content: /*
   * Copyright 2022 The FeatHub Authors
   *
   * 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
   *
   *     https://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.alibaba.feathub.flink.udf.aggregation;
  
  import org.apache.flink.api.java.tuple.Tuple2;
  import org.apache.flink.table.types.DataType;
  
  import java.util.Iterator;
  
  /**
   * Aggregation function decorator that only aggregates up to `limit` number of most recent records.
   */
  public class AggFuncWithLimit<IN_T, OUT_T, ACC_T> extends RawDataAccumulatingAggFunc<IN_T, OUT_T> {
      private final AggFunc<IN_T, OUT_T, ACC_T> aggFunc;
      protected final long limit;
  
      public AggFuncWithLimit(AggFunc<IN_T, OUT_T, ACC_T> aggFunc, long limit) {
          this.aggFunc = aggFunc;
          this.limit = limit;
      }
  
      @Override
      public OUT_T getResult(RawDataAccumulatingAggFunc.RawDataAccumulator<IN_T> accumulator) {
          ACC_T acc = aggFunc.createAccumulator();
  
          Iterator<Tuple2<IN_T, Long>> iterator = accumulator.rawDataList.descendingIterator();
          long count = 0;
          while (count < limit && iterator.hasNext()) {
              count++;
              Tuple2<IN_T, Long> data = iterator.next();
              aggFunc.add(acc, data.f0, data.f1);
          }
  
          return aggFunc.getResult(acc);
      }
  
      @Override
      public DataType getResultDatatype() {
          return aggFunc.getResultDatatype();
      }
  }
  