PostgreSQL的磁盘空间占用问题
我知道通过vacuum可以把一个表的内容整理一下，使磁盘空间的占用变小，但pgsql能不能自动利用表中的空闲空间呢？例如我做了这么一个测试：
在一个表里insert十万条记录，记下它占用的磁盘空间，比如说是1000K,再删除其中的５万条记录，接着再往里插５万条记录，这时这个表的磁盘空间不是接近于先前看到的１０00K，而是变成了１５00K，怎么会是这样呢？删掉的那５万条记录仍然会一直占着空间，等到我来做vacuum吗？
PostgreSQL的磁盘空间占用问题
那我建议你去用oracle,sql server ,sybase也做这样的操作．你看看他们增大不？？？
你以为是方本文件啊．删了在加上．大小还一样．．
里有要日志，rollback段，．．．．．．
PostgreSQL的磁盘空间占用问题
班长兄弟请别发火 :) 这个问题我是真感到比较困惑，所以来这里请教解决方法的。oracle下我做过试验的，我当然没有指望哪个数据库能在一个固定大小的文件里无限制地放数据，这个是最起码的常识了。这个问题我后来自已找到答案了，还是要用vacuum来搞定，与max_fsm_pages这个配置的大小有关，看来这个问题太菜了，所以我也不在这里贴了 :em10:
PostgreSQL的磁盘空间占用问题
哈哈。我以前用SQL SERVER 就发现在天天长大，长啊长啊。。我都没办法。最后得装：）PostgreSQL的磁盘空间占用问题
你可详细介绍一下max_fsm_pages
你的这次操作经验给大家：）
PostgreSQL的磁盘空间占用问题
响应班长号召 :em11:在很久很久以前。。。。。在一篇名为<<Tuning PostgreSQL for performance>;>;的文章，其中有这么一段：
max_fsm_pages:
PostgreSQL records free space in each of its data pages. This information is useful for vacuum to find out how many and which pages to look for when it frees up the space.
If you have a database that does lots of updates and deletes, that is going to generate dead tuples, due to PostgreSQL's MVCC system. The space occupied by dead tuples can be freed with vacuum, unless there is more wasted space than is covered by the Free Space Map, in which case the much less convenient "vacuum full" is required. By expanding the FSM to cover all of those dead tuples, you might never again need to run vacuum full except on holidays.
The best way to set max _fsm_pages is interactive; First, figure out the vacuum (regular) frequency of your database based on write activity; next, run the database under normal production load, and run "vacuum verbose analyze" instead of vacuum, saving the output to a file; finally, calculate the maximum total number of pages reclaimed between vacuums based on the output, and use that.
Remember, this is a database cluster wide setting. So bump it up enough to cover all databases in your database cluster. Also, each FSM page uses 6 bytes of RAM for administrative overhead, so increasing FSM substantially on systems low on RAM may be counter-productive.
大意是说，postgresql.conf中的这个参数（max_fsm_pages）用于告诉PostgreSQL申请多大的内存空间用于保存数据文件的free space信息，按我的简单理解，如果在一个表中删除了一些记录，PostgreSQL会把这一改动记录在"Free Space Map"中，下次如果再往表里插记录时，根据Free Space Map中的信息，就能利用以前删记录而腾出来的磁盘空间。不过Free Space Map是存在于内存中，大小毕竟是有限的，对于大量数据的删除＋插入，要么指定一个较大的max_fsm_pages,要么及时进行vacuum以整理表中的碎片，否则，PostgreSQL只有把新插入的记录添加到文件的末尾，造成文件越来越大。我的一个程序就是意外地因为磁盘空间满了而中止的，它每次要往一个表里插500多万条记录，这之前先要delete同样条数的一批记录，可最后还是占满了整个硬盘。
我觉得PostgreSQL的这种工作方式有它的一个好处，就是如果内存足够大，可以指定一个很大的Free Space Map，对于OLTP型的应用，可能会大幅提高性能（猜测，没有验证过），另外用户可以自已选择在合适的时候进行vacuum或vacuum full，如果你确信一个表只会往里插记录（如记录操作日志），对这个表就可以永远不进行vacuum full，是不是很灵活？
不过，使用vacuum full大量移动数据毕竟是件很耗时的工作，在此期间数据库性能会严重下降，大概这就是“灵活”的代价了。在这方面，Oracle的Block->;Extent->;Segment这种复杂的机制可能更有效一些吧。据说PostgreSQL将引入表空间的概念了，值得期待啊！
至于Free Space Map设多大，上面的文章教了个办法，照着做就行了，只是需要弄明白，这毕竟是一个“Map”，如果打算删掉300M的记录，Free Space Map并不需要申请300M喔 :D
PostgreSQL的磁盘空间占用问题
Tuning PostgreSQL for performanceShridhar Daithankar, Josh Berkus
July 3, 2003 Copyright 2003 Shridhar Daithankar and Josh Berkus.
