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diff --git a/database/engine/README.md b/database/engine/README.md new file mode 100644 index 0000000..191366a --- /dev/null +++ b/database/engine/README.md @@ -0,0 +1,259 @@ +<!-- +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. + +[](<>) |