Spring + Hibernate: Query Plan Cache Использование памяти

Question

Я программирую приложение с последней версией Spring Boot. Я недавно стал проблемой с растущей кучей, которая не может быть собрана мусором. Анализ кучи с Eclipse MAT показал, что в течение одного часа после запуска приложение кучи выросло до 630 МБ и с помощью SessionFactoryImpl Hibernate, используя более 75% всей кучи.

Is ищет возможные источники вокруг запроса план кэша, но единственным, что я нашел this, но это не разыгрывает. Эти свойства были установлены таким образом:

spring.jpa.properties.hibernate.query.plan_cache_max_soft_references=1024 
spring.jpa.properties.hibernate.query.plan_cache_max_strong_references=64 

запросов к базе данных все полученные с помощью магии запросов весной, используя интерфейсы хранилища, как in this documentation. С этим методом генерируется около 20 различных запросов. Нет других родных SQL или HQL. Образец:

@Transactional 
public interface TrendingTopicRepository extends JpaRepository<TrendingTopic, Integer> { 
    List<TrendingTopic> findByNameAndSource(String name, String source); 
    List<TrendingTopic> findByDateBetween(Date dateStart, Date dateEnd); 
    Long countByDateBetweenAndName(Date dateStart, Date dateEnd, String name); 
} 

или

List<SomeObject> findByNameAndUrlIn(String name, Collection<String> urls); 

, как, например, для использования IN.

Вопрос: Почему кеш-план запроса продолжает расти (он не останавливается, он заканчивается полной кучей) и как предотвратить это? Кто-нибудь сталкивался с подобной проблемой?

Версия:

• Spring загрузка 1.2.5
• Hibernate 4.3.10

Answer 1

Я ударил этот вопрос, а также. В основном это сводится к тому, что переменное количество значений в вашем разделе IN и Hibernate пытается кэшировать эти планы запросов.

Есть две отличные сообщения в блогах по этой теме. The first:

Using Hibernate 4.2 and MySQL in a project with an in-clause query such as: select t from Thing t where t.id in (?)

Hibernate caches these parsed HQL queries. Specifically the Hibernate SessionFactoryImpl has QueryPlanCache with queryPlanCache and parameterMetadataCache . But this proved to be a problem when the number of parameters for the in-clause is large and varies.

These caches grow for every distinct query. So this query with 6000 parameters is not the same as 6001.

The in-clause query is expanded to the number of parameters in the collection. Metadata is included in the query plan for each parameter in the query, including a generated name like x10_, x11_ , etc.

Imagine 4000 different variations in the number of in-clause parameter counts, each of these with an average of 4000 parameters. The query metadata for each parameter quickly adds up in memory, filling up the heap, since it can't be garbage collected.

This continues until all different variations in the query parameter count is cached or the JVM runs out of heap memory and starts throwing java.lang.OutOfMemoryError: Java heap space.

Avoiding in-clauses is an option, as well as using a fixed collection size for the parameter (or at least a smaller size).

For configuring the query plan cache max size, see the property hibernate.query.plan_cache_max_size , defaulting to 2048 (easily too large for queries with many parameters).

И second (также ссылки из первого):

Hibernate internally uses a cache that maps HQL statements (as strings) to query plans . The cache consists of a bounded map limited by default to 2048 elements (configurable). All HQL queries are loaded through this cache. In case of a miss, the entry is automatically added to the cache. This makes it very susceptible to thrashing - a scenario in which we constantly put new entries into the cache without ever reusing them and thus preventing the cache from bringing any performance gains (it even adds some cache management overhead). To make things worse, it is hard to detect this situation by chance - you have to explicitly profile the cache in order to notice that you have a problem there. I will say a few words on how this could be done later on.

So the cache thrashing results from new queries being generated at high rates. This can be caused by a multitude of issues. The two most common that I have seen are - bugs in hibernate which cause parameters to be rendered in the JPQL statement instead of being passed as parameters and the use of an "in" - clause.

Due to some obscure bugs in hibernate, there are situations when parameters are not handled correctly and are rendered into the JPQL query (as an example check out HHH-6280). If you have a query that is affected by such defects and it is executed at high rates, it will thrash your query plan cache because each JPQL query generated is almost unique (containing IDs of your entities for example).