Authorized for re-distribution only under the PostgreSQL license (see www.postgresql.org/license).
Table of Contents
1 Introduction
2 Some basic parameters
2.1 Shared buffers
2.2 Sort memory
2.3 Effective Cache Size
2.4 Fsync and the WAL files
3 Some less known parameters
3.1 random_ page_cost
3.2 Vacuum_ mem
3.3 max_fsm_pages
3.4 maxfsm_ relations
3.5 wal_buffers
4 Other tips
4.1 Check your file system
4.2 Try the Auto Vacuum daemon
4.3 Try FreeBSD
5 The CONF Setting Guide
1 Introduction
This is a quick start guide for tuning PostgreSQL's settings for performance. This assumes minimal familiarity with PostgreSQL administration. In particular, one should know,
How to start and stop the postmaster service
How to tune OS parameters
How to test the changes
It also assumes that you have gone through the PostgreSQL administration manual before starting, and to have set up your PostgreSQL server with at least the default configuration.
There are two important things for any performance optimization:
Decide what level of performance you want
If you don't know your expected level of performance, you will end up chasing a carrot always couple of meters ahead of you. The performance tuning measures give diminishing returns after a certain threshold. If you don't set this threshold beforehand, you will end up spending lot of time for minuscule gains.
Know your load
This document focuses entirely tuning postgresql.conf best for your existing setup. This is not the end of performance tuning. After using this document to extract the maximum reasonable performance from your hardware, you should start optimizing your application for efficient data access, which is beyond the scope of this article.
Please also note that the tuning advices described here are hints. You should not implement them all blindly. Tune one parameter at a time and test its impact and decide whether or not you need more tuning. Testing and benchmarking is an integral part of database tuning.
Tuning the software settings explored in this article is only about one-third of database performance tuning, but it's a good start since you can experiment with some basic setting changes in an afternoon, whereas some other aspects of tuning can be very time-consuming. The other two-thirds of database application tuning are:
Hardware Selection and Setup
Databases are very bound to your system's I/O (disk) access and memory usage. As such, selection and configuration of disks, RAID arrays, RAM, operating system, and competition for these resources will have a profound effect on how fast your database is. We hope to have a later article covering this topic.
Efficient Application Design
Your application also needs to be designed to access data efficiently, though careful query writing, planned and tested indexing, good connection management, and avoiding performance pitfalls particular to your version of PostgreSQL. Expect another guide someday helping with this, but really it takes several large books and years of experience to get it right ... or just a lot of time on the mailing lists.
2 Some basic parameters
2.1 Shared buffers
Shared buffers defines a block of memory that PostgreSQL will use to hold requests that are awaiting attention from the kernel buffer and CPU. The default value is quite low for any real world workload and need to be beefed up. However, unlike databases like Oracle, more is not always better. There is a threshold above which increasing this value can hurt performance.
This is the area of memory PostgreSQL actually uses to perform work. It should be sufficient enough to handle load on database server. Otherwise PostgreSQL will start pushing data to file and it will hurt the performance overall. Hence this is the most important setting one needs to tune up.
