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Now where can you use my ParallelSort library ?

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  Now where can you use my ParallelSort library ? "aminer" <aminer@toto.com> - 2012-10-31 17:08 -0500
    Re: Now where can you use my ParallelSort library ? "aminer" <aminer@toto.com> - 2012-10-31 17:23 -0500
    Re: Now where can you use my ParallelSort library ? "aminer" <aminer@toto.com> - 2012-10-31 17:31 -0500
    Re: Now where can you use my ParallelSort library ? "aminer" <aminer@toto.com> - 2012-10-31 17:41 -0500
    Re: Now where can you use my ParallelSort library ? "aminer" <aminer@toto.com> - 2012-10-31 18:16 -0500
    Re: Now where can you use my ParallelSort library ? "aminer" <aminer@toto.com> - 2012-10-31 18:33 -0500

#2420 — Now where can you use my ParallelSort library ?

Hello,

Now  where can you use my ParallelSort library ?

You can use it for exemple if you want to implement an in-memory database
with my Parallel Hahslist(parallel hashtable), so if you want to do for 
exemple
an SQL  Select like this (or another SQL select):

select  name
from titles
where  price  < 50

You can construct the titles table withParallel hashlist(of course you can 
add
more than one table to parallel hashlist), and copy this table in an array 
and
after that sort the array in parallel on the price key with my parallel sort 
library ,
and after that use a binary search function to find the prices in the array 
that are
lower than 50.

This is how you can use Parallel Sort library and Parallel Hashlist as 
in-memory database,
and of course you have to use TCP/IP to be able to use Parallel Hahslist as 
an in-memory database
server.

I have exported the two functions binsearch() and binsearch1() from Parallel 
Sort library.

You can download ParallelSort library and parallel hashlist from:

http://pages.videotron.com/aminer/



Amine Moulay Ramdane.

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#2421

To construct the 'titles' table and other tables with parallel hashlist, of 
course you can copy the data from a database(Access or MSQL or firebirds or 
...) to parallel hashlist used as an in-memory database server.


Amine Moulay Ramdane.


"aminer" <aminer@toto.com> wrote in message 
news:k6s3v0$q15$1@dont-email.me...
>
> Hello,
>
> Now  where can you use my ParallelSort library ?
>
> You can use it for exemple if you want to implement an in-memory database
> with my Parallel Hahslist(parallel hashtable), so if you want to do for 
> exemple
> an SQL  Select like this (or another SQL select):
>
> select  name
> from titles
> where  price  < 50
>
> You can construct the titles table withParallel hashlist(of course you can 
> add
> more than one table to parallel hashlist), and copy this table in an array 
> and
> after that sort the array in parallel on the price key with my parallel 
> sort library ,
> and after that use a binary search function to find the prices in the 
> array that are
> lower than 50.
>
> This is how you can use Parallel Sort library and Parallel Hashlist as 
> in-memory database,
> and of course you have to use TCP/IP to be able to use Parallel Hahslist 
> as an in-memory database
> server.
>
> I have exported the two functions binsearch() and binsearch1() from 
> Parallel Sort library.
>
> You can download ParallelSort library and parallel hashlist from:
>
> http://pages.videotron.com/aminer/
>
>
>
> Amine Moulay Ramdane.
>
>
>
>
>
>
>
> 

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#2422

I wrote:
>You can construct the titles table with Parallel hashlist(of course >you 
>can add more than one table to parallel hashlist), and copy >this table to 
>an array and after that sort the array in parallel on >the price key with 
>my parallel sort library , and after that use a >binary search function to 
>find the prices in the array that are >lower than 50.


Of course when you copy the 'titles' table from parallel hashlist to
an array, you have to copy only the price key and a pointer to the  object. 
Hope the idea is clear.


Amine Moulay Ramdane.




