I'm using sqlite as temporary storage to calculate statistic about moderately large data set.
I'm wondering what will happen if my database exceed 2GB on 32 bit system. (I can't currently change the system to 64 bit)
Does it use memory mapped files and break if size of file exceed addressable memory? (like mongodb)
According sqlite documentation, maximum size of database file is ~140 terabytes and is practically limited by os/file system.
You can read more here (note the Pages section): http://www.sqlite.org/fileformat2.html
Though this is an old question, but let me share my findings for people who reach this question.
Although Sqlite documentation states that maximum size of database file is ~140 terabytes but your OS imposes it's own restrictions on maximum file size for any type of file.
For e.g. if you are using FAT32 disk on Windows, maximum file size that I could achieve for sqLite was 2GB.
(According to Microsoft site, limit on FAT 32 system is 4GB but still my sqlite db size was restricted to 2GB).
While on Linux , I was able to reach 3 GB (where I stopped. it could have reached more size)
Find out your file system type of the partition. Remember that the file size limit its not dependent with the OS 32-bit or 64-bit, but with partition type of your hard disk.
See Wikipedia
Related
The InnoDB uses buffer bool of configurable size to store last recently used pages (b+tree blocks).
Why not mmap the entire file instead? Yes, this does not work for changed pages, because you want to store them in double write buffer before writing back to destination place. But mmap lets kernel manage the LRU for pages and avoids userspace copying. Also inkernel-copy code does not use vector instructions (to avoid storing their registers in the process context).
But when page is not changed, why not use mmap to read pages and let kernel manage caching them in filesystem ram cache? So you need "custom" userspace cache for changed pages only.
LMDB author mentioned that he chosen the mmap approach to avoid data copying from filysystem cache to userspace and to avoid LRU reinvention.
What critical disadvantages of mmap i missing that lead to buffer pool approach?
Disadvantages of MMAP:
Not all operating systems support it (ahem Windows)
Coarse locking. It's difficult to allow many clients to make concurrent access to the file.
Relying on the OS to buffer I/O writes leads to increased risk of data loss if the RDBMS engine crashes. Need to use a journaling filesystem, which may not be supported on all operating systems.
Can only map a file size up to the size of the virtual memory address space, so on 32-bit OS, the database files are limited to 4GB (per comment from Roger Lipscombe above).
Early versions of MongoDB tried to use MMAP in the primary storage engine (the only storage engine in the earliest MongoDB). Since then, they have introduced other storage engines, notably WiredTiger. This has greater support for tuning, better performance on multicore systems, support for encryption and compression, multi-document transactions, and so on.
I am not able to find maria DB recommended RAM,disk,number of Core capacity. We are setting up initial level and very minimum data volume. So just i need maria DB recommended capacity.
Appreciate your help!!!
Seeing that over the last few years Micro-Service architecture is rapidly increasing, and each Micro-Service usually needs its own database, I think this type of question is actually becoming more appropriate.
I was looking for this answer seeing that we were exploring the possibility to create small databases on many servers, and was wondering for interest sake what the minimum requirements for a Maria/MySQL DB would be...
Anyway I got this helpful answer from here that I thought I could also share here if someone else was looking into it...
When starting up, it (the database) allocates all the RAM it needs. By default, it
will use around 400MB of RAM, which isn’t noticible with a database
server with 64GB of RAM, but it is quite significant for a small
virtual machine. If you add in the default InnoDB buffer pool setting
of 128MB, you’re well over your 512MB RAM allotment and that doesn’t
include anything from the operating system.
1 CPU core is more than enough for most MySQL/MariaDB installations.
512MB of RAM is tight, but probably adequate if only MariaDB is running. But you would need to aggressively shrink various settings in my.cnf. Even 1GB is tiny.
1GB of disk is more than enough for the code and minimal data (I think).
Please experiment and report back.
There are minor differences in requirements between Operating system, and between versions of MariaDB.
Turn off most of the Performance_schema. If all the flags are turned on, lots of RAM is consumed.
20 years ago I had MySQL running on my personal 256MB (RAM) Windows box. I suspect today's MariaDB might be too big to work on such tiny machine. Today, the OS is the biggest occupant of any basic machine's disk. If you have only a few MB of data, then disk is not an issue.
Look at it this way -- What is the smallest smartphone you can get? A few GB of RAM and a few GB of "storage". If you cut either of those numbers in half, the phone probably cannot work, even before you add apps.
