If the sorted data cannot fit entirely into the sort heap, which is a block of memory that is allocated each time a sort is performed, it overflows into a temporary table owned by the database.
如果无法将排序的数据整个放入排序堆中(排序堆是每次执行排序时分配的一块内存)，它就会溢出到该数据库所有的临时表中。
In this case, there is only one suspect and the fact that this data structure can account for 84 percent of the total heap size of the primary dump identifies this as a very likely suspect.
在本例中，仅有一个可疑点，此数据结构占主要转储全部堆大小84%，从这一点可以看出该数据结构非常可疑。
After selecting a data structure in the Suspects TAB, you can visit the Browse TAB to see the chain of object references holding the leak container in the heap, as shown in Figure 4.
在Suspects选项卡中选择数据结构后，您可以访问Browse选项卡，查看保留堆中泄漏容器的对象引用链，如图4所示。
To gather more data, you can produce a system dump instead of a heap dump on an OutOfMemoryError exception.
为了收集更多的数据，您可以在OutOf MemoryError异常上生成一个系统转储文件，而非堆转储文件。
Larger objects mean a bigger heap to hold the same amount of data while maintaining similar GC performance, which makes the OS and hardware memory system slower.
更大的对象意味着用更大的堆来保存相同大小的数据，同时维持类似的gc性能，这会拖慢操作系统和硬件内存系统。
In a copying collector, another form of tracing collector, the heap is divided into two equally sized semi-spaces, one of which contains active data and the other is unused.
在另一种形式的跟踪收集器——复制收集器中，堆被分成两个大小相等的半空间，其中一个包含活跃的数据，另一个未使用。
The HAT tool produces statistics for data types that have large number of instances in a single dump and can also compare two heap dumps to identify data types which have increased in number.
HAT工具会对在单个转储中具有大量实例的数据类型生成统计信息，并且还可以比较两个堆转储，以标识在数量上增加的数据类型。
Volume of data: the heap in each JVM sets a finite limit to the amount each server instance can hold, so the more data there is, the more servers you need to hold it all.
数据量：每个J VM中的堆都设定了每个服务器实例可以容纳的有限数量限制，因此，数据越多，就会需要更多的服务器容纳这些数据。
This is a good fit for large-scale server applications which often have large amounts of live heap data and considerable thread-level parallelism.
这对于经常产生大量存活堆数据和线程级别数据的大规模服务器端应用来说是非常棒的。
Later, when the amount of live data grows and the heap needs to be expanded, the JVM can commit a little more, adjacent to the currently committed area.
以后活动数据数量增加，堆需要扩展，JVM可以再提交多一点内存，这些内存与当前提交的部分相邻。
In the event that the amount of live data grows and the JVM needs to expand the heap beyond 4mb, it commits a bit more of the reserved area.
如果活动数据的数量增加，J VM需要将堆的大小扩展到4MB之外，它就会提交稍微多一点的保留区域。
In addition, a single JVM is not sufficient for caching large amounts of data (for example, a 32 bit JVM can only guarantee a maximum of 2 GB of usable heap space).
此外，单个JVM无法缓存大量数据(比如，32位JVM只能提供2GB的可用堆空间)。
An example of such a session bean might be one that provides an interface to a rules engine that caches its rule base (which may be hundreds of megabytes of data) in the heap.
这种会话bean的一个例子是向在堆中缓存其规则基础(可能有几百兆数据)的规则引擎提供接口的会话bean。
These types of memory leaks manifest as fast growing memory leaks, where if the verbose GC data reports a sharp drop in free heap space in a very short time leads to an OutOfMemoryError.
这些类型的内存泄漏表现为内存泄漏快速增长，其中，如果详细的垃圾收集数据显示在很短的时间内可用堆空间急剧减少，则会导致Out Of MemoryError错误。
Listing 1 does not validate user-supplied data when copying it to the buffer member of the previously allocated struct mystruct using the strcpy function, resulting in a heap-based buffer overflow.
在使用strcpy函数将用户提供的数据复制到先前分配的struct mystruct的buffer成员中时，清单1不验证用户提供的数据，造成堆中缓冲区溢出。
Defines the steps and calculations needed to estimate the amount of space required to store the data in a heap.
定义估计用于存储堆中的数据的空间量所需的步骤和计算。
Fibonacci heap is a heap of time with good flat data structure. I am using C language to implement Fibonacci heap.
说明：斐波那契堆是一种具有较好平摊时间的堆数据结构。我使用C语言来实现斐波那契堆。
The structure of the row locator depends on whether the data pages are stored in a heap or a clustered table.
行定位器的结构取决于数据页是存储在堆中还是聚集表中。
The metadata portion of the file contains a series of table and heap data structures.
文件的元数据部分包含一系列的表和堆数据结构。
The metadata portion of the file contains a series of table and heap data structures.
文件的元数据部分包含一系列的表和堆数据结构。
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