On Aug 21, 12:08*am, David BL <davi... (AT) iinet (DOT) net.au> wrote:
But what dictates the block size? Is this defined by the physical
disk, the file system, or the database code?

On Aug 21, 12:08*am, David BL <davi... (AT) iinet (DOT) net.au> wrote:
But what dictates the block size? Is this defined by the physical
disk, the file system, or the database code?

On Aug 21, 12:08*am, David BL <davi... (AT) iinet (DOT) net.au> wrote:
But what dictates the block size? Is this defined by the physical
disk, the file system, or the database code?

On Aug 21, 12:08*am, David BL <davi... (AT) iinet (DOT) net.au> wrote:
But what dictates the block size? Is this defined by the physical
disk, the file system, or the database code?

On Aug 21, 12:08*am, David BL <davi... (AT) iinet (DOT) net.au> wrote:
But what dictates the block size? Is this defined by the physical
disk, the file system, or the database code?

"Darren" <anon5874 (AT) yahoo (DOT) com> wrote

There can be a marginal reduction in cpu cycles and in some cases I/O by
matching the block size of the disk subsystem to the block size specified in
the database engine, but in any system where performance is critical, the
disk subsystem will involve a caching disk array or multiple caching disk
arrays, and the block size becomes moot as a result of the caching disk
array controller reading an entire track at a time. Memory to memory
transfers are negligible when compared to disk to memory transfers--let
alone seeks. Moreover, caching controllers employ a number of technologies,
such as elevator seeking, to minimize the impact of seek times, and by
reading an entire track at a time, latency--that is, the time it takes for
the data requested to arrive at the head for reading--is effectively
eliminated as a factor. (There is still a negligible latency which is
rougly half the time it takes for the head to pass over a sector, but as
there are hundreds of sectors per track, the time involved is not worth
considering.) Not to mention that a savvy dba will spread data access
across as many heads as can be budgeted for to maximize throughput and
minimize seek time. If you have a 100GB database and you put it on single
100GB disk drive, your best average seek time is the average seek time of
the disk drive, but if you put the database on four 100GB disk drives, the
the best average seek time will only be a fraction of the seek time of the
single disk. Suppose that the full-stroke seek time on the 100GB disk is
7ms and the track-to-track seek time is 1ms. Well, with four disks, instead
of an average 4ms seek time, the individual seek time of each disk is
reduced to roughly 2.5ms, and since there are four disks, the average seek
time for the disk subsystem is reduced to a quarter of that or roughly
..625ms. Add a mirror (RAID 0+1 using 8 drives), and you introduce fault
tolerance while at the same time halving again seek time for reads. Note
that except in rare cases, the ratio of reads to writes in a database is
better than 10:1, so any strategy that improves read time without
significantly impeding write time, such as is the case with implementing
RAID 0+1, should be vigorously pursued. Incidentally, RAID 0+1 is also good
for transaction logs and temporary tables, which involve mostly writes or a
roughly equal number of reads and writes, but it usually makes sense to
segregate the logs from the database--for recovery if nothing else, and it
also often makes sense to segregate the location where temporary tables are
housed from both the database and the logs.

