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...ase/kafka-base-sink/src/main/java/com/dtstack/flink/sql/sink/kafka/AbstractKafkaSink.java
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| /* | ||
| * 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. | ||
| */ | ||
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| package com.dtstack.flink.sql.sink.kafka; | ||
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| 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.functions.sink.SinkFunction; | ||
| import org.apache.flink.streaming.connectors.kafka.partitioner.FlinkKafkaPartitioner; | ||
| import org.apache.flink.table.api.TableSchema; | ||
| import org.apache.flink.table.runtime.types.CRow; | ||
| import org.apache.flink.table.runtime.types.CRowTypeInfo; | ||
| import org.apache.flink.table.sinks.RetractStreamTableSink; | ||
| import org.apache.flink.table.sinks.TableSink; | ||
| import org.apache.flink.types.Row; | ||
| import org.apache.flink.util.Preconditions; | ||
| import org.apache.kafka.clients.consumer.ConsumerConfig; | ||
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| import java.util.Optional; | ||
| import java.util.Properties; | ||
| import java.util.stream.IntStream; | ||
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| /** | ||
| * Date: 2020/4/1 | ||
| * Company: www.dtstack.com | ||
| * @author maqi | ||
| */ | ||
| public abstract class AbstractKafkaSink implements RetractStreamTableSink<Row>, IStreamSinkGener { | ||
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| public static final String SINK_OPERATOR_NAME_TPL = "${topic}_${table}"; | ||
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| protected String[] fieldNames; | ||
| protected TypeInformation<?>[] fieldTypes; | ||
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| protected String[] partitionKeys; | ||
| protected String sinkOperatorName; | ||
| protected Properties properties; | ||
| protected int parallelism; | ||
| protected String topic; | ||
| protected String tableName; | ||
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| protected TableSchema schema; | ||
| protected SinkFunction<CRow> kafkaProducer; | ||
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| protected Optional<FlinkKafkaPartitioner<CRow>> partitioner; | ||
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| protected Properties getKafkaProperties(KafkaSinkTableInfo KafkaSinkTableInfo) { | ||
| Properties props = new Properties(); | ||
| props.setProperty(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, KafkaSinkTableInfo.getBootstrapServers()); | ||
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| for (String key : KafkaSinkTableInfo.getKafkaParamKeys()) { | ||
| props.setProperty(key, KafkaSinkTableInfo.getKafkaParam(key)); | ||
| } | ||
| return props; | ||
| } | ||
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| 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; | ||
| } | ||
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| protected TableSchema buildTableSchema(String[] fieldNames, TypeInformation<?>[] fieldTypes) { | ||
| Preconditions.checkArgument(fieldNames.length == fieldTypes.length, "fieldNames length must equals fieldTypes length !"); | ||
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| TableSchema.Builder builder = TableSchema.builder(); | ||
| IntStream.range(0, fieldTypes.length) | ||
| .forEach(i -> builder.field(fieldNames[i], fieldTypes[i])); | ||
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| return builder.build(); | ||
| } | ||
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| @Override | ||
| public void emitDataStream(DataStream<Tuple2<Boolean, Row>> dataStream) { | ||
| DataStream<CRow> mapDataStream = dataStream | ||
| .map((Tuple2<Boolean, Row> record) -> new CRow(record.f1, record.f0)) | ||
| .returns(getRowTypeInfo()) | ||
| .setParallelism(parallelism); | ||
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| mapDataStream.addSink(kafkaProducer).name(sinkOperatorName); | ||
| } | ||
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| public CRowTypeInfo getRowTypeInfo() { | ||
| return new CRowTypeInfo(new RowTypeInfo(fieldTypes, fieldNames)); | ||
| } | ||
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| protected String[] getPartitionKeys(KafkaSinkTableInfo kafkaSinkTableInfo) { | ||
| if (StringUtils.isNotBlank(kafkaSinkTableInfo.getPartitionKeys())) { | ||
| return StringUtils.split(kafkaSinkTableInfo.getPartitionKeys(), ','); | ||
| } | ||
| return null; | ||
| } | ||
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| @Override | ||
| public TupleTypeInfo<Tuple2<Boolean, Row>> getOutputType() { | ||
| return new TupleTypeInfo(org.apache.flink.table.api.Types.BOOLEAN(), new RowTypeInfo(fieldTypes, fieldNames)); | ||
| } | ||
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| @Override | ||
| public String[] getFieldNames() { | ||
| return fieldNames; | ||
| } | ||
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| @Override | ||
| public TypeInformation<?>[] getFieldTypes() { | ||
| return fieldTypes; | ||
| } | ||
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| @Override | ||
| public TableSink<Tuple2<Boolean, Row>> configure(String[] fieldNames, TypeInformation<?>[] fieldTypes) { | ||
| this.fieldNames = fieldNames; | ||
| this.fieldTypes = fieldTypes; | ||
| return this; | ||
| } | ||
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| @Override | ||
| public TypeInformation<Row> getRecordType() { | ||
| return new RowTypeInfo(fieldTypes, fieldNames); | ||
| } | ||
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| } |
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