Fluentd output plugins support the <buffer>
section to configure the buffering of events. The buffering is handled by the Fluentd core.
Buffer section comes under the <match>
section. It is enabled for those output plugins that support buffered output features.
<match tag.*>
@type file
# ...
<buffer>
# ...
</buffer>
# <buffer> section can only be configured once!
</match>
The @type
parameter of <buffer>
section specifies the type of the buffer plugin:
<buffer>
@type file
</buffer>
Fluentd core bundles file
and memory
buffer plugins i.e.:
Third-party plugins may also be installed and configured.
However, the @type
parameter is not mandatory. If omitted, by default, the buffer plugin specified by the output plugin is used (if possible). Otherwise, the memory
buffer plugin is used.
For the usual workload, the file buffer plugin is recommended. It is more durable for the general use-cases.
The output plugins group events into chunks. Chunk keys, specified as the argument of <buffer>
section, control how to group events into chunks.
<buffer ARGUMENT_CHUNK_KEYS>
# ...
</buffer>
If specified, the chunk key arguments must be comma-separated strings.
In case of no or blank chunk key, the output plugin writes all the matched events into a single chunk until its size exceeds provided that the output plugin itself does not specify any default chunk keys.
<match tag.**>
# ...
<buffer> # <--- No chunk key specified as argument
# ...
</buffer>
</match>
# No chunk keys: All events will be appended into the same chunk.
11:59:30 web.access {"key1":"yay","key2":100} --|
|
12:00:01 web.access {"key1":"foo","key2":200} --|---> CHUNK_A
|
12:00:25 ssh.login {"key1":"yay","key2":100} --|
If a tag
is specified as a chunk key, the output plugin writes events into chunks grouped by tag. Events with different tags will be written into different chunks.
<match tag.**>
# ...
<buffer tag>
# ...
</buffer>
</match>
# Tag chunk key: The events will be grouped into chunks by tag.
11:59:30 web.access {"key1":"yay","key2":100} --|
|---> CHUNK_A
12:00:01 web.access {"key1":"foo","key2":200} --|
12:00:25 ssh.login {"key1":"yay","key2":100} ------> CHUNK_B
If the argument time
and the parameter timekey
(required) are specified, the output plugin writes events into chunks grouped by time key.
Time key is calculated like this:
time (unix time) / timekey (seconds)
For example:
-
timekey 60:
["12:00:00", ..., "12:00:59"]
,["12:01:00", ..., "12:01:59"]
,...
-
timekey 180:
["12:00:00", ..., "12:02:59"]
,["12:03:00", ..., "12:05:59"]
,...
-
timekey 3600:
["12:00:00", ..., "12:59:59"]
,["13:00:00", ..., "13:59:59"]
,...
The events will be grouped into chunks by their time range. They will be flushed by the output plugin after the expiration of the time key range.
<match tag.**>
# ...
<buffer time>
timekey 1h # chunks per hours ("3600" also available)
timekey_wait 5m # 5mins delay for flush ("300" also available)
</buffer>
</match>
# Time chunk key: The events will be grouped by timekey with timekey_wait delay.
11:59:30 web.access {"key1":"yay","key2":100} ------> CHUNK_A
12:00:01 web.access {"key1":"foo","key2":200} --|
|---> CHUNK_B
12:00:25 ssh.login {"key1":"yay","key2":100} --|
The timekey_wait
parameter configures the flush delay for events. The default is 600 (10 minutes).
The event time is normally the delayed time from the current timestamp. Fluentd will wait to flush the buffered chunks for delayed events. For example, the figure below shows when the chunks (timekey: 3600) will be flushed actually, for sample timekey_wait
values:
timekey: 3600
-------------------------------------------------------
time range for chunk | timekey_wait | actual flush time
12:00:00 - 12:59:59 | 0s | 13:00:00
12:00:00 - 12:59:59 | 60s (1m) | 13:01:00
12:00:00 - 12:59:59 | 600s (10m) | 13:10:00
The other (non-time/non-tag) keys are handled as the field names of records. The output plugin will group events into chunks by the value of these fields.
<match tag.**>
# ...
<buffer key1>
# ...
</buffer>
</match>
# Chunk keys: The events will be grouped by values of "key1".
11:59:30 web.access {"key1":"yay","key2":100} --|---> CHUNK_A
|
12:00:01 web.access {"key1":"foo","key2":200} --|---> CHUNK_B
|
12:00:25 ssh.login {"key1":"yay","key2":100} --|---> CHUNK_A
The nested field(s) may be specified using the record_accessor
syntax.
Example:
<match tag.**>
# ...
<buffer $.nest.field> # access record['nest']['field']
# ...
</buffer>
</match>
Two or more chunk keys may be combined together. The events will be grouped into chunks by the combination of the values of these combined chunk keys.