The second issue lays in the way that hibernate processes queries with an "in" clause (e.g. give me all person entities whose company id field is one of 1, 2, 10, 18). For each distinct number of parameters in the "in"-clause, hibernate will produce a different query - e.g. select x from Person x where x.company.id in (:id0_) for 1 parameter, select x from Person x where x.company.id in (:id0_, :id1_) for 2 parameters and so on. All these queries are considered different, as far as the query plan cache is concerned, resulting again in cache thrashing. You could probably work around this issue by writing a utility class to produce only certain number of parameters - e.g. 1, 10, 100, 200, 500, 1000. If you, for example, pass 22 parameters, it will return a list of 100 elements with the 22 parameters included in it and the remaining 78 parameters set to an impossible value (e.g. -1 for IDs used for foreign keys). I agree that this is an ugly hack but could get the job done. As a result you will only have at most 6 unique queries in your cache and thus reduce thrashing.

So how do you find out that you have the issue? You could write some additional code and expose metrics with the number of entries in the cache e.g. over JMX, tune logging and analyze the logs, etc. If you do not want to (or can not) modify the application, you could just dump the heap and run this OQL query against it (e.g. using mat): SELECT l.query.toString() FROM INSTANCEOF org.hibernate.engine.query.spi.QueryPlanCache$HQLQueryPlanKey l . It will output all queries currently located in any query plan cache on your heap. It should be pretty easy to spot whether you are affected by any of the aforementioned problems.

As far as the performance impact goes, it is hard to say as it depends on too many factors. I have seen a very trivial query causing 10-20 ms of overhead spent in creating a new HQL query plan. In general, if there is a cache somewhere, there must be a good reason for that - a miss is probably expensive so your should try to avoid misses as much as possible. Last but not least, your database will have to handle large amounts of unique SQL statements too - causing it to parse them and maybe create different execution plans for every one of them.

Answer 2

У меня была большая проблема с этим queryPlanCache, так что я сделал монитор кэша Hibernate, чтобы увидеть запросы в queryPlanCache , Я использую среду QA как задачу Весны каждые 5 минут. Я нашел с запросами IN, которые мне пришлось изменить, чтобы решить проблему с кешем. Деталь: я использую Hibernate 4.2.18, и я не знаю, будет ли полезно использовать другие версии.

import java.lang.reflect.Field; 
import java.util.ArrayList; 
import java.util.Arrays; 
import java.util.List; 
import java.util.Set; 
import javax.persistence.EntityManager; 
import javax.persistence.PersistenceContext; 
import org.hibernate.ejb.HibernateEntityManagerFactory; 
import org.hibernate.internal.SessionFactoryImpl; 
import org.hibernate.internal.util.collections.BoundedConcurrentHashMap; 
import org.slf4j.Logger; 
import org.slf4j.LoggerFactory; 
import com.dao.GenericDAO; 

public class CacheMonitor { 

private final Logger logger = LoggerFactory.getLogger(getClass()); 

@PersistenceContext(unitName = "MyPU") 
private void setEntityManager(EntityManager entityManager) { 
    HibernateEntityManagerFactory hemf = (HibernateEntityManagerFactory) entityManager.getEntityManagerFactory(); 
    sessionFactory = (SessionFactoryImpl) hemf.getSessionFactory(); 
    fillQueryMaps(); 
} 

private SessionFactoryImpl sessionFactory; 
private BoundedConcurrentHashMap queryPlanCache; 
private BoundedConcurrentHashMap parameterMetadataCache; 

/* 
* I tried to use a MAP and use compare compareToIgnoreCase. 
* But remember this is causing memory leak. Doing this 
* you will explode the memory faster that it already was. 
*/ 

public void log() { 
    if (!logger.isDebugEnabled()) { 
     return; 
    } 

    if (queryPlanCache != null) { 
     long cacheSize = queryPlanCache.size(); 
     logger.debug(String.format("QueryPlanCache size is :%s ", Long.toString(cacheSize))); 

     for (Object key : queryPlanCache.keySet()) { 
      int filterKeysSize = 0; 
      // QueryPlanCache.HQLQueryPlanKey (Inner Class) 
      Object queryValue = getValueByField(key, "query", false); 
      if (queryValue == null) { 
       // NativeSQLQuerySpecification 
       queryValue = getValueByField(key, "queryString"); 
       filterKeysSize = ((Set) getValueByField(key, "querySpaces")).size(); 
       if (queryValue != null) { 
        writeLog(queryValue, filterKeysSize, false); 
       } 
      } else { 
       filterKeysSize = ((Set) getValueByField(key, "filterKeys")).size(); 
       writeLog(queryValue, filterKeysSize, true); 
      } 
     } 
    } 

