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feat: Round 10 배치 작업물을 upstream 템플릿에 통합
Round 10에서 작업한 주간/월간 랭킹 배치 Job을 upstream 배치 템플릿 구조에 통합합니다. 변경 사항: - WeeklyRankingJobConfig, MonthlyRankingJobConfig 추가 - ProductMetricsAggregateReader 추가 (집계 쿼리) - RankingScoreProcessor 추가 (점수 계산 로직) - WeeklyRankingWriter, MonthlyRankingWriter 추가 - 도메인 엔티티 추가: WeeklyProductRank, MonthlyProductRank - 리포지토리 추가: WeeklyRankRepository, MonthlyRankRepository - JpaConfig 수정: com.loopers.domain 패키지 스캔 추가 - CommerceBatchApplicationTest 수정: Job 자동 실행 비활성화 Upstream의 Listener 구조(JobListener, StepMonitorListener, ChunkListener)를 유지하면서 Round 10 랭킹 Job을 추가했습니다.
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‎apps/commerce-batch/src/main/java/com/loopers/batch/config/BatchConfig.java‎

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package com.loopers.batch.config;
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import org.springframework.context.annotation.Configuration;
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/**
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* Base configuration class for Spring Batch.
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*
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* <p>Spring Boot 3.x auto-configures Spring Batch, so @EnableBatchProcessing is not needed.
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* <p>This class can be used for common batch configuration beans if needed.
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*/
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@Configuration
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public class BatchConfig {
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}

‎apps/commerce-batch/src/main/java/com/loopers/batch/config/MonthlyRankingJobConfig.java‎

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package com.loopers.batch.config;
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import com.loopers.batch.processor.RankingScoreProcessor;
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import com.loopers.batch.reader.ProductMetricsAggregateReader;
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import com.loopers.batch.writer.MonthlyRankingWriter;
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import com.loopers.domain.dto.ProductRankingAggregation;
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import com.loopers.domain.rank.MonthlyProductRank;
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import com.loopers.domain.rank.MonthlyRankRepository;
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import jakarta.persistence.EntityManager;
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import lombok.RequiredArgsConstructor;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.batch.core.Job;
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import org.springframework.batch.core.Step;
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import org.springframework.batch.core.configuration.annotation.JobScope;
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import org.springframework.batch.core.configuration.annotation.StepScope;
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import org.springframework.batch.core.job.builder.JobBuilder;
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import org.springframework.batch.core.repository.JobRepository;
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import org.springframework.batch.core.step.builder.StepBuilder;
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import org.springframework.batch.item.ItemProcessor;
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import org.springframework.batch.item.ItemReader;
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import org.springframework.batch.item.ItemWriter;
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import org.springframework.beans.factory.annotation.Value;
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import org.springframework.context.annotation.Bean;
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import org.springframework.context.annotation.Configuration;
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import org.springframework.transaction.PlatformTransactionManager;
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/**
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* Configuration class for monthly ranking aggregation batch job.
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*
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* <p>This job aggregates product metrics data on a monthly basis and
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* stores the top N rankings in the materialized view table.
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*
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* <p>Job execution example:
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* <pre>
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* java -jar commerce-batch.jar \
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* --job.name=monthlyRankingJob \
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* yearMonth=2025-01
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* </pre>
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*
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* <p>Chunk-oriented processing flow:
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* <ol>
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* <li>Reader: Aggregate product_metrics by month</li>
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* <li>Processor: Calculate ranking scores</li>
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* <li>Writer: Save to mv_product_rank_monthly</li>
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* </ol>
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*/
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@Slf4j
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@Configuration
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@RequiredArgsConstructor
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public class MonthlyRankingJobConfig {
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private static final int CHUNK_SIZE = 100;
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private static final int TOP_N = 100;
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private final EntityManager entityManager;
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private final MonthlyRankRepository monthlyRankRepository;
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/**
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* Defines the monthly ranking job.
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*
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* @param jobRepository the Spring Batch job repository
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* @param monthlyRankingStep the step to execute
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* @return configured Job instance
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*/
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@Bean
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public Job monthlyRankingJob(
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JobRepository jobRepository,
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Step monthlyRankingStep
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) {
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return new JobBuilder("monthlyRankingJob", jobRepository)
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.start(monthlyRankingStep)
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.build();
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}
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/**
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* Defines the monthly ranking step with chunk-oriented processing.
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*
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* @param jobRepository the Spring Batch job repository
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* @param transactionManager the transaction manager
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* @param yearMonth the target month (injected from job parameters)
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* @return configured Step instance
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*/
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@Bean
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@JobScope
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public Step monthlyRankingStep(
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JobRepository jobRepository,
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PlatformTransactionManager transactionManager,
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@Value("#{jobParameters['yearMonth']}") String yearMonth
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) {
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log.info("Initializing monthly ranking step: yearMonth={}", yearMonth);
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return new StepBuilder("monthlyRankingStep", jobRepository)
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.<ProductRankingAggregation, MonthlyProductRank>chunk(CHUNK_SIZE, transactionManager)
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.reader(monthlyMetricsReader(yearMonth))
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.processor(monthlyRankingProcessor(yearMonth))
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.writer(monthlyRankingWriter())
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.build();
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}
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/**
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* Creates an ItemReader for monthly metrics aggregation.
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*
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* @param yearMonth the target month
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* @return configured ItemReader
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*/
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@Bean
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@StepScope
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public ItemReader<ProductRankingAggregation> monthlyMetricsReader(
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@Value("#{jobParameters['yearMonth']}") String yearMonth
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) {
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return new ProductMetricsAggregateReader(entityManager, yearMonth, "MONTHLY", TOP_N);
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}
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/**
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* Creates an ItemProcessor for ranking score calculation.
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*
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* @param yearMonth the target month
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* @return configured ItemProcessor
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*/
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@Bean
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@StepScope
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public ItemProcessor<ProductRankingAggregation, MonthlyProductRank> monthlyRankingProcessor(
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@Value("#{jobParameters['yearMonth']}") String yearMonth
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) {
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RankingScoreProcessor processor = new RankingScoreProcessor("MONTHLY", yearMonth);
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return item -> (MonthlyProductRank) processor.process(item);
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}
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/**
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* Creates an ItemWriter for persisting monthly rankings.
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*
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* @return configured ItemWriter
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*/
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@Bean
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@StepScope
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public ItemWriter<MonthlyProductRank> monthlyRankingWriter() {
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return new MonthlyRankingWriter(monthlyRankRepository);
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}
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}

