since slave isn't replying to it's master, these errors go unnoticed.
since we don't expect the master to send garbadge to the slave, this should be safe.
(as long as we don't log OOM errors there)
since slave isn't replying to it's master, these errors go unnoticed.
since we don't expect the master to send garbadge to the slave, this should be safe.
(as long as we don't log OOM errors there)
since slave isn't replying to it's master, these errors go unnoticed.
since we don't expect the master to send garbadge to the slave, this should be safe.
(as long as we don't log OOM errors there)
Testing with Solaris C compiler (SunOS 5.11 11.2 sun4v sparc sun4v)
there were issues compiling due to atomicvar.h and running the
tests also failed because of "tail" usage not conform with Solaris
tail implementation. This commit fixes both the issues.
Testing with Solaris C compiler (SunOS 5.11 11.2 sun4v sparc sun4v)
there were issues compiling due to atomicvar.h and running the
tests also failed because of "tail" usage not conform with Solaris
tail implementation. This commit fixes both the issues.
Testing with Solaris C compiler (SunOS 5.11 11.2 sun4v sparc sun4v)
there were issues compiling due to atomicvar.h and running the
tests also failed because of "tail" usage not conform with Solaris
tail implementation. This commit fixes both the issues.
For performance reasons we use a reduced rounds variant of
SipHash. This should still provide enough protection and the
effects in the hash table distribution are non existing.
If some real world attack on SipHash 1-2 will be found we can
trivially switch to something more secure. Anyway it is a
big step forward from Murmurhash, for which it is trivial to
generate *seed independent* colliding keys... The speed
penatly introduced by SipHash 2-4, around 4%, was a too big
price to pay compared to the effectiveness of the HashDoS
attack against SipHash 1-2, and considering so far in the
Redis history, no such an incident ever happened even while
using trivially to collide hash functions.
For performance reasons we use a reduced rounds variant of
SipHash. This should still provide enough protection and the
effects in the hash table distribution are non existing.
If some real world attack on SipHash 1-2 will be found we can
trivially switch to something more secure. Anyway it is a
big step forward from Murmurhash, for which it is trivial to
generate *seed independent* colliding keys... The speed
penatly introduced by SipHash 2-4, around 4%, was a too big
price to pay compared to the effectiveness of the HashDoS
attack against SipHash 1-2, and considering so far in the
Redis history, no such an incident ever happened even while
using trivially to collide hash functions.
For performance reasons we use a reduced rounds variant of
SipHash. This should still provide enough protection and the
effects in the hash table distribution are non existing.
If some real world attack on SipHash 1-2 will be found we can
trivially switch to something more secure. Anyway it is a
big step forward from Murmurhash, for which it is trivial to
generate *seed independent* colliding keys... The speed
penatly introduced by SipHash 2-4, around 4%, was a too big
price to pay compared to the effectiveness of the HashDoS
attack against SipHash 1-2, and considering so far in the
Redis history, no such an incident ever happened even while
using trivially to collide hash functions.
1. Refactor memory overhead computation into a function.
2. Every 10 keys evicted, check if memory usage already reached
the target value directly, since we otherwise don't count all
the memory reclaimed by the background thread right now.
1. Refactor memory overhead computation into a function.
2. Every 10 keys evicted, check if memory usage already reached
the target value directly, since we otherwise don't count all
the memory reclaimed by the background thread right now.
1. Refactor memory overhead computation into a function.
2. Every 10 keys evicted, check if memory usage already reached
the target value directly, since we otherwise don't count all
the memory reclaimed by the background thread right now.
This change attempts to switch to an hash function which mitigates
the effects of the HashDoS attack (denial of service attack trying
to force data structures to worst case behavior) while at the same time
providing Redis with an hash function that does not expect the input
data to be word aligned, a condition no longer true now that sds.c
strings have a varialbe length header.
Note that it is possible sometimes that even using an hash function
for which collisions cannot be generated without knowing the seed,
special implementation details or the exposure of the seed in an
indirect way (for example the ability to add elements to a Set and
check the return in which Redis returns them with SMEMBERS) may
make the attacker's life simpler in the process of trying to guess
the correct seed, however the next step would be to switch to a
log(N) data structure when too many items in a single bucket are
detected: this seems like an overkill in the case of Redis.
