django-elasticsearch-metrics 5.0.0

Django app for storing time-series metrics in Elasticsearch.

django-elasticsearch-metrics

Django app for storing time-series metrics in Elasticsearch.

Pre-requisites

• Python 2.7 or >=3.6
• Django 1.11 or 2.0
• Elasticsearch 6

Install

pip install django-elasticsearch-metrics

Quickstart

Add "elasticseach_metrics" to INSTALLED_APPS.

INSTALLED_APPS += ["elasticsearch_metrics"]

Define the ELASTICSEARCH_DSL setting.

ELASTICSEARCH_DSL = {"default": {"hosts": "localhost:9200"}}

This setting is passed to elasticsearch_dsl.connections.configure so it takes the same parameters.

In one of your apps, define a new metric in metrics.py.

A Metric is a subclass of elasticsearch_dsl.Document.

# myapp/metrics.py

from elasticsearch_metrics import metrics


class PageView(metrics.Metric):
    user_id = metrics.Integer(index=True, doc_values=True)

Use the sync_metrics management command to ensure that the index template for your metric is created in Elasticsearch.

# This will create an index template called myapp_pageview
python manage.py sync_metrics

Now add some data:

from myapp.metrics import PageView

user = User.objects.latest()

# By default we create an index for each day.
# Therefore, this will persist the document
# to an index called, e.g. "myapp_pageview_2020.02.04"
PageView.record(user_id=user.id)

Go forth and search!

# perform a search across all page views
PageView.search()

Per-month or per-year indices

By default, an index is created for every day that a metric is saved. You can change this to create an index per month or per year by changing the ELASTICSEARCH_METRICS_DATE_FORMAT setting.

# settings.py

# Monthly:
ELASTICSEARCH_METRICS_DATE_FORMAT = "%Y.%m"

# Yearly:
ELASTICSEARCH_METRICS_DATE_FORMAT = "%Y"

Index settings

You can configure the index template settings by setting Metric.Index.settings.

class PageView(metrics.Metric):
    user_id = metrics.Integer()

    class Index:
        settings = {"number_of_shards": 2, "refresh_interval": "5s"}

Index templates

Each Metric will have its own index template. The index template name and glob pattern are computed from the app label for the containing app and the class's name. For example, a PageView class defined in myapp/metrics.py will have an index template with the name myapp_pageview and a template glob pattern of myapp_pageview_*.

If you declare a Metric outside of an app, you will need to set app_label.

class PageView(metrics.Metric):
    class Meta:
        app_label = "myapp"

Alternatively, you can set template_name and/or template explicitly.

class PageView(metrics.Metric):
    user_id = metrics.Integer()

    class Meta:
        template_name = "myapp_pviews"
        template = "myapp_pviews_*"

Abstract metrics

from elasticsearch_metrics import metrics


class MyBaseMetric(metrics.Metric):
    user_id = metrics.Integer()

    class Meta:
        abstract = True


class PageView(MyBaseMetric):
    class Meta:
        app_label = "myapp"

Optional factory_boy integration

import factory
from elasticsearch_metrics.factory import MetricFactory

from ..myapp.metrics import MyMetric


class MyMetricFactory(MetricFactory):
    my_int = factory.Faker("pyint")

    class Meta:
        model = MyMetric


def test_something():
    metric = MyMetricFactory()  # index metric in ES
    assert isinstance(metric.my_int, int)

Configuration

• ELASTICSEARCH_DSL: Required. Connection settings passed to elasticsearch_dsl.connections.configure.
• ELASTICSEARCH_METRICS_DATE_FORMAT: Date format to use when creating indexes. Default: %Y.%m.%d (same date format Elasticsearch uses for date math)

Management commands

• sync_metrics: Ensure that index templates have been created for your metrics.
• show_metrics: Pretty-print a listing of all registered metrics.
• check_metrics: Check if index templates are in sync. Exits with an error code if any metrics are out of sync.

Signals

Signals are located in the elasticsearch_metrics.signals module.

• pre_index_template_create(Metric, index_template, using): Sent before PUTting a new index template into Elasticsearch.
• post_index_template_create(Metric, index_template, using): Sent after PUTting a new index template into Elasticsearch.
• pre_save(Metric, instance, using, index): Sent at the beginning of a Metric's save() method.
• post_save(Metric, instance, using, index): Sent at the end of a Metric's save() method.

Caveats

• _source is disabled by default on metric indices in order to save disk space. For most metrics use cases, Users will not need to retrieve the source JSON documents. Be sure to understand the consequences of this: https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping-source-field.html#_disabling_source . To enable _source, you can override it in class Meta.

class MyMetric(metrics.Metric):
    class Meta:
        source = metrics.MetaField(enabled=True)

Resources

• Elasticsearch as a Time Series Data Store
• Pythonic Analytics with Elasticsearch
• In Search of Agile Time Series Database

License

MIT Licensed.