2024-11-14

.ddev/redis/advanced.conf

@@ -0,0 +1,341 @@
+# #ddev-generated
+############################### ADVANCED CONFIG ###############################
+
+# Hashes are encoded using a memory efficient data structure when they have a
+# small number of entries, and the biggest entry does not exceed a given
+# threshold. These thresholds can be configured using the following directives.
+hash-max-ziplist-entries 512
+hash-max-ziplist-value 64
+
+# Lists are also encoded in a special way to save a lot of space.
+# The number of entries allowed per internal list node can be specified
+# as a fixed maximum size or a maximum number of elements.
+# For a fixed maximum size, use -5 through -1, meaning:
+# -5: max size: 64 Kb  <-- not recommended for normal workloads
+# -4: max size: 32 Kb  <-- not recommended
+# -3: max size: 16 Kb  <-- probably not recommended
+# -2: max size: 8 Kb   <-- good
+# -1: max size: 4 Kb   <-- good
+# Positive numbers mean store up to _exactly_ that number of elements
+# per list node.
+# The highest performing option is usually -2 (8 Kb size) or -1 (4 Kb size),
+# but if your use case is unique, adjust the settings as necessary.
+list-max-ziplist-size -2
+
+# Lists may also be compressed.
+# Compress depth is the number of quicklist ziplist nodes from *each* side of
+# the list to *exclude* from compression.  The head and tail of the list
+# are always uncompressed for fast push/pop operations.  Settings are:
+# 0: disable all list compression
+# 1: depth 1 means "don't start compressing until after 1 node into the list,
+#    going from either the head or tail"
+#    So: [head]->node->node->...->node->[tail]
+#    [head], [tail] will always be uncompressed; inner nodes will compress.
+# 2: [head]->[next]->node->node->...->node->[prev]->[tail]
+#    2 here means: don't compress head or head->next or tail->prev or tail,
+#    but compress all nodes between them.
+# 3: [head]->[next]->[next]->node->node->...->node->[prev]->[prev]->[tail]
+# etc.
+list-compress-depth 0
+
+# Sets have a special encoding in just one case: when a set is composed
+# of just strings that happen to be integers in radix 10 in the range
+# of 64 bit signed integers.
+# The following configuration setting sets the limit in the size of the
+# set in order to use this special memory saving encoding.
+set-max-intset-entries 512
+
+# Similarly to hashes and lists, sorted sets are also specially encoded in
+# order to save a lot of space. This encoding is only used when the length and
+# elements of a sorted set are below the following limits:
+zset-max-ziplist-entries 128
+zset-max-ziplist-value 64
+
+# HyperLogLog sparse representation bytes limit. The limit includes the
+# 16 bytes header. When an HyperLogLog using the sparse representation crosses
+# this limit, it is converted into the dense representation.
+#
+# A value greater than 16000 is totally useless, since at that point the
+# dense representation is more memory efficient.
+#
+# The suggested value is ~ 3000 in order to have the benefits of
+# the space efficient encoding without slowing down too much PFADD,
+# which is O(N) with the sparse encoding. The value can be raised to
+# ~ 10000 when CPU is not a concern, but space is, and the data set is
+# composed of many HyperLogLogs with cardinality in the 0 - 15000 range.
+hll-sparse-max-bytes 3000
+
+# Streams macro node max size / items. The stream data structure is a radix
+# tree of big nodes that encode multiple items inside. Using this configuration
+# it is possible to configure how big a single node can be in bytes, and the
+# maximum number of items it may contain before switching to a new node when
+# appending new stream entries. If any of the following settings are set to
+# zero, the limit is ignored, so for instance it is possible to set just a
+# max entires limit by setting max-bytes to 0 and max-entries to the desired
+# value.
+stream-node-max-bytes 4096
+stream-node-max-entries 100
+
+# Active rehashing uses 1 millisecond every 100 milliseconds of CPU time in
+# order to help rehashing the main Redis hash table (the one mapping top-level
+# keys to values). The hash table implementation Redis uses (see dict.c)
+# performs a lazy rehashing: the more operation you run into a hash table
+# that is rehashing, the more rehashing "steps" are performed, so if the
+# server is idle the rehashing is never complete and some more memory is used
+# by the hash table.
+#
+# The default is to use this millisecond 10 times every second in order to
+# actively rehash the main dictionaries, freeing memory when possible.
+#
+# If unsure:
+# use "activerehashing no" if you have hard latency requirements and it is
+# not a good thing in your environment that Redis can reply from time to time
+# to queries with 2 milliseconds delay.
+#
+# use "activerehashing yes" if you don't have such hard requirements but
+# want to free memory asap when possible.
+activerehashing yes
+
+# The client output buffer limits can be used to force disconnection of clients
+# that are not reading data from the server fast enough for some reason (a
+# common reason is that a Pub/Sub client can't consume messages as fast as the
+# publisher can produce them).
