The new opcode is an hint about the size of the dataset (keys and number
of expires) we are going to load for a given Redis database inside the
RDB file. Since hash tables are resized accordingly ASAP, useless
rehashing is avoided, speeding up load times significantly, in the order
of ~ 20% or more for larger data sets.
Related issue: #1719
This removes:
- list-max-ziplist-entries
- list-max-ziplist-value
This adds:
- list-max-ziplist-size
- list-compress-depth
Also updates config file with new sections and updates
tests to use quicklist settings instead of old list settings.
Let user set how many nodes to *not* compress.
We can specify a compression "depth" of how many nodes
to leave uncompressed on each end of the quicklist.
Depth 0 = disable compression.
Depth 1 = only leave head/tail uncompressed.
- (read as: "skip 1 node on each end of the list before compressing")
Depth 2 = leave head, head->next, tail->prev, tail uncompressed.
- ("skip 2 nodes on each end of the list before compressing")
Depth 3 = Depth 2 + head->next->next + tail->prev->prev
- ("skip 3 nodes...")
etc.
This also:
- updates RDB storage to use native quicklist compression (if node is
already compressed) instead of uncompressing, generating the RDB string,
then re-compressing the quicklist node.
- internalizes the "fill" parameter for the quicklist so we don't
need to pass it to _every_ function. Now it's just a property of
the list.
- allows a runtime-configurable compression option, so we can
expose a compresion parameter in the configuration file if people
want to trade slight request-per-second performance for up to 90%+
memory savings in some situations.
- updates the quicklist tests to do multiple passes: 200k+ tests now.
Turns out it's a huge improvement during save/reload/migrate/restore
because, with compression enabled, we're compressing 4k or 8k
chunks of data consisting of multiple elements in one ziplist
instead of compressing series of smaller individual elements.
This replaces individual ziplist vs. linkedlist representations
for Redis list operations.
Big thanks for all the reviews and feedback from everybody in
https://github.com/antirez/redis/pull/2143
1. Server unxtime may remain not updated while loading AOF, so ETA is
not updated correctly.
2. Number of processed byte was not initialized.
3. Possible division by zero condition (likely cause of issue #1932).
We need to avoid that a child -> slaves transfer can continue forever.
We use the same timeout used as global replication timeout, which is
documented to also affect I/O operations during bulk transfers.
To perform a socket write() for each RDB rio API write call was
extremely unefficient, so now rio has minimal buffering capabilities.
Writes are accumulated into a buffer and only when a given limit is
reacehd are actually wrote to the N slaves FDs.
Trivia: rio lacked support for buffering since our targets were:
1) Memory buffers.
2) C standard I/O.
Both were buffered already.
We need to remember what is the saving strategy of the current RDB child
process, since the configuration may be modified at runtime via CONFIG
SET and still we'll need to understand, when the child exists, what to
do and for what goal the process was initiated: to create an RDB file
on disk or to write stuff directly to slave's sockets.
When we are blocked and a few events a processed from time to time, it
is smarter to call the event handler a few times in order to handle the
accept, read, write, close cycle of a client in a single pass, otherwise
there is too much latency added for clients to receive a reply while the
server is busy in some way (for example during the DB loading).
Previously, the (!fp) would only catch lack of free space
under OS X. Linux waits to discover it can't write until
it actually writes contents to disk.
(fwrite() returns success even if the underlying file
has no free space to write into. All the errors
only show up at flush/sync/close time.)
Fixesantirez/redis#1604
server.unixtime and server.mstime are cached less precise timestamps
that we use every time we don't need an accurate time representation and
a syscall would be too slow for the number of calls we require.
Such an example is the initialization and update process of the last
interaction time with the client, that is used for timeouts.
However rdbLoad() can take some time to load the DB, but at the same
time it did not updated the time during DB loading. This resulted in the
bug described in issue #1535, where in the replication process the slave
loads the DB, creates the redisClient representation of its master, but
the timestamp is so old that the master, under certain conditions, is
sensed as already "timed out".
Thanks to @yoav-steinberg and Redis Labs Inc for the bug report and
analysis.
The previous fix for false positive timeout detected by master was not
complete. There is another blocking stage while loading data for the
first synchronization with the master, that is, flushing away the
current data from the DB memory.
This commit uses the newly introduced dict.c callback in order to make
some incremental work (to send "\n" heartbeats to the master) while
flushing the old data from memory.
It is hard to write a regression test for this issue unfortunately. More
support for debugging in the Redis core would be needed in terms of
functionalities to simulate a slow DB loading / deletion.
Starting with Redis 2.8 masters are able to detect timed out slaves,
while before 2.8 only slaves were able to detect a timed out master.
Now that timeout detection is bi-directional the following problem
happens as described "in the field" by issue #1449:
1) Master and slave setup with big dataset.
2) Slave performs the first synchronization, or a full sync
after a failed partial resync.
3) Master sends the RDB payload to the slave.
4) Slave loads this payload.
5) Master detects the slave as timed out since does not receive back the
REPLCONF ACK acknowledges.
Here the problem is that the master has no way to know how much the
slave will take to load the RDB file in memory. The obvious solution is
to use a greater replication timeout setting, but this is a shame since
for the 0.1% of operation time we are forced to use a timeout that is
not what is suited for 99.9% of operation time.
This commit tries to fix this problem with a solution that is a bit of
an hack, but that modifies little of the replication internals, in order
to be back ported to 2.8 safely.
During the RDB loading time, we send the master newlines to avoid
being sensed as timed out. This is the same that the master already does
while saving the RDB file to still signal its presence to the slave.
The single newline is used because:
1) It can't desync the protocol, as it is only transmitted all or
nothing.
2) It can be safely sent while we don't have a client structure for the
master or in similar situations just with write(2).
Previously two string encodings were used for string objects:
1) REDIS_ENCODING_RAW: a string object with obj->ptr pointing to an sds
stirng.
2) REDIS_ENCODING_INT: a string object where the obj->ptr void pointer
is casted to a long.
This commit introduces a experimental new encoding called
REDIS_ENCODING_EMBSTR that implements an object represented by an sds
string that is not modifiable but allocated in the same memory chunk as
the robj structure itself.
The chunk looks like the following:
+--------------+-----------+------------+--------+----+
| robj data... | robj->ptr | sds header | string | \0 |
+--------------+-----+-----+------------+--------+----+
| ^
+-----------------------+
The robj->ptr points to the contiguous sds string data, so the object
can be manipulated with the same functions used to manipulate plan
string objects, however we need just on malloc and one free in order to
allocate or release this kind of objects. Moreover it has better cache
locality.
This new allocation strategy should benefit both the memory usage and
the performances. A performance gain between 60 and 70% was observed
during micro-benchmarks, however there is more work to do to evaluate
the performance impact and the memory usage behavior.
When a BGSAVE fails, Redis used to flood itself trying to BGSAVE at
every next cron call, that is either 10 or 100 times per second
depending on configuration and server version.
This commit does not allow a new automatic BGSAVE attempt to be
performed before a few seconds delay (currently 5).
This avoids both the auto-flood problem and filling the disk with
logs at a serious rate.
The five seconds limit, considering a log entry of 200 bytes, will use
less than 4 MB of disk space per day that is reasonable, the sysadmin
should notice before of catastrofic events especially since by default
Redis will stop serving write queries after the first failed BGSAVE.
This fixes issue #849
This fixes cases where the RDB file does exist but can't be accessed for
any reason. For instance, when the Redis process doesn't have enough
permissions on the file.
