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authorDaniel Baumann <daniel.baumann@progress-linux.org>2019-10-13 08:36:33 +0000
committerDaniel Baumann <daniel.baumann@progress-linux.org>2019-10-13 08:36:33 +0000
commita30a849b78fa4fe8552141b7b2802d1af1b18c09 (patch)
treefab3c8bf29bf2d565595d4fa6a9413916ff02fee /database/README.md
parentAdding upstream version 1.17.1. (diff)
downloadnetdata-a30a849b78fa4fe8552141b7b2802d1af1b18c09.tar.xz
netdata-a30a849b78fa4fe8552141b7b2802d1af1b18c09.zip
Adding upstream version 1.18.0.upstream/1.18.0
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
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diff --git a/database/README.md b/database/README.md
index 2fcb69b6..143615a0 100644
--- a/database/README.md
+++ b/database/README.md
@@ -1,59 +1,54 @@
# Database
-Although `netdata` does all its calculations using `long double`, it stores all values using
-a [custom-made 32-bit number](../libnetdata/storage_number/).
+Although `netdata` does all its calculations using `long double`, it stores all values using a [custom-made 32-bit
+number](../libnetdata/storage_number/).
-So, for each dimension of a chart, Netdata will need: `4 bytes for the value * the entries
-of its history`. It will not store any other data for each value in the time series database.
-Since all its values are stored in a time series with fixed step, the time each value
-corresponds can be calculated at run time, using the position of a value in the round robin database.
+So, for each dimension of a chart, Netdata will need: `4 bytes for the value * the entries of its history`. It will not
+store any other data for each value in the time series database. Since all its values are stored in a time series with
+fixed step, the time each value corresponds can be calculated at run time, using the position of a value in the round
+robin database.
-The default history is 3.600 entries, thus it will need 14.4KB for each chart dimension.
-If you need 1.000 dimensions, they will occupy just 14.4MB.
+The default history is 3.600 entries, thus it will need 14.4KB for each chart dimension. If you need 1.000 dimensions,
+they will occupy just 14.4MB.
-Of course, 3.600 entries is a very short history, especially if data collection frequency is set
-to 1 second. You will have just one hour of data.
+Of course, 3.600 entries is a very short history, especially if data collection frequency is set to 1 second. You will
+have just one hour of data.
-For a day of data and 1.000 dimensions, you will need: 86.400 seconds * 4 bytes * 1.000
-dimensions = 345MB of RAM.
+For a day of data and 1.000 dimensions, you will need: `86.400 seconds * 4 bytes * 1.000 dimensions = 345MB of RAM`.
-One option you have to lower this number is to use
-**[Memory Deduplication - Kernel Same Page Merging - KSM](#ksm)**. Another possibility is to
-use the **[Database Engine](engine/)**.
+One option you have to lower this number is to use **[Memory Deduplication - Kernel Same Page Merging - KSM](#ksm)**.
+Another possibility is to use the **[Database Engine](engine/)**.
## Memory modes
Currently Netdata supports 6 memory modes:
-1. `ram`, data are purely in memory. Data are never saved on disk. This mode uses `mmap()` and
- supports [KSM](#ksm).
+1. `ram`, data are purely in memory. Data are never saved on disk. This mode uses `mmap()` and supports [KSM](#ksm).
-2. `save`, (the default) data are only in RAM while Netdata runs and are saved to / loaded from
- disk on Netdata restart. It also uses `mmap()` and supports [KSM](#ksm).
+2. `save`, data are only in RAM while Netdata runs and are saved to / loaded from disk on Netdata
+ restart. It also uses `mmap()` and supports [KSM](#ksm).
-3. `map`, data are in memory mapped files. This works like the swap. Keep in mind though, this
- will have a constant write on your disk. When Netdata writes data on its memory, the Linux kernel
- marks the related memory pages as dirty and automatically starts updating them on disk.
