieldNames, TypeInformation<?>[] fieldTypes) {
+        this.fieldNames = fieldNames;
+        this.fieldTypes = fieldTypes;
+        return this;
+    }
+
+    @Override
+    public TupleTypeInfo<Tuple2<Boolean, Row>> getOutputType() {
+        return new TupleTypeInfo(org.apache.flink.table.api.Types.BOOLEAN(), new RowTypeInfo(fieldTypes, fieldNames));
+    }
+
+    @Override
+    public TableSchema getTableSchema() {
+        return schema;
+    }
+
+    @Override
+    public TypeInformation<Row> getRecordType() {
+        return new RowTypeInfo(fieldTypes, fieldNames);
+    }
+}