`
liwx2000
  • 浏览: 132224 次
  • 性别: Icon_minigender_1
  • 来自: 杭州
社区版块
存档分类
最新评论

ThreadLocal是否会引起内存溢出?

    博客分类:
  • java
阅读更多
最近碰到一个使用ThreadLocal时因为未调用remove()而险些引起内存溢出的问题,所以看了下ThreadLocal的源码,结合线程池原理做一个简单的分析,确认是否最终会导致内存溢出。

既然是因为没调用remove()方法而险些导致内存溢出,那首先看下remove()方法中做了什么。
 public void remove() {
         ThreadLocalMap m = getMap(Thread.currentThread());
         if (m != null)
             m.remove(this);
     }

从remove()的实现来看就是一个map.remove()的调用。既然不调用map.remove()可能会引起内存溢出的话,就需要看看ThreadLocalMap的实现了。
    /**
     * ThreadLocalMap is a customized hash map suitable only for
     * maintaining thread local values. No operations are exported
     * outside of the ThreadLocal class. The class is package private to
     * allow declaration of fields in class Thread.  To help deal with
     * very large and long-lived usages, the hash table entries use
     * WeakReferences for keys. However, since reference queues are not
     * used, stale entries are guaranteed to be removed only when
     * the table starts running out of space.
     */
    static class ThreadLocalMap {

        /**
         * The entries in this hash map extend WeakReference, using
         * its main ref field as the key (which is always a
         * ThreadLocal object).  Note that null keys (i.e. entry.get()
         * == null) mean that the key is no longer referenced, so the
         * entry can be expunged from table.  Such entries are referred to
         * as "stale entries" in the code that follows.
         */
        static class Entry extends WeakReference<ThreadLocal> {
            /** The value associated with this ThreadLocal. */
            Object value;

            Entry(ThreadLocal k, Object v) {
                super(k);
                value = v;
            }
        }

        /**
         * The initial capacity -- MUST be a power of two.
         */
        private static final int INITIAL_CAPACITY = 16;

        /**
         * The table, resized as necessary.
         * table.length MUST always be a power of two.
         */
        private Entry[] table;

        /**
         * The number of entries in the table.
         */
        private int size = 0;

        /**
         * The next size value at which to resize.
         */
        private int threshold; // Default to 0

        /**
         * Set the resize threshold to maintain at worst a 2/3 load factor.
         */
        private void setThreshold(int len) {
            threshold = len * 2 / 3;
        }

        /**
         * Increment i modulo len.
         */
        private static int nextIndex(int i, int len) {
            return ((i + 1 < len) ? i + 1 : 0);
        }

        /**
         * Decrement i modulo len.
         */
        private static int prevIndex(int i, int len) {
            return ((i - 1 >= 0) ? i - 1 : len - 1);
        }

        /**
         * Construct a new map initially containing (firstKey, firstValue).
         * ThreadLocalMaps are constructed lazily, so we only create
         * one when we have at least one entry to put in it.
         */
        ThreadLocalMap(ThreadLocal firstKey, Object firstValue) {
            table = new Entry[INITIAL_CAPACITY];
            int i = firstKey.threadLocalHashCode & (INITIAL_CAPACITY - 1);
            table[i] = new Entry(firstKey, firstValue);
            size = 1;
            setThreshold(INITIAL_CAPACITY);
        }

        /**
         * Construct a new map including all Inheritable ThreadLocals
         * from given parent map. Called only by createInheritedMap.
         *
         * @param parentMap the map associated with parent thread.
         */
        private ThreadLocalMap(ThreadLocalMap parentMap) {
            Entry[] parentTable = parentMap.table;
            int len = parentTable.length;
            setThreshold(len);
            table = new Entry[len];

            for (int j = 0; j < len; j++) {
                Entry e = parentTable[j];
                if (e != null) {
                    ThreadLocal key = e.get();
                    if (key != null) {
                        Object value = key.childValue(e.value);
                        Entry c = new Entry(key, value);
                        int h = key.threadLocalHashCode & (len - 1);
                        while (table[h] != null)
                            h = nextIndex(h, len);
                        table[h] = c;
                        size++;
                    }
                }
            }
        }

        /**
         * Get the entry associated with key.  This method
         * itself handles only the fast path: a direct hit of existing
         * key. It otherwise relays to getEntryAfterMiss.  This is
         * designed to maximize performance for direct hits, in part
         * by making this method readily inlinable.
         *
         * @param  key the thread local object
         * @return the entry associated with key, or null if no such
         */
        private Entry getEntry(ThreadLocal key) {
            int i = key.threadLocalHashCode & (table.length - 1);
            Entry e = table[i];
            if (e != null && e.get() == key)
                return e;
            else
                return getEntryAfterMiss(key, i, e);
        }

