readahead: on-demand readahead logic
This is a minimal readahead algorithm that aims to replace the current one.
It is more flexible and reliable, while maintaining almost the same behavior
and performance. Also it is full integrated with adaptive readahead.
It is designed to be called on demand:
- on a missing page, to do synchronous readahead
- on a lookahead page, to do asynchronous readahead
In this way it eliminated the awkward workarounds for cache hit/miss,
readahead thrashing, retried read, and unaligned read. It also adopts the
data structure introduced by adaptive readahead, parameterizes readahead
pipelining with `lookahead_index', and reduces the current/ahead windows to
one single window.
HEURISTICS
The logic deals with four cases:
- sequential-next
found a consistent readahead window, so push it forward
- random
standalone small read, so read as is
- sequential-first
create a new readahead window for a sequential/oversize request
- lookahead-clueless
hit a lookahead page not associated with the readahead window,
so create a new readahead window and ramp it up
In each case, three parameters are determined:
- readahead index: where the next readahead begins
- readahead size: how much to readahead
- lookahead size: when to do the next readahead (for pipelining)
BEHAVIORS
The old behaviors are maximally preserved for trivial sequential/random reads.
Notable changes are:
- It no longer imposes strict sequential checks.
It might help some interleaved cases, and clustered random reads.
It does introduce risks of a random lookahead hit triggering an
unexpected readahead. But in general it is more likely to do good
than to do evil.
- Interleaved reads are supported in a minimal way.
Their chances of being detected and proper handled are still low.
- Readahead thrashings are better handled.
The current readahead leads to tiny average I/O sizes, because it
never turn back for the thrashed pages. They have to be fault in
by do_generic_mapping_read() one by one. Whereas the on-demand
readahead will redo readahead for them.
OVERHEADS
The new code reduced the overheads of
- excessively calling the readahead routine on small sized reads
(the current readahead code insists on seeing all requests)
- doing a lot of pointless page-cache lookups for small cached files
(the current readahead only turns itself off after 256 cache hits,
unfortunately most files are < 1MB, so never see that chance)
That accounts for speedup of
- 0.3% on 1-page sequential reads on sparse file
- 1.2% on 1-page cache hot sequential reads
- 3.2% on 256-page cache hot sequential reads
- 1.3% on cache hot `tar /lib`
However, it does introduce one extra page-cache lookup per cache miss, which
impacts random reads slightly. That's 1% overheads for 1-page random reads on
sparse file.
PERFORMANCE
The basic benchmark setup is
- 2.6.20 kernel with on-demand readahead
- 1MB max readahead size
- 2.9GHz Intel Core 2 CPU
- 2GB memory
- 160G/8M Hitachi SATA II 7200 RPM disk
The benchmarks show that
- it maintains the same performance for trivial sequential/random reads
- sysbench/OLTP performance on MySQL gains up to 8%
- performance on readahead thrashing gains up to 3 times
iozone throughput (KB/s): roughly the same
==========================================
iozone -c -t1 -s 4096m -r 64k
2.6.20 on-demand gain
first run
" Initial write " 61437.27 64521.53 +5.0%
" Rewrite " 47893.02 48335.20 +0.9%
" Read " 62111.84 62141.49 +0.0%
" Re-read " 62242.66 62193.17 -0.1%
" Reverse Read " 50031.46 49989.79 -0.1%
" Stride read " 8657.61 8652.81 -0.1%
" Random read " 13914.28 13898.23 -0.1%
" Mixed workload " 19069.27 19033.32 -0.2%
" Random write " 14849.80 14104.38 -5.0%
" Pwrite " 62955.30 65701.57 +4.4%
" Pread " 62209.99 62256.26 +0.1%
second run
" Initial write " 60810.31 66258.69 +9.0%