- Unfortunately we cannot control how frequently this works. The Linux kernel uses exactly the
- same algorithm it uses for its swap memory. Check below for additional information on running a
- dedicated central Netdata server. This mode uses `mmap()` but does not support [KSM](#ksm).
+3. `map`, data are in memory mapped files. This works like the swap. Keep in mind though, this will have a constant
+ write on your disk. When Netdata writes data on its memory, the Linux kernel marks the related memory pages as dirty
+ and automatically starts updating them on disk. Unfortunately we cannot control how frequently this works. The Linux
+ kernel uses exactly the same algorithm it uses for its swap memory. Check below for additional information on
+ running a dedicated central Netdata server. This mode uses `mmap()` but does not support [KSM](#ksm).
4. `none`, without a database (collected metrics can only be streamed to another Netdata).
-5. `alloc`, like `ram` but it uses `calloc()` and does not support [KSM](#ksm). This mode is the
- fallback for all others except `none`.
+5. `alloc`, like `ram` but it uses `calloc()` and does not support [KSM](#ksm). This mode is the fallback for all
+ others except `none`.
-6. `dbengine`, data are in database files. The [Database Engine](engine/) works like a traditional
- database. There is some amount of RAM dedicated to data caching and indexing and the rest of
- the data reside compressed on disk. The number of history entries is not fixed in this case,
- but depends on the configured disk space and the effective compression ratio of the data stored.
- This is the **only mode** that supports changing the data collection update frequency
- (`update_every`) **without losing** the previously stored metrics.
- For more details see [here](engine/).
+6. `dbengine`, (the default) data are in database files. The [Database Engine](engine/) works like a traditional
+ database. There is some amount of RAM dedicated to data caching and indexing and the rest of the data reside
+ compressed on disk. The number of history entries is not fixed in this case, but depends on the configured disk
+ space and the effective compression ratio of the data stored. This is the **only mode** that supports changing the
+ data collection update frequency (`update_every`) **without losing** the previously stored metrics. For more details
+ see [here](engine/).
You can select the memory mode by editing `netdata.conf` and setting:
-```
+```conf
[global]
# ram, save (the default, save on exit, load on start), map (swap like)
memory mode = save
@@ -69,64 +64,60 @@ Embedded devices usually have very limited RAM resources available.
There are 2 settings for you to tweak:
1. `update every`, which controls the data collection frequency
-2. `history`, which controls the size of the database in RAM
+2. `history`, which controls the size of the database in RAM (except for `memory mode = dbengine`)
-By default `update every = 1` and `history = 3600`. This gives you an hour of data with per
-second updates.
+By default `update every = 1` and `history = 3600`. This gives you an hour of data with per second updates.
-If you set `update every = 2` and `history = 1800`, you will still have an hour of data, but
-collected once every 2 seconds. This will **cut in half** both CPU and RAM resources consumed
-by Netdata. Of course experiment a bit. On very weak devices you might have to use
-`update every = 5` and `history = 720` (still 1 hour of data, but 1/5 of the CPU and RAM resources).
+If you set `update every = 2` and `history = 1800`, you will still have an hour of data, but collected once every 2
+seconds. This will **cut in half** both CPU and RAM resources consumed by Netdata. Of course experiment a bit. On very
+weak devices you might have to use `update every = 5` and `history = 720` (still 1 hour of data, but 1/5 of the CPU and
+RAM resources).
-You can also disable [data collection plugins](../collectors) you don't need.
-Disabling such plugins will also free both CPU and RAM resources.
+You can also disable [data collection plugins](../collectors) you don't need. Disabling such plugins will also free both
+CPU and RAM resources.
## Running a dedicated central Netdata server
-Netdata allows streaming data between Netdata nodes. This allows us to have a central Netdata
-server that will maintain the entire database for all nodes, and will also run health checks/alarms
-for all nodes.
+Netdata allows streaming data between Netdata nodes. This allows us to have a central Netdata server that will maintain
+the entire database for all nodes, and will also run health checks/alarms for all nodes.
