content: /*
   * 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.
   */
  
  //   beam-playground:
  //     name: CoreTransformsSolution2
  //     description: Core Transforms second motivating challenge.
  //     multifile: false
  //     context_line: 46
  //     categories:
  //       - Quickstart
  //     complexity: BASIC
  //     tags:
  //       - hellobeam
  
  import org.apache.beam.sdk.Pipeline;
  import org.apache.beam.sdk.io.TextIO;
  import org.apache.beam.sdk.options.PipelineOptions;
  import org.apache.beam.sdk.options.PipelineOptionsFactory;
  import org.apache.beam.sdk.transforms.*;
  import org.apache.beam.sdk.values.KV;
  import org.apache.beam.sdk.values.PCollection;
  import org.slf4j.Logger;
  import org.slf4j.LoggerFactory;
  import org.apache.beam.sdk.transforms.Flatten;
  
  public class Task {
  
      private static final Logger LOG = LoggerFactory.getLogger(Task.class);
      private static final String REGEX_FOR_CSV = ",(?=(?:[^\"]*\"[^\"]*\")*[^\"]*$)";
  
      public static void main(String[] args) {
          LOG.info("Running Task");
          PipelineOptions options = PipelineOptionsFactory.fromArgs(args).create();
          Pipeline pipeline = Pipeline.create(options);
  
          PCollection<KV<String, Integer>> input = pipeline.apply(TextIO.read().from("gs://apache-beam-samples/game/small/gaming_data.csv"))
                  .apply("Data", ParDo.of(new ExtractDataFn()));
  
          final PTransform<PCollection<KV<String, Integer>>, PCollection<Iterable<KV<String, Integer>>>> sample = Sample.fixedSizeGlobally(100);
  
          PCollection<KV<String,Integer>> limitedPCollection = input.apply(sample).apply(Flatten.iterables());
  
          combine(limitedPCollection).apply("Log score", ParDo.of(new LogOutput<>()));
  
          pipeline.run();
      }
  
      static PCollection<KV<String, Integer>> combine(PCollection<KV<String, Integer>> input) {
          return input.apply(Combine.perKey(new SumScoreCombineFn()));
      }
  
      static class SumScoreCombineFn extends Combine.BinaryCombineFn<Integer> {
          @Override
          public Integer apply(Integer left, Integer right) {
              return left + right;
          }
      }
  
      static class ExtractDataFn extends DoFn<String, KV<String, Integer>> {
          @ProcessElement
          public void processElement(ProcessContext c) {
              String[] items = c.element().split(REGEX_FOR_CSV);
              try {
                  c.output(KV.of(items[1], Integer.valueOf(items[2])));
              } catch (Exception e) {
                  System.out.println("Skip header");
              }
          }
      }
  
      static class LogOutput<T> extends DoFn<T, T> {
          private final String prefix;
  
          LogOutput() {
              this.prefix = "Processing element";
          }
  
          LogOutput(String prefix) {
              this.prefix = prefix;
          }
  
          @ProcessElement
          public void processElement(ProcessContext c) throws Exception {
              LOG.info(prefix + ": {}", c.element());
          }
      }
  
  
  }
  