" Rewrite " 49373.89 57833.66 +17.1%
" Read " 62059.39 62251.28 +0.3%
" Re-read " 62264.32 62256.82 -0.0%
" Reverse Read " 49970.96 50565.72 +1.2%
" Stride read " 8654.81 8638.45 -0.2%
" Random read " 13901.44 13949.91 +0.3%
" Mixed workload " 19041.32 19092.04 +0.3%
" Random write " 14019.99 14161.72 +1.0%
" Pwrite " 64121.67 68224.17 +6.4%
" Pread " 62225.08 62274.28 +0.1%
In summary, writes are unstable, reads are pretty close on average:
access pattern 2.6.20 on-demand gain
Read 62085.61 62196.38 +0.2%
Re-read 62253.49 62224.99 -0.0%
Reverse Read 50001.21 50277.75 +0.6%
Stride read 8656.21 8645.63 -0.1%
Random read 13907.86 13924.07 +0.1%
Mixed workload 19055.29 19062.68 +0.0%
Pread 62217.53 62265.27 +0.1%
aio-stress: roughly the same
============================
aio-stress -l -s4096 -r128 -t1 -o1 knoppix511-dvd-cn.iso
aio-stress -l -s4096 -r128 -t1 -o3 knoppix511-dvd-cn.iso
2.6.20 on-demand delta
sequential 92.57s 92.54s -0.0%
random 311.87s 312.15s +0.1%
sysbench fileio: roughly the same
=================================
sysbench --test=fileio --file-io-mode=async --file-test-mode=rndrw \
--file-total-size=4G --file-block-size=64K \
--num-threads=001 --max-requests=10000 --max-time=900 run
threads 2.6.20 on-demand delta
first run
1 59.1974s 59.2262s +0.0%
2 58.0575s 58.2269s +0.3%
4 48.0545s 47.1164s -2.0%
8 41.0684s 41.2229s +0.4%
16 35.8817s 36.4448s +1.6%
32 32.6614s 32.8240s +0.5%
64 23.7601s 24.1481s +1.6%
128 24.3719s 23.8225s -2.3%
256 23.2366s 22.0488s -5.1%
second run
1 59.6720s 59.5671s -0.2%
8 41.5158s 41.9541s +1.1%
64 25.0200s 23.9634s -4.2%
256 22.5491s 20.9486s -7.1%
Note that the numbers are not very stable because of the writes.
The overall performance is close when we sum all seconds up:
sum all up 495.046s 491.514s -0.7%
sysbench oltp (trans/sec): up to 8% gain
========================================
sysbench --test=oltp --oltp-table-size=
10000000 --oltp-read-only \
--mysql-socket=/var/run/mysqld/mysqld.sock \
--mysql-user=root --mysql-password=readahead \
--num-threads=064 --max-requests=10000 --max-time=900 run
10000-transactions run
threads 2.6.20 on-demand gain
1 62.81 64.56 +2.8%
2 67.97 70.93 +4.4%
4 81.81 85.87 +5.0%
8 94.60 97.89 +3.5%
16 99.07 104.68 +5.7%
32 95.93 104.28 +8.7%
64 96.48 103.68 +7.5%
5000-transactions run
1 48.21 48.65 +0.9%
8 68.60 70.19 +2.3%
64 70.57 74.72 +5.9%
2000-transactions run
1 37.57 38.04 +1.3%
2 38.43 38.99 +1.5%
4 45.39 46.45 +2.3%
8 51.64 52.36 +1.4%
16 54.39 55.18 +1.5%
32 52.13 54.49 +4.5%
64 54.13 54.61 +0.9%
That's interesting results. Some investigations show that
- MySQL is accessing the db file non-uniformly: some parts are
more hot than others
- It is mostly doing 4-page random reads, and sometimes doing two
reads in a row, the latter one triggers a 16-page readahead.
- The on-demand readahead leaves many lookahead pages (flagged
PG_readahead) there. Many of them will be hit, and trigger
more readahead pages. Which might save more seeks.
- Naturally, the readahead windows tend to lie in hot areas,
and the lookahead pages in hot areas is more likely to be hit.
- The more overall read density, the more possible gain.
That also explains the adaptive readahead tricks for clustered random reads.
readahead thrashing: 3 times better
===================================
We boot kernel with "mem=128m single", and start a 100KB/s stream on every
second, until reaching 200 streams.
max throughput min avg I/O size
2.6.20: 5MB/s 16KB
on-demand: 15MB/s 140KB
Signed-off-by: Fengguang Wu <wfg@mail.ustc.edu.cn>
Cc: Steven Pratt <slpratt@austin.ibm.com>
Cc: Ram Pai <linuxram@us.ibm.com>
Cc: Rusty Russell <rusty@rustcorp.com.au>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
projects / GitHub / moto-9609 / android_kernel_motorola_exynos9610.git / commit