"aminer" <aminer@toto.com> wrote in message 
news:k6s3v0$q15$1@dont-email.me...
>
> Hello,
>
> Now  where can you use my ParallelSort library ?
>
> You can use it for exemple if you want to implement an in-memory database
> with my Parallel Hahslist(parallel hashtable), so if you want to do for 
> exemple
> an SQL  Select like this (or another SQL select):
>
> select  name
> from titles
> where  price  < 50
>
> You can construct the titles table withParallel hashlist(of course you can 
> add
> more than one table to parallel hashlist), and copy this table in an array 
> and
> after that sort the array in parallel on the price key with my parallel 
> sort library ,
> and after that use a binary search function to find the prices in the 
> array that are
> lower than 50.
>
> This is how you can use Parallel Sort library and Parallel Hashlist as 
> in-memory database,
> and of course you have to use TCP/IP to be able to use Parallel Hahslist 
> as an in-memory database
> server.
>
> I have exported the two functions binsearch() and binsearch1() from 
> Parallel Sort library.
>
> You can download ParallelSort library and parallel hashlist from:
>
> http://pages.videotron.com/aminer/
>
>
>
> Amine Moulay Ramdane.
>
>
>
>
>
>
>
> 

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#2423

Also i have tried in this post to answer also a question by Scott Meyer:

Read his post on Sep 2 2010:

"Libraries of data structures designed to support concurrent operations and 
to
scale well with the number of threads are common, e.g., ConcurrentHashMap 
and
ConcurrentLinkedQueue in Java, ConcurrentQueue and ConcurrentBag in .NET,
concurrent_queue and concurrent_vector in TBB and PPL.  If the comments in a
recent thread in comp.lang.c++ ( http://tinyurl.com/2ey8mta ) are
representative, however, there is considerable skepticism that such data
structures are useful and some concern that designs employing them are 
almost
certainly misguided.  Considerable googling on my part has failed to turn up
examples of compelling use cases for these kinds of data structures, but I 
find
it hard to believe that the people at Sun, Microsoft, and Intel (among 
others)
have devoted so much effort to creating libraries of data structures for 
which
there is little use.

I'd be grateful if people could sketch compelling use cases for concurrent 
data
structures, ideally with examples of situations in which they have been
successfully employed.  Such data structures need not be lock-free (e.g., 
they
might use fine-grained locking or lock striping), but they should be
substantially more scalable than a design based on locking an entire data
structure for each access.


Thanks,


Scott


-- 
* C++ and Beyond: Meyers, Sutter, & Alexandrescu, Oct. 24-27 near Seattle
(http://cppandbeyond.com/)
* License my training materials for commercial (http://tinyurl.com/yfzvkp9) 
or
personal use (http://tinyurl.com/yl5ka5p). "





"aminer" <aminer@toto.com> wrote in message 
news:k6s3v0$q15$1@dont-email.me...
>
> Hello,
>
> Now  where can you use my ParallelSort library ?
>
> You can use it for exemple if you want to implement an in-memory database
> with my Parallel Hahslist(parallel hashtable), so if you want to do for 
> exemple
> an SQL  Select like this (or another SQL select):
>
> select  name
> from titles
> where  price  < 50
>
> You can construct the titles table withParallel hashlist(of course you can 
> add
> more than one table to parallel hashlist), and copy this table in an array 
> and
> after that sort the array in parallel on the price key with my parallel 
> sort library ,
> and after that use a binary search function to find the prices in the 
> array that are
> lower than 50.
>
> This is how you can use Parallel Sort library and Parallel Hashlist as 
> in-memory database,
> and of course you have to use TCP/IP to be able to use Parallel Hahslist 
> as an in-memory database
> server.
>
> I have exported the two functions binsearch() and binsearch1() from 
> Parallel Sort library.
>
> You can download ParallelSort library and parallel hashlist from:
>
> http://pages.videotron.com/aminer/
>
>
>
> Amine Moulay Ramdane.
>
>
>
>
>
>
>
> 

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#2424

Hello,

If you don't want to use a binary search in my previous exemple e, don't use 
it.

