task-45: ASIN 去重与无效品牌查询统一为批量集合查询
新增 CollectDataBatchQuery 把 dedupe 表查询与 invalid_asin 表查询 合并为两次批量集合查询，输出与旧两段式语义等价，并返回两类过滤计数 由 service 维护 stats。8 个测试覆盖默认/批量/幂等/空输入/单元素/ 超限/非法参数/依赖失败，全量回归 712 通过。
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package com.nanri.aiimage.modules.collectdata.util;
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import com.nanri.aiimage.modules.collectdata.model.vo.CollectDataResultRowVo;
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import com.nanri.aiimage.modules.dedupe.mapper.DedupeTotalDataMapper;
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import com.nanri.aiimage.modules.invalidasin.mapper.InvalidAsinDataMapper;
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import com.nanri.aiimage.modules.invalidasin.model.entity.InvalidAsinDataEntity;
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import org.junit.jupiter.api.BeforeEach;
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import org.junit.jupiter.api.Test;
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import java.util.ArrayList;
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import java.util.List;
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import static org.junit.jupiter.api.Assertions.assertEquals;
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import static org.junit.jupiter.api.Assertions.assertTrue;
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import static org.mockito.ArgumentMatchers.anyList;
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import static org.mockito.ArgumentMatchers.any;
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import static org.mockito.Mockito.mock;
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import static org.mockito.Mockito.never;
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import static org.mockito.Mockito.times;
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import static org.mockito.Mockito.verify;
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import static org.mockito.Mockito.when;
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/**
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* Task 45：将 ASIN 去重查询与无效品牌查询统一为批量集合查询。
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* CollectDataBatchQuery 对输入行集合一次性批量查询去重表与无效品牌表，
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* 输出与原有两段式逐行语义完全等价（区分 dedupe 与 invalid 两类过滤），
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* 空输入/单元素/超限集合行为确定，依赖失败可恢复且不创建无效资源。
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*/
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class CollectDataBatchQueryTest {
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private DedupeTotalDataMapper dedupeMapper;
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private InvalidAsinDataMapper invalidAsinMapper;
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private CollectDataBatchQuery query;
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@BeforeEach
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void setUp() {
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dedupeMapper = mock(DedupeTotalDataMapper.class);
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invalidAsinMapper = mock(InvalidAsinDataMapper.class);
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query = new CollectDataBatchQuery(dedupeMapper, invalidAsinMapper);
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}
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@Test
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void test_task_045_asin_brand_normal_default_path() {
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// 正常输入：去重表已存在的 ASIN 被过滤，无效品牌表中的品牌被过滤，其余保留。
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when(dedupeMapper.selectExistingDataValues(anyList()))
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.thenReturn(List.of("B000000001"));
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when(invalidAsinMapper.selectList(any())).thenReturn(List.of(entity("Zara")));
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List<CollectDataResultRowVo> out = query.filterByExistingAsin(List.of(
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row("B000000001", "Nike"),
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row("B000000002", "Zara"),
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row("B000000003", "H&M")
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));
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assertEquals(1, out.size(), "仅未命中行保留");
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assertEquals("B000000003", out.get(0).getAsin(), "保留行 ASIN 正确");
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assertEquals("H&M", out.get(0).getBrand(), "保留行品牌正确");
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}
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@Test
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void test_task_045_asin_brand_normal_multiple_items() {
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// 批量场景：前 300 行 ASIN 唯一、品牌干净；后 300 行品牌无效。
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// 去重表命中前 100 个 ASIN，输出顺序稳定、过滤数量精确。
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List<CollectDataResultRowVo> rows = new ArrayList<>();
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for (int i = 0; i < 300; i++) {
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rows.add(row("D" + String.format("%09d", i + 1), "clean"));
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}
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for (int i = 0; i < 300; i++) {
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rows.add(row("B" + String.format("%09d", i + 1), "bad"));
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}
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List<String> existing = new ArrayList<>();
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for (int i = 0; i < 100; i++) {
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existing.add("D" + String.format("%09d", i + 1));
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}
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when(dedupeMapper.selectExistingDataValues(anyList())).thenReturn(existing);
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when(invalidAsinMapper.selectList(any())).thenReturn(List.of(entity("bad")));
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List<CollectDataResultRowVo> out = query.filterByExistingAsin(rows);
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assertEquals(200, out.size(), "100 行去重 + 300 行无效品牌 = 过滤 400 行");
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assertEquals("D000000101", out.get(0).getAsin(), "输出首行保持输入顺序");
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assertEquals("D000000300", out.get(200 - 1).getAsin(), "输出末行为第 300 行");
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assertTrue(out.stream().allMatch(r -> r.getBrand().equals("clean")),
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"输出全部为干净品牌行");
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}
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@Test
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void test_task_045_asin_brand_normal_repeated_operation_is_idempotent() {
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// 幂等：同一输入重复执行输出一致，两次都发批量查询。
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when(dedupeMapper.selectExistingDataValues(anyList()))
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.thenReturn(List.of("B000000001"));
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when(invalidAsinMapper.selectList(any())).thenReturn(List.of(entity("bad")));
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List<CollectDataResultRowVo> rows = List.of(
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row("B000000001", "bad"),
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row("B000000002", "good")
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);
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List<CollectDataResultRowVo> first = query.filterByExistingAsin(rows);
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List<CollectDataResultRowVo> second = query.filterByExistingAsin(rows);
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assertEquals(first, second, "重复执行输出一致");
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assertEquals(1, first.size());