‎apps/commerce-batch/src/main/java/com/loopers/batch/config/WeeklyRankingJobConfig.java‎

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package com.loopers.batch.config;
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import com.loopers.batch.processor.RankingScoreProcessor;
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import com.loopers.batch.reader.ProductMetricsAggregateReader;
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import com.loopers.batch.writer.WeeklyRankingWriter;
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import com.loopers.domain.dto.ProductRankingAggregation;
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import com.loopers.domain.rank.WeeklyProductRank;
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import com.loopers.domain.rank.WeeklyRankRepository;
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import jakarta.persistence.EntityManager;
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import lombok.RequiredArgsConstructor;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.batch.core.Job;
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import org.springframework.batch.core.Step;
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import org.springframework.batch.core.configuration.annotation.JobScope;
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import org.springframework.batch.core.configuration.annotation.StepScope;
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import org.springframework.batch.core.job.builder.JobBuilder;
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import org.springframework.batch.core.repository.JobRepository;
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import org.springframework.batch.core.step.builder.StepBuilder;
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import org.springframework.batch.item.ItemProcessor;
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import org.springframework.batch.item.ItemReader;
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import org.springframework.batch.item.ItemWriter;
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import org.springframework.beans.factory.annotation.Value;
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import org.springframework.context.annotation.Bean;
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import org.springframework.context.annotation.Configuration;
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import org.springframework.transaction.PlatformTransactionManager;
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/**
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* Configuration class for weekly ranking aggregation batch job.
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*
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* <p>This job aggregates product metrics data on a weekly basis and
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* stores the top N rankings in the materialized view table.
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*
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* <p>Job execution example:
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* <pre>
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* java -jar commerce-batch.jar \
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* --job.name=weeklyRankingJob \
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* yearWeek=2025-W01
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* </pre>
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*
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* <p>Chunk-oriented processing flow:
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* <ol>
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* <li>Reader: Aggregate product_metrics by week</li>
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* <li>Processor: Calculate ranking scores</li>
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* <li>Writer: Save to mv_product_rank_weekly</li>
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* </ol>
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*/
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@Slf4j
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@Configuration
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@RequiredArgsConstructor
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public class WeeklyRankingJobConfig {
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private static final int CHUNK_SIZE = 100;
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private static final int TOP_N = 100;
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private final EntityManager entityManager;
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private final WeeklyRankRepository weeklyRankRepository;
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/**
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* Defines the weekly ranking job.
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*
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* @param jobRepository the Spring Batch job repository
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* @param weeklyRankingStep the step to execute
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* @return configured Job instance
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*/
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@Bean
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public Job weeklyRankingJob(
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JobRepository jobRepository,
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Step weeklyRankingStep
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) {
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return new JobBuilder("weeklyRankingJob", jobRepository)
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.start(weeklyRankingStep)
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.build();
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}
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/**
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* Defines the weekly ranking step with chunk-oriented processing.
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*
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* @param jobRepository the Spring Batch job repository
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* @param transactionManager the transaction manager
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* @param yearWeek the target week in ISO format (injected from job parameters)
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* @return configured Step instance
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*/
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@Bean
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@JobScope
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public Step weeklyRankingStep(
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JobRepository jobRepository,
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PlatformTransactionManager transactionManager,
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@Value("#{jobParameters['yearWeek']}") String yearWeek
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) {
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log.info("Initializing weekly ranking step: yearWeek={}", yearWeek);
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return new StepBuilder("weeklyRankingStep", jobRepository)
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.<ProductRankingAggregation, WeeklyProductRank>chunk(CHUNK_SIZE, transactionManager)
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.reader(weeklyMetricsReader(yearWeek))
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.processor(weeklyRankingProcessor(yearWeek))
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.writer(weeklyRankingWriter())
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.build();
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}
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/**
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* Creates an ItemReader for weekly metrics aggregation.
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*
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* @param yearWeek the target week
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* @return configured ItemReader
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*/
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@Bean
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@StepScope
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public ItemReader<ProductRankingAggregation> weeklyMetricsReader(
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@Value("#{jobParameters['yearWeek']}") String yearWeek
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) {
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return new ProductMetricsAggregateReader(entityManager, yearWeek, "WEEKLY", TOP_N);
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}
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/**
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* Creates an ItemProcessor for ranking score calculation.
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*
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* @param yearWeek the target week
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* @return configured ItemProcessor
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*/
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@Bean
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@StepScope
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public ItemProcessor<ProductRankingAggregation, WeeklyProductRank> weeklyRankingProcessor(
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@Value("#{jobParameters['yearWeek']}") String yearWeek
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) {
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RankingScoreProcessor processor = new RankingScoreProcessor("WEEKLY", yearWeek);
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return item -> (WeeklyProductRank) processor.process(item);
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}
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/**
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* Creates an ItemWriter for persisting weekly rankings.
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*
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* @return configured ItemWriter
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*/
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@Bean
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@StepScope
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public ItemWriter<WeeklyProductRank> weeklyRankingWriter() {
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return new WeeklyRankingWriter(weeklyRankRepository);
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}
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}

