Package ts provides a basic time series datastore on top of the underlying CockroachDB key/value datastore. It is used to serve basic metrics generated by CockroachDB.
Storing time series data is a unique challenge for databases. Time series data is typically generated at an extremely high volume, and is queried by providing a range of time of arbitrary size, which can lead to an enormous amount of data being scanned for a query. Many specialized time series databases already exist to meet these challenges; those solutions are built on top of specialized storage engines which are often unsuitable for general data storage needs, but currently superior to CockroachDB for the purpose of time series data.
However, it is a broad goal of CockroachDB to provide a good experience for developers, and out-of-the-box recording of internal metrics is helpful for small and prototype deployments.
Time series data is organized on disk according to two basic, sortable properties: + Time series name (i.e "sql.operations.selects") + Timestamp
This is optimized for querying data for a single series over multiple timestamps: data for the same series at different timestamps is stored contiguously.
The amount of data produced by time series sampling can be considerable; storing every incoming data point with perfect fidelity can command a tremendous amount of computing and storage resources.
However, in many use cases perfect fidelity is not necessary; the exact time a sample was taken is unimportant, with the overall trend of the data over time being far more important to analysis than the individual samples.
With this in mind, CockroachDB downsamples data before storing it; the original timestamp for each data point in a series is not recorded. CockroachDB instead divides time into contiguous slots of uniform length (currently 10 seconds); if multiple data points for a series fall in the same slot, only the most recent sample is kept.
In order to use key space efficiently, we pack data for multiple contiguous samples into "slab" values, with data for each slab stored in a CockroachDB key. This is done by again dividing time into contiguous slots, but with a longer duration; this is known as the "slab duration". For example, CockroachDB downsamples its internal data at a resolution of 10 seconds, but stores it with a "slab duration" of 1 hour, meaning that all samples that fall in the same hour are stored at the same key. This strategy helps reduce the number of keys scanned during a query.
Another common use case of time series queries is the aggregation of multiple series; for example, you may want to query the same metric (e.g. "queries per second") across multiple machines on a cluster, and aggregate the result.
Specialized Time-series databases can often aggregate across arbitrary series; however, CockroachDB is specialized for aggregation of the same series across different machines or disks.
This is done by creating a "source key", typically a node or store ID, which is an optional identifier that is separate from the series name itself. The source key is are appended to the key as a suffix, after the series name and timestamp; this means that data that is from the same series and time period, but from different nodes, will be stored contiguously in the key space. Data from all sources in a series can thus be queried in a single scan.
Unused Feature: Multiple resolutions
CockroachDB time series database has rudimentary support for a planned feature: recording the same series at multiple sample durations, commonly known as a "rollup".
For example, a single series may be recorded with a sample size of 10 seconds, but also record the same data with a sample size of 1 hour. The 1 hour data will have much less information, but can be queried much faster; this is very useful when querying a series over a very long period of time (e.g. an entire month or year).
A specific sample duration in CockroachDB is known as a Resolution. CockroachDB supports a fixed set of Resolutions; each Resolution has a fixed sample duration and a slab duration. For example, the resolution "Resolution10s" has a sample duration of 10 seconds and a slab duration of 1 hour.
This feature was planned and slightly informs our key structure (resolution information is encoded in every time series key); however, all time series in CockroachDB are currently recorded at a downsample duration of 10 seconds, and a slab duration of 1 hour.
A hypothetical example from CockroachDB: we want to record the available capacity of all stores in the cluster.
The series name is: cockroach.capacity.available
Data points for this series are automatically collected from all stores. When data points are written, they are recorded with a source key of: [store id]
There are 3 stores which contain data: 1, 2 and 3. These are arbitrary and may change over time.
Data is recorded for January 1st, 2016 between 10:05 pm and 11:05 pm. The data is recorded at a 10 second resolution.
The data is recorded into keys structurally similar to the following:
tsd.cockroach.capacity.available.10s.403234.1 tsd.cockroach.capacity.available.10s.403234.2 tsd.cockroach.capacity.available.10s.403234.3 tsd.cockroach.capacity.available.10s.403235.1 tsd.cockroach.capacity.available.10s.403235.2 tsd.cockroach.capacity.available.10s.403235.3
Data for each source is stored in two keys: one for the 10 pm hour, and one for the 11pm hour. Each key contains the tsd prefix, the series name, the resolution (10s), a timestamp representing the hour, and finally the series key. The keys will appear in the data store in the order shown above.
(Note that the keys will NOT be exactly as pictured above; they will be encoded in a way that is more efficient, but is not readily human readable.)