Update some obsolete info about GEQO.

diff --git a/doc/src/sgml/geqo.sgml b/doc/src/sgml/geqo.sgml
index 0f12b3db3c3ec2653b982583ec3429299eec414f..546a864901b8d5f2010ed755ecfbe929f3ad2e35 100644 (file)
--- a/doc/src/sgml/geqo.sgml
+++ b/doc/src/sgml/geqo.sgml
@@ -1,5 +1,5 @@
 
 
@@ -49,7 +49,7 @@ Genetic Optimizer
     grows exponentially with the number of joins included in it. Further
     optimization effort is caused by the support of a variety of
     join methods
-    (e.g., nested loop, index scan, merge join in Postgres) to
+    (e.g., nested loop, hash join, merge join in Postgres) to
     process individual joins and a diversity of
     indices (e.g., r-tree,
     b-tree, hash in Postgres) as access paths for relations.
@@ -57,8 +57,8 @@ Genetic Optimizer
 
    
     The current Postgres optimizer
-    implementation performs a near-
-     exhaustive search over the space of alternative strategies. This query
+    implementation performs a near-exhaustive search
+    over the space of alternative strategies. This query 
     optimization technique is inadequate to support database application
     domains that involve the need for extensive queries, such as artificial
     intelligence.
@@ -74,8 +74,8 @@ Genetic Optimizer
    
 
    
-    Performance difficulties within exploring the space of possible query
-    plans arose the demand for a new optimization technique being developed.
+    Performance difficulties in exploring the space of possible query
+    plans created the demand for a new optimization technique being developed.
    
 
    
@@ -88,10 +88,11 @@ Genetic Optimizer
    Genetic Algorithms (<acronym>GA</acronym>)
 
    
-    The GA is a heuristic optimization method which operates through 
+    The GA is a heuristic optimization method which
+    operates through
     determined, randomized search. The set of possible solutions for the
     optimization problem is considered as a
-    erm>populaerm> of individuals.
+    populationerm> of individuals.
     The degree of adaption of an individual to its environment is specified
     by its fitness.
    
@@ -167,7 +168,8 @@ P''(t)  generation of descendants at a time t
     
     is encoded by the integer string '4-1-3-2',
     which means, first join relation '4' and '1', then '3', and
-    then '2', where 1, 2, 3, 4 are relids in Postgres.
+    then '2', where 1, 2, 3, 4 are relids within the
+    Postgres optimizer.
    
 
    
@@ -192,9 +194,10 @@ P''(t)  generation of descendants at a time t
 
      
       
-       Usage of edge recombination crossover which is especially suited
+       Usage of edge recombination crossover which is
+       especially suited
        to keep edge losses low for the solution of the
-       crocronym> by means of a GA;
+       TSPcronym> by means of a GA;
       
      
 
@@ -208,40 +211,19 @@ P''(t)  generation of descendants at a time t
    
 
    
-    The GEQO module gives the following benefits to
-    the Postgres DBMS
-    compared to the Postgres query optimizer implementation:
-
-    
-     
-      
-       Handling of large join queries through non-exhaustive search;
-      
-     
-
-     
-      
-       Improved cost size approximation of query plans since no longer
-       plan merging is needed (the GEQO module evaluates the cost for a
-       query plan as an individual).
-      
-     
-    
+    The GEQO module allows
+    the Postgres query optimizer to
+    support large join queries effectively through
+    non-exhaustive search.
    
 
-  
-
-  
+  
    Future Implementation Tasks for</div>
<div class="diff ctx">     <productname>PostgreSQL</> <acronym>GEQO</acronym>
 
-   
-    Basic Improvements
-
-    
-     Improve genetic algorithm parameter settings
-
      
+      Work is still needed to improve the genetic algorithm parameter
+      settings.
       In file backend/optimizer/geqo/geqo_params.c, routines
       gimme_pool_size and gimme_number_generations,
       we have to find a compromise for the parameter settings
@@ -259,38 +241,9 @@ P''(t)  generation of descendants at a time t
        
       
      
-    
-
-    
-     Find better solution for integer overflow
-
-     
-      In file backend/optimizer/geqo/geqo_eval.c, routine
-      geqo_joinrel_size,
-      the present hack for MAXINT overflow is to set the Postgres integer
-      value of rel->size to its logarithm.
-      Modifications of Rel in backend/nodes/relation.h will
-      surely have severe impacts on the whole Postgres implementation.
-     
-    
-
-    
-     Find solution for exhausted memory
 
-     
-      Memory exhaustion may occur with more than 10 relations involved in a query.
-      In file backend/optimizer/geqo/geqo_eval.c, routine
-      gimme_tree is recursively called.
-      Maybe I forgot something to be freed correctly, but I dunno what.
-      Of course the rel data structure of the
-      join keeps growing and
-      growing the more relations are packed into it.
-      Suggestions are welcome :-(
-     
-    
    
 
-
    
     </div>
<div class="diff ctx">      References</div>
</div>
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