mirror of https://github.com/apache/druid.git
116 lines
5.4 KiB
Markdown
116 lines
5.4 KiB
Markdown
---
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id: tutorial-retention
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title: "Tutorial: Configuring data retention"
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sidebar_label: "Configuring data retention"
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---
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<!--
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~ Licensed to the Apache Software Foundation (ASF) under one
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~ or more contributor license agreements. See the NOTICE file
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~ to you under the Apache License, Version 2.0 (the
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This tutorial demonstrates how to configure retention rules on a datasource to set the time intervals of data that will be retained or dropped.
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For this tutorial, we'll assume you've already downloaded Apache Druid as described in
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the [single-machine quickstart](index.md) and have it running on your local machine.
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It will also be helpful to have finished [Tutorial: Loading a file](../tutorials/tutorial-batch.md) and [Tutorial: Querying data](../tutorials/tutorial-query.md).
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## Load the example data
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For this tutorial, we'll be using the Wikipedia edits sample data, with an ingestion task spec that will create a separate segment for each hour in the input data.
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The ingestion spec can be found at `quickstart/tutorial/retention-index.json`. Let's submit that spec, which will create a datasource called `retention-tutorial`:
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```bash
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bin/post-index-task --file quickstart/tutorial/retention-index.json --url http://localhost:8081
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```
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After the ingestion completes, go to [http://localhost:8888/unified-console.html#datasources](http://localhost:8888/unified-console.html#datasources) in a browser to access the web console's datasource view.
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This view shows the available datasources and a summary of the retention rules for each datasource:
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Currently there are no rules set for the `retention-tutorial` datasource. Note that there are default rules for the cluster: load forever with 2 replicas in `_default_tier`.
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This means that all data will be loaded regardless of timestamp, and each segment will be replicated to two Historical processes in the default tier.
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In this tutorial, we will ignore the tiering and redundancy concepts for now.
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Let's view the segments for the `retention-tutorial` datasource by clicking the "24 Segments" link next to "Fully Available".
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The segments view ([http://localhost:8888/unified-console.html#segments](http://localhost:8888/unified-console.html#segments)) provides information about what segments a datasource contains. The page shows that there are 24 segments, each one containing data for a specific hour of 2015-09-12:
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## Set retention rules
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Suppose we want to drop data for the first 12 hours of 2015-09-12 and keep data for the later 12 hours of 2015-09-12.
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Go to the [datasources view](http://localhost:8888/unified-console.html#datasources) and click the blue pencil icon next to `Cluster default: loadForever` for the `retention-tutorial` datasource.
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A rule configuration window will appear:
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Now click the `+ New rule` button twice.
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In the upper rule box, select `Load` and `by interval`, and then enter `2015-09-12T12:00:00.000Z/2015-09-13T00:00:00.000Z` in field next to `by interval`. Replicas can remain at 2 in the `_default_tier`.
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In the lower rule box, select `Drop` and `forever`.
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The rules should look like this:
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Now click `Next`. The rule configuration process will ask for a user name and comment, for change logging purposes. You can enter `tutorial` for both.
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Now click `Save`. You can see the new rules in the datasources view:
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Give the cluster a few minutes to apply the rule change, and go to the [segments view](http://localhost:8888/unified-console.html#segments) in the web console.
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The segments for the first 12 hours of 2015-09-12 are now gone:
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The resulting retention rule chain is the following:
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1. loadByInterval 2015-09-12T12/2015-09-13 (12 hours)
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2. dropForever
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3. loadForever (default rule)
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The rule chain is evaluated from top to bottom, with the default rule chain always added at the bottom.
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The tutorial rule chain we just created loads data if it is within the specified 12 hour interval.
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If data is not within the 12 hour interval, the rule chain evaluates `dropForever` next, which will drop any data.
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The `dropForever` terminates the rule chain, effectively overriding the default `loadForever` rule, which will never be reached in this rule chain.
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Note that in this tutorial we defined a load rule on a specific interval.
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If instead you want to retain data based on how old it is (e.g., retain data that ranges from 3 months in the past to the present time), you would define a Period load rule instead.
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## Further reading
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* [Load rules](../operations/rule-configuration.md)
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