        /**
         * Version of getEntry method for use when key is not found in
         * its direct hash slot.
         *
         * @param  key the thread local object
         * @param  i the table index for key's hash code
         * @param  e the entry at table[i]
         * @return the entry associated with key, or null if no such
         */
        private Entry getEntryAfterMiss(ThreadLocal key, int i, Entry e) {
            Entry[] tab = table;
            int len = tab.length;

            while (e != null) {
                ThreadLocal k = e.get();
                if (k == key)
                    return e;
                if (k == null)
                    expungeStaleEntry(i);
                else
                    i = nextIndex(i, len);
                e = tab[i];
            }
            return null;
        }

        /**
         * Set the value associated with key.
         *
         * @param key the thread local object
         * @param value the value to be set
         */
        private void set(ThreadLocal key, Object value) {

            // We don't use a fast path as with get() because it is at
            // least as common to use set() to create new entries as
            // it is to replace existing ones, in which case, a fast
            // path would fail more often than not.

            Entry[] tab = table;
            int len = tab.length;
            int i = key.threadLocalHashCode & (len-1);

            for (Entry e = tab[i];
		 e != null;
		 e = tab[i = nextIndex(i, len)]) {
                ThreadLocal k = e.get();

                if (k == key) {
                    e.value = value;
                    return;
                }

                if (k == null) {
                    replaceStaleEntry(key, value, i);
                    return;
                }
            }

            tab[i] = new Entry(key, value);
            int sz = ++size;
            if (!cleanSomeSlots(i, sz) && sz >= threshold)
                rehash();
        }

        /**
         * Remove the entry for key.
         */
        private void remove(ThreadLocal key) {
            Entry[] tab = table;
            int len = tab.length;
            int i = key.threadLocalHashCode & (len-1);
            for (Entry e = tab[i];
		 e != null;
		 e = tab[i = nextIndex(i, len)]) {
                if (e.get() == key) {
                    e.clear();
                    expungeStaleEntry(i);
                    return;
                }
            }
        }

        /**
         * Replace a stale entry encountered during a set operation
         * with an entry for the specified key.  The value passed in
         * the value parameter is stored in the entry, whether or not
         * an entry already exists for the specified key.
         *
         * As a side effect, this method expunges all stale entries in the
         * "run" containing the stale entry.  (A run is a sequence of entries
         * between two null slots.)
         *
         * @param  key the key
         * @param  value the value to be associated with key
         * @param  staleSlot index of the first stale entry encountered while
         *         searching for key.
         */
        private void replaceStaleEntry(ThreadLocal key, Object value,
                                       int staleSlot) {
            Entry[] tab = table;
            int len = tab.length;
            Entry e;

            // Back up to check for prior stale entry in current run.
            // We clean out whole runs at a time to avoid continual
            // incremental rehashing due to garbage collector freeing
            // up refs in bunches (i.e., whenever the collector runs).
            int slotToExpunge = staleSlot;
            for (int i = prevIndex(staleSlot, len);
		 (e = tab[i]) != null;
                 i = prevIndex(i, len))
                if (e.get() == null)
                    slotToExpunge = i;

            // Find either the key or trailing null slot of run, whichever
            // occurs first
            for (int i = nextIndex(staleSlot, len);
		 (e = tab[i]) != null;
                 i = nextIndex(i, len)) {
                ThreadLocal k = e.get();

                // If we find key, then we need to swap it
                // with the stale entry to maintain hash table order.
                // The newly stale slot, or any other stale slot
                // encountered above it, can then be sent to expungeStaleEntry
                // to remove or rehash all of the other entries in run.
                if (k == key) {
                    e.value = value;

                    tab[i] = tab[staleSlot];
                    tab[staleSlot] = e;

                    // Start expunge at preceding stale entry if it exists
                    if (slotToExpunge == staleSlot)
                        slotToExpunge = i;
                    cleanSomeSlots(expungeStaleEntry(slotToExpunge), len);
                    return;
                }

                // If we didn't find stale entry on backward scan, the
                // first stale entry seen while scanning for key is the
                // first still present in the run.
                if (k == null && slotToExpunge == staleSlot)
                    slotToExpunge = i;
            }

            // If key not found, put new entry in stale slot
            tab[staleSlot].value = null;   
            tab[staleSlot] = new Entry(key, value);