"Darren" <anon5874 (AT) yahoo (DOT) com> wrote

There can be a marginal reduction in cpu cycles and in some cases I/O by
matching the block size of the disk subsystem to the block size specified in
the database engine, but in any system where performance is critical, the
disk subsystem will involve a caching disk array or multiple caching disk
arrays, and the block size becomes moot as a result of the caching disk
array controller reading an entire track at a time. Memory to memory
transfers are negligible when compared to disk to memory transfers--let
alone seeks. Moreover, caching controllers employ a number of technologies,
such as elevator seeking, to minimize the impact of seek times, and by
reading an entire track at a time, latency--that is, the time it takes for
the data requested to arrive at the head for reading--is effectively
eliminated as a factor. (There is still a negligible latency which is
rougly half the time it takes for the head to pass over a sector, but as
there are hundreds of sectors per track, the time involved is not worth
considering.) Not to mention that a savvy dba will spread data access
across as many heads as can be budgeted for to maximize throughput and
minimize seek time. If you have a 100GB database and you put it on single
100GB disk drive, your best average seek time is the average seek time of
the disk drive, but if you put the database on four 100GB disk drives, the
the best average seek time will only be a fraction of the seek time of the
single disk. Suppose that the full-stroke seek time on the 100GB disk is
7ms and the track-to-track seek time is 1ms. Well, with four disks, instead
of an average 4ms seek time, the individual seek time of each disk is
reduced to roughly 2.5ms, and since there are four disks, the average seek
time for the disk subsystem is reduced to a quarter of that or roughly
..625ms. Add a mirror (RAID 0+1 using 8 drives), and you introduce fault
tolerance while at the same time halving again seek time for reads. Note
that except in rare cases, the ratio of reads to writes in a database is
better than 10:1, so any strategy that improves read time without
significantly impeding write time, such as is the case with implementing
RAID 0+1, should be vigorously pursued. Incidentally, RAID 0+1 is also good
for transaction logs and temporary tables, which involve mostly writes or a
roughly equal number of reads and writes, but it usually makes sense to
segregate the logs from the database--for recovery if nothing else, and it
also often makes sense to segregate the location where temporary tables are
housed from both the database and the logs.

"Darren" <anon5874 (AT) yahoo (DOT) com> wrote

There can be a marginal reduction in cpu cycles and in some cases I/O by
matching the block size of the disk subsystem to the block size specified in
the database engine, but in any system where performance is critical, the
disk subsystem will involve a caching disk array or multiple caching disk
arrays, and the block size becomes moot as a result of the caching disk
array controller reading an entire track at a time. Memory to memory
transfers are negligible when compared to disk to memory transfers--let
alone seeks. Moreover, caching controllers employ a number of technologies,
such as elevator seeking, to minimize the impact of seek times, and by
reading an entire track at a time, latency--that is, the time it takes for
the data requested to arrive at the head for reading--is effectively
eliminated as a factor. (There is still a negligible latency which is
rougly half the time it takes for the head to pass over a sector, but as
there are hundreds of sectors per track, the time involved is not worth
considering.) Not to mention that a savvy dba will spread data access
across as many heads as can be budgeted for to maximize throughput and
minimize seek time. If you have a 100GB database and you put it on single
100GB disk drive, your best average seek time is the average seek time of
the disk drive, but if you put the database on four 100GB disk drives, the
the best average seek time will only be a fraction of the seek time of the
single disk. Suppose that the full-stroke seek time on the 100GB disk is
7ms and the track-to-track seek time is 1ms. Well, with four disks, instead
of an average 4ms seek time, the individual seek time of each disk is
reduced to roughly 2.5ms, and since there are four disks, the average seek
time for the disk subsystem is reduced to a quarter of that or roughly
..625ms. Add a mirror (RAID 0+1 using 8 drives), and you introduce fault
tolerance while at the same time halving again seek time for reads. Note
that except in rare cases, the ratio of reads to writes in a database is
better than 10:1, so any strategy that improves read time without
significantly impeding write time, such as is the case with implementing
RAID 0+1, should be vigorously pursued. Incidentally, RAID 0+1 is also good
for transaction logs and temporary tables, which involve mostly writes or a
roughly equal number of reads and writes, but it usually makes sense to
segregate the logs from the database--for recovery if nothing else, and it
also often makes sense to segregate the location where temporary tables are
housed from both the database and the logs.

