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= Notes about RAID5 Internals =
+
<small>''(Updated: Dec 2009)''</small>
 +
__TOC__
 +
This page contents some notes about RAID internals.
  
 
== Structures ==
 
== Structures ==
Line 5: Line 7:
 
In Linux, RAID5 handles all incoming requests by small units called '''stripes'''.
 
In Linux, RAID5 handles all incoming requests by small units called '''stripes'''.
 
A stripe is a set of '''blocks''' taken from all disks at the same position.
 
A stripe is a set of '''blocks''' taken from all disks at the same position.
A block is defined as unit of PAGE_SIZE bytes.  
+
A block is defined as a unit of PAGE_SIZE bytes.  
  
For example, suppose you have 3 disks and have specified 8K chunksize. Then, internally, RAID5 will look as follows:
+
For example, suppose you have 3 disks and have specified 8K chunksize. Internally, RAID5 will look like this:
 
{|border=1 cellspacing=0
 
{|border=1 cellspacing=0
 
|-
 
|-
Line 22: Line 24:
  
 
* Sn -- Number of internal stripe
 
* Sn -- Number of internal stripe
* #n -- An offset in sectors (512bytes)
+
* #n -- An offset in sectors (512 bytes)
 
* Pn -- Parity for other blocks in the stripe (actually, it floats among disks)
 
* Pn -- Parity for other blocks in the stripe (actually, it floats among disks)
  
As you can see, 8K chunksize means 2 contiguous blocks.
+
As you can see, an 8K chunksize means 2 contiguous blocks.
  
 
== Logic ==
 
== Logic ==
  
''make_request()'' goes through an incoming request, breaking it into '''blocks''' (PAGE_SIZE) and handling them separately. given bio with bi_sector = 0 bi_size = 24K and array described above, ''make_request()'' would handle #0,#8 and #16.
+
''make_request()'' goes through an incoming request, breaking it into '''blocks''' (PAGE_SIZE) and handling them separately. Given bio with bi_sector = 0 bi_size = 24K and the array described above, ''make_request()'' would handle #0, #8 and #16.
  
 
For every block, ''add_stripe_bio()'' and ''handle_stripe()'' are called.
 
For every block, ''add_stripe_bio()'' and ''handle_stripe()'' are called.
  
''add_stripe_bio()'' the intention is to add bio to a given stripe. Later, in ''handle_stripe()'', we will be able to use bio and its data for serving requests.
+
''add_stripe_bio()'' adds bio to a given stripe. Later, in ''handle_stripe()'', we can use bio and its data to serve requests.
  
''handle_stripe()'' is a core of raid5 (discussed in the next section).
+
''handle_stripe()'' is a core of RAID5 (as discussed in the next section).
  
 
== handle_stripe() ==
 
== handle_stripe() ==
  
The routine works with a stripe. It checks what should be done, learns the current state of a stripe in the internal cache, makes decision what I/O is needed to satisfy user requests, and does recovery.
+
The routine works with a stripe. It checks what should be done, learns the current state of a stripe in the internal cache, decides what I/O is needed to satisfy user requests, and does recovery.
  
For example, if a user wants to write block #0 (8 sectors starting from sector 0). RAID5's responsibility is to store new data and update parity P0. There are a few possibilities here:
+
For example, if a user wants to write block #0 (8 sectors starting from sector 0), RAID5's responsibility is to store new data and update parity P0. There are a few possibilities here:
  
# delay serving until the data for block #16 is ready -- probably the user will want to write #16 very soon?
+
* Delay serving until the data for block #16 is ready -- probably the user will want to write #16 very soon?
# read #16, make a new parity P0; write #0 and P0
+
* Read #16, make a new parity P0; write #0 and P0.
# read P0, roll back the old #0 from P0 (so it looks like we did parity with #0) and re-compute parity with the new #0
+
* Read P0, roll back the old #0 from P0 (so it looks like we did parity with #0) and re-compute parity with the new #0.
  
The first way looks like the better option because it does not require a very expensive read, but the problem is that user may need to write only #0 and not #16 in near future.
+
The first possibility looks like the best option because it does not require a very expensive read, but the problem is that user may need to write only #0 and not #16 in near future.
  
Also, the queue can get unplugged meaning that user wants all requests to
+
Also, the queue can get unplugged, meaning that the user wants all requests to
complete (unfortunately, in current block layer there is no way to specify
+
complete. (Unfortunately, in the current block layer, there is no way to specify the exact request that the user is interested in, so any completion interest requires that the entire queue be immediately served).
which exact request user is interested in, so any completion interest means
 
immediate serving of the whole queue).
 
