I'm trying to understand the apc.shm_strings_buffer setting in apc.ini. After restarting PHP, the pie chart in the APC admin shows 8MB of cache is already used, even though there are no cached entries (except for apc.php, of course). I've found this relates to the apc.shm_strings_buffer setting.
Can someone help me understand what the setting means? The config file notes that this is the "shared memory size reserved for strings, with M/G suffixe", but I fail to comprehend.
I'm using APC with PHP-FPM.
The easy part to explain is "with M/G suffixe" which means that if you set it to 8M, then 8 megabytes would be allocated, or 1G would allocated 1 gigabyte of memory.
The more difficult bit to explain is that it's a cache for storing strings that are used internally by APC when it's compiling and caching opcode.
The config value was introduced in this change and the bulk of the change was to add apc_string.c to the APC project. The main function that is defined in that C file is apc_new_interned_string which is then used in apc_string_pmemcpy in apc_compile.c. the rest of the APC module to store strings.
For example in apc_compile.c
/* private members are stored inside property_info as a mangled
* string of the form:
* \0<classname>\0<membername>\0
*/
CHECK((dst->name = apc_string_pmemcpy((char *)src->name, src->name_length+1, pool TSRMLS_CC)));
When APC goes to store a string, the function apc_new_interned_string looks to see if it that string is already saved in memory by doing a hash on the string, and if it is already stored in memory, it returns the previous instance of the stored string.
Only if that string is not already stored in the cache does a new piece of memory get allocated to store the string.
If you're running PHP with PHP-FPM, I'm 90% confident that the cache of stored strings is shared amongst all the workers in a single pool, but am still double-checking that.
The whole size allocated to storing shared strings is allocated when PHP starts up - it's not allocated dynamically. So it's to be expected that APC shows the 8MB used for the string cache, even though hardly any strings have actually been cached yet.
Edit
Although this answers what it does, I have no idea how to see how much of the shared string buffer is being used, so there's no way of knowing what it should be set to.
Related
Older, now deprecated, macOS file system APIs provided flags to read a file unbuffered.
I seek a modern way to accomplish the same, so that I can read a file's data into memory without it being cached needlessly somewhere else in memory (such as the volume cache).
Reading with fread and first calling setvbuf (fp, NULL, _IONBF, 0) is not having the desired effect in my tests, for example. I am seeking other low-level functions that let me read into a prepared memory buffer and that let me avoid buffering of the whole data.
Background
I am writing a file search program. It reads large amounts of file content (many GBs) that isn't and won't be used by the user otherwise. It would be a waste to have all this data cached in the volume cache as it'll soon get purged by further reads again, anyway. It'll also likely lead to purging file data that's actually in use by the user or system, causing more cache misses.
Therefore, I should be able to tell the system that I do not need the file data cached. The little caching needed for cluster boundaries is not an issue. It's the many large chunks that I read briefly into memory to search it that is not needed to be cached.
Two suggestions:
Use the read() system call instead of stdio.
Disable data caching with the F_NOCACHE option for fcntl().
In Swift that would be something like (error checking omitted for brevity):
import Foundation
let path = "/path/to/file"
let fd = open(path, O_RDONLY)
fcntl(fd, F_NOCACHE, 1)
var buffer = Data(count: 1024 * 1024)
buffer.withUnsafeMutableBytes { ptr in
let amount = read(fd, ptr.baseAddress, ptr.count)
}
close(fd)
If I understand it correctly, I'm supposed to create an empty VkPipelineCache object, pass it into vkCreateGraphicsPipelinesand data will be written into it. I can then reuse it with other pipelines I'm creating or save it to a file and use it on the next run.
I've tried following the LunarG example to extra the info:
uint32_t headerLength = pData[0];
uint32_t cacheHeaderVersion = pData[1];
uint32_t vendorID = pData[2];
uint32_t deviceID = pData[3];
But I always get headerLength is 32 and the rest 0. Looking at the spec (https://vulkan.lunarg.com/doc/view/1.0.26.0/linux/vkspec.chunked/ch09s06.html Table 9.1), the cacheHeaderVersion should always be 1, as the only available cache header version is VK_PIPELINE_CACHE_HEADER_VERSION_ONE = 1.