# <buffer tag,time>
11:58:01 ssh.login {"key1":"yay","key2":100} ------> CHUNK_A
11:59:13 web.access {"key1":"yay","key2":100} --|
|---> CHUNK_B
11:59:30 web.access {"key1":"yay","key2":100} --|
12:00:01 web.access {"key1":"foo","key2":200} ------> CHUNK_C
12:00:25 ssh.login {"key1":"yay","key2":100} ------> CHUNK_D
NOTE: There is no hard limit on the total number of chunk keys. But, too many chunk keys may degrade the I/O performance and/or increase the total resource utilization.
Buffer chunk keys may be specified empty by using []
as the buffer
section argument.
<match tag.**>
# ...
<buffer []>
# ...
</buffer>
</match>
This is particularly useful when the output plugin has its own default chunk keys and it needs to disable those.
When the chunk keys are specified, these values can be extracted in configuration parameter values. It depends on whether the plugin applies a method(extract_placeholders
) on configuration values or not.
The following configuration shows file
output plugin that applies extract_placeholders
on path
:
# chunk_key: tag
# ${tag} will be replaced with actual tag string
<match log.*>
@type file
path /data/${tag}/access.log #=> "/data/log.map/access.log"
<buffer tag>
# ...
</buffer>
</match>
The value of timekey
in buffer chunk keys can be extracted using strptime
placeholders. The extracted time value is the first second of the timekey range.
Example:
# chunk_key: tag and time
# ${tag[1]} will be replaced with 2nd part of tag ("map" of "log.map"), zero-origin index
# %Y, %m, %d, %H, %M, %S: strptime placeholder are available when "time" chunk key specified
<match log.*>
@type file
path /data/${tag[1]}/access.%Y-%m-%d.%H%M.log #=> "/data/map/access.2017-02-28.20:48.log"
<buffer tag,time>
timekey 1m
</buffer>
</match>
Any key is acceptable as a chunk key. If a key other than specified in the chunk keys is referenced, Fluentd raises configuration errors.
<match log.*>
@type file
path /data/${tag}/access.${key1}.log #=> "/data/log.map/access.yay.log"
<buffer tag,key1>
# ...
</buffer>
</match>
${chunk_id}
will be replaced with internal chunk id. No need to specify chunk_id
in chunk keys.
<match test.**>
@type file
path /path/to/app_${tag}_${chunk_id}
append true
<buffer tag>
flush_interval 5s
</buffer>
</match>
The result with test.foo
tag is like below:
# 5b35967b2d6c93cb19735b7f7d19100c is chunk id
/path/to/app_test.foo_5b35967b2d6c93cb19735b7f7d19100c.log
This placeholder is useful for identifying chunks, e.g. secondary_file
, s3
and more.
Same with chunk keys:
<match log.*>
@type file
path /data/${tag}/access.${$.nest.field}.log #=> "/data/log.map/access.nested_yay.log"
<buffer tag,$.nest.field> # access record['nest']['field']
# ...
</buffer>
</match>
It is an array of chunk keys that must be a list of comma-separated strings. It can also be left blank.
<buffer> # blank
# ...
</buffer>
<buffer tag, time, key1> # keys
# ...
</buffer>
NOTE: The tag
and time
chunk keys are reserved for tag and time and cannot be used for the record fields.
With time
, the following parameters are available:
timekey
[time]-
Required (no default value)
-
Output plugin will flush chunks per specified time (enabled when
time
is specified in chunk keys)
-
timekey_wait
[time]-
Default: 600 (10m)
-
Output plugin will write chunks after
timekey_wait
seconds later aftertimekey
expiration -
If a user configures
timekey 60m
, output plugin will wait delayedevents for flushed
timekey
and write the chunk at 10 minutes of eachhour
-
timekey_use_utc
[bool]-
Default: false (to use local timezone)
-
Output plugin decides to use UTC or not to format placeholders using
timekey
-
timekey_zone
[string]-
Default: local timezone
-
The timezone (
-0700
orAsia/Tokyo
) string for formatting timekeyplaceholders
-
The @type
parameter specifies the type of the buffer plugin. The default type is memory
for bare output plugin but it may be overridden by the output plugin implementations.
For example, the default is file
buffer plugin for the file
output plugin:
<buffer>
@type file
# ...
</buffer>
Following are the configuration parameters for buffer plugin and its chunks:
chunk_limit_size
[size]-
Default: 8MB (memory) / 256MB (file)
-
The max size of each chunks: events will be written into chunks until
the size of chunks become this size
-
chunk_limit_records
[integer]- Optional
- The max number of events that each chunks can store in it
total_limit_size
[size]-
Default: 512MB (memory) / 64GB (file)
-
The size limitation of this buffer plugin instance
-
Once the total size of stored buffer reached this threshold, all append
operations will fail with error (and data will be lost)
-
queue_limit_length
[integer]-
Default:
nil
-
The queue length limitation of this buffer plugin instance
-
This parameter is for v0.12 compatibility.
Use
total_limit_size
instead for v1 configuration.
