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You can configure your Vertica integration to collect metrics from custom queries of your Vertica database by following the configuration syntax in these lines of the Datadog Vertica integration’s conf.yaml.example
file. While you do this, there are a few things you want to keep in mind.
Define custom queries in the following format:
custom_queries:
- query: <QUERY>
columns: <COLUMNS>
tags: <TAGS>
Queries in Vertica resemble the same SQL queries used in other databases. Use the pipe symbol (|
) in the query
field to use a multi line query.
The columns
field is a list representing each column, ordered sequentially from left to right. The number of columns must equal the number of columns returned in the query. Each column requires two pieces of data: name
and type
:
name
field represents the suffix to append to vertica.
in order to form the full metric name.type
field represents the submission method: gauge
, monotonic_count
, etc. Setting the type
to tag
results in tagging each metric in the row with the name and value of the item in this column.The tags
field is optional and represents a list of tags to apply to each metric.
custom_queries:
- query: |
SELECT force_outer,
table_name
FROM v_catalog.tables
columns:
- name: table.force_outer
type: gauge
- name: table_name
type: tag
tags:
- env:dev
You can define custom queries at the instance level, but if you wish to apply certain queries across all instances, use the global_custom_queries
parameter in the init_config
section.
In each instance, you can define the behavior of global custom queries using the use_global_custom_queries
parameter. This value defaults to true
.
global_custom_queries value | Behavior |
---|---|
true | global_custom_queries overrides custom_queries . |
false | custom_queries overrides global_custom_queries . |
extend | global_custom_queries is used in addition to custom_queries . |