            // If there are any other stale entries in run, expunge them
            if (slotToExpunge != staleSlot)
                cleanSomeSlots(expungeStaleEntry(slotToExpunge), len);
        }

        /**
         * Expunge a stale entry by rehashing any possibly colliding entries
         * lying between staleSlot and the next null slot.  This also expunges
         * any other stale entries encountered before the trailing null.  See
         * Knuth, Section 6.4
         *
         * @param staleSlot index of slot known to have null key
         * @return the index of the next null slot after staleSlot
         * (all between staleSlot and this slot will have been checked
         * for expunging).
         */
        private int expungeStaleEntry(int staleSlot) {
            Entry[] tab = table;
            int len = tab.length;

            // expunge entry at staleSlot
            tab[staleSlot].value = null;   
            tab[staleSlot] = null;
            size--;

            // Rehash until we encounter null
            Entry e;
            int i;
            for (i = nextIndex(staleSlot, len);
		 (e = tab[i]) != null;
                 i = nextIndex(i, len)) {
                ThreadLocal k = e.get();
                if (k == null) {
                    e.value = null;
                    tab[i] = null;
                    size--;
                } else {
                    int h = k.threadLocalHashCode & (len - 1);
                    if (h != i) {
                        tab[i] = null;

                        // Unlike Knuth 6.4 Algorithm R, we must scan until
                        // null because multiple entries could have been stale.
                        while (tab[h] != null)
                            h = nextIndex(h, len);
                        tab[h] = e;
                    }
                }
            }
            return i;
        }

        /**
         * Heuristically scan some cells looking for stale entries.
         * This is invoked when either a new element is added, or
         * another stale one has been expunged. It performs a
         * logarithmic number of scans, as a balance between no
         * scanning (fast but retains garbage) and a number of scans
         * proportional to number of elements, that would find all
         * garbage but would cause some insertions to take O(n) time.
         *
         * @param i a position known NOT to hold a stale entry. The
         * scan starts at the element after i.
         *
         * @param n scan control: <tt>log2(n)</tt> cells are scanned,
         * unless a stale entry is found, in which case
         * <tt>log2(table.length)-1</tt> additional cells are scanned.
         * When called from insertions, this parameter is the number
         * of elements, but when from replaceStaleEntry, it is the
         * table length. (Note: all this could be changed to be either
         * more or less aggressive by weighting n instead of just
         * using straight log n. But this version is simple, fast, and
         * seems to work well.)
         *
         * @return true if any stale entries have been removed.
         */
        private boolean cleanSomeSlots(int i, int n) {
            boolean removed = false;
            Entry[] tab = table;
            int len = tab.length;
            do {
                i = nextIndex(i, len);
                Entry e = tab[i];
                if (e != null && e.get() == null) {
                    n = len;
                    removed = true;
                    i = expungeStaleEntry(i);
                }
            } while ( (n >>>= 1) != 0);
            return removed;
        }

        /**
         * Re-pack and/or re-size the table. First scan the entire
         * table removing stale entries. If this doesn't sufficiently
         * shrink the size of the table, double the table size.
         */
        private void rehash() {
            expungeStaleEntries();

            // Use lower threshold for doubling to avoid hysteresis
            if (size >= threshold - threshold / 4)
                resize();
        }

        /**
         * Double the capacity of the table.
         */
        private void resize() {
            Entry[] oldTab = table;
            int oldLen = oldTab.length;
            int newLen = oldLen * 2;
            Entry[] newTab = new Entry[newLen];
            int count = 0;

            for (int j = 0; j < oldLen; ++j) {
                Entry e = oldTab[j];
                if (e != null) {
                    ThreadLocal k = e.get();
                    if (k == null) {
                        e.value = null; // Help the GC
                    } else {
                        int h = k.threadLocalHashCode & (newLen - 1);
                        while (newTab[h] != null)
                            h = nextIndex(h, newLen);
                        newTab[h] = e;
                        count++;
                    }
                }
            }

            setThreshold(newLen);
            size = count;
            table = newTab;
        }

        /**
         * Expunge all stale entries in the table.
         */
        private void expungeStaleEntries() {
            Entry[] tab = table;
            int len = tab.length;
            for (int j = 0; j < len; j++) {
                Entry e = tab[j];
                if (e != null && e.get() == null)
                    expungeStaleEntry(j);
            }
        }
    }

首先从声明上来看,ThreadLocalMap并不是一个java.util.Map接口的实现,但是从Entry的实现和整个ThreadLocalMap的实现来看却实现了一个Map的功能,并且从具体的方法的实现上来看,整个ThreadLocalMap实现了一个HashMap的功能,对比HashMap的实现就能看出。

