Adding upstream version 1.29.3.upstream/1.29.3upstream

Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>

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+<!--
+title: "Database engine"
+description: "Netdata's highly-efficient database engine use both RAM and disk for distributed, long-term storage of per-second metrics."
+custom_edit_url: https://github.com/netdata/netdata/edit/master/database/engine/README.md
+-->
+
+# Database engine
+
+The Database Engine works like a traditional database. It dedicates a certain amount of RAM to data caching and
+indexing, while the rest of the data resides compressed on disk. Unlike other [memory modes](/database/README.md), the
+amount of historical metrics stored is based on the amount of disk space you allocate and the effective compression
+ratio, not a fixed number of metrics collected.
+
+By using both RAM and disk space, the database engine allows for long-term storage of per-second metrics inside of the
+Agent itself.
+
+In addition, the database engine is the only memory mode that supports changing the data collection update frequency
+(`update_every`) without losing the metrics your Agent already gathered and stored.
+
+## Configuration
+
+To use the database engine, open `netdata.conf` and set `memory mode` to `dbengine`.
+
+```conf
+[global]
+    memory mode = dbengine
+```
+
+To configure the database engine, look for the `page cache size` and `dbengine multihost disk space` settings in the
+`[global]` section of your `netdata.conf`. The Agent ignores the `history` setting when using the database engine.
+
+```conf
+[global]
+    page cache size = 32
+    dbengine multihost disk space = 256
+```
+
+The above values are the default values for Page Cache size and DB engine disk space quota. Both numbers are
+in **MiB**.
+
+The `page cache size` option determines the amount of RAM in **MiB** dedicated to caching Netdata metric values. The
+actual page cache size will be slightly larger than this figure—see the [memory requirements](#memory-requirements)
+section for details.
+
+The `dbengine multihost 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. You can use the [**database engine
+calculator**](/docs/store/change-metrics-storage.md#calculate-the-system-resources-RAM-disk-space-needed-to-store-metrics)
+to correctly set `dbengine multihost disk space` based on your metrics retention policy. The calculator gives an
+accurate estimate based on how many child nodes you have, how many metrics your Agent collects, and more.
+
+### Legacy configuration
+
+The deprecated `dbengine disk space` option determines the amount of disk space in **MiB** that is dedicated to storing
+Netdata metric values per legacy database engine instance (see [details on the legacy mode](#legacy-mode) below).
+
+```conf
+[global]
+    dbengine disk space = 256
+```
+
+### Streaming metrics to the database engine
+
+When using the multihost database engine, all parent and child nodes share the same `page cache size` and `dbengine
+multihost disk space` in a single dbengine instance. The [**database engine
+calculator**](/docs/store/change-metrics-storage.md#calculate-the-system-resources-RAM-disk-space-needed-to-store-metrics)
+helps you properly set `page cache size` and `dbengine multihost disk space` on your parent node to allocate enough
+resources based on your metrics retention policy and how many child nodes you have.
+
+#### Legacy mode
+
+_For Netdata Agents earlier than v1.23.2_, the Agent on the parent node uses one dbengine instance for itself, and
+another instance for every child node it receives metrics from. If you had four streaming nodes, you would have five
+instances in total (`1 parent + 4 child nodes = 5 instances`).
+
+The Agent allocates resources for each instance separately using the `dbengine disk space` (**deprecated**) setting. If
+`dbengine disk space`(**deprecated**) is set to the default `256`, each instance is given 256 MiB in disk space, which
+means the total disk space required to store all instances is, roughly, `256 MiB * 1 parent * 4 child nodes = 1280 MiB`.
+
+#### Backward compatibility
+
+All existing metrics belonging to child nodes are automatically converted to legacy dbengine instances and the localhost
+metrics are transferred to the multihost dbengine instance.
+
+All new child nodes are automatically transferred to the multihost dbengine instance and share its page cache and disk
+space. If you want to migrate a child node from its legacy dbengine instance to the multihost dbengine instance, you
+must delete the instance's directory, which is located in `/var/cache/netdata/MACHINE_GUID/dbengine`, after stopping the
+Agent.
+
+##### Information
+
+For more information about setting `memory mode` on your nodes, in addition to other streaming configurations, see
+[streaming](/streaming/README.md).
+
+### Memory requirements
+
+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**:
+
+-   The total page cache memory footprint will be an additional `#dimensions-being-collected x 4096 x 2` bytes over what
+    the user configured with `page cache size`.
+
+-   an additional `#pages-on-disk x 4096 x 0.03` bytes of RAM are allocated for metadata.
+
+    -   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.
+
+An important observation is that RAM usage depends on both the `page cache size` and the `dbengine multihost disk space`
+options.