  
 
== Problems ==
 
== Problems ==
  
Short list of the problem in raid5 we met in Thumper project:
+
This is a short list of RAID5 problems we encountered in the Thumper project:
  
; * order of handling isn't good for large requests
+
* Order of handling is not good for large requests
  As ''handle_stripe()'' goes in logical block order, it
+
: As ''handle_stripe()'' goes in logical block order, it handles S0, then S8, and then again S0 and S8. After the first touch, S0 is left with block #0 up-to-date, while #16 and P0 are not. If the stripe is forced to completion, we would need to read block #16 or P0 to get a fully up-to-date stripe. Such reads hurt throughput, almost to death. If a single process writes, things are okay because no one unplugs the queue, and there are no requests to force completion of a pending request. If there are more writers and a queue unplug occurs often, then pending requests are often forced to completion. Consider that we use a large chunk size (128K, 256K, and even larger). In the end, there are many out-of-date stripes in the cache and many reads.
  handles S0, then S8, then again S0 and S8. After the first touch
 
  S0 is left with block #0 uptodate, while #16 and P0 are not. Thus
 
  if the stripe is forced for completion, we'd need to read block
 
  #16 or P0 to get full uptodate stripe. Such reads hurt throughput
 
  almost to death. If just a single process writes, then things are
 
  OK, because nobody unplugs the queue and there is no requests to
 
  force completion of pending request. But the more writers, the
 
  often queue unplug happens and the often pending requests are forced
 
  for completion. Take into account that in reallity we use large
 
  chuck size (128K, 256K and even larger), hence tons of non-uptodate
 
  stripes in the cache and tons of reads in the end.
 
  
; * memcpy() is top consumer
+
* memcpy() is a top consumer
  all requests go via internal cache. on dual-core 2way opteron
+
:  All requests are handled via internal cache, on dual-core, two-way Opteron. This takes up to 30-33% of CPU doing 1 GB/s writes.
  it takes up to 30-33% of CPU doing 1GB/s write
 
  
; * small requests
+
* Small requests
  to fill I/O pipes and reach good throughput we need quite large
+
:  To fill I/O pipes and reach good throughput, we need very large I/O requests. Lustre™ does this by using a bio subsystem on 2.6. As described above, RAID5 handles all blocks separately, and issues separate I/O (bio) for each block. This is partially solved by an I/O scheduler that merges small requests into bigger ones. But, due to the nature of the block subsystem, any process that wants I/O to be completed ''unplugs'' the queue, causing many small requests in the pipe.
  I/O requests. Lustre does this using bio subsystem on 2.6. but
 
  as it was mentioned, raid5 handles all blocks separately and
 
  issues for every block separate I/O (bio). this is solved partial
 
  by I/O scheduler that merges small requests into bigger ones, but
 
  due to nature of block subsystem, any process that wants I/O to
 
  get completed, ''unplug'' queue and we can get many small requests
 
  in the pipe.
 
  
We developed patches that address described problems. You can find
+
We have developed patches that address the described problems. You can find
them in ftp://ftp.clusterfs.com/pub/people/alex/raid5
+
them at [http://downloads.lustre.org/people/alex/raid5/ http://downloads.lustre.org/people/alex/raid5/] .
 +
 
 +
== Zero-copy Patch ==
 +
 
 +
In the current RAID5 implementation, there is a cache for each device. For each I/O instance, the RAID5 driver first updates the device cache, and then submits the read/write request to the real block device. The cache update operation consumes lots of CPU time to copy data to/from the device cache. For Lustre's bulk write, it is meaningless to update this cache space. This is the basis of the zero-copy patch for RAID5.
 +
 
 +
To avoid data copy, pages from bio are used directly to calculate the parity page and feed the I/O source to disks. These pages (bio pages from the file system layer) should not be modified when calculating the parity page. Otherwise, the wrong parity will be written to storage, which causes garbage data to be generated if the administrator tries to rebuild the array in the future.
 +
 
 +
If pages are being mapped, our solution is to lock the pages and then unmap them (to keep the pages from being modified). For this purpose, an additional page flag (PG_constant) has been introduced. Set this bit to let the RAID5 driver know that the page will not be modified during I/O. After I/O completes against this page, the bit will be cleared, so the page can be written again.

Latest revision as of 11:57, 22 February 2010

(Updated: Dec 2009)

This page contents some notes about RAID internals.