SPEED REGRESION TESTS:
In order to verify that switching from MurmurHash to SipHash had
no impact on speed, a set of benchmarks involving fast insertion
of 5 million of keys were performed.
The result shows Redis with SipHash in high pipelining conditions
to be about 4% slower compared to using the previous hash function.
However this could partially be related to the fact that the current
implementation does not attempt to hash whole words at a time but
reads single bytes, in order to have an output which is endian-netural
and at the same time working on systems where unaligned memory accesses
are a problem.
Further X86 specific optimizations should be tested, the function
may easily get at the same level of MurMurHash2 if a few optimizations
are performed.
This change attempts to switch to an hash function which mitigates
the effects of the HashDoS attack (denial of service attack trying
to force data structures to worst case behavior) while at the same time
providing Redis with an hash function that does not expect the input
data to be word aligned, a condition no longer true now that sds.c
strings have a varialbe length header.
Note that it is possible sometimes that even using an hash function
for which collisions cannot be generated without knowing the seed,
special implementation details or the exposure of the seed in an
indirect way (for example the ability to add elements to a Set and
check the return in which Redis returns them with SMEMBERS) may
make the attacker's life simpler in the process of trying to guess
the correct seed, however the next step would be to switch to a
log(N) data structure when too many items in a single bucket are
detected: this seems like an overkill in the case of Redis.
SPEED REGRESION TESTS:
In order to verify that switching from MurmurHash to SipHash had
no impact on speed, a set of benchmarks involving fast insertion
of 5 million of keys were performed.
The result shows Redis with SipHash in high pipelining conditions
to be about 4% slower compared to using the previous hash function.
However this could partially be related to the fact that the current
implementation does not attempt to hash whole words at a time but
reads single bytes, in order to have an output which is endian-netural
and at the same time working on systems where unaligned memory accesses
are a problem.
Further X86 specific optimizations should be tested, the function
may easily get at the same level of MurMurHash2 if a few optimizations
are performed.
This change attempts to switch to an hash function which mitigates
the effects of the HashDoS attack (denial of service attack trying
to force data structures to worst case behavior) while at the same time
providing Redis with an hash function that does not expect the input
data to be word aligned, a condition no longer true now that sds.c
strings have a varialbe length header.
Note that it is possible sometimes that even using an hash function
for which collisions cannot be generated without knowing the seed,
special implementation details or the exposure of the seed in an
indirect way (for example the ability to add elements to a Set and
check the return in which Redis returns them with SMEMBERS) may
make the attacker's life simpler in the process of trying to guess
the correct seed, however the next step would be to switch to a
log(N) data structure when too many items in a single bucket are
detected: this seems like an overkill in the case of Redis.
SPEED REGRESION TESTS:
In order to verify that switching from MurmurHash to SipHash had
no impact on speed, a set of benchmarks involving fast insertion
of 5 million of keys were performed.
The result shows Redis with SipHash in high pipelining conditions
to be about 4% slower compared to using the previous hash function.
However this could partially be related to the fact that the current
implementation does not attempt to hash whole words at a time but
reads single bytes, in order to have an output which is endian-netural
and at the same time working on systems where unaligned memory accesses
are a problem.
Further X86 specific optimizations should be tested, the function
may easily get at the same level of MurMurHash2 if a few optimizations
are performed.
GCC will produce certain unaligned multi load-store instructions
that will be trapped by the Linux kernel since ARM v6 cannot
handle them with unaligned addresses. Better to use the slower
but safer implementation instead of generating the exception which
should be anyway very slow.
GCC will produce certain unaligned multi load-store instructions
that will be trapped by the Linux kernel since ARM v6 cannot
handle them with unaligned addresses. Better to use the slower
but safer implementation instead of generating the exception which
should be anyway very slow.
GCC will produce certain unaligned multi load-store instructions
that will be trapped by the Linux kernel since ARM v6 cannot
handle them with unaligned addresses. Better to use the slower
but safer implementation instead of generating the exception which
should be anyway very slow.
I'm not sure how much test Jemalloc gets on ARM, moreover
compiling Redis with Jemalloc support in not very powerful
devices, like most ARMs people will build Redis on, is extremely
slow. It is possible to enable Jemalloc build anyway if needed
by using "make MALLOC=jemalloc".
