1. Add `redis-server test all` support to run all tests.
2. Add redis test to daily ci.
3. Add `--accurate` option to run slow tests for more iterations (so that
by default we run less cycles (shorter time, and less prints).
4. Move dict benchmark to REDIS_TEST.
5. fix some leaks in tests
6. make quicklist tests run on a specific fill set of options rather than huge ranges
7. move some prints in quicklist test outside their loops to reduce prints
8. removing sds.h from dict.c since it is now used in both redis-server and
redis-cli (uses hiredis sds)
The `dict` field `iterators` is misleading and incorrect.
This variable is used for 1 purpose - to pause rehashing.
The current `iterators` field doesn't actually count "iterators".
It counts "safe iterators". But - it doesn't actually count safe iterators
either. For one, it's only incremented once the safe iterator begins to
iterate, not when it's created. It's also incremented in `dictScan` to
prevent rehashing (and commented to make it clear why `iterators` is
being incremented during a scan).
This update renames the field as `pauserehash` and creates 2 helper
macros `dictPauseRehashing(d)` and `dictResumeRehashing(d)`
When a database on a 64 bit build grows past 2^31 keys, the underlying hash table expands to 2^32 buckets. After this point, the algorithms for selecting random elements only return elements from half of the available buckets because they use random() which has a range of 0 to 2^31 - 1. This causes problems for eviction policies which use dictGetSomeKeys or dictGetRandomKey. Over time they cause the hash table to become unbalanced because, while new keys are spread out evenly across all buckets, evictions come from only half of the available buckets. Eventually this half of the table starts to run out of keys and it takes longer and longer to find candidates for eviction. This continues until no more evictions can happen.
This solution addresses this by using a 64 bit PRNG instead of libc random().
Co-authored-by: Greg Femec <gfemec@google.com>
As we know, redis may reject user's requests or evict some keys if
used memory is over maxmemory. Dictionaries expanding may make
things worse, some big dictionaries, such as main db and expires dict,
may eat huge memory at once for allocating a new big hash table and be
far more than maxmemory after expanding.
There are related issues: #4213#4583
More details, when expand dict in redis, we will allocate a new big
ht[1] that generally is double of ht[0], The size of ht[1] will be
very big if ht[0] already is big. For db dict, if we have more than
64 million keys, we need to cost 1GB for ht[1] when dict expands.
If the sum of used memory and new hash table of dict needed exceeds
maxmemory, we shouldn't allow the dict to expand. Because, if we
enable keys eviction, we still couldn't add much more keys after
eviction and rehashing, what's worse, redis will keep less keys when
redis only remains a little memory for storing new hash table instead
of users' data. Moreover users can't write data in redis if disable
keys eviction.
What this commit changed ?
Add a new member function expandAllowed for dict type, it provide a way
for caller to allow expand or not. We expose two parameters for this
function: more memory needed for expanding and dict current load factor,
users can implement a function to make a decision by them.
For main db dict and expires dict type, these dictionaries may be very
big and cost huge memory for expanding, so we implement a judgement
function: we can stop dict to expand provisionally if used memory will
be over maxmemory after dict expands, but to guarantee the performance
of redis, we still allow dict to expand if dict load factor exceeds the
safe load factor.
Add test cases to verify we don't allow main db to expand when left
memory is not enough, so that avoid keys eviction.
Other changes:
For new hash table size when expand. Before this commit, the size is
that double used of dict and later _dictNextPower. Actually we aim to
control a dict load factor between 0.5 and 1.0. Now we replace *2 with
+1, since the first check is that used >= size, the outcome of before
will usually be the same as _dictNextPower(used+1). The only case where
it'll differ is when dict_can_resize is false during fork, so that later
the _dictNextPower(used*2) will cause the dict to jump to *4 (i.e.
_dictNextPower(1025*2) will return 4096).
Fix rehash test cases due to changing algorithm of new hash table size
when expand.
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.