+
+You can use our [database engine
+calculator](/docs/store/change-metrics-storage.md#calculate-the-system-resources-RAM-disk-space-needed-to-store-metrics)
+to validate the memory requirements for your particular system(s) and configuration (**out-of-date**).
+
+### Disk space requirements
+
+There are explicit disk space requirements **per** DB engine **instance**:
+
+-   The total disk space footprint will be the maximum between `#dimensions-being-collected x 4096 x 2` bytes or what
+    the user configured with `dbengine multihost disk space` or `dbengine disk space`.
+
+### File descriptor requirements
+
+The Database Engine may keep a **significant** amount of files open per instance (e.g. per streaming child or
+parent 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 child 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:
+
+```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:
+
+```conf
+fs.file-max = 65536
+```
+
+In FreeBSD and OS X you change the lines like this:
+
+```conf
+kern.maxfilesperproc=65536
+kern.maxfiles=65536
+```
+
+You can apply the settings by running `sysctl -p` or by rebooting.
+
+## 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.:
+
+```sh
+datafile-1-0000000001.ndf
+journalfile-1-0000000001.njf
+datafile-1-0000000002.ndf
+journalfile-1-0000000002.njf
+datafile-1-0000000003.ndf
+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.
+
+_Users should_ **back up** _their `./dbengine` folders if they consider this data to be important._ You can also set up
+one or more [exporting connectors](/exporting/README.md) to send your Netdata metrics to other databases for long-term
+storage at lower granularity.
+
+## 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**.
+
+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. 
+
+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.
+
+## Evaluation
+
+We have evaluated the performance of the `dbengine` API that the netdata daemon uses internally. This is **not** the web
+API of netdata. Our benchmarks ran on a **single** `dbengine` instance, multiple of which can be running in a Netdata
+parent node. We used a server with an AMD Ryzen Threadripper 2950X 16-Core Processor and 2 disk drives, a Seagate
+Constellation ES.3 2TB magnetic HDD and a SAMSUNG MZQLB960HAJR-00007 960GB NAND Flash SSD.
+
+For our workload, we defined 32 charts with 128 metrics each, giving us a total of 4096 metrics. We defined 1 worker
+thread per chart (32 threads) that generates new data points with a data generation interval of 1 second. The time axis
+of the time-series is emulated and accelerated so that the worker threads can generate as many data points as possible
+without delays. 
+
+We also defined 32 worker threads that perform queries on random metrics with semi-random time ranges. The
+starting time of the query is randomly selected between the beginning of the time-series and the time of the latest data
+point. The ending time is randomly selected between 1 second and 1 hour after the starting time. The pseudo-random
+numbers are generated with a uniform distribution.
+
+The data are written to the database at the same time as they are read from it. This is a concurrent read/write mixed
+workload with a duration of 60 seconds. The faster `dbengine` runs, the bigger the dataset size becomes since more
+data points will be generated. We set a page cache size of 64MiB for the two disk-bound scenarios. This way, the dataset
+size of the metric data is much bigger than the RAM that is being used for caching so as to trigger I/O requests most
+of the time. In our final scenario, we set the page cache size to 16 GiB. That way, the dataset fits in the page cache
+so as to avoid all disk bottlenecks.
+
+The reported numbers are the following:
+
+| device | page cache | dataset | reads/sec | writes/sec |
+| :----: | :--------: | ------: | --------: | ---------: |
+| HDD    | 64 MiB     | 4.1 GiB | 813K      | 18.0M      |
+| SSD    | 64 MiB     | 9.8 GiB | 1.7M      | 43.0M      |
+| N/A    | 16 GiB     | 6.8 GiB | 118.2M    | 30.2M      |
+
+where "reads/sec" is the number of metric data points being read from the database via its API per second and
+"writes/sec" is the number of metric data points being written to the database per second. 
+
+Notice that the HDD numbers are pretty high and not much slower than the SSD numbers. This is thanks to the database
+engine design being optimized for rotating media. In the database engine disk I/O requests are:
+
+-   asynchronous to mask the high I/O latency of HDDs.
+-   mostly large to reduce the amount of HDD seeking time.
+-   mostly sequential to reduce the amount of HDD seeking time.
+-   compressed to reduce the amount of required throughput.
+
+As a result, the HDD is not thousands of times slower than the SSD, which is typical for other workloads.
+
+An interesting observation to make is that the CPU-bound run (16 GiB page cache) generates fewer data than the SSD run
+(6.8 GiB vs 9.8 GiB). The reason is that the 32 reader threads in the SSD scenario are more frequently blocked by I/O,
+and generate a read load of 1.7M/sec, whereas in the CPU-bound scenario the read load is 70 times higher at 118M/sec.
+Consequently, there is a significant degree of interference by the reader threads, that slow down the writer threads.
+This is also possible because the interference effects are greater than the SSD impact on data generation throughput.
+
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