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cache - cache utitur 2

2024-07-12

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1. Cache naufragii, penetratio, avalanche

1. Cache penetratio

Refertur ad interrogationem datam quae non debet existere. Cum cella non feritur, datorum interrogatio erit, sed datorum tale testimonium non habet in omni petitione huius notitiae non-existentium. Debes ire ad tabulatum repositionis ad interrogationem, quae significationem caching amittit.

periculum;

Usura non-existentia data ad impetus perficiendos augebit pressionem momentaneam in datorum et tandem ad ruinam ducendam.

solvere;

Nullum exitum conditivo conditivo ac brevi temporis spatio additur.

2. Cache NIVIS

Cache avalanche: Cache NIVIS CAELI significat quod cum latibulum statuimus, Clavis idem exspirationis tempus adoptat, ut cella certo momento irrita fiant, omnes petitiones ad DB et DB sub instanti pressione et avalanches transmittuntur.

Solutio: valorem temere addere ad tempus originalis exspirationis, sicut passim 1-5 minuta, ita ut repetitio uniuscuiusque temporis exspirationis conditivorum reducatur, difficilis effectus causare collectivum defectum.

3. Cache naufragii

Cache naufragii:

  • Aliquae claves cum exspiratione temporis statuto, si hae claves ad certas punctos tempore ipso concurrentes accedere possunt, notitia valde "calidum" est.
  • Si hoc hotspot clavem exspirat antequam numerus petitionum simul ingrediatur, omnes notitiae huius clavis in db cadent, quae naufragii cache dicuntur.

solvere;

cincinno

Magna vis concursus unum tantum ad reprimendum permittit, et alii exspectant. Sera dimissa est, et alii seram adipiscuntur, latibulum ante obverto, et notitia sine itu db futura erit.

2. solve quaestionem

Solve cache penetratio et NIVIS primum

  1.   private static final String CATALOG_JSON="CATALOG_JSON";
  2.     @Override
  3.     public Map<String, List<Catelog2Vo>> getCatalogJson() {
  4.  
  5.         /**
  6.          * 空结果缓存:解决缓存穿透
  7.          * 设置过期时间(加随机值) 缓存雪崩
  8.          * 加锁 解决缓存击穿
  9.          */
  10.         Object result = redisTemplate.opsForValue().get(CATALOG_JSON);
  11.         if(result!=null){
  12.             return (Map<String, List<Catelog2Vo>>) result;
  13.         }
  14.  
  15.         Map<String, List<Catelog2Vo>> map = getCatalogJsonFromDB();
  16.         if (map==null){
  17.             /**
  18.              * 解决缓存穿透
  19.              */
  20.             map=new HashMap<>();
  21.         }
  22.         redisTemplate.opsForValue().set(CATALOG_JSON,map, Duration.ofDays(1));
  23.         return map;
  24.     }

Solve cache naufragii

1. usus loci cincinno ut solve

Objectum verboot continens in modo per defaltam singleton est, ut idem obiectum synchronum et claudatur.

  1.  public synchronized Map<String, List<Catelog2Vo>> getCatalogJsonFromDB() {
  2.  
  3.         Object result = redisTemplate.opsForValue().get(CATALOG_JSON);
  4.         if (result != null) {
  5.             return (Map<String, List<Catelog2Vo>>) result;
  6.         }
  7.  
  8.  
  9.         //1.查出所有1级分类
  10.         List<CategoryEntity> selectList = baseMapper.selectList(null);
  11.         /**
  12.          * 将数据库的多次查询变成一次
  13.          */
  14.  
  15.         //2. 封装数据
  16.         List<CategoryEntity> level1Category = selectList.stream().filter(s -> s.getParentCid().equals(0L)).collect(Collectors.toList());
  17.         Map<String, List<Catelog2Vo>> map = level1Category.stream().collect(Collectors.toMap(k -> k.getCatId().toString(), v -> {
  18.             //1.每一个的一级分类,查到1级分类的所有二级分类
  19.             List<CategoryEntity> categoryEntities = selectList.stream().filter(s -> s.getParentCid().equals(v.getCatId())).collect(Collectors.toList());
  20.  
  21.             List<Catelog2Vo> catelog2VoList = categoryEntities.stream().map(c -> {
  22.                 Catelog2Vo catelog2Vo = new Catelog2Vo();
  23.                 catelog2Vo.setId(c.getCatId().toString());
  24.                 catelog2Vo.setName(c.getName());
  25.                 catelog2Vo.setCatalog1Id(v.getCatId().toString());
  26.  
  27.                 List<CategoryEntity> categoryEntities1 = selectList.stream().filter(s -> s.getParentCid().equals(c.getCatId())).collect(Collectors.toList());
  28.                 List<Catelog2Vo.Catelog3Vo> collect = categoryEntities1.stream().map(c3 -> {
  29.                     Catelog2Vo.Catelog3Vo catelog3Vo = new Catelog2Vo.Catelog3Vo();
  30.                     catelog3Vo.setId(c3.getCatId().toString());
  31.                     catelog3Vo.setName(c3.getName());
  32.                     catelog3Vo.setCatalog2Id(c.getCatId().toString());
  33.                     return catelog3Vo;
  34.                 }).collect(Collectors.toList());
  35.  
  36.                 catelog2Vo.setCatalog3List(collect);
  37.  
  38.                 return catelog2Vo;
  39.             }).collect(Collectors.toList());
  40.  
  41.  
  42.             return catelog2VoList;
  43.         }));
  44.         return map;
  45.     }
  1.  public Map<String, List<Catelog2Vo>> getCatalogJson() {
  2.  
  3.         /**
  4.          * 空结果缓存:解决缓存穿透
  5.          * 设置过期时间(加随机值) 缓存雪崩
  6.          * 加锁 解决缓存击穿
  7.          */
  8.         Object result = redisTemplate.opsForValue().get(CATALOG_JSON);
  9.         if (result != null) {
  10.             return (Map<String, List<Catelog2Vo>>) result;
  11.         }
  12.  
  13.         Map<String, List<Catelog2Vo>> map = getCatalogJsonFromDB();
  14.         if (map == null) {
  15.             /**
  16.              * 解决缓存穿透
  17.              */
  18.             map = new HashMap<>();
  19.         }
  20.         redisTemplate.opsForValue().set(CATALOG_JSON, map, Duration.ofDays(1));
  21.         return map;
  22.     }