This value should be set based on the dataset size which the database server is supposed to handle at peak loads and on your available RAM (keep in mind that RAM used by other applications on the server is not available). We recommend following rule of thumb for this parameter:
Start at 4MB (512) for a workstation
Medium size data set and 256-512MB available RAM: 16-32MB (2048-4096)
Large dataset and lots of available RAM (1-4GB): 64-256MB (8192-32768)
PLEASE NOTE. PostgreSQL counts a lot on the OS to cache data files and hence does not bother with duplicating its file caching effort. The shared buffers parameter assumes that OS is going to cache a lot of files and hence it is generally very low compared with system RAM. Even for a dataset in excess of 20GB, a setting of 128MB may be too much, if you have only 1GB RAM and an aggressive-at-caching OS like Linux.
There is one way to decide what is best for you. Set a high value of this parameter and run the database for typical usage. Watch usage of shared memory using ipcs or similar tools. A recommended figure would be between 1.2 to 2 times peak shared memory usage.
2.2 Sort memory
This parameter sets maximum limit on memory that a database connection can use to perform sorts. If your queries have order-by or group-by clauses that require sorting large data set, increasing this parameter would help. But beware: this parameter is per sort, per connection. Think twice before setting this parameter too high on any database with many users. A recommended approach is to set this parameter per connection as and when required; that is, low for most simple queries and higher for large, complex queries and data dumps.
2.3 Effective Cache Size
This parameter allows PostgreSQL to make best possible use of RAM available on your server. It tells PostgreSQL the size of OS data cache. So that PostgreSQL can draw different execution plan based on that data.
Say there is 1.5GB RAM in your machine, shared buffers are set to 32MB and effective cache size is set to 800MB. So if a query needs 700MB of data set, PostgreSQL would estimate that all the data required should be available in memory and would opt for more aggressive plan in terms of optimization, involving heavier index usage and merge joins. But if effective cache is set to only 200MB, the query planner is liable to opt for the more I/O efficient sequential scan.
While setting this parameter size, leave room for other applications running on the server machine. The objective is to set this value at the highest amount of RAM which will be available to PostgreSQL all the time.
2.4 Fsync and the WAL files
This parameters sets whether or not write data to disk as soon as it is committed, which is done through Write Ahead Logging (WAL). If you trust your hardware, your power company, and your battery power supply enough, you set this to No for an immediate boost to data write speed. But be very aware that any unexpected database shutdown will force you to restore the database from your last backup.
If that's not an option for you, you can still have the protection of WAL and better performance. Simply move your WAL files, using either a mount or a symlink to the pg_xlog directory, to a separate disk or array from your main database files. In high-write-activity databases, WAL should have its own disk or array to ensure continuous high-speed access. Very large RAID arrays and SAN/NAS devices frequently handle this for you through their internal management systems.
3 Some less known parameters
3.1 random_page_cost
This parameter sets the cost to fetch a random tuple from the database, which influences the planner's choice of index vs. table scan. This is set to a high value as the default default based on the expectation of slow disk access. If you have reasonably fast disks like SCSI or RAID, you can lower the cost to 2. You need to experiment to find out what works best for your setup by running a variety of queries and comparing execution times.
3.2 Vacuum_mem
This parameter sets the memory allocated to Vacuum. Normally, vacuum is a disk intensive process, but raising this parameter will speed it up by allowing PostgreSQL to copy larger blocks into memory. Just don't set it so high it takes significant memory away from normal database operation. Things between 16-32MB should be good enough for most setups.
3.3 max_fsm_pages
PostgreSQL records free space in each of its data pages. This information is useful for vacuum to find out how many and which pages to look for when it frees up the space.
If you have a database that does lots of updates and deletes, that is going to generate dead tuples, due to PostgreSQL's MVCC system. The space occupied by dead tuples can be freed with vacuum, unless there is more wasted space than is covered by the Free Space Map, in which case the much less convenient "vacuum full" is required. By expanding the FSM to cover all of those dead tuples, you might never again need to run vacuum full except on holidays.
The best way to set max _ fsm _ pages is interactive; First, figure out the vacuum (regular) frequency of your database based on write activity; next, run the database under normal production load, and run "vacuum verbose analyze" instead of vacuum, saving the output to a file; finally, calculate the maximum total number of pages reclaimed between vacuums based on the output, and use that.
Remember, this is a database cluster wide setting. So bump it up enough to cover all databases in your database cluster. Also, each FSM page uses 6 bytes of RAM for administrative overhead, so increasing FSM substantially on systems low on RAM may be counter-productive.
