Fix Remark Lint for READMEs in Database (#6942)

* fix remark lint Database engine

* fix remark lint of database README

* rewrap dbengine readme for consistency

* rewrap database README

* make character limit to 120 not 80

2 files changed, 159 insertions, 175 deletions

diff --git a/database/README.md b/database/README.md
index 2fcb69b679..1efdd9a94b 100644
--- a/database/README.md
+++ b/database/README.md
@@ -1,59 +1,53 @@
 # 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`, (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).
 
-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`, 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
@@ -71,62 +65,58 @@ 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
 
-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 +124,59 @@ 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 +190,20 @@ 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 +214,8 @@ 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 +225,4 @@ 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
diff --git a/database/engine/README.md b/database/engine/README.md
index 7791a549f8..12c22a92c2 100644
--- a/database/engine/README.md
+++ b/database/engine/README.md
@@ -1,18 +1,17 @@
 # Database engine
 
-The Database 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.
+The Database 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.
 
 ## Files
 
-With the DB engine memory mode the metric data are stored in database files. These files are
-organized in pairs, the datafiles and their corresponding journalfiles, e.g.:
+With the DB engine memory mode the metric data are stored in database files. These files are organized in pairs, the
+datafiles and their corresponding journalfiles, e.g.:
 
-```
+```sh
 datafile-1-0000000001.ndf
 journalfile-1-0000000001.njf
 datafile-1-0000000002.ndf
@@ -22,21 +21,19 @@ journalfile-1-0000000003.njf
 ...
 ```
 
-They are located under their host's cache directory in the directory `./dbengine`
-(e.g. for localhost the default location is `/var/cache/netdata/dbengine/*`). The higher
-numbered filenames contain more recent metric data. The user can safely delete some pairs
-of files when Netdata is stopped to manually free up some space.
+They are located under their host's cache directory in the directory `./dbengine` (e.g. for localhost the default
+location is `/var/cache/netdata/dbengine/*`). The higher numbered filenames contain more recent metric data. The user
+can safely delete some pairs of files when Netdata is stopped to manually free up some space.
 
 _Users should_ **back up** _their `./dbengine` folders if they consider this data to be important._
 
 ## Configuration
 
-There is one DB engine instance per Netdata host/node. That is, there is one `./dbengine` folder
-per node, and all charts of `dbengine` memory mode in such a host share the same storage space
-and DB engine instance memory state. You can select the memory mode for localhost by editing
-netdata.conf and setting:
+There is one DB engine instance per Netdata host/node. That is, there is one `./dbengine` folder per node, and all
+charts of `dbengine` memory mode in such a host share the same storage space and DB engine instance memory state. You
+can select the memory mode for localhost by editing netdata.conf and setting:
 
-```
+```conf
 [global]
     memory mode = dbengine
 ```
@@ -44,57 +41,52 @@ netdata.conf and setting:
 For setting the memory mode for the rest of the nodes you should look at
 [streaming](../../streaming/).
 
-The `history` configuration option is meaningless for `memory mode = dbengine` and is ignored
-for any metrics being stored in the DB engine.
+The `history` configuration option is meaningless for `memory mode = dbengine` and is ignored for any metrics being
+stored in the DB engine.
 
-All DB engine instances, for localhost and all other streaming recipient nodes inherit their
-configuration from `netdata.conf`:
+All DB engine instances, for localhost and all other streaming recipient nodes inherit their configuration from
+`netdata.conf`:
 