Notes by @antirez:
This patch was picked from a larger commit by Oran and adapted to change
the API a bit. The basic idea is to avoid double lookups when there is
to use the value of the deleted entry.
BEFORE:
entry = dictFind( ... ); /* 1st lookup. */
/* Do somethjing with the entry. */
dictDelete(...); /* 2nd lookup. */
AFTER:
entry = dictUnlink( ... ); /* 1st lookup. */
/* Do somethjing with the entry. */
dictFreeUnlinkedEntry(entry); /* No lookups!. */
The command reports information about the hash table internal state
representing the specified database ID.
This can be used in order to investigate rehashings, memory usage issues
and for other debugging purposes.
The old version of SPOP with "count" argument used an API call of dict.c
which was actually designed for a different goal, and was not capable of
good distribution. We follow a different three-cases approach optimized
for different ratiion between sets and requested number of elements.
The implementation is simpler and allowed the removal of a large amount
of code.
This allows to support datasets with more than 2 billion of keys
(possible in very large memory instances, this bug was actually
reported).
Closes issue #1814.
This new function is useful to get a number of random entries from an
hash table when we just need to do some sampling without particularly
good distribution.
It just jumps at a random place of the hash table and returns the first
N items encountered by scanning linearly.
The main usefulness of this function is to speedup Redis internal
sampling of the key space, for example for key eviction or expiry.
Redis hash table implementation has many non-blocking features like
incremental rehashing, however while deleting a large hash table there
was no way to have a callback called to do some incremental work.
This commit adds this support, as an optiona callback argument to
dictEmpty() that is currently called at a fixed interval (one time every
65k deletions).
dict.c allows the user to create unsafe iterators, that are iterators
that will not touch the dictionary data structure in any way, preventing
copy on write, but at the same time are limited in their usage.
The limitation is that when itearting with an unsafe iterator, no call
to other dictionary functions must be done inside the iteration loop,
otherwise the dictionary may be incrementally rehashed resulting into
missing elements in the set of the elements returned by the iterator.
However after introducing this kind of iterators a number of bugs were
found due to misuses of the API, and we are still finding
bugs about this issue. The bugs are not trivial to track because the
effect is just missing elements during the iteartion.
This commit introduces auto-detection of the API misuse. The idea is
that an unsafe iterator has a contract: from initialization to the
release of the iterator the dictionary should not change.
So we take a fingerprint of the dictionary state, xoring a few important
dict properties when the unsafe iteartor is initialized. We later check
when the iterator is released if the fingerprint is still the same. If it
is not, we found a misuse of the iterator, as not allowed API calls
changed the internal state of the dictionary.
This code was checked against a real bug, issue #1240.
This is what Redis prints (aborting) when a misuse is detected:
Assertion failed: (iter->fingerprint == dictFingerprint(iter->d)),
function dictReleaseIterator, file dict.c, line 587.
The previously used hash function, djbhash, is not secure against
collision attacks even when the seed is randomized as there are simple
ways to find seed-independent collisions.
The new hash function appears to be safe (or much harder to exploit at
least) in this case, and has better distribution.
Better distribution does not always means that's better. For instance in
a fast benchmark with "DEBUG POPULATE 1000000" I obtained the following
results:
1.6 seconds with djbhash
2.0 seconds with murmurhash2
This is due to the fact that djbhash will hash objects that follow the
pattern `prefix:<id>` and where the id is numerically near, to near
buckets. This improves the locality.
However in other access patterns with keys that have no relation
murmurhash2 has some (apparently minimal) speed advantage.
On the other hand a better distribution should significantly
improve the quality of the distribution of elements returned with
dictGetRandomKey() that is used in SPOP, SRANDMEMBER, RANDOMKEY, and
other commands.
Everything considered, and under the suspect that this commit fixes a
security issue in Redis, we are switching to the new hash function.
If some serious speed regression will be found in the future we'll be able
to step back easiliy.
This commit fixes issue #663.