3.4 max _ fsm _ relations
This setting dictates how many number of relations (tables) will be tracked in free space map. Again this is a database cluster-wide setting, so set it accordingly. In version 7.3.3 and later, this parameter should be set correctly as a default. In older versions, bump it up to 300-1000.
3.5 wal_buffers
This setting decides the number of buffers WAL(Write ahead Log) can have. If your database has many write transactions, setting this value bit higher than default could result better usage of disk space. Experiment and decide. A good start would be around 32-64 corresponding to 256-512K memory.
4 Other tips
4.1 Check your file system
On OS like Linux, which offers multiple file systems, one should be careful about choosing the right one from a performance point of view. There is no agreement between PostgreSQL users about which one is best.
Contrary to popular belief, today's journaling file systems are not necessarily slower compared to non-journaling ones. Ext2 can be faster on some setups but the recovery issues generally make its use prohibitive. Different people have reported widely different experiences with the speed of Ext3, ReiserFS, and XFS; quite possibly this kind of benchmark depends on a combination of file system, disk/array configuration, OS version, and database table size and distribution. As such, you may be better off sticking with the file system best supported by your distribution, such as ReiserFS for SuSE Linux or Ext3 for Red Hat Linux, not to forget XFS known for it's large file support . Of course, if you have time to run comprehensive benchmarks, we would be interested in seeing the results!
As an easy performance boost with no downside, make sure the file system on which your database is kept is mounted "noatime", which turns off the access time bookkeeping.
4.2 Try the Auto Vacuum daemon
There is a little known module in PostgreSQL contrib directory called as pgavd. It works in conjunction with statistics collector. It periodically connects to a database and checks if it has done enough operations since the last check. If yes, it will vacuum the database.
Essentially it will vacuum the database when it needs it. It would get rid of playing with cron settings for vacuum frequency. It should result in better database performance by eliminating overdue vacuum issues.
4.3 Try FreeBSD
Large updates, deletes, and vacuum in PostgreSQL are very disk intensive processes. In particular, since vacuum gobbles up IO bandwidth, the rest of the database activities could be affected adversely when vacuuming very large tables.
OS's from the BSD family, such as FreeBSD, dynamically alter the IO priority of a process. So if you lower the priority of a vacuum process, it should not chew as much bandwidth and will better allow the database to perform normally. Of course this means that vacuum could take longer, which would be problematic for a "vacuum full."
If you are not done with your choice of OS for your server platform, consider BSD for this reason.
5 The CONF Setting Guide
Available here is an Annotated Guide to the PostgreSQL configuration file settings, in both OpenOffice.org and PDF format. This guide expands on the official documentation and may eventually be incorporated into it.
The first column of the chart is the GUC setting in the postgresql.conf file.
The second is the maximum range of the variable; note that the maximum range is often much larger than the practical range. For example, random_page_cost will accept any number between 0 and several billion, but all practical numbers are between 1 and 5.
The third column contains an enumeration of RAM or disk space used by each unit of the parameter.
The fourth column indicates whether or not the variable may be SET from the PSQL terminal during an interactive setting. Most settings marked as "no" may only be changed by restarting PostgreSQL.
The fifth column quotes the official documentation available from the PostgreSQL web site.
The last column is our notes on the setting, how to set it, resources it uses, etc. You'll notice some blank spaces, and should be warned as well that there is still strong disagreement on the value of many settings.
Users of PostgreSQL 7.3 and earlier will notice that the order of the parameters in this guide do not match the order of the parameters in your postgresql.conf file. This is because this document was generated as part of an effort to re-organize the conf parameters and documentation; starting with 7.4, this document, the official documentation, and the postgresql.conf file are all in the same logical order.
As noted in the worksheet, it covers PostgreSQL versions 7.3 and 7.4. If you are using an earlier version, you will not have access to all of these settings, and defaults and effects of some settings will be different.
PostgreSQL的磁盘空间占用问题
加个trigger做vacuum如何?PostgreSQL的磁盘空间占用问题
受教了! :shock:PostgreSQL的磁盘空间占用问题
pg占空间就是大，没办法！
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