但是,值得注意的是ThreadLocalMap并没有put(K key, V value)方法,而是set(ThreadLocal key, Object value),从这里可以看出,ThreadLocalMap并不是想象那样以Thread为key,而是以ThreadLocal为key。

了解了ThreadLocalMap的实现,也知道ThreadLocal.remove()其实就是ThreadLocalMap.remove(),那么再看看ThreadLocal的set(T value)方法,看看value是如何存储的。
public void set(T value) {
        Thread t = Thread.currentThread();
        ThreadLocalMap map = getMap(t);
        if (map != null)
            map.set(this, value);
        else
            createMap(t, value);
    }

    ThreadLocalMap getMap(Thread t) {
        return t.threadLocals;
    }

    void createMap(Thread t, T firstValue) {
        t.threadLocals = new ThreadLocalMap(this, firstValue);
    }

可以看到,set(T value)方法为每个Thread对象都创建了一个ThreadLocalMap,并且将value放入ThreadLocalMap中,ThreadLocalMap作为Thread对象的成员变量保存。那么可以用下图来表示ThreadLocal在存储value时的关系。



所以当ThreadLocal作为单例时,每个Thread对应的ThreadLocalMap中只会有一个键值对。那么如果不调用remove()会怎么样呢?

假设一种场景,使用线程池,线程池中有200个线程,并且这些线程都不会释放,ThreadLocal做单例使用。那么最多也就会产生200个ThreadLocalMap,而每个ThreadLocalMap中只有一个键值对,那最多也就是200个键值对存在。

但是线程池并不是固定一个线程数不改变,下面贴一段tomcat的线程池配置
<Connector executor="tomcatThreadPool" 
			port="8080" protocol="HTTP/1.1"
			connectionTimeout="60000"
			keepAliveTimeout="30000"
			minProcessors="5"
			maxProcessors="75"
			maxKeepAliveRequests="150"
			redirectPort="8443" URIEncoding="UTF-8" acceptCount="1000" disableUploadTimeout="true"/>

可以看到线程池其实有线程最小值和最大值的,并且有超时时间,所以当线程空闲时间超时后,线程会被销毁。那么当线程销毁时,线程所持有的ThreadLocalMap也会失去引用,并且由于ThreadLocalMap中的Entry是WeakReference,所以当YGC时,被销毁的Thread所对应的value也会被回收掉,所以即使不调用remove()方法,也不会引起内存溢出。
  • 大小: 43.7 KB
分享到:
评论
1 楼 zhuyucheng123 2014-06-11  
对问题的分析很精彩,但是我想问问,像后面配置文件这样解释的话,那么内存是否泄露是不是要依赖与第三方线程池呢?如果第三方线程池刚好没有所谓的“超时时间”的话,就会发生内存泄露了,对吗?

相关推荐

    一次使用Eclipse Memory Analyzer分析Tomcat内存溢出

    假设在生产环境中,一个项目运行三周左右会出现内存溢出异常。JDK 使用的是 64 位版本,配置参数为 `-Xmx3078M -Xms3078M -XX:PermSize=1024M -XX:MaxPermSize=1024M`。通过 MAT 分析发现: - **Histogram** 显示 ...

    ThreadLocal 内存泄露的实例分析1

    在 `LeakingServlet` 的 `doGet` 方法中,如果 `ThreadLocal` 没有设置值,那么会创建一个新的 `MyCounter` 并设置到 `ThreadLocal` 中。关键在于,一旦 `MyCounter` 被设置到 `ThreadLocal`,那么它将与当前线程...

    ThreadLocal中内存泄漏和数据丢失问题的问题浅析及解决方案.docx

    然而,在使用 ThreadLocal 时,可能会出现内存泄漏和数据丢失问题。本文将对 ThreadLocal 中内存泄漏和数据丢失问题进行浅析,并提供解决方案。 ThreadLocal 的特点: 1. 依托于线程的生命周期而存在,贯穿于整个...

    ThreadLocal,你真的了解吗?

    - 弱引用对象会在垃圾回收器扫描时立即回收,无论内存是否充足。 - 示例:`WeakReference sr = new WeakReference(new String("hello"));` - ThreadLocal 内部使用弱引用来管理线程局部变量,当线程退出或者 ...

    ThreadLocal内存泄露分析

    - **谨慎在长生命周期对象中使用ThreadLocal**:避免在会存活很长时间的对象(如单例、全局服务等)中使用ThreadLocal,因为这可能导致线程长时间保持对ThreadLocal的引用,增加内存泄露的风险。 - **合理设计类结构...