-For this central Netdata, memory size can be a problem. Fortunately, Netdata supports several
-memory modes. **One interesting option** for this setup is `memory mode = map`.
+For this central Netdata, memory size can be a problem. Fortunately, Netdata supports several memory modes. **One
+interesting option** for this setup is `memory mode = map`.
### map
-In this mode, the database of Netdata is stored in memory mapped files. Netdata continues to read
-and write the database in memory, but the kernel automatically loads and saves memory pages from/to
-disk.
+In this mode, the database of Netdata is stored in memory mapped files. Netdata continues to read and write the database
+in memory, but the kernel automatically loads and saves memory pages from/to disk.
-**We suggest _not_ to use this mode on nodes that run other applications.** There will always be
-dirty memory to be synced and this syncing process may influence the way other applications work.
-This mode however is useful when we need a central Netdata server that would normally need huge
-amounts of memory. Using memory mode `map` we can overcome all memory restrictions.
+**We suggest _not_ to use this mode on nodes that run other applications.** There will always be dirty memory to be
+synced and this syncing process may influence the way other applications work. This mode however is useful when we need
+a central Netdata server that would normally need huge amounts of memory. Using memory mode `map` we can overcome all
+memory restrictions.
-There are a few kernel options that provide finer control on the way this syncing works. But before
-explaining them, a brief introduction of how Netdata database works is needed.
+There are a few kernel options that provide finer control on the way this syncing works. But before explaining them, a
+brief introduction of how Netdata database works is needed.
For each chart, Netdata maps the following files:
-1. `chart/main.db`, this is the file that maintains chart information. Every time data are collected
- for a chart, this is updated.
-2. `chart/dimension_name.db`, this is the file for each dimension. At its beginning there is a
- header, followed by the round robin database where metrics are stored.
+1. `chart/main.db`, this is the file that maintains chart information. Every time data are collected for a chart, this
+ is updated.
+2. `chart/dimension_name.db`, this is the file for each dimension. At its beginning there is a header, followed by the
+ round robin database where metrics are stored.
So, every time Netdata collects data, the following pages will become dirty:
1. the chart file
2. the header part of all dimension files
-3. if the collected metrics are stored far enough in the dimension file, another page will
- become dirty, for each dimension
+3. if the collected metrics are stored far enough in the dimension file, another page will become dirty, for each
+ dimension
-Each page in Linux is 4KB. So, with 200 charts and 1000 dimensions, there will be 1200 to 2200 4KB
-pages dirty pages every second. Of course 1200 of them will always be dirty (the chart header and
-the dimensions headers) and 1000 will be dirty for about 1000 seconds (4 bytes per metric, 4KB per
-page, so 1000 seconds, or 16 minutes per page).
+Each page in Linux is 4KB. So, with 200 charts and 1000 dimensions, there will be 1200 to 2200 4KB pages dirty pages
+every second. Of course 1200 of them will always be dirty (the chart header and the dimensions headers) and 1000 will be
+dirty for about 1000 seconds (4 bytes per metric, 4KB per page, so 1000 seconds, or 16 minutes per page).
-Hopefully, the Linux kernel does not sync all these data every second. The frequency they are
-synced is controlled by `/proc/sys/vm/dirty_expire_centisecs` or the
-`sysctl` `vm.dirty_expire_centisecs`. The default on most systems is 3000 (30 seconds).
+Hopefully, the Linux kernel does not sync all these data every second. The frequency they are synced is controlled by
+`/proc/sys/vm/dirty_expire_centisecs` or the `sysctl` `vm.dirty_expire_centisecs`. The default on most systems is 3000
+(30 seconds).
On a busy server centralizing metrics from 20+ servers you will experience this:
@@ -134,62 +125,59 @@ On a busy server centralizing metrics from 20+ servers you will experience this:
As you can see, there is quite some stress (this is `iowait`) every 30 seconds.