-
chunk_full_threshold
[float]-
Default: 0.95
-
The percentage of chunk size threshold for flushing
-
output plugin will flush the chunk when actual size reaches
chunk_limit_size * chunk_full_threshold (== 8MB * 0.95 in default)
-
queued_chunks_limit_size
[integer] (since v1.1.3)-
Default: 1 (equals to the same value as the
flush_thread_count
parameter)
-
Limit the number of queued chunks.
-
If a smaller
flush_interval
is set, e.g. 1s, there are lots of smallqueued chunks in the buffer. With file buffer, it may consume a lot of
fd resources when output destination has a problem. This parameter
mitigates such situations.
-
compress
[enum:text
/gzip
]-
Default:
text
-
If
gzip
is set, Fluentd compresses data records before writing tobuffer chunks.
-
Fluentd will decompress these compressed chunks automatically before
passing them to the output plugin (The exceptional case is when the
output plugin can transfer data in compressed form. In this case, the
data will be passed to the plugin as is).
-
The default
text
means that no compression is applied.
-
Following are the flushing parameters for chunks to optimize performance (latency and throughput):
flush_at_shutdown
[bool]-
Default:
false
for persistent buffers (e.g.buf_file
),true
fornon-persistent buffers (e.g.
buf_memory
) -
This specifies whether to flush/write all buffer chunks on shutdown or
not
-
flush_mode
[enum:default
/lazy
/interval
/immediate
]-
Default:
default
(equals tolazy
iftime
is specified as chunkkey,
interval
otherwise) -
lazy
: flushes/writes chunks once per timekey -
interval
: flushes/writes chunks per specified time viaflush_interval
-
immediate
: flushes/writes chunks immediately after events are appendedinto chunks
-
flush_interval
[time]- Default: 60s
flush_thread_count
[integer]- Default: 1
- The number of threads to flush/write chunks in parallel
flush_thread_interval
[float]-
Default: 1.0
-
The sleep interval (seconds) for threads to wait for the next flush try
(when no chunks are waiting)
-
flush_thread_burst_interval
[float]-
Default: 1.0
-
The sleep interval (seconds) for threads between flushes when the output
plugin flushes the waiting chunks to the next ones
-
delayed_commit_timeout
[time]-
Default: 60
-
The timeout (seconds) until output plugin decides if the async write
operation has failed
-
overflow_action
[enum:throw_exception
/block
/drop_oldest_chunk
]- Default:
throw_exception
- How does output plugin behave when its buffer queue is full?
-
throw_exception
: raises an exception to show the error in log -
block
: wait until buffer can store more data.After buffer is ready for storing more data, writing buffer is retried.
Because of such behavior,
block
is suitable for processing batch execution,so do not use for improving processing throughput or performance.
-
drop_oldest_chunk
: drops/purges the oldest chunk to accept newlyincoming chunk
-
- Default:
retry_timeout
[time]-
Default: 72h
-
The maximum time (seconds) to retry to flush again the failed chunks,
until the plugin discards the buffer chunks.
If the next retry is going to exceed this time limit, the last retry
will be made at exactly this time limit.
-
retry_forever
[bool]-
Default:
false
-
If true, plugin will ignore
retry_timeout
andretry_max_times
options and retry flushing forever
-
retry_max_times
[integer]- Default:
none
- The maximum number of times to retry to flush the failed chunks
- Default:
retry_secondary_threshold
[float]-
Default: 0.8
-
The ratio of
retry_timeout
to switch to use the secondary whilefailing (maximum valid value is 1.0)
-
retry_type
[enum:exponential_backoff
/periodic
]-
Default:
exponential_backoff
-
exponential_backoff
: wait in seconds will become large exponentiallyper failure
-
periodic
: output plugin will retry periodically with fixed intervals(configured via
retry_wait
)
-
retry_wait
[time]-
Default: 1s
-
Wait in seconds before the next retry to flush or constant factor of
exponential backoff
-
retry_exponential_backoff_base
[float]- Default: 2
- The base number of exponential backoff for retries
retry_max_interval
[time]-
Default: none
-
The maximum interval (seconds) for exponential backoff between retries
while failing
-
retry_randomize
[bool]-
Default: true
-
If true, the output plugin will retry after randomized interval not to
do burst retries
-
disable_chunk_backup
[bool]-
Default: false
-
Instead of storing unrecoverable chunks in the backup directory, just
discard them. This option is new in Fluentd v1.2.6.
-
With exponential_backoff
, retry_wait
interval will be calculated as below:
- c: constant factor,
@retry_wait
- b: base factor,
@retry_exponential_backoff_base
- k: number of retry times
- total retry time:
c + c*b^1 + (...) + c*b^(k-1) = c*(b^k - 1) / (b - 1)
- =
2^k - 1
by default
- =
If this article is incorrect or outdated, or omits critical information, please let us know. Fluentd is an open-source project under Cloud Native Computing Foundation (CNCF). All components are available under the Apache 2 License.