    ThreadLocal应用示例及理解

    当线程结束时,与其关联的ThreadLocal变量不会自动清除,可能会导致内存泄漏。因此,推荐在不再使用ThreadLocal时显式调用`remove()`方法。 ```java threadLocal.remove(); ``` ### 示例:线程安全的计数器 假设...

    hashCode内存溢出和内存泄漏的问题解决.docx

    内存管理和优化是编程中至关重要的环节,尤其是在Java这样的高级语言中,由于自动内存管理机制的存在,内存泄漏和溢出问题可能会变得难以察觉但后果严重。本文将深入探讨内存泄漏及其可能导致的内存溢出问题,以及...

    ThreadLocal

    当我们创建一个新的ThreadLocal实例时,它并不会立即分配内存,而是等到线程第一次调用`set`或`get`方法时才会为该线程创建一个副本。这个副本存储在线程的ThreadLocalMap中,这个Map是由Thread类维护的,键是...

    java并发编程面试题分享给需要的同学.docx

    threadLocal会发生内存泄漏吗?谈谈你对threadLocal的理解 为什么会发生内存泄漏? 对threadLocal的理解 并发、并行、串行的区别? 如何查看线程死锁 1. linux服务器 2. MySQL中的思索可以通过语句查询判断,如下 ...

    04、导致JVM内存泄露的ThreadLocal详解-ev

    04、导致JVM内存泄露的ThreadLocal详解_ev04、导致JVM内存泄露的ThreadLocal详解_ev04、导致JVM内存泄露的ThreadLocal详解_ev04、导致JVM内存泄露的ThreadLocal详解_ev04、导致JVM内存泄露的ThreadLocal详解_ev04、...

    使用ThreadLocal管理“session”数据

    通常,这些信息会存储在服务器内存中,并通过session ID与客户端进行通信,每次请求时将session ID通过cookie发送回服务器,以便服务器识别当前请求属于哪个session。 2. **为什么使用ThreadLocal管理Session?** ...

    java中ThreadLocal详解

    尽管使用弱引用来避免内存泄漏,但在某些情况下,仍然可能引起内存泄漏。例如,如果一个`ThreadLocal`实例没有被正确地清理或释放,即使线程已经结束,其`ThreadLocalMap`也不会被垃圾回收。 为了解决这个问题,`...

    ThreadLocal原理及在多层架构中的应用

    - **内存泄漏风险**:如果不正确地使用ThreadLocal,如忘记清理ThreadLocal变量,可能导致内存泄漏。 - **线程隔离性**:ThreadLocal只在创建它的线程内有效,无法跨线程共享数据。 - **难以调试**:由于ThreadLocal...

    2、导致JVM内存泄露的ThreadLocal详解

    1. **线程未正确销毁**:如果线程执行完毕后没有正确销毁或者线程池中线程长期存活,而`ThreadLocal`对象又未能及时清除,那么线程内的`ThreadLocalMap`将会持续占用内存,进而可能导致内存泄漏。 2. **...

    JVM的基础和调优【JMM 内存结构 GC OOM 性能调优 ThreadLocal】

    JVM的基础和调优【JMM 内存结构 GC OOM 性能调优 ThreadLocal】 内存泄露:是指程序在申请内存后,无法释放已申请的内存空间就造成了内存泄露, 一次的内存泄露似乎不会有大的影响,但是内存泄露堆积的后果就是内存...

    ThreadLocal_ThreadLocal源码分析_

    这样,当ThreadLocal对象不再被其他地方引用时,即使其在Map中,也会被垃圾收集器回收,降低了内存泄漏的风险。同时,弱引用的使用也使得Map能够更早地释放不再使用的Entry,提高内存利用率。 **ThreadLocal的生命...

    ThreadLocal原理及内存泄漏原因

    总的来说,ThreadLocal提供了一种方便的方式在多线程环境中管理线程局部变量,但如果不正确使用,可能会导致内存泄漏。因此,理解和妥善处理ThreadLocal的生命周期至关重要,特别是在长生命周期的线程如守护线程...

    ThreadLocal整理.docx

    同时, ThreadLocal 还提供了扩容机制,当数组的 size 大于总长度的 2/3 时,会触发扩容操作,扩容后将原来的数组长度乘以 2倍。 在 ThreadLocal 中,set 方法的逻辑是先获取当前线程的存取副本变量的 map,然后...

Global site tag (gtag.js) - Google Analytics