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Top Forums UNIX for Advanced & Expert Users How to test RAID10 array performance [Debian Wheezy]? Post 302918537 by gull04 on Wednesday 24th of September 2014 03:35:10 AM
Old 09-24-2014
Hi Gacanepa,

You don't really provide enough information about the actual makeup of the disks, what is the actual backend you are using as this can make a significant difference. How are the devices accessed - there are a shedload more questions on this front.

In general and it is a generalisation the RAID10 (striped then mirrored) should provide the better performance (true also for RAID01) than RAID1. But it is not really possible to comment further than that without knowing a bit more information about your setup.

Regards

Dave
 

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PREPARE(7)							   SQL Commands 							PREPARE(7)

NAME
PREPARE - create a prepared query SYNOPSIS
PREPARE plan_name [ (datatype [, ...] ) ] AS query INPUTS plan_name An arbitrary name given to this particular prepared query. It must be unique within a single session, and is used to execute or remove a previously prepared query. datatype The data-type of a parameter to the prepared query. To refer to the parameters in the prepared query itself, use $1, $2, etc. OUTPUTS PREPARE The query has been prepared successfully. DESCRIPTION
PREPARE creates a prepared query. A prepared query is a server-side object that can be used to optimize performance. When the PREPARE statement is executed, the specified query is parsed, rewritten, and planned. When a subsequent EXECUTE statement is issued, the prepared query need only be executed. Thus, the parsing, rewriting, and planning stages are only performed once, instead of every time the query is executed. Prepared queries can take parameters: values that are substituted into the query when it is executed. To specify the parameters to a pre- pared query, include a list of data-types with the PREPARE statement. In the query itself, you can refer to the parameters by position using $1, $2, etc. When executing the query, specify the actual values for these parameters in the EXECUTE statement -- refer to EXECUTE [execute(7)] for more information. Prepared queries are stored locally (in the current backend), and only exist for the duration of the current database session. When the client exits, the prepared query is forgotten, and so it must be re-created before being used again. This also means that a single prepared query cannot be used by multiple simultaneous database clients; however, each client can create their own prepared query to use. Prepared queries have the largest performance advantage when a single backend is being used to execute a large number of similar queries. The performance difference will be particularly significant if the queries are complex to plan or rewrite. For example, if the query involves a join of many tables or requires the application of several rules. If the query is relatively simple to plan and rewrite but rel- atively expensive to execute, the performance advantage of prepared queries will be less noticeable. NOTES In some situations, the query plan produced by PostgreSQL for a prepared query may be inferior to the plan produced if the query were sub- mitted and executed normally. This is because when the query is planned (and the optimizer attempts to determine the optimal query plan), the actual values of any parameters specified in the query are unavailable. PostgreSQL collects statistics on the distribution of data in the table, and can use constant values in a query to make guesses about the likely result of executing the query. Since this data is unavailable when planning prepared queries with parameters, the chosen plan may be sub-optimal. For more information on query planning and the statistics collected by PostgreSQL for query optimization purposes, see the ANALYZE [ana- lyze(7)] documentation. COMPATIBILITY
SQL92 SQL92 includes a PREPARE statement, but it is only for use in embedded SQL clients. The PREPARE statement implemented by PostgreSQL also uses a somewhat different syntax. SQL - Language Statements 2002-11-22 PREPARE(7)
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