    if (parameterMetadataCache != null) { 
     long cacheSize = parameterMetadataCache.size(); 
     logger.debug(String.format("ParameterMetadataCache size is :%s ", Long.toString(cacheSize))); 
     for (Object key : parameterMetadataCache.keySet()) { 
      logger.debug("Query:{}", key); 
     } 
    } 
} 

private void writeLog(Object query, Integer size, boolean b) { 
    if (query == null || query.toString().trim().isEmpty()) { 
     return; 
    } 
    StringBuilder builder = new StringBuilder(); 
    builder.append(b == true ? "JPQL " : "NATIVE "); 
    builder.append("filterKeysSize").append(":").append(size); 
    builder.append("\n").append(query).append("\n"); 
    logger.debug(builder.toString()); 
} 

private void fillQueryMaps() { 
    Field queryPlanCacheSessionField = null; 
    Field queryPlanCacheField = null; 
    Field parameterMetadataCacheField = null; 
    try { 
     queryPlanCacheSessionField = searchField(sessionFactory.getClass(), "queryPlanCache"); 
     queryPlanCacheSessionField.setAccessible(true); 
     queryPlanCacheField = searchField(queryPlanCacheSessionField.get(sessionFactory).getClass(), "queryPlanCache"); 
     queryPlanCacheField.setAccessible(true); 
     parameterMetadataCacheField = searchField(queryPlanCacheSessionField.get(sessionFactory).getClass(), "parameterMetadataCache"); 
     parameterMetadataCacheField.setAccessible(true); 
     queryPlanCache = (BoundedConcurrentHashMap) queryPlanCacheField.get(queryPlanCacheSessionField.get(sessionFactory)); 
     parameterMetadataCache = (BoundedConcurrentHashMap) parameterMetadataCacheField.get(queryPlanCacheSessionField.get(sessionFactory)); 
    } catch (Exception e) { 
     logger.error("Failed fillQueryMaps", e); 
    } finally { 
     queryPlanCacheSessionField.setAccessible(false); 
     queryPlanCacheField.setAccessible(false); 
     parameterMetadataCacheField.setAccessible(false); 
    } 
} 

private <T> T getValueByField(Object toBeSearched, String fieldName) { 
    return getValueByField(toBeSearched, fieldName, true); 
} 

@SuppressWarnings("unchecked") 
private <T> T getValueByField(Object toBeSearched, String fieldName, boolean logErro) { 
    Boolean accessible = null; 
    Field f = null; 
    try { 
     f = searchField(toBeSearched.getClass(), fieldName, logErro); 
     accessible = f.isAccessible(); 
     f.setAccessible(true); 
    return (T) f.get(toBeSearched); 
    } catch (Exception e) { 
     if (logErro) { 
      logger.error("Field: {} error trying to get for: {}", fieldName, toBeSearched.getClass().getName()); 
     } 
     return null; 
    } finally { 
     if (accessible != null) { 
      f.setAccessible(accessible); 
     } 
    } 
} 

private Field searchField(Class<?> type, String fieldName) { 
    return searchField(type, fieldName, true); 
} 

private Field searchField(Class<?> type, String fieldName, boolean log) { 

    List<Field> fields = new ArrayList<Field>(); 
    for (Class<?> c = type; c != null; c = c.getSuperclass()) { 
     fields.addAll(Arrays.asList(c.getDeclaredFields())); 
     for (Field f : c.getDeclaredFields()) { 

      if (fieldName.equals(f.getName())) { 
       return f; 
      } 
     } 
    } 
    if (log) { 
     logger.warn("Field: {} not found for type: {}", fieldName, type.getName()); 
    } 
    return null; 
} 
} 

Answer 3

У меня была точно такая же проблема с использованием Spring бутсу 1.5.7 с Spring Data (спящий режим) и следующей конфигурации решена проблема (утечка памяти):

spring: 
    jpa: 
    properties: 
     hibernate: 
     query: 
      plan_cache_max_size: 64 
      plan_parameter_metadata_max_size: 32 

Answer 4

Начиная с Hibernate 5.2.12, вы можете указать свойство конфигурации спящего режима, чтобы изменить то, как литералы должны быть связаны с основным JDBC, подготовленные заявления, используя следующие:

hibernate.criteria.literal_handling_mode=BIND 

Из документации Java, это свойство конфигурации имеет 3 настройки

1. AUTO (по умолчанию)
2. BIND - Увеличивает вероятность кеширования операторов jdbc с использованием параметров привязки.
3. INLINE - Вводит значения, а не использует параметры (будьте осторожны с SQL-инъекцией).