Indexing Metrics

While metrics are primarily quantitative measurements, dimensions are attributes that describe our data. For example, we following are all valid examples of dimensional data, for CPU usage:

Dimension	Value
hostname	bluefrog
cpu	1
uom	%

Together these metrics form part of a metric's identity, and the above would be distinct from CPU usage data recorded for another hostname blackbear, even though the data may have the same unit of measurement and CPU number.

DalmatinerDB allows for these dimensions to be used in queries, typically to refine the number of paths under observation. It is also possible to use wildcards as part of a metric path, in order to expand the number of paths under observation. This is made possible by the metric indexer.

It is the job of the metric indexer to store and maintain these dimensional data attributes. At a conceptual level, the query engine consults the indexer with the specific purpose of reducing a relational query to a more specific query consisting of a list of bucket/value pairs. These are then fetched concurrently from DalmatinerDB, by the query engine.

Delegating all of this responsibility to the indexer allows DalmatinerDB to remain independent from the indexing middleware. This also grants the freedom to choose storage technologies that are optimal for relational dimensional data, such as Postgres.

Creating a dbs

DalmatinerDB Indexer

This indexer is provided out of the box, and is limited in capability.

Dependencies	None
Namespace listing	Yes
Wildcard support	Yes
Dimension support	No

Postgres Indexer

This indexer is fast and has a broad capability set, however it requires a working Postgres installation and involves more configuration.

SQL

CREATE USER ddb WITH PASSWORD 'ddb';
CREATE DATABASE metric_metadata OWNER ddb;
GRANT ALL ON DATABASE metric_metadata TO ddb;
ALTER ROLE ddb WITH SUPERUSER;

Dependencies	Postgres 9.6
Namespace listing	Yes
Wildcard support	Yes
Dimension support	Yes

The Postgres indexer requires a database schema consisting of a dimensions and metrics table. The schema can be imported as follows:

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Configuration

Consult the section titled idx.backend in the configuration documentation in order to ensure that the Postgres indexer is used by the Frontend and the Proxy.