I've been thinking about this topic some more, and as I don't know when I'll
be able to go and implement it I'd want to publish the ideas here. This way
I'll be able to find them again :)
Le mardi 05 février 2008, Dimitri Fontaine a écrit :
> Le mardi 05 février 2008, Simon Riggs a écrit :
> > Much better than triggers and rules, but it will be hard to get it to
> > work.
> Well, I'm thinking about providing a somewhat modular approach where
> pgloader code is able to recognize CHECK constraints, load a module
> registered to the operator and data types, then use it.
Here's how I think I'm gonna implement it:
User level configuration
At user level, you will have to add a constraint_exclusion = on parameter to
pgloader section configuration for it to bother checking if the destination
table has some children etc.
You'll need to provide also a global ce_path parameter (where to find user
python constraint exclusion modules) and a ce_modules parameter for each
section where constraint_exclusion = on:
ce_modules = columnA:module:class, columnB:module:class
As the ce_path could point to any number of modules where a single type is
supported by several modules, I'll let the user choose which module to use.
Constraint exclusion modules
The modules will provide one or several class(es) (kind of a packaging issue),
each one will have to register which datatypes and operators they know about.
Here's some pseudo-code of a module, which certainly is the best way to
express a code design idea:
def __init__(self, operator, constant, cside='r'):
""" CHECK ( col operator constant ) => cside = 'r', could be 'l' """
def support_type(cls, type):
return type in ['integer', 'bigint', 'smallint', 'real', 'double']
def support_operator(cls, op):
return op in ['=', '>', '<', '>=', '<=', '%']
def check(self, op, data):
if op == '>' : return self.gt(data)
def gt(self, data):
if cside == 'l':
return self.constant > data
elif cside == 'r':
return data > self.constant
This way pgloader will be able to support any datatype (user datatype like
IP4R included) and operator (@@, ~<= or whatever). For pgloader to handle a
CHECK() constraint, though, it'll have to be configured to use a CE class
supporting the used operators and datatypes.
PGLoader constraint exclusion support
The CHECK() constraint being a tree of check expressions[*] linked by logical
operators, pgloader will have to build some logic tree of MyCE (user CE
modules) and evaluate all the checks in order to be able to choose the input
[*]: check((a % 10) = 1) makes an expression tree containing 2 check nodes
After having parsed pg_constraint.consrc (not conbin which seems too much an
internal dump for using it from user code) and built a CHECK tree for each
partition, pgloader will try to decide if it's about range partitioning (most
If each partition CHECK tree is AND((a>=b, a<c) or a variation of it, we have
range partitioning. Then surely we can optimize the code to run to choose the
partition where to COPY data to and still use the module operator
implementation, e.g. making a binary search on a partitions limits tree.
If you want some other widely used (or not) partitioning scheme to be
recognized and optimized by pgloader, just tell me and we'll see about it :)
Having this step as a user module seems overkill at the moment, though.
Multi-Threading behavior and CE support
Now, pgloader will be able to run N threads, each one loading some data to a
partitionned child-table target. N will certainly be configured depending on
the number of server cores and not depending on the partition numbers...
So what do we do when reading a tuple we want to store in a partition which
has no dedicated Thread started yet, and we already have N Threads running?
I'm thinking about some LRU(Thread) to choose a Thread to terminate (launch
COPY with current buffer and quit) and start a new one for the current
Hopefully there won't be such high values of N that the LRU is a bad choice
per see, and the input data won't be so messy to have to stop/start Threads
at each new line.
Comments welcome, regards,
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