Also the size of pData is usually only 32 bytes, even when I create 10 pipelines with it. What am I doing wrong?
A Vulkan pipeline cache is an opaque object that's only meaningful to the driver. There are very few operations that you're supposed to use on it.
Creating a pipeline cache, optionally with a block of opaque binary data that was saved from an earlier run
Getting the opaque binary data from an existing pipeline cache, typically to serialize to disk before exiting your application
Destroying a pipeline cache as part of the proper shutdown process.
The idea is that the driver can use the cache to speed up creation of pipelines within your program, and also to speed up pipeline creation on subsequent runs of your application.
You should not be attempting to interpret the cache data returned from vkGetPipelineCacheData at all. The only purpose for that data is to be passed into a later call to vkCreatePipelineCache.
Also the size of pData is usually only 32 bytes, even when I create 10 pipelines with it. What am I doing wrong?
Drivers must implement vkCreatePipelineCache, vkGetPipelineCacheData, etc. But they don't actually have to support caching. So if you're working with a driver that doesn't have anything it can cache, or hasn't done the work to support caching, then you'd naturally get back an empty cache (other than the header).
I'm using Gemfire v7.0.1.3 on Linux. Below is my cache xml.
<?xml version.....>
<!DOCTYPE....>
<cache is-server="true">
<disk-store name="myStore" auto-compact="false" max-oplog-size="1000" queue-size="10000" time-interval="150">
<disk-dirs>
<disk-dir>.....</disk-dir>
</disk-dirs>
</disk-store>
<region name="myRegion" refid="PARTITION_PARSISTENT_OVERFLOW">
<region-attributes disk-store-name="myStore" disk-synchronous="true">
<eviction-attributes>
<lru-entry-count maximum="500" action="overflow-to-disk" />
</eviction-attributes>
</region-attributes>
</region>
</cache>
Now I start cache server allocating 8GB. When I'm using String as cache key and a custom object (each object has 4 double arrays, each of 10000 size) as value, I can store 500 millions objects in the cache without any issue. I can see the disk store directory having .crf, .krf, .drf files. If I restart the cache, the elements are getting restored, all good stuff. But, if I use the custom object as key and value, I start getting low memory exception after creating 25000 (approx) entries in region. Is it expected behavior? Because Gemfire documentation says when we use persistence and overflow together, all the keys and least recently used values are overflowed to disk and most active entry values are kept in memory. So, I was expecting that, I can store any number of objects in the region as long as I have space available in my disk store. But I'm getting low memory exception. Please help me understand.
Thanks
Keys are never overflown to disk, so your memory must be large enough to accommodate all keys. For a persistent region, the keys are also written to disk, but that is only for recovery purpose. So, this behavior is expected if the size of your object keys much larger than the size of your string keys.
Recently, I am testing the proper usage of ext4 filesystem. what is my expert is that:
when system crashed, the data had been write return ok can not loss, but metadate can.
Here is my usage:
1. call fallocate to alloc centain space
fallocate(fd, 0, 0, 4*1024*1024); //4MB
2. call fsync(fd) let data and metadata write to disks
3. then i call function to randomly write the file with 4k size(random data but not 0). with O_DRICT flagļ¼but not call fsync. I log the offset with return write ok.
4. check the offset that logged. but i find in some offset, read 4k data, is 0. It seems mean that offset isn't used like hole files.
My question is that:
<1. why after calling fallocate and fsync the metadata of the file still seems
indicate some blocks is not used, so when read it return null. It is my understand .
<2. have other api to call, can make sure that in allocate space with file is not holes ,after that when write data return ok with O_DIRECT can make sure the data will not be loss even the system crashed.
Thanks.