Structures

In Linux, RAID5 handles all incoming requests by small units called stripes. A stripe is a set of blocks taken from all disks at the same position. A block is defined as a unit of PAGE_SIZE bytes.

For example, suppose you have 3 disks and have specified 8K chunksize. Internally, RAID5 will look like this:

S0 S8 S32 S40
Disk1 #0 #8 #32 #40
Disk2 #16 #24 #48 #56
Disk3 P0 P8 P32 P40

where:

  • Sn -- Number of internal stripe
  • #n -- An offset in sectors (512 bytes)
  • Pn -- Parity for other blocks in the stripe (actually, it floats among disks)

As you can see, an 8K chunksize means 2 contiguous blocks.

Logic

make_request() goes through an incoming request, breaking it into blocks (PAGE_SIZE) and handling them separately. Given bio with bi_sector = 0 bi_size = 24K and the array described above, make_request() would handle #0, #8 and #16.

For every block, add_stripe_bio() and handle_stripe() are called.

add_stripe_bio() adds bio to a given stripe. Later, in handle_stripe(), we can use bio and its data to serve requests.

handle_stripe() is a core of RAID5 (as discussed in the next section).

handle_stripe()

The routine works with a stripe. It checks what should be done, learns the current state of a stripe in the internal cache, decides what I/O is needed to satisfy user requests, and does recovery.

For example, if a user wants to write block #0 (8 sectors starting from sector 0), RAID5's responsibility is to store new data and update parity P0. There are a few possibilities here:

  • Delay serving until the data for block #16 is ready -- probably the user will want to write #16 very soon?
  • Read #16, make a new parity P0; write #0 and P0.
  • Read P0, roll back the old #0 from P0 (so it looks like we did parity with #0) and re-compute parity with the new #0.

The first possibility looks like the best option because it does not require a very expensive read, but the problem is that user may need to write only #0 and not #16 in near future.

Also, the queue can get unplugged, meaning that the user wants all requests to complete. (Unfortunately, in the current block layer, there is no way to specify the exact request that the user is interested in, so any completion interest requires that the entire queue be immediately served).

Problems

This is a short list of RAID5 problems we encountered in the Thumper project:

  • Order of handling is not good for large requests
As handle_stripe() goes in logical block order, it handles S0, then S8, and then again S0 and S8. After the first touch, S0 is left with block #0 up-to-date, while #16 and P0 are not. If the stripe is forced to completion, we would need to read block #16 or P0 to get a fully up-to-date stripe. Such reads hurt throughput, almost to death. If a single process writes, things are okay because no one unplugs the queue, and there are no requests to force completion of a pending request. If there are more writers and a queue unplug occurs often, then pending requests are often forced to completion. Consider that we use a large chunk size (128K, 256K, and even larger). In the end, there are many out-of-date stripes in the cache and many reads.
  • memcpy() is a top consumer
All requests are handled via internal cache, on dual-core, two-way Opteron. This takes up to 30-33% of CPU doing 1 GB/s writes.
  • Small requests
To fill I/O pipes and reach good throughput, we need very large I/O requests. Lustre™ does this by using a bio subsystem on 2.6. As described above, RAID5 handles all blocks separately, and issues separate I/O (bio) for each block. This is partially solved by an I/O scheduler that merges small requests into bigger ones. But, due to the nature of the block subsystem, any process that wants I/O to be completed unplugs the queue, causing many small requests in the pipe.

We have developed patches that address the described problems. You can find them at http://downloads.lustre.org/people/alex/raid5/ .

Zero-copy Patch

In the current RAID5 implementation, there is a cache for each device. For each I/O instance, the RAID5 driver first updates the device cache, and then submits the read/write request to the real block device. The cache update operation consumes lots of CPU time to copy data to/from the device cache. For Lustre's bulk write, it is meaningless to update this cache space. This is the basis of the zero-copy patch for RAID5.

To avoid data copy, pages from bio are used directly to calculate the parity page and feed the I/O source to disks. These pages (bio pages from the file system layer) should not be modified when calculating the parity page. Otherwise, the wrong parity will be written to storage, which causes garbage data to be generated if the administrator tries to rebuild the array in the future.

If pages are being mapped, our solution is to lock the pages and then unmap them (to keep the pages from being modified). For this purpose, an additional page flag (PG_constant) has been introduced. Set this bit to let the RAID5 driver know that the page will not be modified during I/O. After I/O completes against this page, the bit will be cleared, so the page can be written again.