10-16-2013
Exporting 10 million records to a flat file and processing that is unlikely to be faster than just doing it in SQL, at least if the relevant columns are indexed. Have you checked your query with explain plan or similar to see if you can optimise it at all?
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LEARN ABOUT REDHAT
prepare
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)