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The more files you have in your Dropbox folder, the more memory Dropbox will need to keep track of them. It's normal for there to be multiple Dropbox processes running at the same time. They may be helping the main desktop app or other Dropbox features.
They also look for version updates and monitor for system crashes. Please check each of the following:.
Increase your system's virtual memory for large file compares
The desktop app may cause high CPU usage if there are a large number of files to sync. This is especially true the first time files on your computer have been synced. Some third-party apps access files in your Dropbox folder.
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Dropbox may interpret this access as edits to the files, and sync these perceived changes. If a third-party app continually requests access to your files, Dropbox will continue to sync, which will in turn lead to high CPU usage. This loop usually occurs with third-party syncing apps, backup apps, and anti-virus or security software, or when a third-party app is installed within the Dropbox folder. The excess is stored on hard disk and copied to RAM as required. Virtual memory is usually much larger than physical memory, making it possible to run programs for which the total code plus data size is greater than the amount of RAM available.
This is known as " demand paged virtual memory".
Mnemonic: Memory Management for Big Data
A page is copied from disk to RAM "paged in" when an attempt is made to access it and it is not already present. This paging is performed automatically by collaboration between the CPU , the memory management unit MMU , and the operating system kernel. The program is unaware of virtual memory, it just sees a large address space , only part of which corresponds to physical memory at any instant. The virtual address space is divided into pages.
Since each Page Tables entry contains the virtual-to-physical translation of all memory pages being used by the process, for a very large System Global Area SGA , the Page Tables entry can be very large for each process. As you can see, that is a huge number of pages to manage. Again, the Page Tables entries are used by the operating system to manage the memory used by the processes in the system.
In Linux, the OS process that does this management is called kswapd and can be seen by operating system tools.
viptarif.ru/wp-content/whatsapp/2327.php The typical TLB cache holds between 4 and 4, entries. With millions or billions of Page Tables entries, this cache is insufficient. This can be a significant overhead on the system.
I have personally seen Page Tables entries in the gigabytes. In Linux operating systems, HugePages is a kernel feature that allows the OS to support the large page size capabilities of modern hardware architectures. For Oracle Database, enabling HugePages and using the large page size reduces the operating system maintenance of page states and increases the TLB cache hit ratio by managing more memory with a single page table entry for a large page, rather than with many entries for a smaller page.
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In Linux, the large page size is 2 MB. In the example shown in Listing 1, the number of virtual-to-physical translations for a single record will be reduced to 4, from 2,, This will reduce the size of the Page Tables structure, improve the TLB cache hit ratio, and reduce kswapd usage.
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In Linux, the HugePages capability is configured by setting the Linux initialization parameter vm. Setting this parameter can reduce the number of pages by making them larger. The performance improvement that is provided by HugePages outweighs the ease of use provided by automatic memory management. The details on implementing the HugePages configuration can be found in the My Oracle Support documents shown in Table 1.
In addition to configuring vm.
This parameter is set to 0 by default, thus allowing all groups permissions to use HugePages. This parameter can be set to an OS group that the Oracle Database process is part of, such as oinstall. You can verify that large pages are enabled for your database instance by checking the alert log.