"Darren" <anon5874 (AT) yahoo (DOT) com> wrote

There can be a marginal reduction in cpu cycles and in some cases I/O by
matching the block size of the disk subsystem to the block size specified in
the database engine, but in any system where performance is critical, the
disk subsystem will involve a caching disk array or multiple caching disk
arrays, and the block size becomes moot as a result of the caching disk
array controller reading an entire track at a time. Memory to memory
transfers are negligible when compared to disk to memory transfers--let
alone seeks. Moreover, caching controllers employ a number of technologies,
such as elevator seeking, to minimize the impact of seek times, and by
reading an entire track at a time, latency--that is, the time it takes for
the data requested to arrive at the head for reading--is effectively
eliminated as a factor. (There is still a negligible latency which is
rougly half the time it takes for the head to pass over a sector, but as
there are hundreds of sectors per track, the time involved is not worth
considering.) Not to mention that a savvy dba will spread data access
across as many heads as can be budgeted for to maximize throughput and
minimize seek time. If you have a 100GB database and you put it on single
100GB disk drive, your best average seek time is the average seek time of
the disk drive, but if you put the database on four 100GB disk drives, the
the best average seek time will only be a fraction of the seek time of the
single disk. Suppose that the full-stroke seek time on the 100GB disk is
7ms and the track-to-track seek time is 1ms. Well, with four disks, instead
of an average 4ms seek time, the individual seek time of each disk is
reduced to roughly 2.5ms, and since there are four disks, the average seek
time for the disk subsystem is reduced to a quarter of that or roughly
..625ms. Add a mirror (RAID 0+1 using 8 drives), and you introduce fault
tolerance while at the same time halving again seek time for reads. Note
that except in rare cases, the ratio of reads to writes in a database is
better than 10:1, so any strategy that improves read time without
significantly impeding write time, such as is the case with implementing
RAID 0+1, should be vigorously pursued. Incidentally, RAID 0+1 is also good
for transaction logs and temporary tables, which involve mostly writes or a
roughly equal number of reads and writes, but it usually makes sense to
segregate the logs from the database--for recovery if nothing else, and it
also often makes sense to segregate the location where temporary tables are
housed from both the database and the logs.

"Darren" <anon5874 (AT) yahoo (DOT) com> wrote

There can be a marginal reduction in cpu cycles and in some cases I/O by
matching the block size of the disk subsystem to the block size specified in
the database engine, but in any system where performance is critical, the
disk subsystem will involve a caching disk array or multiple caching disk
arrays, and the block size becomes moot as a result of the caching disk
array controller reading an entire track at a time. Memory to memory
transfers are negligible when compared to disk to memory transfers--let
alone seeks. Moreover, caching controllers employ a number of technologies,
such as elevator seeking, to minimize the impact of seek times, and by
reading an entire track at a time, latency--that is, the time it takes for
the data requested to arrive at the head for reading--is effectively
eliminated as a factor. (There is still a negligible latency which is
rougly half the time it takes for the head to pass over a sector, but as
there are hundreds of sectors per track, the time involved is not worth
considering.) Not to mention that a savvy dba will spread data access
across as many heads as can be budgeted for to maximize throughput and
minimize seek time. If you have a 100GB database and you put it on single
100GB disk drive, your best average seek time is the average seek time of
the disk drive, but if you put the database on four 100GB disk drives, the
the best average seek time will only be a fraction of the seek time of the
single disk. Suppose that the full-stroke seek time on the 100GB disk is
7ms and the track-to-track seek time is 1ms. Well, with four disks, instead
of an average 4ms seek time, the individual seek time of each disk is
reduced to roughly 2.5ms, and since there are four disks, the average seek
time for the disk subsystem is reduced to a quarter of that or roughly
..625ms. Add a mirror (RAID 0+1 using 8 drives), and you introduce fault
tolerance while at the same time halving again seek time for reads. Note
that except in rare cases, the ratio of reads to writes in a database is
better than 10:1, so any strategy that improves read time without
significantly impeding write time, such as is the case with implementing
RAID 0+1, should be vigorously pursued. Incidentally, RAID 0+1 is also good
for transaction logs and temporary tables, which involve mostly writes or a
roughly equal number of reads and writes, but it usually makes sense to
segregate the logs from the database--for recovery if nothing else, and it
also often makes sense to segregate the location where temporary tables are
housed from both the database and the logs.