+#
+# The limit can be set differently for the three different classes of clients:
+#
+# normal -> normal clients including MONITOR clients
+# replica  -> replica clients
+# pubsub -> clients subscribed to at least one pubsub channel or pattern
+#
+# The syntax of every client-output-buffer-limit directive is the following:
+#
+# client-output-buffer-limit <class> <hard limit> <soft limit> <soft seconds>
+#
+# A client is immediately disconnected once the hard limit is reached, or if
+# the soft limit is reached and remains reached for the specified number of
+# seconds (continuously).
+# So for instance if the hard limit is 32 megabytes and the soft limit is
+# 16 megabytes / 10 seconds, the client will get disconnected immediately
+# if the size of the output buffers reach 32 megabytes, but will also get
+# disconnected if the client reaches 16 megabytes and continuously overcomes
+# the limit for 10 seconds.
+#
+# By default normal clients are not limited because they don't receive data
+# without asking (in a push way), but just after a request, so only
+# asynchronous clients may create a scenario where data is requested faster
+# than it can read.
+#
+# Instead there is a default limit for pubsub and replica clients, since
+# subscribers and replicas receive data in a push fashion.
+#
+# Both the hard or the soft limit can be disabled by setting them to zero.
+client-output-buffer-limit normal 0 0 0
+client-output-buffer-limit replica 256mb 64mb 60
+client-output-buffer-limit pubsub 32mb 8mb 60
+
+# Client query buffers accumulate new commands. They are limited to a fixed
+# amount by default in order to avoid that a protocol desynchronization (for
+# instance due to a bug in the client) will lead to unbound memory usage in
+# the query buffer. However you can configure it here if you have very special
+# needs, such us huge multi/exec requests or alike.
+#
+# client-query-buffer-limit 1gb
+
+# In the Redis protocol, bulk requests, that are, elements representing single
+# strings, are normally limited to 512 mb. However you can change this limit
+# here, but must be 1mb or greater
+#
+# proto-max-bulk-len 512mb
+
+# Redis calls an internal function to perform many background tasks, like
+# closing connections of clients in timeout, purging expired keys that are
+# never requested, and so forth.
+#
+# Not all tasks are performed with the same frequency, but Redis checks for
+# tasks to perform according to the specified "hz" value.
+#
+# By default "hz" is set to 10. Raising the value will use more CPU when
+# Redis is idle, but at the same time will make Redis more responsive when
+# there are many keys expiring at the same time, and timeouts may be
+# handled with more precision.
+#
+# The range is between 1 and 500, however a value over 100 is usually not
+# a good idea. Most users should use the default of 10 and raise this up to
+# 100 only in environments where very low latency is required.
+hz 10
+
+# Normally it is useful to have an HZ value which is proportional to the
+# number of clients connected. This is useful in order, for instance, to
+# avoid too many clients are processed for each background task invocation
+# in order to avoid latency spikes.
+#
+# Since the default HZ value by default is conservatively set to 10, Redis
+# offers, and enables by default, the ability to use an adaptive HZ value
+# which will temporarily raise when there are many connected clients.
+#
+# When dynamic HZ is enabled, the actual configured HZ will be used
+# as a baseline, but multiples of the configured HZ value will be actually
+# used as needed once more clients are connected. In this way an idle
+# instance will use very little CPU time while a busy instance will be
+# more responsive.
+dynamic-hz yes
+
+# When a child rewrites the AOF file, if the following option is enabled
+# the file will be fsync-ed every 32 MB of data generated. This is useful
+# in order to commit the file to the disk more incrementally and avoid
+# big latency spikes.
+aof-rewrite-incremental-fsync yes
+
+# When redis saves RDB file, if the following option is enabled
+# the file will be fsync-ed every 32 MB of data generated. This is useful
+# in order to commit the file to the disk more incrementally and avoid
+# big latency spikes.
+rdb-save-incremental-fsync yes
+
+# Redis LFU eviction (see maxmemory setting) can be tuned. However it is a good
+# idea to start with the default settings and only change them after investigating
+# how to improve the performances and how the keys LFU change over time, which
+# is possible to inspect via the OBJECT FREQ command.
+#
+# There are two tunable parameters in the Redis LFU implementation: the
+# counter logarithm factor and the counter decay time. It is important to
+# understand what the two parameters mean before changing them.
+#
+# The LFU counter is just 8 bits per key, it's maximum value is 255, so Redis
+# uses a probabilistic increment with logarithmic behavior. Given the value
+# of the old counter, when a key is accessed, the counter is incremented in
+# this way:
+#
+# 1. A random number R between 0 and 1 is extracted.
+# 2. A probability P is calculated as 1/(old_value*lfu_log_factor+1).
+# 3. The counter is incremented only if R < P.