-A simple solution is to increase this time to 10 minutes (60000). This is the same system
-with this setting in 10 minutes:
+A simple solution is to increase this time to 10 minutes (60000). This is the same system with this setting in 10
+minutes:
![image](https://cloud.githubusercontent.com/assets/2662304/23834784/d2304f72-0764-11e7-8389-fb830ffd973a.png)
-Of course, setting this to 10 minutes means that data on disk might be up to 10 minutes old if you
-get an abnormal shutdown.
+Of course, setting this to 10 minutes means that data on disk might be up to 10 minutes old if you get an abnormal
+shutdown.
There are 2 more options to tweak:
1. `dirty_background_ratio`, by default `10`.
2. `dirty_ratio`, by default `20`.
-These control the amount of memory that should be dirty for disk syncing to be triggered.
-On dedicated Netdata servers, you can use: `80` and `90` respectively, so that all RAM is given
-to Netdata.
+These control the amount of memory that should be dirty for disk syncing to be triggered. On dedicated Netdata servers,
+you can use: `80` and `90` respectively, so that all RAM is given to Netdata.
-With these settings, you can expect a little `iowait` spike once every 10 minutes and in case
-of system crash, data on disk will be up to 10 minutes old.
+With these settings, you can expect a little `iowait` spike once every 10 minutes and in case of system crash, data on
+disk will be up to 10 minutes old.
![image](https://cloud.githubusercontent.com/assets/2662304/23835030/ba4bf506-0768-11e7-9bc6-3b23e080c69f.png)
-To have these settings automatically applied on boot, create the file `/etc/sysctl.d/netdata-memory.conf` with these contents:
+To have these settings automatically applied on boot, create the file `/etc/sysctl.d/netdata-memory.conf` with these
+contents:
-```
+```conf
vm.dirty_expire_centisecs = 60000
vm.dirty_background_ratio = 80
vm.dirty_ratio = 90
vm.dirty_writeback_centisecs = 0
```
-There is another memory mode to help overcome the memory size problem. What is **most interesting
-for this setup** is `memory mode = dbengine`.
+There is another memory mode to help overcome the memory size problem. What is **most interesting for this setup** is
+`memory mode = dbengine`.
### dbengine
-In this mode, the database of Netdata is stored in database files. The [Database Engine](engine/)
-works like a traditional database. There is some amount of RAM dedicated to data caching and
-indexing and the rest of the data reside compressed on disk. The number of history entries is not
-fixed in this case, but depends on the configured disk space and the effective compression ratio
-of the data stored.
+In this mode, the database of Netdata is stored in database files. The [Database Engine](engine/) works like a
+traditional database. There is some amount of RAM dedicated to data caching and indexing and the rest of the data reside
+compressed on disk. The number of history entries is not fixed in this case, but depends on the configured disk space
+and the effective compression ratio of the data stored.
-We suggest to use **this** mode on nodes that also run other applications. The Database Engine uses
-direct I/O to avoid polluting the OS filesystem caches and does not generate excessive I/O traffic
-so as to create the minimum possible interference with other applications. Using memory mode
-`dbengine` we can overcome most memory restrictions. For more details see [here](engine/).
+We suggest to use **this** mode on nodes that also run other applications. The Database Engine uses direct I/O to avoid
+polluting the OS filesystem caches and does not generate excessive I/O traffic so as to create the minimum possible
+interference with other applications. Using memory mode `dbengine` we can overcome most memory restrictions. For more
+details see [here](engine/).
## KSM
-Netdata offers all its round robin database to kernel for deduplication
-(except for `memory mode = dbengine`).
+Netdata offers all its round robin database to kernel for deduplication (except for `memory mode = dbengine`).
-In the past KSM has been criticized for consuming a lot of CPU resources.
-Although this is true when KSM is used for deduplicating certain applications, it is not true with
-netdata, since the Netdata memory is written very infrequently (if you have 24 hours of metrics in
-netdata, each byte at the in-memory database will be updated just once per day).