-```
+```conf
 [global]
     page cache size = 32
     dbengine disk space = 256
 ```
 
-The above values are the default and minimum values for Page Cache size and DB engine disk space
-quota. Both numbers are in **MiB**. All DB engine instances will allocate the configured resources
-separately.
+The above values are the default and minimum values for Page Cache size and DB engine disk space quota. Both numbers are
+in **MiB**. All DB engine instances will allocate the configured resources separately.
 
-The `page cache size` option determines the amount of RAM in **MiB** that is dedicated to caching
-Netdata metric values themselves.
+The `page cache size` option determines the amount of RAM in **MiB** that is dedicated to caching Netdata metric values
+themselves.
 
-The `dbengine disk space` option determines the amount of disk space in **MiB** that is dedicated
-to storing Netdata metric values and all related metadata describing them.
+The `dbengine disk space` option determines the amount of disk space in **MiB** that is dedicated to storing Netdata
+metric values and all related metadata describing them.
 
 ## Operation
 
-The DB engine stores chart metric values in 4096-byte pages in memory. Each chart dimension gets
-its own page to store consecutive values generated from the data collectors. Those pages comprise
-the **Page Cache**.
+The DB engine stores chart metric values in 4096-byte pages in memory. Each chart dimension gets its own page to store
+consecutive values generated from the data collectors. Those pages comprise the **Page Cache**.
 
-When those pages fill up they are slowly compressed and flushed to disk.
-It can take `4096 / 4 = 1024 seconds = 17 minutes`, for a chart dimension that is being collected
-every 1 second, to fill a page. Pages can be cut short when we stop Netdata or the DB engine
-instance so as to not lose the data. When we query the DB engine for data we trigger disk read
-I/O requests that fill the Page Cache with the requested pages and potentially evict cold
-(not recently used) pages. 
+When those pages fill up they are slowly compressed and flushed to disk. It can take `4096 / 4 = 1024 seconds = 17
+minutes`, for a chart dimension that is being collected every 1 second, to fill a page. Pages can be cut short when we
+stop Netdata or the DB engine instance so as to not lose the data. When we query the DB engine for data we trigger disk
+read I/O requests that fill the Page Cache with the requested pages and potentially evict cold (not recently used)
+pages. 
 
-When the disk quota is exceeded the oldest values are removed from the DB engine at real time, by
-automatically deleting the oldest datafile and journalfile pair. Any corresponding pages residing
-in the Page Cache will also be invalidated and removed. The DB engine logic will try to maintain
-between 10 and 20 file pairs at any point in time. 
+When the disk quota is exceeded the oldest values are removed from the DB engine at real time, by automatically deleting
+the oldest datafile and journalfile pair. Any corresponding pages residing in the Page Cache will also be invalidated
+and removed. The DB engine logic will try to maintain between 10 and 20 file pairs at any point in time. 
 
-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.
+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.
 
 ## Memory requirements
 
-Using memory mode `dbengine` we can overcome most memory restrictions and store a dataset that
-is much larger than the available memory.
+Using memory mode `dbengine` we can overcome most memory restrictions and store a dataset that is much larger than the
+available memory.
 
-There are explicit memory requirements **per** DB engine **instance**, meaning **per** Netdata 
-**node** (e.g. localhost and streaming recipient nodes):
+There are explicit memory requirements **per** DB engine **instance**, meaning **per** Netdata **node** (e.g. localhost
+and streaming recipient nodes):
 
 -   `page cache size` must be at least `#dimensions-being-collected x 4096 x 2` bytes.
 
@@ -102,48 +94,47 @@ There are explicit memory requirements **per** DB engine **instance**, meaning *
 
     -   roughly speaking this is 3% of the uncompressed disk space taken by the DB files.
 
-    -   for very highly compressible data (compression ratio > 90%) this RAM overhead
-        is comparable to the disk space footprint.
+    -   for very highly compressible data (compression ratio > 90%) this RAM overhead is comparable to the disk space
+        footprint.
 
-An important observation is that RAM usage depends on both the `page cache size` and the 
-`dbengine disk space` options. 
+An important observation is that RAM usage depends on both the `page cache size` and the `dbengine disk space` options.
 
 ## File descriptor requirements
 
-The Database Engine may keep a **significant** amount of files open per instance (e.g. per streaming
-slave or master server). When configuring your system you should make sure there are at least 50
-file descriptors available per `dbengine` instance.
+The Database Engine may keep a **significant** amount of files open per instance (e.g. per streaming slave or master
+server). When configuring your system you should make sure there are at least 50 file descriptors available per
+`dbengine` instance.
 
-Netdata allocates 25% of the available file descriptors to its Database Engine instances. This means that only 25%
-of the file descriptors that are available to the Netdata service are accessible by dbengine instances.
-You should take that into account when configuring your service
-or system-wide file descriptor limits. You can roughly estimate that the Netdata service needs 2048 file
-descriptors for every 10 streaming slave hosts when streaming is configured to use `memory mode = dbengine`.
+Netdata allocates 25% of the available file descriptors to its Database Engine instances. This means that only 25% of
+the file descriptors that are available to the Netdata service are accessible by dbengine instances. You should take
+that into account when configuring your service or system-wide file descriptor limits. You can roughly estimate that the
+Netdata service needs 2048 file descriptors for every 10 streaming slave hosts when streaming is configured to use
+`memory mode = dbengine`.
 
-If for example one wants to allocate 65536 file descriptors to the Netdata service on a systemd system
-one needs to override the Netdata service by running `sudo systemctl edit netdata` and creating a
-file with contents:
+If for example one wants to allocate 65536 file descriptors to the Netdata service on a systemd system one needs to
+override the Netdata service by running `sudo systemctl edit netdata` and creating a file with contents:
 
-```
+```sh
 [Service]
 LimitNOFILE=65536
 ```
 
 For other types of services one can add the line:
 
-```
+```sh
 ulimit -n 65536
 ```
 
-at the beginning of the service file. Alternatively you can change the system-wide limits of the kernel by changing `/etc/sysctl.conf`. For linux that would be:
+at the beginning of the service file. Alternatively you can change the system-wide limits of the kernel by changing
+ `/etc/sysctl.conf`. For linux that would be:
 
-```
+```conf
 fs.file-max = 65536
 ```
 
 In FreeBSD and OS X you change the lines like this:
 
-```
+```conf
 kern.maxfilesperproc=65536
 kern.maxfiles=65536
 ```