MariaDB or MySQL both actually use very less memory. About 50 MB to 150 MB is the range I found in some of my servers. These servers are running a few databases, having a handful of tables each and limited user load. MySQL documentation claims in needs 2 GB. That is very confusing to me. I understand why MariaDB does not specify any minimum requirements. If they say 50 MB there are going to be a lot of folks who will want to disagree. If they say 1 GB then they are unnecessarily inflating the minimum requirements. Come to think of it, more memory means better cache and performance. However, a well designed database can do disk reads every time without any performance issues. My apache installs (on the same server) consistently use up more memory (about double) than the database.
Why do the sizes of the Oracle Database block and the Operating System Block differ? I have searched the Oracle website but haven't found a satisfactory answer.
The database block is a logical unit of storage, and the operating system block is a physical unit of storage. They don't have to be different sizes, but they can be, as long as the logical block size is equal to or larger than, and a multiple of, the physical block size. This allows Oracle to retrieve an optimal amount of data regardless of the underlying hardware, so it can be more efficient and has less overhead.
From the database concepts guide:
Data Blocks and Operating System Blocks
At the physical level, database data is stored in disk files made up
of operating system blocks. An operating system block is the minimum
unit of data that the operating system can read or write. In contrast,
an Oracle block is a logical storage structure whose size and
structure are not known to the operating system.
...
The database requests data in multiples of data blocks, not operating
system blocks.
When the database requests a data block, the operating system
translates this operation into a requests for data in permanent
storage. The logical separation of data blocks from operating system
blocks has the following implications:
Applications do not need to determine the physical addresses of data on disk.
Database data can be striped or mirrored on multiple physical disks.
The administration guide also says this:
If the database block size is different from the operating system
block size, then ensure that the database block size is a multiple of
the operating system block size.
...
A larger data block size provides greater efficiency in disk and
memory I/O (access and storage of data). Therefore, consider
specifying a block size larger than your operating system block size
if the following conditions exist:
Oracle Database is on a large computer system with a large amount of memory and fast disk drives. For example, databases controlled by
mainframe computers with vast hardware resources typically use a data
block size of 4K or greater.
The operating system that runs Oracle Database uses a small operating system block size. For example, if the operating system
block size is 1K and the default data block size matches this, the
database may be performing an excessive amount of disk I/O during
normal operation. For best performance in this case, a database block
should consist of multiple operating system blocks.
I will try to explain my problem. There are 365 (global map)files in two directories dir1 and dir2, which have the same format ,byte,extend,etc. I computed the bias between two datasets using the function and code given below as follows:
How can I solve this problem?please
I suspect this is due to memory limitations on a 32-bit system. You want to allocate an array of 933M doubles, that requires 7.6Gb of continuous memory. I suggest you to read ?Memory and ?"Memory-limits" for more details. In particular, the latter says:
Error messages beginning ‘cannot allocate vector of size’ indicate
a failure to obtain memory, either because the size exceeded the
address-space limit for a process or, more likely, because the
system was unable to provide the memory. Note that on a 32-bit
build there may well be enough free memory available, but not a
large enough contiguous block of address space into which to map
it.
If this is indeed your problem, you may look into bigmemory package (http://cran.r-project.org/web/packages/bigmemory/index.html) which allows to manage massive matrixes with shared and file-based memory. There are also other strategies (e.g. using an SQLite database) to manage data that doesn't fit in memory all at once.
Update. Here is an excerpt from Memory-limit for Windows:
The address-space limit is 2Gb under 32-bit Windows unless the OS's default has been changed to allow more (up to 3Gb). See http://www.microsoft.com/whdc/system/platform/server/PAE/PAEmem.mspx and http://msdn.microsoft.com/en-us/library/bb613473(VS.85).aspx. Under most 64-bit versions of Windows the limit for a 32-bit build of R is 4Gb: for the oldest ones it is 2Gb. The limit for a 64-bit build of R (imposed by the OS) is 8Tb.
It is not normally possible to allocate as much as 2Gb to a single vector in a 32-bit build of R even on 64-bit Windows because of preallocations by Windows in the middle of the address space.
Under Windows, R imposes limits on the total memory allocation available to a single session as the OS provides no way to do so: see memory.size and memory.limit.
Before starting application, I just would like to know the feasibility here.
I have data around 15GB (text and some Images) stored in SQLite database of my SD Card, I need to access it from my application. Data will get increased on daily basis and may reach till 64 GB.
Can any one tell me limitations in accessing such huge database stored in SD card from the application?
SQLite itself supports databases in that range like 16-32GB (it may start working slower, but it should still work).
However, you are likely to hit a limit of FAT32 maximum file size, which is just 4GB - and this will be tough to overcome. SQLite allows to use attached databases which allow you to split it into smaller chunks, but this is really cumbersome.
If you can format your SD card as ext4, or use internal storage as ext4, then you should not really have big problems.