Adhuc problemata erunt cum logica codicis suprascripti. Cum simul currit, primum filum reprimendo datorum perficiet et seram dimittet antequam in cella ponatur et nulla data est, et iterum database reprehendo

Recta aditus

  1.   public synchronized Map<String, List<Catelog2Vo>> getCatalogJsonFromDB() {
  2.  
  3.         Object result = redisTemplate.opsForValue().get(CATALOG_JSON);
  4.         if (result != null) {
  5.             return (Map<String, List<Catelog2Vo>>) result;
  6.         }
  7.  
  8.  
  9.         //1.查出所有1级分类
  10.         List<CategoryEntity> selectList = baseMapper.selectList(null);
  11.         /**
  12.          * 将数据库的多次查询变成一次
  13.          */
  14.  
  15.         //2. 封装数据
  16.         List<CategoryEntity> level1Category = selectList.stream().filter(s -> s.getParentCid().equals(0L)).collect(Collectors.toList());
  17.         Map<String, List<Catelog2Vo>> map = level1Category.stream().collect(Collectors.toMap(k -> k.getCatId().toString(), v -> {
  18.             //1.每一个的一级分类,查到1级分类的所有二级分类
  19.             List<CategoryEntity> categoryEntities = selectList.stream().filter(s -> s.getParentCid().equals(v.getCatId())).collect(Collectors.toList());
  20.  
  21.             List<Catelog2Vo> catelog2VoList = categoryEntities.stream().map(c -> {
  22.                 Catelog2Vo catelog2Vo = new Catelog2Vo();
  23.                 catelog2Vo.setId(c.getCatId().toString());
  24.                 catelog2Vo.setName(c.getName());
  25.                 catelog2Vo.setCatalog1Id(v.getCatId().toString());
  26.  
  27.                 List<CategoryEntity> categoryEntities1 = selectList.stream().filter(s -> s.getParentCid().equals(c.getCatId())).collect(Collectors.toList());
  28.                 List<Catelog2Vo.Catelog3Vo> collect = categoryEntities1.stream().map(c3 -> {
  29.                     Catelog2Vo.Catelog3Vo catelog3Vo = new Catelog2Vo.Catelog3Vo();
  30.                     catelog3Vo.setId(c3.getCatId().toString());
  31.                     catelog3Vo.setName(c3.getName());
  32.                     catelog3Vo.setCatalog2Id(c.getCatId().toString());
  33.                     return catelog3Vo;
  34.                 }).collect(Collectors.toList());
  35.  
  36.                 catelog2Vo.setCatalog3List(collect);
  37.  
  38.                 return catelog2Vo;
  39.             }).collect(Collectors.toList());
  40.  
  41.  
  42.             return catelog2VoList;
  43.         }));
  44.         if (map == null) {
  45.             /**
  46.              * 解决缓存穿透
  47.              */
  48.             map = new HashMap<>();
  49.         }
  50.         redisTemplate.opsForValue().set(CATALOG_JSON, map, Duration.ofDays(1));
  51.         return map;
  52.     }

Operatio salutaris in cella in synchronisation code scandalum pone

  1.  @Override
  2.     public Map<String, List<Catelog2Vo>> getCatalogJson() {
  3.  
  4.         /**
  5.          * 空结果缓存:解决缓存穿透
  6.          * 设置过期时间(加随机值) 缓存雪崩
  7.          * 加锁 解决缓存击穿
  8.          */
  9.         Object result = redisTemplate.opsForValue().get(CATALOG_JSON);
  10.         if (result != null) {
  11.             return (Map<String, List<Catelog2Vo>>) result;
  12.         }
  13.  
  14.         Map<String, List<Catelog2Vo>> map = getCatalogJsonFromDB();
  15.  
  16.         return map;
  17.     }

 

 

Loci crines solum currentem cohibere possunt processum, ideo comas distributas oportet

3. Problemata cum cincinnis localibus in ambitus distributis

Hoc est, quodlibet cincinnum solum processum hodiernam claudere potest, id est, quodlibet servitium datorum reprehendo.

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