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verify(dedupeMapper, times(2)).selectExistingDataValues(anyList());
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verify(invalidAsinMapper, times(2)).selectList(any());
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}
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@Test
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void test_task_045_asin_brand_boundary_empty_input() {
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// 空输入：空列表/无 ASIN 无品牌的行集合不触发数据库查询，安全跳过。
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List<CollectDataResultRowVo> empty = query.filterByExistingAsin(List.of());
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assertEquals(0, empty.size(), "空列表返回空");
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List<CollectDataResultRowVo> blankRows = query.filterByExistingAsin(List.of(
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row("", ""), row(null, null)
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));
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assertEquals(2, blankRows.size(), "无 ASIN 无品牌行不触发查询且全保留");
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verify(dedupeMapper, never()).selectExistingDataValues(anyList());
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verify(invalidAsinMapper, never()).selectList(any());
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}
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@Test
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void test_task_045_asin_brand_boundary_single_item() {
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// 单元素：单行命中/未命中均正确，不依赖批量路径。
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when(dedupeMapper.selectExistingDataValues(anyList())).thenReturn(List.of());
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when(invalidAsinMapper.selectList(any())).thenReturn(List.of());
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List<CollectDataResultRowVo> out = query.filterByExistingAsin(List.of(
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row("B000000001", "solo")
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));
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assertEquals(1, out.size(), "单行未命中保留");
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assertEquals("solo", out.get(0).getBrand());
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when(dedupeMapper.selectExistingDataValues(anyList())).thenReturn(List.of("B000000001"));
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List<CollectDataResultRowVo> hit = query.filterByExistingAsin(List.of(
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row("B000000001", "solo")
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));
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assertEquals(0, hit.size(), "单行命中去重表被过滤");
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}
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@Test
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void test_task_045_asin_brand_boundary_limit_and_overflow() {
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// 上限/超限：超大输入集合批量查询一次完成，不产生逐行查询（无无界增长）。
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List<CollectDataResultRowVo> rows = new ArrayList<>();
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for (int i = 0; i < 5000; i++) {
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rows.add(row("B" + String.format("%09d", i), "brand-" + i));
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}
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when(dedupeMapper.selectExistingDataValues(anyList())).thenReturn(List.of());
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when(invalidAsinMapper.selectList(any())).thenReturn(List.of());
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List<CollectDataResultRowVo> out = query.filterByExistingAsin(rows);
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assertEquals(5000, out.size(), "超大集合全量保留");
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verify(dedupeMapper).selectExistingDataValues(anyList());
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verify(invalidAsinMapper).selectList(any());
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}
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@Test
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void test_task_045_asin_brand_invalid_input_rejected() {
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// 非法参数：null 行安全跳过；数据库返回 null 集合安全处理。
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when(dedupeMapper.selectExistingDataValues(anyList())).thenReturn(null);
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when(invalidAsinMapper.selectList(any())).thenReturn(null);
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List<CollectDataResultRowVo> rows = new ArrayList<>();
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rows.add(null);
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rows.add(row("B000000001", " Nike "));
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List<CollectDataResultRowVo> out = query.filterByExistingAsin(rows);
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assertEquals(1, out.size(), "null 行不丢弃");
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assertEquals("B000000001", out.get(0).getAsin(), "正常行保留");
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assertEquals(" Nike ", out.get(0).getBrand(), "品牌保留原始值（过滤时仅标准化用于匹配）");
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}
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@Test
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void test_task_045_asin_brand_dependency_failure_releases_resources() {
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// 依赖失败：去重表查询抛错时异常向上传播；恢复后再次执行成功，不残留状态。
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when(dedupeMapper.selectExistingDataValues(anyList()))
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.thenThrow(new RuntimeException("db down"))
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.thenReturn(List.of("B000000001"));
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when(invalidAsinMapper.selectList(any())).thenReturn(List.of());
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boolean threw = false;
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try {
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query.filterByExistingAsin(List.of(row("B000000001", "nike")));
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} catch (RuntimeException ex) {
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threw = "db down".equals(ex.getMessage());
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}
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assertTrue(threw, "去重查询失败向上抛错");
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List<CollectDataResultRowVo> out = query.filterByExistingAsin(List.of(
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row("B000000001", "nike"), row("B000000002", "adidas")
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));
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assertEquals(1, out.size(), "恢复后过滤正确");
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assertEquals("B000000002", out.get(0).getAsin(), "恢复后命中逻辑仍生效");
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}
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private static CollectDataResultRowVo row(String asin, String brand) {
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CollectDataResultRowVo row = new CollectDataResultRowVo();
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row.setAsin(asin);
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row.setBrand(brand);
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return row;
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}
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private static InvalidAsinDataEntity entity(String brand) {
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InvalidAsinDataEntity entity = new InvalidAsinDataEntity();
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entity.setBrand(brand);
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return entity;
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}
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}
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