Only writing to the file space can eliminate the hole. Without writing, there is no dirty page and fsync simply does nothing.
I am wondering how did you execute you step 4. It seems that you did it by a manual crash, did you? If you read it after write without a crash, it should not be zero, provided you wrote non-zeros. If you read it after a crash, zero can happen if disk cache existed. However, this kind of zero is not like holes, they are zeros read from the disk (very probably the disk contains zeros).
Recently I'm into creating checksums for files in go. My code is working with small and big files. I tried two methods, the first uses ioutil.ReadFile("filename") and the second is working with os.Open("filename").
Examples:
The first function is working with the io/ioutil and works for small files. When I try to copy a big file my ram gets blastet and for a 1.5GB iso it uses 3GB of ram.
func byteCopy(fileToCopy string) {
file, err := ioutil.ReadFile(fileToCopy) //1.5GB file
omg(err) //error handling function
ioutil.WriteFile("2.iso", file, 0777)
os.Remove("2.iso")
}
Even worse when I want to create a checksum with crypto/sha512 and io/ioutil.
It will never finish and abort because it runs out of memory.
func ioutilHash() {
file, _ := ioutil.ReadFile(iso)
h := sha512.New()
fmt.Printf("%x", h.Sum(file))
}
When using the function below everything works fine.
func ioHash() {
f, err := os.Open(iso) //iso is a big ~ 1.5tb file
omg(err) //error handling function
defer f.Close()
h := sha512.New()
io.Copy(h, f)
fmt.Printf("%x", h.Sum(nil))
}
My Question:
Why is the ioutil.ReadFile() function not working right? The 1.5GB file should not fill my 16GB of ram. I don't know where to look right now.
Could somebody explain the differences between the methods? I don't get it with reading the go-doc and examples.
Having usable code is nice, but understanding why its working is way above that.
Thanks in advance!
The following code doesn't do what you think it does.
func ioutilHash() {
file, _ := ioutil.ReadFile(iso)
h := sha512.New()
fmt.Printf("%x", h.Sum(file))
}
This first reads your 1.5GB iso. As jnml pointed out, it continuously makes bigger and bigger buffers to fill it. In the end, And total buffer size is no less than 1.5GB and no greater than 1.875GB (by the current implementation).
However, after that you then make another buffer! h.Sum(file) doesn't hash file. It appends the current hash to file! This may or may not cause yet another allocation.
The real problem is that you are taking that file, now appended with the hash, and printing it with %x. Fmt actually pre-computes using the same type of method jnml pointed out that ioutil.ReadAll used. So it constantly allocated bigger and bigger buffers to store the hex of your file. Since each letter is 4 bits, that means we are talking about no less than a 3GB buffer for that and no greater than 3.75GB.
This means your active buffers may be as big 5.625GB. Combine that with the GC not being perfect and not removing all the intermediate buffers, and it could very easily fill your space.
The correct way to write that code would have been.
func ioutilHash() {
file, _ := ioutil.ReadFile(iso)
h := sha512.New()
h.Write(file)
fmt.Printf("%x", h.Sum(nil))
}
This doesn't do nearly the number the allocations.
The bottom line is that ReadFile is rarely what you want to use. IO streaming (using readers and writers) is always the best way when it is an option. Not only do you allocate much less when you use io.Copy, you also hash and read the disk concurrently. In your ReadFile example, the two resources are used synchronously when they don't depend on each other.
ioutil.ReadFile is working right. It's your fault to abuse the system resources by using that function for things you know are huge.
ioutil.ReadFile is a handy helper for files you're pretty sure in advance that they're going to be small. Like configuration files, most source code files etc. (Actually it's optimizing things for files <= 1e9 bytes, but that's an implementation detail and not part of the API contract. Your 1.5GB file forces it to use slice growing and thus allocating more than one big buffer for your data in the process of reading the file.)
Even your other approach using os.File is not okay. You definitely should be using the "bufio" package for sequential processing of large files, see bufio.NewReader.