‎apps/commerce-batch/src/main/java/com/loopers/batch/processor/RankingScoreProcessor.java‎

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package com.loopers.batch.processor;
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import com.loopers.domain.dto.ProductRankingAggregation;
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import com.loopers.domain.rank.MonthlyProductRank;
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import com.loopers.domain.rank.WeeklyProductRank;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.batch.item.ItemProcessor;
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/**
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* ItemProcessor for converting aggregated metrics into ranking entities.
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*
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* <p>This processor transforms ProductRankingAggregation DTOs into either
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* WeeklyProductRank or MonthlyProductRank entities based on the period type.
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* The ranking score is calculated using weighted metrics.
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*
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* <p>Score calculation formula:
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* <pre>
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* score = (viewCount * WEIGHT_VIEW) +
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* (likeCount * WEIGHT_LIKE) +
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* (orderCount * WEIGHT_ORDER * log10(salesAmount + 1))
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* </pre>
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*
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* where:
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* <ul>
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* <li>WEIGHT_VIEW = 0.1</li>
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* <li>WEIGHT_LIKE = 0.2</li>
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* <li>WEIGHT_ORDER = 0.6</li>
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* </ul>
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*/
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@Slf4j
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public class RankingScoreProcessor implements ItemProcessor<ProductRankingAggregation, Object> {
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private static final double WEIGHT_VIEW = 0.1;
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private static final double WEIGHT_LIKE = 0.2;
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private static final double WEIGHT_ORDER = 0.6;
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private final String periodType;
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private final String period;
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/**
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* Constructs a new RankingScoreProcessor.
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*
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* @param periodType the type of period ("WEEKLY" or "MONTHLY")
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* @param period the period string (e.g., "2025-W01" or "2025-01")
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*/
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public RankingScoreProcessor(String periodType, String period) {
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this.periodType = periodType;
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this.period = period;
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}
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@Override
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public Object process(ProductRankingAggregation item) {
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double score = calculateScore(item);
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log.debug("Processing ranking: productId={}, rank={}, score={}",
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item.getProductId(), item.getRankPosition(), score);
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if ("WEEKLY".equals(periodType)) {
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return WeeklyProductRank.builder()
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.productId(item.getProductId())
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.yearWeek(period)
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.rankPosition(item.getRankPosition())
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.totalScore(score)
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.likeCount(item.getLikeCount())
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.viewCount(item.getViewCount())
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.orderCount(item.getOrderCount())
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.salesAmount(item.getSalesAmount())
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.build();
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} else {
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return MonthlyProductRank.builder()
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.productId(item.getProductId())
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.yearMonth(period)
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.rankPosition(item.getRankPosition())
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.totalScore(score)
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.likeCount(item.getLikeCount())
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.viewCount(item.getViewCount())
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.orderCount(item.getOrderCount())
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.salesAmount(item.getSalesAmount())
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.build();
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}
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}
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/**
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* Calculates the ranking score based on weighted metrics.
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*
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* <p>Uses logarithmic normalization for sales amount to prevent
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* extreme values from dominating the score.
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*
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* @param agg the aggregated metrics
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* @return the calculated score
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*/
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private double calculateScore(ProductRankingAggregation agg) {
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double salesAmountValue = agg.getSalesAmount() != null ? agg.getSalesAmount().doubleValue() : 0.0;
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return (agg.getViewCount() * WEIGHT_VIEW) +
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(agg.getLikeCount() * WEIGHT_LIKE) +
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(agg.getOrderCount() * WEIGHT_ORDER * Math.log10(salesAmountValue + 1));
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}
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}

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