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Re: Sizing - RAC, storage subsystem EMC

From: Yechiel Adar <>
Date: Thu, 22 May 2003 03:04:49 -0800
Message-ID: <>

I really do not know. It requires in-depth knowledge of the SAN internal. It depends how the SAN service requests. Splitting table and indexes does not seems right to me. I think that we need to separate heavy disk activity across mount points. It also depends on the OS of the computer. It can be that the OS keeps a queue for each mount point and new I/O for the same mount point is waiting until the previous one is completed, since the O/S does not know that this is SAN that map the mount point to many volumes.

Yechiel Adar

  Hi Yeichel,    

  If the database is writing to the cache memory (and then to disk behind the scenes), then does the rule of separating tables and indexes on different devices still apply? Last implementation I did on a SAN I followed that rule anyway, figuring it couldn't hurt. What do you think?    

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    -----Original Message-----
    From: Yechiel Adar []     Sent: Wednesday, May 21, 2003 8:55 AM     To: Multiple recipients of list ORACLE-L     Subject: Re: Sizing - RAC, storage subsystem EMC

    With EMC, or any other SAN, you do not write to the disks. You write into a cache memory on the controller and the controller then writes the data to the disks at his own time. If you have big enough write cache on the controller the raid-5 write speed does not concern you.

    Raid-5 might be a little slow but it save almost 1/2 the disk space needed to ensure the correctness of the data since it can use one parity disk for 10-20 disks.

    Yechiel Adar

      Hi all, hope you can give some input ideas.        

      I am in the process of designing a system for a client of ours for a proposal        

      The sizing information I have been given is as follows.        

      58.1 million tickets/day at 351 bytes per record. The record was complete populated (all columns filled to max) in a table and then analyzed. Average row size 351 bytes.

      =~ 19 GB/day. Raw data. Plus overhead (indexes, temp space, rollback, some other data etc) here and there I have requested 5 TB.        

      We need to keep records for a month. Table design I am looking at is a date partition with a second level hash partition. This is so that I can move data in the oldest week/table space off line and write them to optical storage for possible retrieval at a later date (requirement).        

      Of course this will be on locally managed table spaces with auto storage management for segments.        


      The database will be a Oracle RAC on Sun cluster 3 build on 2 x Sun StarFire V880, 4 CPU's, 4 GB RAM each,

      Connected to an EMC SAN via Fiber Channel        

      I do not have more information about the EMC array at the moment. Hitachi has been mentioned. (excuse the spelling)        

      Question I have.        

      I have been asked how many writes the Database will be doing to the SAN per second.

      I have determined that I should expect about 2000 tickets/second.

      The table in question will have 2 indexes.        

      Now following rough guessing I said I should expect at least 16 000 writes/second        

      This was done by say/assuming        

      2 writes for the redo log files (2 members)

      2 writes for the control files (2 control files)

      2 writes to index blocks

      1 write to undo table space block

      1 write to table block for data

      total 8 blocks written to per ticket.        

      Now I know the above is a real rough. And probably very wrong, if someone can shed some more light on it and give me a more accurate method/guess I would appreciate it.        

      Another question.

      The hardware SAN engineers are telling me they want to configure the SAN in a RAID 5 configuration. I have requested Raid 0 + 1. They say this is going to be to expensive and the new technology allows them to give me the performance I want using RAID 5.        

      I would prefer to err on the side of caution and follow Oracle industry wide recommendation and follow the SAME methodology.




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Author: Yechiel Adar

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