On Fri, Jan 25, 2002 at 01:05:12PM +0530, Chetan Lavti wrote:
> 
> I am going to use the MySQL version 3.23.47 for as our database.
> The issue is which table type to use.
>
> I want that the database should be (memory-resident). I have tried
> with the MyISAM tables which doesn't solves my purpose as in this
> case the data are stored in the files.

Right.

> I have also tried with the HEAP tables that uses a hashed index and
> are stored in memory. This makes them very fast, but if MySQL
> crashes I am loosing all data stored in that. As, I have created one
> table as a heap type but when I make my server down and start it
> again all rows created nowhere exists.

Correct.

It sounds like you might want to look at InnoDB tables.  They are disk
based, but the InnoDB table handler can use a significant amount of
RAM (if you allow it to) to cache index *and* record data.  MyISAM
only caches index data in memory.  The InnoDB buffer pool is where
this cached data is stored.

> So, if anybody can suggest me any process by which I can populated
> HEAP table(es) from a duplicate table(es) (which is on secondary
> storage) at the time of startup. Also, any runtime modifications in
> the tables will need to be updated in both the tables (one in memory
> and another one on disk).  If any other method by which I can
> achieve the same.

There was talk last year of implementing a hybrid HEAP/MyISAM table
type (originally motived by the DBA at Slashdot).  Upon startup, the
MyISAM table would be loaded into a RAM-based HEAP-table.  Any changes
to the HEAP table would get written to the underlying MyISAM table as
well.  Read-only queries, of course, would be run against the
RAM-based HEAP table.

I suspect that will never be implemented, since InnoDB and it's buffer
pool go a long way toward solving the same problem.

Hope that helps,

Jeremy
-- 
Jeremy D. Zawodny, <[EMAIL PROTECTED]>
Technical Yahoo - Yahoo Finance
Desk: (408) 349-7878   Fax: (408) 349-5454   Cell: (408) 685-5936

MySQL 3.23.41-max: up 22 days, processed 513,100,530 queries (265/sec. avg)

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