+#
+# The default lfu-log-factor is 10. This is a table of how the frequency
+# counter changes with a different number of accesses with different
+# logarithmic factors:
+#
+# +--------+------------+------------+------------+------------+------------+
+# | factor | 100 hits   | 1000 hits  | 100K hits  | 1M hits    | 10M hits   |
+# +--------+------------+------------+------------+------------+------------+
+# | 0      | 104        | 255        | 255        | 255        | 255        |
+# +--------+------------+------------+------------+------------+------------+
+# | 1      | 18         | 49         | 255        | 255        | 255        |
+# +--------+------------+------------+------------+------------+------------+
+# | 10     | 10         | 18         | 142        | 255        | 255        |
+# +--------+------------+------------+------------+------------+------------+
+# | 100    | 8          | 11         | 49         | 143        | 255        |
+# +--------+------------+------------+------------+------------+------------+
+#
+# NOTE: The above table was obtained by running the following commands:
+#
+#   redis-benchmark -n 1000000 incr foo
+#   redis-cli object freq foo
+#
+# NOTE 2: The counter initial value is 5 in order to give new objects a chance
+# to accumulate hits.
+#
+# The counter decay time is the time, in minutes, that must elapse in order
+# for the key counter to be divided by two (or decremented if it has a value
+# less <= 10).
+#
+# The default value for the lfu-decay-time is 1. A special value of 0 means to
+# decay the counter every time it happens to be scanned.
+#
+# lfu-log-factor 10
+# lfu-decay-time 1
+
+############################## DEBUG COMMAND #############################
+
+enable-debug-command yes
+
+########################### ACTIVE DEFRAGMENTATION #######################
+#
+# What is active defragmentation?
+# -------------------------------
+#
+# Active (online) defragmentation allows a Redis server to compact the
+# spaces left between small allocations and deallocations of data in memory,
+# thus allowing to reclaim back memory.
+#
+# Fragmentation is a natural process that happens with every allocator (but
+# less so with Jemalloc, fortunately) and certain workloads. Normally a server
+# restart is needed in order to lower the fragmentation, or at least to flush
+# away all the data and create it again. However thanks to this feature
+# implemented by Oran Agra for Redis 4.0 this process can happen at runtime
+# in a "hot" way, while the server is running.
+#
+# Basically when the fragmentation is over a certain level (see the
+# configuration options below) Redis will start to create new copies of the
+# values in contiguous memory regions by exploiting certain specific Jemalloc
+# features (in order to understand if an allocation is causing fragmentation
+# and to allocate it in a better place), and at the same time, will release the
+# old copies of the data. This process, repeated incrementally for all the keys
+# will cause the fragmentation to drop back to normal values.
+#
+# Important things to understand:
+#
+# 1. This feature is disabled by default, and only works if you compiled Redis
+#    to use the copy of Jemalloc we ship with the source code of Redis.
+#    This is the default with Linux builds.
+#
+# 2. You never need to enable this feature if you don't have fragmentation
+#    issues.
+#
+# 3. Once you experience fragmentation, you can enable this feature when
+#    needed with the command "CONFIG SET activedefrag yes".
+#
+# The configuration parameters are able to fine tune the behavior of the
+# defragmentation process. If you are not sure about what they mean it is
+# a good idea to leave the defaults untouched.
+
+# Enabled active defragmentation
+# activedefrag no
+
+# Minimum amount of fragmentation waste to start active defrag
+# active-defrag-ignore-bytes 100mb
+
+# Minimum percentage of fragmentation to start active defrag
+# active-defrag-threshold-lower 10
+
+# Maximum percentage of fragmentation at which we use maximum effort
+# active-defrag-threshold-upper 100
+
+# Minimal effort for defrag in CPU percentage, to be used when the lower
+# threshold is reached
+# active-defrag-cycle-min 1
+
+# Maximal effort for defrag in CPU percentage, to be used when the upper
+# threshold is reached
+# active-defrag-cycle-max 25
+
+# Maximum number of set/hash/zset/list fields that will be processed from
+# the main dictionary scan
+# active-defrag-max-scan-fields 1000
+
+# Jemalloc background thread for purging will be enabled by default
+jemalloc-bg-thread yes
+
+# It is possible to pin different threads and processes of Redis to specific
+# CPUs in your system, in order to maximize the performances of the server.
+# This is useful both in order to pin different Redis threads in different
+# CPUs, but also in order to make sure that multiple Redis instances running
+# in the same host will be pinned to different CPUs.
+#
+# Normally you can do this using the "taskset" command, however it is also
+# possible to this via Redis configuration directly, both in Linux and FreeBSD.
+#
+# You can pin the server/IO threads, bio threads, aof rewrite child process, and
+# the bgsave child process. The syntax to specify the cpu list is the same as
+# the taskset command:
+#
+# Set redis server/io threads to cpu affinity 0,2,4,6:
+# server_cpulist 0-7:2
+#
+# Set bio threads to cpu affinity 1,3:
+# bio_cpulist 1,3
+#
+# Set aof rewrite child process to cpu affinity 8,9,10,11:
+# aof_rewrite_cpulist 8-11
+#
+# Set bgsave child process to cpu affinity 1,10,11
+# bgsave_cpulist 1,10-11