+In the past KSM has been criticized for consuming a lot of CPU resources. Although this is true when KSM is used for
+deduplicating certain applications, it is not true with netdata, since the Netdata memory is written very infrequently
+(if you have 24 hours of metrics in netdata, each byte at the in-memory database will be updated just once per day).
KSM is a solution that will provide 60+% memory savings to Netdata.
@@ -203,15 +191,20 @@ CONFIG_KSM=y
When KSM is enabled at the kernel is just available for the user to enable it.
-So, if you build a kernel with `CONFIG_KSM=y` you will just get a few files in `/sys/kernel/mm/ksm`. Nothing else happens. There is no performance penalty (apart I guess from the memory this code occupies into the kernel).
+So, if you build a kernel with `CONFIG_KSM=y` you will just get a few files in `/sys/kernel/mm/ksm`. Nothing else
+happens. There is no performance penalty (apart I guess from the memory this code occupies into the kernel).
The files that `CONFIG_KSM=y` offers include:
-- `/sys/kernel/mm/ksm/run` by default `0`. You have to set this to `1` for the kernel to spawn `ksmd`.
-- `/sys/kernel/mm/ksm/sleep_millisecs`, by default `20`. The frequency ksmd should evaluate memory for deduplication.
-- `/sys/kernel/mm/ksm/pages_to_scan`, by default `100`. The amount of pages ksmd will evaluate on each run.
+- `/sys/kernel/mm/ksm/run` by default `0`. You have to set this to `1` for the
+ kernel to spawn `ksmd`.
+- `/sys/kernel/mm/ksm/sleep_millisecs`, by default `20`. The frequency ksmd
+ should evaluate memory for deduplication.
+- `/sys/kernel/mm/ksm/pages_to_scan`, by default `100`. The amount of pages
+ ksmd will evaluate on each run.
-So, by default `ksmd` is just disabled. It will not harm performance and the user/admin can control the CPU resources he/she is willing `ksmd` to use.
+So, by default `ksmd` is just disabled. It will not harm performance and the user/admin can control the CPU resources
+he/she is willing `ksmd` to use.
### Run `ksmd` kernel daemon
@@ -222,7 +215,8 @@ echo 1 >/sys/kernel/mm/ksm/run
echo 1000 >/sys/kernel/mm/ksm/sleep_millisecs
```
-With these settings ksmd does not even appear in the running process list (it will run once per second and evaluate 100 pages for de-duplication).
+With these settings ksmd does not even appear in the running process list (it will run once per second and evaluate 100
+pages for de-duplication).
Put the above lines in your boot sequence (`/etc/rc.local` or equivalent) to have `ksmd` run at boot.
@@ -232,4 +226,4 @@ Netdata will create charts for kernel memory de-duplication performance, like th
![image](https://cloud.githubusercontent.com/assets/2662304/11998786/eb23ae54-aab6-11e5-94d4-e848e8a5c56a.png)
-[![analytics](https://www.google-analytics.com/collect?v=1&aip=1&t=pageview&_s=1&ds=github&dr=https%3A%2F%2Fgithub.com%2Fnetdata%2Fnetdata&dl=https%3A%2F%2Fmy-netdata.io%2Fgithub%2Fdatabase%2FREADME&_u=MAC~&cid=5792dfd7-8dc4-476b-af31-da2fdb9f93d2&tid=UA-64295674-3)](<>)
+[![analytics](https://www.google-analytics.com/collect?v=1&aip=1&t=pageview&_s=1&ds=github&dr=https%3A%2F%2Fgithub.com%2Fnetdata%2Fnetdata&dl=https%3A%2F%2Fmy-netdata.io%2Fgithub%2Fdatabase%2FREADME&_u=MAC~&cid=5792dfd7-8dc4-476b-af31-da2fdb9f93d2&tid=UA-64295674-3)](<>) \ No newline at end of file