But in the following SQL select:

select name
from titles
where (type = 'business' or type = 'psychology')


It is better to use a binary search after you have sorted the array
with parallel sort library.

Here you can construct the titles table with Parallel hashlist(of course you 
can add
more than one table to parallel hashlist)  by copying, for exemple, the data 
from a database to the parallel hashlist's table, and after that copy this 
table to an array and after that sort the array in parallel on the type key 
with my parallel sort library ,
and after that use a binary search function to find the type that
equal 'business' or equal 'psychology' etc.

This is how you can use Parallel Sort library and Parallel Hashlist as 
in-memory database,
and of course you have to use TCP/IP to be able to use Parallel Hahslist as 
an in-memory database
server.


Amine Moulay Ramdane.



"aminer" <aminer@toto.com> wrote in message 
news:k6s3v0$q15$1@dont-email.me...
>
> Hello,
>
> Now  where can you use my ParallelSort library ?
>
> You can use it for exemple if you want to implement an in-memory database
> with my Parallel Hahslist(parallel hashtable), so if you want to do for 
> exemple
> an SQL  Select like this (or another SQL select):
>
> select  name
> from titles
> where  price  < 50
>
> You can construct the titles table withParallel hashlist(of course you can 
> add
> more than one table to parallel hashlist), and copy this table in an array 
> and
> after that sort the array in parallel on the price key with my parallel 
> sort library ,
> and after that use a binary search function to find the prices in the 
> array that are
> lower than 50.
>
> This is how you can use Parallel Sort library and Parallel Hashlist as 
> in-memory database,
> and of course you have to use TCP/IP to be able to use Parallel Hahslist 
> as an in-memory database
> server.
>
> I have exported the two functions binsearch() and binsearch1() from 
> Parallel Sort library.
>
> You can download ParallelSort library and parallel hashlist from:
>
> http://pages.videotron.com/aminer/
>
>
>
> Amine Moulay Ramdane.
>
>
>
>
>
>
>
> 

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#2425

Hello again,

But why use my Parallel Hashlist(parallel hashtable) for exemple  as an 
in-memory database server  ?


Read this:

"A parallel HashList with O(1) best case and O(log(n)) worst case access 
that uses lock striping and lightweight 
MREWs(multiple-readers-exclusive-writer) , this allows multiple threads to 
write and read concurently. also parallelhashlist maintains an independant 
counter , that counts the number of entries , for each segment of the 
hashtable and uses a lock for each counter, this is also for better 
scalability."

Cause it allows multiple threads to write and read concurently,
and it scales very well.


You can download Parallel Hashlist and Parallel Sort library
from:

http://pages.videotron.com/aminer/


Thank you,
Amine Moulay Ramdane.





"aminer" <aminer@toto.com> wrote in message 
news:k6s3v0$q15$1@dont-email.me...
>
> Hello,
>
> Now  where can you use my ParallelSort library ?
>
> You can use it for exemple if you want to implement an in-memory database
> with my Parallel Hahslist(parallel hashtable), so if you want to do for 
> exemple
> an SQL  Select like this (or another SQL select):
>
> select  name
> from titles
> where  price  < 50
>
> You can construct the titles table withParallel hashlist(of course you can 
> add
> more than one table to parallel hashlist), and copy this table in an array 
> and
> after that sort the array in parallel on the price key with my parallel 
> sort library ,
> and after that use a binary search function to find the prices in the 
> array that are
> lower than 50.
>
> This is how you can use Parallel Sort library and Parallel Hashlist as 
> in-memory database,
> and of course you have to use TCP/IP to be able to use Parallel Hahslist 
> as an in-memory database
> server.
>
> I have exported the two functions binsearch() and binsearch1() from 
> Parallel Sort library.
>
> You can download ParallelSort library and parallel hashlist from:
>
> http://pages.videotron.com/aminer/
>
>
>
> Amine Moulay Ramdane.
>
>
>
>
>
>
>
> 

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